October 22, 2014

October 22nd, 2014

With every day, the stock market’s gyrations grow:

U.S. stocks retreated, after the Standard & Poor’s 500 Index rose the most in a year yesterday, as energy shares led losses amid a drop in oil prices.

The S&P 500 slipped 0.7 percent to 1,927.11 at 4 p.m. in New York. The Dow Jones Industrial Average slid 153.49 points, or 0.9 percent, to 16,461.32. The Nasdaq Composite Index lost 0.8 percent. Crude oil slid 2.4 percent to $80.52 a barrel, the lowest level on a closing basis in more than two years, after a U.S. report showed inventories increased by 7.11 million barrels last week.

Four consecutive advances in the S&P 500 through yesterday pushed the gauge up 4.2 percent since Oct. 15, recouping half the losses from a selloff that began in mid-September. The equity index surged 2 percent yesterday, its best day since October 2013, as speculation the European Central Bank will boost stimulus to spur growth in the region.

The cost of living in the U.S. barely rose in September, leaving inflation below the Federal Reserve’s goal as fuel prices plunge this month. The consumer-price index climbed 0.1 percent after decreasing 0.2 percent in August, a Labor Department report showed.

… and there is chatter about currency wars:

Weak price growth is stifling economies from the euro region to Israel and Japan. Eight of the 10 currencies with the biggest forecasted declines through 2015 are from nations that are either in deflation or pursuing policies that weaken their exchange rates, data compiled by Bloomberg show.

“This beggar-thy-neighbor policy is not about rebalancing, not about growth,” David Bloom, the global head of currency strategy at London-based HSBC Holdings Plc, which does business in 74 countries and territories, said in an Oct. 17 interview. “This is about deflation, exporting your deflationary problems to someone else.”

Bloom puts it in these terms because, when one jurisdiction weakens its exchange rate, another’s gets stronger, making imported goods cheaper. Deflation is a both a consequence of, and contributor to, the global economic slowdown that’s pushing the euro region closer to recession and reducing demand for exports from countries such as China and New Zealand.

Hungary and Switzerland entered deflation in the past two months, while Swedish central-bank Deputy Governor Per Jansson last week blamed his country’s falling prices partly on rate cuts the ECB used to boost its own inflation. A policy response may be necessary, he warned.

But there will be no deflation in North America … will there?

The cost of living in the U.S. barely rose in September, restrained by decelerating prices for a broad array of goods and services that signal the Federal Reserve can keep interest rates low well into 2015.

The consumer-price index climbed 0.1 percent after decreasing 0.2 percent in August, a Labor Department report showed today in Washington. Over the past year, costs increased 1.7 percent, the same as in the 12 months through August.

While plunging fuel costs are one reason for the restraint in pricing, clothing retailers, medical-care providers and airlines are also among those keeping a lid on charges. With inflation falling short of the Fed’s goal, policy makers need not rush to raise rates even as the world’s largest economy shows no sign of succumbing to a slowdown in global growth.

… so the Bank of Canada is maintaining its policy rate:

The Bank of Canada today announced that it is maintaining its target for the overnight rate at 1 per cent. The Bank Rate is correspondingly 1 1/4 per cent and the deposit rate is 3/4 per cent.

Inflation in Canada is close to the 2 per cent target. Core inflation rose more rapidly than was expected in the Bank’s July Monetary Policy Report (MPR), mainly reflecting unexpected sector-specific factors. Total CPI inflation is evolving broadly as expected, as the pickup in core inflation was largely offset by lower energy prices. Underlying inflationary pressures are muted, given the persistent slack in the economy and the continued effects of competition in the retail sector.

In this context, Canada’s exports have begun to respond. However, business investment remains weak. Meanwhile, the housing market and consumer spending are showing renewed vigour and auto sales have reached record highs, all fuelled by very low borrowing rates. The lower terms of trade will have a tempering effect on income.

Canada’s real GDP growth is projected to average close to 2 1/2 per cent over the next year before slowing gradually to 2 per cent by the end of 2016, roughly the estimated growth rate of potential output. As global headwinds recede, confidence in the sustainability of domestic and global demand should improve and business investment should pick up. Together with a moderation in the growth of household spending, this is expected to gradually return Canada’s economy to a more balanced growth path. As the economy reaches its full capacity in the second half of 2016, both core and total CPI inflation are projected to be about 2 per cent on a sustained basis.

Weighing all of these factors, the Bank judges that the risks to its inflation projection are roughly balanced. Meanwhile, the financial stability risks associated with household imbalances are edging higher. Overall, the balance of risks falls within the zone for which the current stance of monetary policy is appropriate and therefore the target for the overnight rate remains at 1 per cent.

The Monetary Policy Report highlighted housing:

Housing starts have remained broadly in line with demographic demand in recent months (Chart 24). However, sales of existing homes have picked up noticeably since the beginning of the year, to a four-year high (Chart 25). This is contributing to sizable increases in house prices, although the national picture continues to mask important regional divergences (Chart 26 and Chart 27). In general, with historically low price increases and sales volumes, markets in Eastern Canada appear to show signs consistent with a soft landing. This contrasts with major cities in Ontario, Alberta and British Columbia, where housing markets are generally robust and much tighter.

… and the Globe chimed in with:

According to the Teranet-National house price index, home prices in Canada rose 0.3 per cent in September from August and 4.9 per cent from a year earlier.

Notably, Calgary, Toronto and Vancouver were well above the national average, at 9.5 per cent, 7.4 per cent and 6.5 per cent, respectively.

It was a good day for the Canadian preferred share market, with PerpetualDiscounts up 10bp, FixedResets winning 13bp and DeemedRetractibles gaining 2bp. Volatility was average. Volume was low.

HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices

Values are provisional and are finalized monthly
Index Mean
Current
Yield
(at bid)
Median
YTW
Median
Average
Trading
Value
Median
Mod Dur
(YTW)
Issues Day’s Perf. Index Value
Ratchet 3.15 % 3.15 % 20,898 19.34 1 0.0000 % 2,649.2
FixedFloater 0.00 % 0.00 % 0 0.00 0 0.5452 % 3,987.9
Floater 2.99 % 3.15 % 65,125 19.35 4 0.5452 % 2,677.7
OpRet 4.04 % 2.26 % 101,617 0.08 1 0.0000 % 2,735.7
SplitShare 4.29 % 3.90 % 82,216 3.81 5 -0.0582 % 3,152.5
Interest-Bearing 0.00 % 0.00 % 0 0.00 0 0.0000 % 2,501.5
Perpetual-Premium 5.48 % -0.15 % 73,560 0.08 18 -0.0437 % 2,457.4
Perpetual-Discount 5.30 % 5.14 % 95,792 15.15 18 0.0953 % 2,601.2
FixedReset 4.22 % 3.60 % 167,507 16.73 75 0.1301 % 2,551.5
Deemed-Retractible 5.02 % 2.49 % 103,051 0.34 42 0.0200 % 2,562.3
FloatingReset 2.55 % -6.10 % 60,705 0.08 6 -0.0719 % 2,545.5
Performance Highlights
Issue Index Change Notes
CIU.PR.C FixedReset -1.21 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 20.40
Evaluated at bid price : 20.40
Bid-YTW : 3.53 %
TRP.PR.B FixedReset 1.51 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 18.80
Evaluated at bid price : 18.80
Bid-YTW : 3.64 %
PWF.PR.A Floater 1.93 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 20.00
Evaluated at bid price : 20.00
Bid-YTW : 2.61 %
FTS.PR.J Perpetual-Discount 1.98 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 23.76
Evaluated at bid price : 24.15
Bid-YTW : 4.97 %
Volume Highlights
Issue Index Shares
Traded
Notes
BMO.PR.K Deemed-Retractible 131,289 Scotia crossed 40,000 at 26.05; Nesbitt crossed blocks of 35,000 and 50,000 at the same price.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-11-25
Maturity Price : 25.50
Evaluated at bid price : 26.03
Bid-YTW : -8.09 %
NA.PR.W FixedReset 67,325 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 23.09
Evaluated at bid price : 24.85
Bid-YTW : 3.63 %
TD.PF.B FixedReset 64,463 Scotia crossed 51,000 at 25.15.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 23.23
Evaluated at bid price : 25.15
Bid-YTW : 3.54 %
BAM.PR.R FixedReset 53,235 RBC crossed 46,800 at 25.25.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 23.74
Evaluated at bid price : 25.18
Bid-YTW : 3.74 %
GWO.PR.N FixedReset 39,397 Nesbitt crossed 35,000 at 21.82.
YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 21.75
Bid-YTW : 4.47 %
ENB.PF.G FixedReset 34,284 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 23.14
Evaluated at bid price : 25.08
Bid-YTW : 4.07 %
There were 19 other index-included issues trading in excess of 10,000 shares.
Wide Spread Highlights
Issue Index Quote Data and Yield Notes
W.PR.H Perpetual-Premium Quote: 25.02 – 25.35
Spot Rate : 0.3300
Average : 0.2080

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 24.80
Evaluated at bid price : 25.02
Bid-YTW : 5.53 %

TRP.PR.B FixedReset Quote: 18.80 – 19.20
Spot Rate : 0.4000
Average : 0.2881

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 18.80
Evaluated at bid price : 18.80
Bid-YTW : 3.64 %

CGI.PR.D SplitShare Quote: 25.25 – 25.68
Spot Rate : 0.4300
Average : 0.3357

YTW SCENARIO
Maturity Type : Soft Maturity
Maturity Date : 2023-06-14
Maturity Price : 25.00
Evaluated at bid price : 25.25
Bid-YTW : 3.68 %

FTS.PR.H FixedReset Quote: 20.11 – 20.40
Spot Rate : 0.2900
Average : 0.2130

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 20.11
Evaluated at bid price : 20.11
Bid-YTW : 3.64 %

TD.PR.S FixedReset Quote: 25.07 – 25.34
Spot Rate : 0.2700
Average : 0.1991

YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2022-01-31
Maturity Price : 25.00
Evaluated at bid price : 25.07
Bid-YTW : 3.16 %

TRP.PR.C FixedReset Quote: 20.92 – 21.19
Spot Rate : 0.2700
Average : 0.2047

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-22
Maturity Price : 20.92
Evaluated at bid price : 20.92
Bid-YTW : 3.63 %

RY.PR.Y Called For Redemption

October 22nd, 2014

Royal Bank of Canada finally announced:

its intention to redeem all of its issued and outstanding Non-Cumulative 5-Year Rate Reset First Preferred Shares Series AX (the “Series AX shares”) on November 24, 2014, for cash at a redemption price of $25.00 per share.

There are 13,000,000 Series AX shares outstanding, representing $325 million of capital. The redemption of the Series AX shares will be financed out of the general corporate funds of Royal Bank of Canada.

Separately from the redemption price, the final quarterly dividend of $0.38125 per share for the Series AX shares will be paid in the usual manner on November 24, 2014 to shareholders of record on October 27, 2014.

No surprises here, since the issue commenced trading April 29, 2009 and came with a massive Issue Reset Spread of 413bp. It is tracked by HIMIPref™ and has been assigned to the FixedReset index since inception.

SBN.PR.A Term Extended

October 22nd, 2014

Strathbridge Asset Management Inc. has announced (although not yet on their website):

S Split Corp. (the “Fund”) (TSX:SBN)(TSX:SBN.PR.A) is pleased to announce that holders of Class A Shares and holders of Preferred Shares of the Fund have approved a proposal to extend the term of the Fund for seven years beyond its scheduled termination date of December 1, 2014, and for automatic successive seven-year terms after November 31, 2021.

As a result, holders of Class A Shares will continue to benefit from the potential for leveraged capital appreciation in a portfolio consisting of common shares of The Bank of Nova Scotia and monthly distributions of 6.0% per annum of the net asset value of the Class A Shares. Holders of Preferred Shares will continue to benefit from fixed cumulative preferential monthly cash dividends in the amount of $0.043750 per Preferred Share representing a yield of 5.25% per annum on the original issue price of $10.00 per Preferred Share.

As part of the extension of the term of the Fund, the Fund will also make other changes, including: (i) provide a special redemption right to enable holders of Class A Shares and Preferred Shares to retract their shares on December 1, 2014 on the same terms that would have applied had the Fund redeemed all Class A Shares and Preferred Shares in accordance with the existing terms of such shares; (ii) change the monthly retraction prices for the Class A Shares and the Preferred Shares such that monthly retraction prices are calculated by reference to market price in addition to net asset value; and (iii) consolidate the Class A Shares or redeem the Preferred Shares on a pro rata basis, as the case may be, in order to maintain the same number of Class A Shares and Preferred Shares outstanding.

Shareholders who exercise the special redemption right will receive the amount which they would have received had the December 1, 2014 termination date not been extended. Payments for shares tendered pursuant to the Special Retraction Right will be made no later than 10 business days after December 1, 2014, provided that such shares have been surrendered for redemption on or prior to 5:00 p.m. (Toronto time) on November 17, 2014. The retraction price per Class A Share to be received by a holder of Class A Shares under the Special Retraction Right will be equal to the greater of (a) the NAV per Unit on December 1, 2014 (the “Special Retraction Date”) minus $10.00 and (b) nil. The retraction price per Preferred Share to be received by a holder of Preferred Shares under the Special Retraction Right will be equal to the lesser of: (a) $10.00; and (b) the NAV of the Fund divided by the number of Preferred Shares outstanding on the Special Retraction Date. Any declared and unpaid distributions payable on or before the Special Retraction Date in respect of Class A Shares or Preferred Shares tendered for retraction on the Special Retraction Date will also be paid on the retraction payment date.

For further information, please contact Investor Relations at 416.681.3966, toll free at 1.800.725.7172 or visit www.strathbridge.com.

The term extension was proposed on September 8, 2014.

The Information Circular dated 2014-9-11 has some more details (note that the Class A shares are the Capital Units):

No distributions may be paid on the Class A Shares if (a) the distributions payable on the Preferred Shares are in arrears; or (b) the NAV per Unit is equal to or less than $16.50. In addition, the Fund will not pay special distributions, meaning distributions in excess of the targeted 6.0% per annum monthly distribution, on the Class A Shares if after payment of the distribution the NAV per Unit would be less than $25.00 unless the Fund would need to make such distribution so as to fully recover refundable taxes.

Holders of Class A Shares and Preferred Shares are being asked to extend the term of the Fund for an additional seven years by changing the redemption date of the Class A Shares and the Preferred Shares to November 30, 2021. The redemption date will be further extended for successive seven-year terms thereafter and shareholders will be able to retract their Class A Shares or Preferred Shares at NAV prior to any such additional extension. In such circumstances, the Fund will provide at least 30 days’ notice to shareholders of the retraction date by way of press release.

The Fund proposes to extend the redemption date to November 30, 2021, with possible additional extensions of the term of the Fund, so that it may continue to provide shareholders with the opportunity to participate in the performance of the Portfolio.

Following the Reorganization, the Fund would initially maintain the current dividend rate on the Preferred Shares at 5.25% per annum on the $10.00 original issue price. However, the Board of Directors would be permitted to change the dividend rate on the Preferred Shares to reflect future market conditions following November 30, 2021. Any such change would be announced by way of the press release issued in connection with such extension of the term of the Fund.

To preserve the rights that were originally provided to holders of Class A Shares and Preferred Shares, the Fund proposes to amend the terms of such shares to permit holders of such shares to retract such shares (the “Special Retraction Right”) on December 1, 2014 (the “Special Retraction Date”) on the terms on which such shares would have been redeemed had the December 1, 2014 redemption date not been extended.

If more Class A Shares than Preferred Shares are retracted under the Special Retraction Right, the Fund will redeem Preferred Shares (the “Call Right”) on a pro rata basis to ensure an equal number of Class A Shares and Preferred Shares remain outstanding from and after the effective date of the Reorganization.

Going forward, the Annual Valuation Date, which is the time at which the annual concurrent retraction right may be exercised, will be changed to the November Valuation Date from the June Valuation Date, commencing in 2015. In addition, the Special Retraction Right will replace the annual concurrent retraction right in each year in which the Fund’s existing term is subsequently extended.

Shareholders whose Preferred Shares are retracted on a Valuation Date are entitled to receive a retraction price per share (the “Preferred NAV Retraction Price”) equal to 95% of the lesser of (a) the NAV per Unit as of the applicable Valuation Date less the cost to the Fund of purchasing a Class A Share in the market for cancellation and (b) $10.00.

Under the Reorganization, the monthly retraction price for the Preferred Shares will be changed and shareholders whose Preferred Shares are retracted on a Valuation Date will be entitled to receive a retraction price per share equal to the lesser of:
(a) the Preferred NAV Retraction Price; and
(b) 95% of the lesser of (i) the Unit Market Price less the cost to the Fund of purchasing a Class A Share in the market for cancellation and (ii) $10.00.

Class A Market Price means the weighted average trading price of the Class A Shares on the principal stock exchange on which the Class A Shares are listed (or, if the Class A Shares are not listed on any stock exchange, on the principal market on which the Class A Shares are quoted for trading) for the 10 trading days immediately preceding the applicable Valuation Date.

Unit Market Price means the sum of the Class A Market Price and the Preferred Market Price.

So on the bright side, it’s nice to see that big fat 5.25% coupon being extended for another seven years. Regrettably, the incorporation of “Unit Market Price” in the preferred share retraction price formula means that monthly retractions will no longer act as a price support in times of crisis; the chance of making a fast whopping profit when the units are trading below NAV has now disappeared. On the other hand, since there is no longer a price support, maybe the preferred shares will fall even more in such a crisis and become even more attractive purchases. We will see!

From the original prospectus:

Annual Concurrent Retraction: A holder of Class A Shares may concurrently retract an equal number of Class A Shares and Preferred Shares on the June Valuation Date of each year (the ‘‘Annual Valuation Date’’) at a retraction price equal to the NAV per Unit on that date, less any costs associated with the retraction, including commissions and other such costs, if any, related to the liquidation of any portion of the Company’s portfolio required to fund such retraction. The Class A Shares and the Preferred Shares must be surrendered for retraction at least 10 business days prior to the Annual Valuation Date. Payment of the proceeds of retraction will be made on or before the fifteenth business day of the following month. Such retractions are subject to a Retraction Fee. See ‘‘Details of the Offering — Retraction Fee’’.

The above isn’t affected by the extension, which is good. Some Split Share Corporations have provisions whereby the Capital Units can be retracted at the NAV on the annual date, with any imbalance of Capital Units over retracted Preferred Shares being made up by a par call. This is bad for holders, since calls are bad.

SBN.PR.A is a small issue, with only 2.9-million shares outstanding according to TMXMoney. Consequently, volumes are low.

SBN.PR.A is tracked by HIMIPref™ but is relegated to the Scraps index on both volume and credit concerns. It was last mentioned on PrefBlog with respect to the 2010 Annual Report.

October 21, 2014

October 21st, 2014

It was a nice day to own equities:

The S&P 500 climbed 2 percent to 1,941.28 at 4 p.m. in New York, its best gain since October 2013. The equity gauge is up 4.2 percent since Oct. 15 in the biggest four-day rally since January 2013. The Dow Jones Industrial Average climbed 215.14 points, or 1.3 percent, to 16,615 today. The Nasdaq 100 surged 2.6 percent, the most since January 2013, as about 7.2 billion shares traded hands in the U.S.

The ECB bought Italian covered bonds as it returned to the market for a second day under its asset purchase program, according to two people familiar with the matter. Debt issued by Intesa Sanpaolo SpA was included in the purchases, according to one of the people, who asked not to be identified because the information is private.

The ECB entered the 2.6 trillion-euro ($3.3 trillion) covered bond market after President Mario Draghi unveiled plans last month to bolster companies’ and households’ access to financing. Draghi, who also included asset-backed securities in the program, intends to expand the bank’s balance sheet by as much as 1 trillion euros to stave off deflation in the euro area.

U.S. stocks have rallied after St. Louis Federal Reserve Bank President James Bullard said on Oct. 16 that policy makers should consider delaying the end of bond purchases. He was the first Fed official to publicly suggest the central bank should extend its asset-purchase program when policy makers meet later this month.

CWB.PR.B has been confirmed at Pfd-3 by DBRS:

CWB’s has strong asset quality as evidenced by its history of low write-off rates, a proven niche strategy using relationship-based lending, a favourable efficiency ratio that reflects its business mix and strong internal capital generation. Challenges remain, though, particularly concentration in the loan book, both geographically (Alberta and British Columbia) and by industry (commercial, construction and real estate lending). Like its Canadian peers, the Bank has exposure to Canadian real estate-supported lending. A slowdown in the real estate markets may slow earnings generation and could hurt asset quality indicators, which ultimately may have an impact on provisioning levels. Funding diversification at CWB has been slowly improving over the past several years, but continues to rely heavily on brokered deposit.

CWB recently reported earnings available to common shareholders of $160 million (a return on equity of 14.7%) for the nine months ended July 31, 2014, an 18% increase over the same period in 2013. The earnings increase was largely due to loan growth year-to-date and higher non-interest income, offset by a narrower net interest margin in the continued low interest environment. CWB’s 105th consecutive profitable quarter was accompanied by low loan loss provisions. Capital levels are viewed as strong with a Basel III Common Equity Tier 1 ratio of 8.0% based on risk-weighted assets calculated using the standardized approach.

I recently came across a very good review of the US TruPS market by Yalman Onaran and Jody Shenn of Bloomberg. An oldie but goodie!

Bloomberg also has a good review of CoCos, by John Glover:

Regulators noted that investors often did a better job of predicting which banks would buckle in the crisis than they had themselves. CoCo bonds are designed to harness this “wisdom of the crowd” by putting bondholders on the front line, giving them a vested interest in the health of wobbly banks. The problem is that they are untested: When the first one goes sour and halts coupon payments, it’s possible investors could suddenly wake up to the inherent risk and flee all CoCos, destabilizing the corporate bond market and possibly even the financial system. Critics charge that the securities are too complex to be properly understood, too varied and too much like equity to be considered bonds. The banks themselves are opaque, definitions of capital vary from bond to bond, and the distance between a bank’s current position and the moment disaster will strike is almost impossible to calculate. When the first one blows, regulators will get a better sense of whether CoCos helped save the banking system, or sink it.

I feel that the current model for CoCos is inherently flawed since the triggers are based on regulatory capital, which didn’t work out all that well during the Credit Crunch; I continue to advocate high-trigger CoCos with a conversion trigger based on the common stock price.

It was a mixed day for the Canadian preferred share market, with PerpetualDiscounts up 30bp, FixedResets off 7bp and DeemedRetractibles gaining 11bp. Volatility was high, notable for FixedReset losers and Floating Rate winners. Volume was low.

HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices

Values are provisional and are finalized monthly
Index Mean
Current
Yield
(at bid)
Median
YTW
Median
Average
Trading
Value
Median
Mod Dur
(YTW)
Issues Day’s Perf. Index Value
Ratchet 3.15 % 3.15 % 21,768 19.34 1 -0.7506 % 2,649.2
FixedFloater 0.00 % 0.00 % 0 0.00 0 2.1920 % 3,966.2
Floater 3.00 % 3.15 % 65,855 19.35 4 2.1920 % 2,663.2
OpRet 4.04 % 2.12 % 100,680 0.08 1 -0.0787 % 2,735.7
SplitShare 4.29 % 3.88 % 85,593 3.82 5 0.5594 % 3,154.3
Interest-Bearing 0.00 % 0.00 % 0 0.00 0 -0.0787 % 2,501.5
Perpetual-Premium 5.48 % -0.10 % 74,099 0.08 18 0.1095 % 2,458.5
Perpetual-Discount 5.31 % 5.12 % 96,031 15.14 18 0.3012 % 2,598.7
FixedReset 4.23 % 3.61 % 169,544 16.73 75 -0.0664 % 2,548.2
Deemed-Retractible 5.02 % 2.62 % 103,192 0.34 42 0.1147 % 2,561.8
FloatingReset 2.55 % -6.10 % 61,142 0.08 6 -0.0522 % 2,547.3
Performance Highlights
Issue Index Change Notes
TRP.PR.B FixedReset -2.22 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 18.52
Evaluated at bid price : 18.52
Bid-YTW : 3.70 %
TRP.PR.A FixedReset -1.05 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 21.47
Evaluated at bid price : 21.77
Bid-YTW : 3.84 %
FTS.PR.K FixedReset -1.00 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.09
Evaluated at bid price : 24.65
Bid-YTW : 3.54 %
IAG.PR.A Deemed-Retractible 1.05 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 23.10
Bid-YTW : 5.65 %
CIU.PR.C FixedReset 1.23 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 20.65
Evaluated at bid price : 20.65
Bid-YTW : 3.48 %
CGI.PR.D SplitShare 1.56 % YTW SCENARIO
Maturity Type : Soft Maturity
Maturity Date : 2023-06-14
Maturity Price : 25.00
Evaluated at bid price : 25.40
Bid-YTW : 3.60 %
BAM.PR.B Floater 1.70 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 16.75
Evaluated at bid price : 16.75
Bid-YTW : 3.15 %
BAM.PR.C Floater 1.71 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 16.68
Evaluated at bid price : 16.68
Bid-YTW : 3.17 %
BAM.PR.K Floater 1.82 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 16.75
Evaluated at bid price : 16.75
Bid-YTW : 3.15 %
PWF.PR.A Floater 3.35 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 19.75
Evaluated at bid price : 19.75
Bid-YTW : 2.68 %
Volume Highlights
Issue Index Shares
Traded
Notes
ENB.PF.G FixedReset 115,860 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.13
Evaluated at bid price : 25.06
Bid-YTW : 4.07 %
NA.PR.W FixedReset 78,851 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.10
Evaluated at bid price : 24.87
Bid-YTW : 3.62 %
RY.PR.Y FixedReset 71,482 There is still nothing on their website about the upcoming call date. C’mon, Royal, hurry up and call this thing so I don’t have to check any more! CIBC bought 20,000 from RBC at 25.40, and blocks of 10,000 and 25,000 from TD at the same price.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-11-24
Maturity Price : 25.00
Evaluated at bid price : 25.36
Bid-YTW : 1.02 %
BAM.PF.G FixedReset 56,256 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.17
Evaluated at bid price : 25.14
Bid-YTW : 4.19 %
TRP.PR.A FixedReset 26,123 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 21.47
Evaluated at bid price : 21.77
Bid-YTW : 3.84 %
ENB.PF.C FixedReset 23,592 YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.16
Evaluated at bid price : 25.05
Bid-YTW : 4.05 %
There were 17 other index-included issues trading in excess of 10,000 shares.
Wide Spread Highlights
Issue Index Quote Data and Yield Notes
ELF.PR.H Perpetual-Discount Quote: 25.00 – 25.50
Spot Rate : 0.5000
Average : 0.2965

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 24.56
Evaluated at bid price : 25.00
Bid-YTW : 5.52 %

FTS.PR.F Perpetual-Discount Quote: 24.30 – 24.74
Spot Rate : 0.4400
Average : 0.2923

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 24.04
Evaluated at bid price : 24.30
Bid-YTW : 5.10 %

BAM.PR.E Ratchet Quote: 23.80 – 24.46
Spot Rate : 0.6600
Average : 0.5666

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 23.46
Evaluated at bid price : 23.80
Bid-YTW : 3.15 %

TRP.PR.B FixedReset Quote: 18.52 – 18.77
Spot Rate : 0.2500
Average : 0.1653

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-21
Maturity Price : 18.52
Evaluated at bid price : 18.52
Bid-YTW : 3.70 %

NEW.PR.D SplitShare Quote: 32.59 – 32.99
Spot Rate : 0.4000
Average : 0.3262

YTW SCENARIO
Maturity Type : Call
Maturity Date : 2015-06-26
Maturity Price : 32.07
Evaluated at bid price : 32.59
Bid-YTW : 2.19 %

MFC.PR.B Deemed-Retractible Quote: 22.88 – 23.14
Spot Rate : 0.2600
Average : 0.1921

YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.88
Bid-YTW : 5.85 %

DBRS Upgrades LB to Pfd-3(high) and Pfd-3

October 20th, 2014

DBRS has announced that it:

has today upgraded Laurentian Bank of Canada’s (Laurentian or the Bank) long-term ratings, including its Issuer Rating and Deposits & Senior Debt ratings, to A (low) from BBB (high) and its NVCC Preferred Share rating to Pfd-3 from Pfd-3 (low). DBRS has also confirmed Laurentian’s Short-Term Instruments rating at R-1 (low). All trends are now Stable.

The ratings upgrade resolves the positive trend which DBRS has held on Laurentian’s long-term ratings for two years. Laurentian’s credit profile has benefitted from diversification both geographically, through increased presence outside of Québec, and by business line, notably with the growth of B2B Bank. Efficiency at the Bank has been more recently trending in the right direction, and management has targeted further efficiency improvements over the medium term, particularly through the expansion of higher margin products and business lines which, if realized, should support the earnings profile of the Bank. DBRS anticipates that efficiency and geographic diversity should continue to improve, particularly as B2B Bank becomes a larger contributor. The rating is supported by the Bank’s overall lower-risk business profile, which is focused on retail lending funded by retail deposits, real estate and mid-market commercial financing, serves financial advisors and brokers through B2B Bank and includes a mid-sized Montréal-based capital markets business. Its high-cost structure and remaining geographic concentration remain challenging.

The affected issues are:

LB Preferred Shares Upgrade
Ticker Type of Preferred NVCC Status New DBRS Rating
LB.PR.F FixedReset
4.00%+260
Non-Compliant Pfd-3(high)
LB.PR.H FixedReset
4.30%+255
Compliant Pfd-3

LB.PR.F and LB.PR.H were last mentioned on PrefBlog when they were downgraded by S&P earlier this month. Both are tracked by HIMIPref™ but relegated to the Scraps index on credit concerns.

October 20, 2014

October 20th, 2014

On September 22 I highlighted the Blackrock publication CORPORATE BOND MARKET STRUCTURE: THE TIME FOR REFORM IS NOW, but it turns out they’ve been pushing the ‘scheduled issuance’ idea for a while. It’s also been proposed in their May, 2013, publication Setting New Standards: The Liquidity Challenge II, which comes with some great illustrative charts.

concession
Click for Big

If the Shitty Price Hypothesis (described in the post TRACE and the Bond Market is correct, we expect to see a decrease in the concession from pre-TRACE days, perhaps even going negative.

dealerInventory
Click for Big

This one is interesting in conjunction with the Trading Volume chart below. Note that dealer inventories have dropped by about half since 2005.

friction
Click for Big

So a bigger proportion of the spread-to-Treasuries is being eaten up by the bid-ask spread.

issuance
Click for Big

Issuance is huge relative to outstanding, which may be why the world hasn’t ground to a halt despite the pernicious influence of TRACE.

issuanceTenor
Click for Big

But it could be that decreasing liquidity is reducing the tenor of new issues. Investors have to get their liquidity somehow!

liquidityPremium
Click for Big

An increasing liquidity premium is consistent with the Shitty Price Hypothesis

newIssueTrading
Click for Big

New issues will change hands a few times, then settle into their permanent homes.

tradingVolume
Click for Big

This is particularly interesting in conjunction with the Dealer Inventory chart above. Note that although trading volume has decreased, it has decreased less, proportionally, than dealer inventories have, indicating that dealer inventory turnover is increasing. This is consistent with the Shitty Price Hypothesis

Victoria Stilwell of Bloomberg complains:

Federal Reserve policy makers are missing a key element as they assess the health of the labor market: data that includes whether those who are employed are overqualified for their job or would like to work more hours.

As a result, the “significant underutilization of labor resources” that Fed officials highlighted last month as they renewed a pledge to keep interest rates low for a “considerable period” is probably even more severe than currently estimated. And the information gap means policy makers may have more difficulty gauging the right moment to raise rates off zero.

Private surveys have attempted to fill in the gaps. Some 46 percent of workers who graduated from college in 2012 or 2013 said that they were in a job that did not require their degree, according to a study released in May by Accenture Plc. That’s a five percentage point increase from last year, the New York-based management-consulting company’s report showed.

So, the study, titled Great Expectations: Insights from the Accenture 2014 College Graduate Employment Survey states:

46 percent of 2012/2013 grads working today report that they are underemployed (meaning they are working in a job that does not require their college degree). This is a 5 percent increase from last year’s survey.

I’m not sure I agree with that, entirely. It has been a long time since somebody asked me to explain the Schrödinger Wave Equation for a hydrogen atom, or to whip them up a batch of cis-stilbenes with a 4-substituent. So my chemistry degree hasn’t been required for a while. But I don’t feel underemployed!

It was a mixed day for the Canadian preferred share market, with PerpetualDiscounts up 15bp, FixedResets off 2bp and DeemedRetractibles gaining 4bp. Volatility was average, but enlivened by some sloppy trading at the close in PWF.PR.A. Volume was very low.

HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices

Values are provisional and are finalized monthly
Index Mean
Current
Yield
(at bid)
Median
YTW
Median
Average
Trading
Value
Median
Mod Dur
(YTW)
Issues Day’s Perf. Index Value
Ratchet 3.13 % 3.11 % 22,123 19.40 1 0.0417 % 2,669.3
FixedFloater 0.00 % 0.00 % 0 0.00 0 -2.6600 % 3,881.2
Floater 3.07 % 3.21 % 64,680 19.22 4 -2.6600 % 2,606.1
OpRet 4.04 % 1.02 % 101,190 0.08 1 0.1577 % 2,737.9
SplitShare 4.31 % 4.03 % 84,793 3.82 5 -0.1994 % 3,136.8
Interest-Bearing 0.00 % 0.00 % 0 0.00 0 0.1577 % 2,503.5
Perpetual-Premium 5.49 % 1.16 % 73,386 0.08 18 0.1272 % 2,455.8
Perpetual-Discount 5.32 % 5.15 % 96,596 15.16 18 0.1508 % 2,590.9
FixedReset 4.22 % 3.60 % 170,794 16.73 75 -0.0190 % 2,549.8
Deemed-Retractible 5.03 % 2.78 % 102,712 0.44 42 0.0382 % 2,558.9
FloatingReset 2.55 % -6.10 % 61,836 0.08 6 -0.0848 % 2,548.6
Performance Highlights
Issue Index Change Notes
PWF.PR.A Floater -7.95 % It appears that Desjardins put in a Market or low-limit order at 3:58, which took out the bid – Five hundred went at 20.00 and 20.01, time-stamped 3:58, then six hundred shares traded at 19.02 and 188 at 19.01, time-stamped 3:59. Whoosh!

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 19.11
Evaluated at bid price : 19.11
Bid-YTW : 2.77 %

CGI.PR.D SplitShare -1.54 % YTW SCENARIO
Maturity Type : Soft Maturity
Maturity Date : 2023-06-14
Maturity Price : 25.00
Evaluated at bid price : 25.01
Bid-YTW : 3.81 %
MFC.PR.F FixedReset -1.12 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.10
Bid-YTW : 4.54 %
PWF.PR.F Perpetual-Premium 1.12 % YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-11-19
Maturity Price : 25.00
Evaluated at bid price : 25.21
Bid-YTW : -6.75 %
Volume Highlights
Issue Index Shares
Traded
Notes
TRP.PR.A FixedReset 207,140 RBC crossed two blocks of 100,000 each, both at 21.97.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 21.63
Evaluated at bid price : 22.00
Bid-YTW : 3.79 %
NA.PR.W FixedReset 163,450 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 23.06
Evaluated at bid price : 24.77
Bid-YTW : 3.64 %
FTS.PR.M FixedReset 90,638 Scotia crossed blocks of 22,000 and 16,100, both at 25.20. Nesbitt bought 17,500 from RBC at the same price.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 23.20
Evaluated at bid price : 25.15
Bid-YTW : 3.81 %
FTS.PR.H FixedReset 81,452 RBC crossed two blocks of 40,000 each, both at 20.39.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 20.30
Evaluated at bid price : 20.30
Bid-YTW : 3.60 %
ENB.PF.G FixedReset 61,675 Recent new issue.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 23.13
Evaluated at bid price : 25.06
Bid-YTW : 4.07 %
IFC.PR.C FixedReset 54,411 RBC crossed 50,000 at 25.54.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2016-09-30
Maturity Price : 25.00
Evaluated at bid price : 25.50
Bid-YTW : 3.27 %
There were 18 other index-included issues trading in excess of 10,000 shares.
Wide Spread Highlights
Issue Index Quote Data and Yield Notes
PWF.PR.A Floater Quote: 19.11 – 20.75
Spot Rate : 1.6400
Average : 0.9689

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-20
Maturity Price : 19.11
Evaluated at bid price : 19.11
Bid-YTW : 2.77 %

CGI.PR.D SplitShare Quote: 25.01 – 25.60
Spot Rate : 0.5900
Average : 0.3772

YTW SCENARIO
Maturity Type : Soft Maturity
Maturity Date : 2023-06-14
Maturity Price : 25.00
Evaluated at bid price : 25.01
Bid-YTW : 3.81 %

HSB.PR.D Deemed-Retractible Quote: 25.20 – 25.78
Spot Rate : 0.5800
Average : 0.3743

YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-12-31
Maturity Price : 25.00
Evaluated at bid price : 25.20
Bid-YTW : 2.34 %

TD.PR.Q Deemed-Retractible Quote: 25.92 – 26.24
Spot Rate : 0.3200
Average : 0.2030

YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-11-19
Maturity Price : 25.75
Evaluated at bid price : 25.92
Bid-YTW : -4.52 %

MFC.PR.F FixedReset Quote: 22.10 – 22.50
Spot Rate : 0.4000
Average : 0.3095

YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.10
Bid-YTW : 4.54 %

BNS.PR.N Deemed-Retractible Quote: 25.78 – 26.00
Spot Rate : 0.2200
Average : 0.1367

YTW SCENARIO
Maturity Type : Call
Maturity Date : 2015-01-28
Maturity Price : 25.50
Evaluated at bid price : 25.78
Bid-YTW : 0.57 %

TRACE and Structured Credit Products

October 19th, 2014

The FINRA page titled “Independent TRACE Studies” leads me to some studies that have come out of mandatory TRACE reporting for Structured Credit. The data collected are not made public in raw form, but aggregate data is made available on a daily and monthly basis.

Structured Credit is a little far from my bailiwick, but some of the statistics cited are so entertaining I just had to highlight them here.

A 2013 paper by Hendrik Bessembinder, William F. Maxwell and Kumar Venkataraman is titled Trading Activity and Transaction Costs in Structured Credit Products:

After conducting the first study of secondary trading in structured credit products, the authors report that the majority of products did not trade even once during the 21-month sample. Execution costs averaged 24 bps when trades occurred and were considerably higher for products with a greater proportion of retail-size trades. The authors estimate that the introduction of public trade reporting would decrease trading costs in retail-oriented products by 5-7 bps.

An acknowledgement in this paper, by the way, introduced me to the Montreal Institute of Structured Finance and Derivatives, which appears to be funded by agencies of the Province of Quebec and provides modest funding to genuine research – only $300,000 p.a., but that’s not bad when compared to their 10-year total budget of $15-million (meanwhile, here in Ontari-ari-ari-owe, we fund ex-regulators and lawyers at FAIR Canada. Gag.) You learn something new every day!

Anyway, back to Bessembinder et al. and the amazing statistics:

Notably, less than twenty percent of the SCP universe trades at all during the twenty-one month sample period. One-way trade execution costs for SCPs average about 24 basis points. However, trade execution costs vary substantially across SCP categories, from 92 basis points for CBOs to just 1 basis point for TBAs. We show that trading costs depend in particular on what we term the product’s “customer profile,” which depends on issue size and the proportion of Retail- versus Institutional-size trades. Sub-products with an Institutional Profile tend to have lower costs. The highest average trading costs are observed for Agency CMOs (74 basis points) and CBOs (92 basis points), each of which has a low (22% or less) proportion of large trades. The lowest average trading cost estimates are observed for TBA securities (1 basis point), CMBS (12 basis points), and ABS secured by auto loans and equipment (7 basis points), each of which has a large (54% or greater) percentage of large trades.

Structured Products (SCPs), including asset-backed (ABS) and mortgage-backed (MBS) securities, comprise one of the largest but least-studied segments of the financial services industry. As of the end of 2012, there was $8.6 trillion outstanding in mortgage-backed securities and $1.7 trillion outstanding in asset-backed securities, implying that the SCPs markets are comparable in size to the $11 trillion U.S. Treasury Security market

Increased transparency has the potential to reduce the dealer mark-ups or bid-ask spreads, provide more information on the fair price of the security, and improve regulators and customers’ ability to control and evaluate trade execution costs. These ideas have been emphasized by Rick Ketchum, Chairman and CEO of the Finance Industry Regulatory Authority (FINRA):
“From the standpoint of investor protection, which is and always will be FINRA’s top priority, we simply must shed more light on the darker areas of the fixed income market.

That last quote from Rick Ketchum illustrates the big problem with securities regulation nowadays. They have swung so far over to the ‘consumer protection’ objective that they have – at least to some degree – lost sight of why capital markets exist in the first place: to get money from savers to those who want to invest in their businesses. I will certainly agree that investor protection is a worthy objective; and I will agree that it is related reasonably closely to the objective of having a well functioning capital market; but for it to be called the “top priority” shows very strange priorities.

So the first amazing statistic is:

The MBS database provided to us by FINRA contains almost 1.1 million distinct securities. The large number of securities reflects that a basic pool of assets may have more than a hundred tranches, each with a unique payoff structure, and assets can be re-securitized (By comparison, less than 5,000 companies were listed on the U.S. equity exchanges at the end of 2012). However, as Panel A of Table 1 shows, many of these issues are very small, as the 25th percentile issue size is less than $2MM. The median issue size is less than $5MM. However, the distribution is positively skewed, as the mean issue size is $22.8MM. The MBS securities are of long average maturity, as shown on Panel B, with a mean maturity close to 19 years.

Holy smokes! I knew there were lots, but I would have guessed ‘under a million’. Hundred-tranche structured products sound pretty amazing, too.

Table 2 reports on trading activity for MBS. Notably, only 17.8% of the issues traded at all during the twenty one month period studied. The mean dollar volume traded across the full sample of MBS securities is $106MM, with an average of only 4.1 trades in each security. Fannie’s issues average six trades during the sample, and the average trading volume for Fannie issues is almost three times as large as for the next most frequently traded issue (Ginnie). Freddie’s issues are traded significantly less than either of the other agencies. Non-Agency issues trade an average of only 1.8 times each, but surprisingly have the largest proportion of issues (23%) that trade at all. Non-Agency issues have an average of 3.5 dealers at issuance, compared to slightly over four dealers for each Agency issue

Table 3 contains information regarding the ABS data, which contains slightly over 300,000 issues (compared to 1.1 million issues in the MBS universe).5 The ABS issues are larger than MBS issues, with the mean ($114MM) and median ($29MM) issue size each close to five times larger than for ABS. Still, some ABS issues are very small; the 5th percentile of the issue size distribution is only $100,000 for ABS, compared to over $1MM for MBS. ABS issues have an average maturity of 23.2 years, about 5 years longer than MBS products.

Panel B of Table 3 reports on trading activity in the ABS market. Like MBS, ABS trade infrequently, but the percentage of issues that trade at all is almost 30%, considerably higher than MBS at 18%. The average number of trades per security is 4.97, but the trades are on average smaller for ABS; the mean cumulative trading volume for ABS is $16.3MM, compared to the $106MM for MBS issues. The likelihood of trading and mean number of trades is surprisingly homogenous across issue size terciles. However, average trade size and cumulative dollar volume is larger for ABS of greater issue size.

And what are these trades?

Table 5 reports on the distribution of trade sizes in SCPs. We consider a trade to be small if it is for less than $100,000 and large if it is for more than $1MM.

For comparison purposes, we examine the distribution of trade sizes for corporate bonds during the six months before and after the introduction of public transaction dissemination. Our analysis includes 1.9 Million trades in 10,108 corporate bonds phased into TRACE dissemination between January 2003 and March 2011.8 We find that 72% of corporate bond trades are small (less than $100,000), both before and after trades were publicly disseminated. We conclude that, on average, the market for corporate bonds is more similar to the retail-oriented markets for SCPs, including CMOs and MBSs, and is more distinct from the institutionally-oriented markets for CMBS and TBA securities.

And the cost?

The resulting estimates of customer trade execution costs are reported on Table 6. For the full
sample, the estimated average one-way trade execution cost is 24 basis points. Consistent with results previously reported for corporate and municipal bonds, trade execution costs for SCPs decline with trade size, averaging 83 basis points for small trades, 24 basis points for medium-sized trades, and only five basis points for large trades. Trade execution costs also vary depending on trading frequencies. Average costs for the least-heavily-traded tercile of securities are 31 basis points, compared to 28 basis points for the second tercile and 24 basis points for the most frequently traded tercile. The finding that trade execution costs for SCPs decline with trade size mirrors the findings reported for corporate bonds by Edwards, Harris and Piwowar (2007) and Goldstein, Hotchkiss and Sirri (2007) and for municipal bonds by Harris and Piwowar (2006) and Green, Hollifield, and Schurhoff (2007). The overall level of estimated trading costs for SCP is in line with estimates for corporate bonds.

Bessembinder, Maxwell and Venkataraman (2006) study institutional trades in corporate bonds, and report average one-way trade execution costs (prior to transaction dissemination) that average 10 to 20 basis points. Schultz (2001) also studies institutional trades in corporate bonds and estimates that trading costs average 27 basis points. Edwards, Harris and Piwowar (2007) study a broader cross-section that includes retail trades, and estimate that one-way trade execution costs for corporate bonds range from 75 basis points for very small trades to 4 basis points for very large trades.

And the effect of TRACE?

We first implement expression (2) for the full set of corporate bonds that became TRACE-eligible in March of 2003, including in the analysis trades executed six months before to six months after the initiation of public trade dissemination. We find that trading costs for corporate bonds were reduced after the introduction of price dissemination by 9 basis points for small trades, 6 basis points for medium trades, and 3 basis points for large trades. These results are quite similar to those reported by Edwards, Harris, and Piwowar (2006), who study the same sample but rely on more complex estimation techniques.

I take issue with the authors when they claim:

These estimates of lower trading costs for SCPs have important implications for security issuers, investors in these products and broker-dealers who supply liquidity. Improved liquidity that is attributable to post-trade price transparency has the potential to affect the valuation of the bonds themselves and lower yield spreads (see Chen, Lesmond and Wei (2007) for evidence from corporate bonds) for SCP issues. Additionally, the cumulative dollar impact of these trading cost reductions is potentially large. In the case of the transparency experiment for corporate bonds, Bessembinder, Maxwell and Venkataraman (2006) estimate annual trading cost reductions of about $1 billion for the full corporate bond market. In addition, they document the existence of “liquidity externalities”, by which improved transparency for some products can lead to improved valuation and lower trade execution costs for related securities.

As I pointed out in an earlier post, a tighter spread between the dealer buy price and dealer sell price does not necessarily indicate “fairer” prices, since the dealer may well quote only stink bids on customer sales so that a profitable re-sale can be executed quickly. This mechanism, if correct, would actually mean that the liquidity-seeker in the chain of trades is paying more for liquidity under TRACE and that both the interim and ultimate liquidity providers are making excess profits (I refer to this as the Shitty Price Hypothesis). The authors do not examine how the execution prices in the secondary market compare with new-issue prices, which renders their conclusion regarding the “improvement” in liquidity dubious.

In addition to this, the putative benefits of TRACE, estimated as “annual trading cost reductions of about $1 billion for the full corporate bond market”, does not make any attempt to compare this with the cost of the programme. And I don’t mean direct costs, either. If the Shitty Price Hypothesis is correct – and it is consistent with the finding of lower trading levels in the Asquith, Covert and Pathak paper, then actual liquidity has decreased, which means issuers will have to pay more for funds, which means that some bricks-and-mortar projects will be abandoned (this link in the chain is the entire basis for central banking policy rates) … and how much does that cost? Huh?

Anyway, the authors told us to “see Chen, Lesmond and Wei (2007) for evidence from corporate bonds”, so let’s look at Chen, Lesmond and Wei (2007) and see what they have to say.

The paper by Long Chen, David A. Lesmond & Jason Wei is titled Corporate Yield Spreads and Bond Liquidity and it turns out that the last named author is from our very own Rotman School of Management at UofT:

We examine whether liquidity is priced in corporate yield spreads. Using a battery of liquidity measures covering over 4000 corporate bonds and spanning investment grade and speculative categories, we find that more illiquid bonds earn higher yield spreads; and that an improvement of liquidity causes a significant reduction in yield spreads. These results hold after controlling for common bond-specific, firm-specific, and macroeconomic variables, and are robust to issuers’ fixed effect and potential endogeneity bias. Our finding mitigates the concern in the default risk literature that neither the level nor the dynamic of yield spreads can be fully explained by default risk determinants, and suggests that liquidity plays an important role in corporate bond valuation.

The notion that investors demand a liquidity premium for illiquid securities dates back to Amihud and Mendelson (1986). Lo, Mamaysky, and Wang (2004) further argue that liquidity costs inhibit the frequency of trading. Because investors cannot continuously hedge their risk, they demand an ex-ante risk premium by lowering security prices. Therefore, for the same promised cash flows, less liquid bonds will be traded less frequently, have lower prices, and exhibit higher yield spreads. Thus, the theoretical prior is that liquidity is expected to be priced in yield spreads. We investigate bond-specific liquidity effects on the yield spread using three separate liquidity measures. These include the bid-ask spread, the liquidity proxy of zero returns, and a liquidity estimator based on a model variant of Lesmond, Ogden, and Trzcinka (1999). We find that liquidity is indeed priced in both levels and changes of the yield spread.

Contemporaneous studies by Longstaff et al. (2004) and Ericsson and Renault (2002) also relate corporate bond liquidity to yield spreads.

Historically, the lack of credible information on spread prices or bond quotes has been a major impediment in the analysis of liquidity (Goodhart and O’Hara, 1997) and liquidity’s impact on yield spreads. We employ Bloomberg and Datastream to provide our three liquidity estimates. Among them, the bid-ask spread is arguably the most demonstrable measure of liquidity costs, while the percentage of zero returns is increasingly used as a liquidity proxy in a host of empirical studies.2 Despite the clear intuition surrounding the zero return proxy, it is a noisy measure of liquidity, since it is the combination of a zero return and the simultaneous movement of bond price determinants that more properly estimates liquidity costs, not the lack of price changes per se.

We find a significant association between corporate bond liquidity and the yield spread with each of the three liquidity measures. Depending on the liquidity measure, liquidity alone can explain as much as 7% of the cross-sectional variation in bond yields for investment grade bonds, and 22% for speculative grade bonds. Using the bid-ask spread as the measure, we find that one basis point increase in bid-ask spread is related to 0.42 basis point increase in the yield spread for investment grade bonds, and 2.30 basis point increase for speculative grade bonds.

So I don’t find anything objectionable in the conclusion; I’ve argued in this blog for a long time that liquidity is a major factor in corporate bond yields, far outweighing credit quality considerations. I will, however, point out that their primary liquidity estimator is at least a little suspect:

Data on the quarterly bid-ask quotes are hand-collected from the Bloomberg Terminals. Most quotes are available only from 2000 to 2003. For each quarter, we calculate the proportional spread as the ask minus the bid divided by the average bid and ask price. The bond-year’s proportional bid-ask spread is then calculated as the average of the quarterly proportional spreads. To include as many bonds as possible, we compute the annual proportional spread as long as there is at least one quarterly quote for the year. The bid-ask quotes recorded are the Bloomberg Generic Quote which reflects the consensus quotes among market participants.

I have to point out that Bloomberg quotes are suspect according to the Jankowitsch, Nashikkar and Subrahmanyam paper referenced in an earlier post, with almost half of actual trades executed outside the quote. This doesn’t necessarily mean that the Bloomberg quotation spreads are useless as a liquidity estimator, but it does mean that somebody has to do some work to show that Bloomberg spreads do in fact have a solid relationship to real life (e.g., that if the bid on bond A is less than the bid on bond B, then you can in fact sell B at a higher price than A).

So what it comes down to is that I agree with Bessembinder, Maxwell and Venkataraman that if TRACE does improve liquidity, then this is a good thing, but I will claim that you cannot measure liquidity in a practical way by comparing dealer sell prices with dealer buy prices if the Shitty Price Hypothesis holds.

As it happens, there is a paper by Nils Friewald, Rainer Jankowitschy and Marti G. Subrahmanyamz which seeks to validate the round-trip trading cost as a measure of liquidity, titled Transparency and Liquidity in the Structured Product Market:

We use a unique data set from the Trade Reporting and Compliance Engine (TRACE) to study liquidity effects in the US structured product market. Our main contribution is the analysis of the relation between the accuracy in measuring liquidity and the potential degree of disclosure. We provide evidence that transaction cost measures that use dealer-speci c information can be eciently proxied by measures that use less detailed information. In addition, we analyze liquidity, in general, and show that securities that are mainly institutionally traded, guaranteed by a federal authority, or have low credit risk, tend to be more liquid.

For example, measuring liquidity based on the round-trip cost uses the most detailed information, i.e., each transaction needs to be linked to a particular dealer, on each side of the trade. Other liquidity metrics, such as the effective bid-ask spread, do not need such detailed trade information for their computation; but, transactions need to be flagged as buy or sell trades. Many alternative liquidity measures rely on trading data as well: However, they use only information regarding the price and/or volume of each transaction. On the other hand, product characteristics or trading activity variables represent simpler proxies, using either static or aggregated data.

Exploring the various liquidity metrics and focusing on the predictive power of transaction data, we show that simple product characteristics and trading activity variables, by themselves, may not be sufficient statistics for measuring market liquidity. In particular, when regressing state-of-the-art liquidity measures on product characteristics and trading activity variables, we find that the various liquidity measures over significant idiosyncratic information. Thus, dissemination of detailed transaction data, necessary for the estimation of liquidity measures, is of importance in the fixed-income structured product market. However, there is evidence that liquidity measures based on price and volume information alone (e.g., the imputed round-trip cost measure) can explain most of the variation observed in the benchmark measure, which uses significantly more information and certainly runs the risk of compromising the confidentiality of trader identity. In a second set of regressions, we explain the observed yield spreads using various combinations of liquidity variables and nd similar results: Liquidity measures provide higher explanatory power than product characteristics and trading activity variables alone. However, this result is mostly driven by price and volume information. Thus, details regarding the identities of the specific dealers involved with a particular trade or the direction of the trade are not an absolute necessity in terms of their informational value to market participants: Reasonable estimates of liquidity can be calculated based on prices and volumes of individual trades, without divulging dealer-specific information. This is an important result for all market participants, as it provides valuable insights concerning the information content of reported transaction data.

They acknowledge the Bessembinder paper and discuss the differences:

However, our paper is different from Bessembinder et al. (2013) for at least five important reasons, relating to various aspects of liquidity effects in the structure product market: First, while their analysis is based only on one single estimate of liquidity, we, in contrast, rely on a much broader set of liquidity proxies, which allows us to discuss the information contained in measures employing reported data at different levels of detail. Second, while Bessembinder et al. (2013) use a regression based estimate of liquidity, our round-trip cost measure (which serves as our benchmark) reflects the cost of trading more accurately, since it is based on detailed dealer-specific transaction costs, which are straightforward to compute, and does not depend, in any way, on modeling assumptions. Third, in their analysis, they focus solely on customer-to-dealer trades which constitute only a rather small fraction of all trades in the structured product market, whereas our analysis is based on all customer-to-dealer and dealer-to-dealer transactions. Fourth, unlike their study, we analyze different sub-segments (e.g., tranche seniority, issuing authority, credit rating) of the overall market in much more detail. These sub-segments have either turned out to be important in other fixed income markets, or are unique to the structured product market. Finally, a novel contribution of our paper is that we also analyze which of the liquidity measures best serves to explain yield spreads in the securitized product market.

So more particularly:

Thus, we ask how much information should be disseminated to allow for the accurate measurement of liquidity, compared to our benchmark measure using the most detailed information, in particular trader identity and trade direction, which certainly runs the risk of compromising the identities of individual traders or their trading strategies. Therefore, we measure the efficacy of liquidity metrics that require different levels of detail in terms of the information used to compute them. We analyze two aspects of this question, using different sets of regressions: First, we explore to what extent product characteristics, trading activity variables and liquidity measures using less information can proxy for the benchmark measure which is based on all available information. Second, we study which liquidity measures can best explain the cross-sectional differences in yield spreads for our sample.

Product characteristics are rather crude proxies of liquidity that rely on the lowest level of informational detail of all the categories.13 Thus, product characteristics are typically used as liquidity metrics when there is a limitation on the level of detail in the transaction data. In particular, we use the amount issued of a security measured in millions of US dollars. We presume securities with a larger amount issued to be more liquid, in general. Another important product characteristic is the time-to-maturity, which corresponds to the time, in years, between the trading date and the maturity date of the security. We expect securities with longer maturities (over ten years) to be generally less liquid, since they are often bought by “buy-and-hold” investors, who trade infrequently. We also consider the instrument’s average coupon as a relevant proxy. Despite the ambiguity of the relationship between the coupon and both liquidity and credit risk, we expect that instruments with larger coupons are generally less liquid.

Trading activity variables such as the number of trades observed for a product on a given day represent the aggregate market activity.15 Other similar variables that we calculate on a daily basis, for each product, are the number of dealers involved in trading a specific product, and the trading volume measured in millions of US dollars. We expect these variables to be larger, the more liquid the product. On the contrary, the longer the trading interval, which refers to the time elapsed between two consecutive trades in a particular product (measured in days), the less liquid we would expect the product to be.

Note that the Shitty Price Hypothesis negates this last assumption: dealers will set prices so they can exit their positions quickly.

Liquidity measures are conceptually based, and hence, more direct proxies for measuring liquidity, and require transaction information for their computation. However, the level of detail concerning the required information set varies considerably across measures. The liquidity measure that uses the most detailed information and, thus, serves as our benchmark measure, is the round-trip cost measure, which can be computed only if the traded prices and volumes can be linked to the individual dealer; see, e.g., Goldstein et al. (2007). It is defined as the price difference, for a given dealer, between buying (selling) a certain amount of a security and selling (buying) the same amount of this security, within a particular time period, e.g., one day. Thus, it is assumed that in a “round-trip” trade, the price is not affected by changes in the fundamentals during this period. Following the literature, the round-trip trade may either consist of a single trade or a sequence of trades, which are of equal size in aggregate, on each side. The effective bid-ask spread, proposed by Hong and Warga (2000), can be computed when there is information about trade direction available. The effective bid-ask spread is then defined as the difference between the daily average sell and buy prices (relative to the mid-price).

Many other liquidity measures use only the price and/or volume of each transaction, without relying on dealer-specific or buy/sell-side information. A well-known metric proposed by Amihud (2002), and conceptually based on Kyle (1985), is the Amihud measure. It was originally designed for exchange-traded equity markets, but has also become popular for measuring liquidity in OTC markets. It measures the price impact of trades on a particular day, i.e., it is the ratio of the absolute
price change measured as a return, to the trade volume given in US dollars. A larger Amihud measure implies that trading a financial instrument causes its price to move more in response to a given volume of trading and, in turn, reflects lower liquidity. An alternative method for measuring the bid-ask spread is the imputed round-trip cost, introduced by Feldhutter (2012). The idea here is to identify round-trip trades, which are assumed to consist of two or three trades on a given day with exactly the same traded volume. This likely represents the sale and purchase of an asset via one or more dealers to others in smaller trades. Thus, the dealer identity is not employed in this matching procedure; rather, differences between the prices paid for small trades, and those paid for large trades, based on overall identical volumes, are used as the measure. The price dispersion measure is a new liquidity metric recently introduced for the OTC market by Jankowitsch et al. (2011). This measure is based on the dispersion of traded prices around the market-wide consensus valuation, and is derived from a market microstructure model with inventory and search costs. A low dispersion around this valuation indicates that the nancial instrument can be bought for a price close to its fair value and, therefore, represents low trading costs and high liquidity, whereas a high dispersion implies high transaction costs and hence low liquidity. The price dispersion measure is defined as the root mean squared difference between the traded prices and the average price, the latter being a proxy for the respective market valuation.

The Roll measure, developed by Roll (1984) and applied by Bao et al. (2011) and Friewald et al. (2012), for example, in the context of OTC markets, is a transaction cost measure that is simply based on observed prices. Under certain assumptions, adjacent price movements can be interpreted as a “bid-ask bounce”, resulting in transitory price movements that are serially negatively correlated. The strength of this covariation is a proxy for the round-trip transaction costs for a particular nancial instrument, and hence, a measure of its liquidity. This measure requires the lowest level of detail as only traded prices, and not trading volume or dealer-specific information, are used in the computation.

Whoosh! That’s a lot of liquidity measures! And I thought I was obsessive!

The descriptive statistics and correlations presented in Section 5.1 provide initial indications of the informational value of the various liquidity measures. When analyzing the liquidity of the different markets and their sub-segments, the liquidity measures offer additional insights compared to the product characteristics and trading activity variables. For example, when comparing the different market segments, higher trading activity is not always associated with lower transaction costs. The correlation analysis hints in the same direction: There is low correlation between the product characteristics and the liquidity measures (the highest correlation coefficient is 0.26 in absolute terms) and between trading activity variables and liquidity measures (less than 0.20 in absolute terms). Thus, it seems that liquidity measures that rely on more detailed transaction data can provide important additional information, based on this perspective.

Table 10 shows the results for this analysis, presenting the six specifications. In regressions
(1) to (5), we use each of the liquidity measures in turn, plus all trading activity variables and product characteristics, to explain the round-trip costs. When we add just one individual proxy to the regression analysis, we find that the imputed round-trip cost, the effective bid-ask spread and the price dispersion measure are the best proxies, with R2 values of around 50% to 60%, whereas the Amihud and Roll measures slightly increase the R2 to around 40% compared to regressions without liquidity measures. When adding all the liquidity measures to the regression equation, in regression (6), we obtain an R2 of 67%, i.e., the explanatory power increases considerably when we include all these proxies. We consider this level of explanatory power quite high, given the rather diverse instruments with potentially different liquidity characteristics and the low number of trades per security and day, in general. We get similar results (not reported here) when explaining the effective bid-ask spread with liquidity measures using less information. Thus, we find evidence that liquidity measures using more detailed data can be proxied reasonably well by similar measures using less data. We further discuss this issue in the next section and analyze the importance of the disclosure in the context of pricing.

And correlation with yields?

Analyzing the effect of the trading activity variables in the full model, we find economically significant results only for the trading interval: An increase in the trading interval by one standard deviation is associated with an increase in the yield spread of 15 bp. The information contained in the other trading activity variables, e.g., traded volume, seems to be adequately represented by the liquidity measures. However, more important are the results for the product characteristics. The most relevant variable in the full model turns out to be the coupon. A one-standard-deviation higher coupon results in an increase of 137 bp in the yield spread. Thus, the coupon rate has the highest explanatory power of all the variables, indicating that a higher coupon is also associated with higher credit risk for certain products, in particular when there is no credit rating available. The amount issued shows important effects as well, where a one-standard-deviation increase leads to an 19 bp decrease in the yield spread: Larger issues have lower yield spreads. The maturity of a structured product is related to the yield spread as well, indicating that longer maturities are associated with somewhat lower spreads. However, compared with the other product characteristics, the maturity is of minor importance. Overall, the full model has an R2 of 69.9% with significant incremental explanatory power shown by the liquidity measures. Thus, liquidity is an important driver of yield spreads in the structured product market; therefore, the dissemination of trading activity information is important, given the size and complexity of this market.

And they conclude:

Exploring the relation between the various liquidity proxies and the depth of disseminated information, we find that product characteristics or variables based on aggregated trading activity, by themselves, are not sucient proxies for market liquidity. The dissemination of the price and volume of each individual trade is important for the quantification of liquidity effects, particularly for explaining yield spreads. However, we also provide evidence that liquidity measures that use additional dealer-specific information (i.e., trader identity and sell/buy-side categorization) can be efficiently proxied by measures using less information. In our regression analysis, we find that liquidity effects cover around 10% of the explained variation in yield spreads. Thus, the dissemination of trading activity is essential, given the trade volume and complexity of this market. These results are important for all market participants in the context of OTC markets, as it allows establishing an understanding of the information content contained in the disclosure of trading data.

FAIR Canada Picking Our Pockets Again

October 18th, 2014

The Canadian Foundation for Advancement of Investor Rights (FAIR Canada) has announced (back in August, actually, but I don’t spend a lot of time refreshing my knowledge of them):

the receipt of significant new funding from both the Ontario Securities Commission (OSC) and the Investment Industry Regulatory Organization of Canada (IIROC).

The OSC has provided a $2.5 million contribution toward FAIR Canada’s fundraising campaign. The OSC’s contribution comes from funds collected from monetary sanctions and settlements.

“We are thrilled that the OSC has again demonstrated its strong support of FAIR Canada’s work through a substantial funding contribution,” said Neil Gross, Executive Director of FAIR Canada. “FAIR Canada has developed an ambitious fundraising plan and we are grateful to lead donors like the OSC and Stephen Jarislowsky for getting our campaign off to a terrific start.”

Earlier this year, FAIR Canada announced that one of its long-standing directors, Stephen Jarislowsky, had made a $2 million contribution which challenged FAIR Canada to raise at least an additional $4 million to provide a $6 million endowment fund.

“The OSC’s contribution will go a long way to meeting this challenge and will help to provide a sustainable basis of funding for the organization going forward. FAIR Canada encourages like-minded individuals and organizations to contribute to our campaign,” said Gross.

From this one-time commitment of funds by the OSC, $500,000 will be allocated to cover day-to-day operating expenses and $2 million will be placed in trust with the FAIR Canada Jarislowsky Endowment Fund for long-term funding of the organization.

“On behalf of the board of directors of FAIR Canada, we would like to express our sincere thanks to the OSC for its generous financial support and its support of our activities,” said FAIR Canada board Chair Ellen Roseman. “FAIR Canada provides an important voice in the policy development process and we thank the OSC for recognizing the value of our work. With this new funding we will continue to be able to fulfill our mission.”

FAIR Canada also announced today that, with IIROC’s final payment under its second round of funding totaling $900,000, IIROC’s funding commitment has now been completed.

IIROC has played a pivotal role in supporting FAIR Canada since FAIR Canada’s inception in 2008. “FAIR Canada thanks IIROC for this grant and for the generous financial support they have provided throughout the past six years,” said Gross, noting that IIROC had supplied FAIR Canada with very substantial original funding and had made additional contributions pursuant to a 2012 agreement.

FAIR Canada was founded by ex-regulators and currently trumpets its staff of lawyers; they receive cash from the regulatory slush funds. Nice work, if you can get it.

TRACE and the Bond Market

October 18th, 2014

Paul Asquith, Thomas R. Covert and Parag Pathak have written a paper titled The Effects of Mandatory Transparency in Financial Market Design: Evidence from the Corporate Bond Market:

Many financial markets have recently become subject to new regulations requiring transparency. This paper studies how mandatory transparency affects trading in the corporate bond market. In July 2002, TRACE began requiring the public dissemination of post-trade price and volume information for corporate bonds. Dissemination took place in Phases, with actively traded, investment grade bonds becoming transparent before thinly traded, high-yield bonds. Using new data and a differences-in-differences research design, we find that transparency causes a significant decrease in price dispersion for all bonds and a significant decrease in trading activity for some categories of bonds. The largest decrease in daily price standard deviation, 24.7%, and the largest decrease in trading activity, 41.3%, occurs for bonds in the final Phase, which consisted primarily of high-yield bonds. These results indicate that mandated transparency may help some investors and dealers through a decline in price dispersion, while harming others through a reduction in trading activity.

Proponents of TRACE argue that transparency makes the corporate bond market accessible to retail clients, enhances market integrity and stability, and provides regulators greater ability to monitor the market. They reason that with the introduction of transparency, price discovery and the bargaining power of previously uninformed participants should improve (NASD 2005). This in turn should be reflected in a decrease in bond price dispersion and, if more stable prices attract additional participants, an increase in trading activity (Levitt 1999).

Opponents of TRACE object to mandatory transparency, saying that is unnecessary and potentially harmful. They argue that “transparency would add little or no value” to highly liquid and investment grade bonds since these issues often trade based on widely known US Treasury benchmarks (NASD 2006). They further argue that if additional information about trades was indeed valuable, then third‐party participants would already collect and provide it, a view that dates back to Stigler (1963). Opponents also forecast adverse consequences for investors since, if price transparency reduces dealer margins, dealers would be less willing to commit capital to hold certain securities in inventory making it more difficult to trade in these securities. The Bond Market Association argued that the adverse effects of transparency may be exacerbated for lower‐rated and less frequently traded bonds (Mullen 2004). Lastly, opponents saw TRACE as imposing heavy compliance costs, particularly for small firms who do not self‐clear (Jamieson 2006). Thus, opponents argue that market transparency reduces overall trading activity and the depth of the market. Not surprisingly, similar arguments for and against transparency have resurfaced in response to the recent introduction of the Dodd‐Frank’s post‐trade transparency requirements for swaps (Economist 2011).

With all respect to the various debaters, and while recognizing that the above is an extremely quick summary of their thoughts, I have to say that all the quoted arguments miss the mark. The fundamental question is: what is the corporate bond market for? I claim that the purpose of the corporate bond market is to allow issuers to access capital at as little cost as possible; therefore, all regulation related to the bond market should be first examined through the lens of ‘what will this do to new issue spreads?’. While this is not the only thing to be addressed, it is the most important thing and it is something I rarely see addressed.

It was addressed, however, in a 2012 comment letter to FINRA from SIFMA:

Issuers face the ultimate risk from decreases to market liquidity since the public dissemination of trade information, as a general matter, makes broker-dealers less willing to take risk on large size trades. A reduction in liquidity will cause institutional investors to demand greater yield from issuers (to compensate for the reduced liquidity), or to simply refuse to buy new issues in meaningful size. Therefore, a careful balance between transparency and the preservation of liquidity must be struck. Data shows that dealers have recently chosen to (or been forced to, in the case of rules like the Volcker Rule) put capital to work elsewhere. This means that institutional investors will face greater difficulty selling a larger sized amount of an issue. Pre-TRACE, and pre-financial crisis, dealers provided a much larger outlet where they would take the risk temporarily while they worked to uncover a buyer. This outlet has been much reduced in recent years, due to a combination of regulation and other market structure issues. The real liquidity differential for larger vs. smaller “on the run” amounts has been meaningfully amplified, and eliminating caps on disseminated volumes would exacerbate this problem. At a much more specific level, it is more difficult to issue securities in smaller sizes when participant’s transactions are immediately made public and expose exact amounts taken down by particular investors. An increase in the dissemination caps will increase the threshold where these securities issuances are somewhat more challenging, and disproportionately harm smaller issuers. In each case, the macro and the granular, the result is a higher cost of capital for issuers.

Letting that issue slide for a moment and returning to Asquith, Covert and Pathak:

FINRA implemented TRACE in Phases because of concerns about the possible negative impact of transparency on thinly traded, small issue and low‐credit rated bonds. Examining issue size across all Phases, we find that trading activity decreases more for large issue size bonds, but that the reduction in price dispersion is uncorrelated with issue size. Credit ratings, however, matter for both trading activity and price dispersion. High‐yield bonds experience a large and significant reduction in trading activity, while the results are mixed for investment grade bonds. High‐yield bonds also experience the largest decrease in price dispersion, but price dispersion significantly falls across all credit qualities. Therefore, the introduction of transparency in the corporate bond market has heterogeneous effects across sizes and rating classes.

Price dispersion also decreases due to TRACE. This decrease is significant across bonds that change dissemination in Phases 2, 3A, and 3B, but is largest, 24.7%, for Phase 3B bonds. This finding is also robust across different measures of price dispersion and alternative regression specifications. Moreover, event studies show that the fall in price dispersion occurs immediately after the start of dissemination. It is important to note, if the transparency introduced in Phase 1 affects bonds that become transparent in subsequent Phases, our estimates are probably lower bounds on TRACE’s overall impact.

There are several welfare implications of increased transparency in the corporate bond market. One consequence is that it may change the relative bargaining positions of investors and dealers, allowing investors to obtain fairer prices at the expense of dealers. The reduction in price dispersion should allow investors and dealers to base their capital allocation and inventory holding decisions on more stable prices. Therefore, the reduction of price dispersion likely benefits customers and possibly, but not necessarily, dealers.

The implications of a reduction in trading activity are not as clear. Whether a reduction in trading activity is desirable depends on why market participants trade. A decrease in trading activity may be beneficial if much of the trading in a bond is unnecessary “noise” trading. On the other hand, if most trading is information‐based, a decrease in trading activity may slow down how quickly prices reflect new information. In addition, if the decrease in trading activity is the result of dealers’ unwillingness to hold inventory, transparency will have caused a reduction in the range of investing opportunities. That is, even if a decline in price dispersion reflects a decrease in transaction costs, the concomitant decrease in trading activity could reflect an increased cost of transacting due to the inability to complete trades.

Our results on the corporate bond market have two major implications for the current and planned expansions of mandated market transparency. The implicit assumption underlying the proposed TRACE extensions and the use of TRACE as a template for regulations such as Dodd‐Frank is that transparency is universally beneficial. First, it is not clear that transparency for all instruments is necessarily beneficial. Overall, trading in the corporate bond market is large and active, although, as seen, not comparable across all types of bonds. Many over‐the‐counter securities are similar to the bonds FINRA placed in Phase 3B. That is, they are infrequently traded, subject to dealer inventory availability, and trading in these securities is motivated by idiosyncratic, firm‐specific information. Therefore, the expansion of TRACE‐inspired regulations, such as those for 144a bonds, asset‐ and mortgage‐backed securities, and the swap market, may have adverse consequences on trading activity and may not, on net, be beneficial.

Second, our results indicate that transparency affects different segments of the same market in different ways. As a consequence, our results provide empirical support for the view that not every segment of each security market should be subject to the same degree of mandated transparency. Both academic commentators (French et al., (2010), Acharya et al. (2009)) and leading industry associations (e.g., Financial Services Forum, et al., (2011)) have articulated this position. Despite these recommendations, the expansion of transparency by the Commodity Futures Trading Commission (CFTC) in various swap markets, i.e. interest rate, credit index, equity, foreign exchange and commodities, in December 2012 and February 2013 was immediate for all swaps in those markets. This stands in sharp contrast to FINRA’s cautious implementation of TRACE in Phases. The fact that the effect of transparency varies significantly across categories of bonds within the corporate bond market suggests that additional research will be required to evaluate the tradeoffs associated universal transparency in other over‐the‐counter securities.

There is one assertion in the above with which I take particular issue: One consequence is that it may change the relative bargaining positions of investors and dealers, allowing investors to obtain fairer prices at the expense of dealers. Long time Assiduous Readers will probably be snickering to themselves, having determined that I am probably going to complain about the use of the word “fairer”, since I don’t know what “fair” means, and they’re quite right.

By “fair”, I assume the authors mean “at a price closer to the dealers’ cost than otherwise”, but that is not necessarily “fair” when examined in a broader context.

Suppose, for instance, that you are a bond dealer – horns, pitchfork, cloven hooves and all – and somebody asks you to bid on something. OK, so you do – but why do you? The answer, of course, is to make a profit and as a rational economic actor you seek to maximize your profit. But you’re not seeking to maximize your profit on every possible transaction or even to maximize your gross profit; you’re seeking to maximize the annual profit of your desk expressed as a fraction of your capital. This has a number of implications; for instance, you might give regular customers who deal exclusively with you slightly better prices than the other ones, simply to ensure that these guys never have any reason to consider going anywhere else.

But the most important consideration for purposes of this discussion is the question of maximizing profitability as a fraction of capital. That’s what determines the firm’s capital allocation and that’s what determines your bonus. And for a single given transaction, we can write the following equation:

Desirability = (Sell – Buy) / (Capital * Days)

Where the gross profitability is the Sell price less the Buy price, Capital is the amount of capital used when financing the position and Days is the number of days you have to hold the thing in inventory until it’s sold (or bought, if the position was initiated with a short sale). In this equation I am ignoring the Carry (the difference between the yield of the bond and the cost of financing it); I’m also ignoring default risk and lots of other considerations, with the objective of keeping this simple.

Under the pre-TRACE regime, one way to maximize trade desirability was, obviously, to maximize the difference between your Sell and Buy prices, but TRACE makes that a lot more difficult; after all, that’s the whole point of TRACE and Asquith, Covert and Pathak have made a solid argument that it is not happening to the same extent under TRACE as it was in the good old days. So for practical purposes, when the dealer is putting a price on taking a position, he is doing so with the knowledge that gross profit is capped.

The “Capital” term in the simplified equation is set by regulation and the bond desk has no control over it. As far as they’re concerned, it’s a constant.

Therefore, in order to increase the Desirability of the trade, the only avenue left open to the dealer is Days, which is inversely related. If they can make their $0.50 per bond profit in one day, that’s a whole lot better than if it takes a month! Therefore, when taking a position, they will concentrate their energies on how they will flatten their position. This will, of course, be much easier if they offer their position to a potential buyer at an attractive price. Therefore, I claim, TRACE will lead to the initial seller getting a really lousy price for his bond, which is turned over in short order to the ultimate buyer who gets a really good price.

There is evidence for this in the secondary GIC market, which has to be one of the most ridiculously infinitesimal markets in the world, but which exists at the major dealers not so much as a money-maker, but as a service to clients. Some GICs are transferrable and the dealer will buy them from the owner at a really, really lousy price – I think the bid yield is about 150bp over the market rate, but I confess I’m not too sure of that. I have a major dealer’s offering sheet from 2012 on hand, which is headed by the statement: “ALL Secondary GICS offered at approximately +50bps over today’s Best GIC Rates (on the [Redacted] System”

This is a great deal for buyers, and I have often recommended to clients that they open accounts at a major dealer for the purpose of access to new issues and access to secondary GICs. And why I am I saying this? Because I think the buyer will get a “fair” price, just like teacher talked about in kindergarten? Hell, no! It’s because I think the buyer will get a really good price, courtesy of the really, really shitty price that was offered to the poor sucker who needed to cash his GIC early.

Now this example comes from a market that barely exists, but I claim that it shows in sharp relief the problem with TRACE – which is that it encourages prices that are not “fair”, but prices that really stick it to the liquidity seeker in order to reward both the interim and the ultimate liquidity supplier.

And I will claim that this cannot be considered a Good Thing. This is an increase in the cost of liquidity, which leads to a decline in liquidity, which leads to an increase in the liquidity premium demanded for holding a position, which leads to higher coupons required from the issuer at issue time. And I claim that this is a Bad Thing because the purpose of the corporate bond market is to allow issuers to source cheap capital.

Note that none of these assertions has been tested, but for now we’ll call it the Shitty Price Hypothesis. It has the advantage of actually providing a causal mechanism for the reduction of trading experienced under TRACE: say you’re a portfolio manager and there’s a wave of redemptions. You have to raise cash. In the old days, you could utilize the opportunity to rebalance and improve your portfolio slightly. Got too much junk in the portfolio? Fine, raise the cash by selling it. But if all you see is stink-bids, you’re almost forced to move up the credit quality ladder and sell something more liquid. Thus, TRACE has made it more difficult for you to do your job.

To be fair, the authors make what might be an indirect allusion to this at the end of their Section 6:

In addition, the bond market is a dealer market, so dealer inventory will affect trading levels and the potential impacts of TRACE. Dealers only hold inventory in those bonds with sufficient trading activity to cover their carry cost. Thinly traded bonds may require dealers to have higher spreads to cover their holding costs. Since TRACE reduces price dispersion significantly, the benefit of holding bonds in inventory decreases. TRACE reduces price dispersion the most for high‐yield bonds, so the incentive to reduce inventory is strongest for those bonds. Thus, lower trading activity in high‐yield bonds post‐TRACE may be the result of a supply‐side response of dealers.

Another paper I found while updating myself on academic commentary about TRACE was by Rainer Jankowitsch, Amrut J. Nashikkar and Marti G. Subrahmanyam, titled Price Dispersion in OTC Markets: A New Measure of Liquidity:

In this paper, we model price dispersion effects in over-the-counter (OTC) markets to show that in the presence of inventory risk for dealers and search costs for investors, traded prices may deviate from the expected market valuation of an asset. We interpret this deviation as a liquidity effect and develop a new liquidity measure quantifying the price dispersion in the context of the US corporate bond market. This market offers a unique opportunity to study liquidity effects since, from October 2004 onwards, all OTC transactions in this market have to be reported to a common database known as the Trade Reporting and Compliance Engine (TRACE). Furthermore, market-wide average price quotes are available from Markit Group Limited, a financial information provider. Thus, it is possible, for the first time, to directly observe deviations between transaction prices and the expected market valuation of securities. We quantify and analyze our new liquidity measure for this market and find significant price dispersion effects that cannot be simply captured by bid-ask spreads. We show that our new measure is indeed related to liquidity by regressing it on commonly-used liquidity proxies and find a strong relation between our proposed liquidity measure and bond characteristics, as well as trading activity variables. Furthermore, we evaluate the reliability of end-of-day marks that traders use to value their positions. Our evidence suggests that the price deviations are significantly larger and more volatile than previously assumed. Overall, the results presented here improve our understanding of the drivers of liquidity and are important for many applications in OTC markets, in general.

Using a volume-weighted hit-rate analysis, we find that only 51.12% of the TRACE prices and 58.59% of the Markit quotations lie within the bid and ask range quoted on Bloomberg. These numbers are far smaller than previously assumed. Since these marks are widely used in the financial services industry, our findings may be of interest to financial institutions and their regulators.

The evidence that so many actual prices are outside the pre-trade quote is supportive of the Shitty Price Hypothesis, but more detail is needed!

And now 144a (exempt) bonds are being TRACEd:

Corporate-bond brokers may face a squeeze on profits as regulators start publishing prices for almost $1 trillion of privately sold debt, if the past is any guide.

The Financial Industry Regulatory Authority, seeking to “foster more competitive pricing,” plans to start disseminating trading levels for securities issued under a rule known as 144a on its 11-year-old Trace system within the next year. That means the notes, sold only to institutional investors, will face the same price transparency as publicly registered corporate bonds for which buyers demand half a percentage point less in yield spreads. Brokers typically are paid larger fees from higher-yielding debt.

Firms from Knight Capital Group Inc. to Gleacher & Co. and Pierpont Securities LLC sold or shuttered credit units this year as corporate-bond trading volumes fell to the lowest proportion of the market on record and smaller price swings shrink potential profit margins.

Stamford, Connecticut-based Pierpont, one of the dealers started after the 2008 collapse of Lehman Brothers Holdings Inc. decided to exit the high-yield bond and loan business this month. New York-based Gleacher said in April that it was exiting fixed-income trading and sales. Knight in Jersey City, New Jersey, sold its credit-brokerage unit to Stifel Financial Corp., according to a July 1 statement.

Jefferies Group LLC, the investment bank owned by Leucadia National Corp., said profit plunged 83 percent in the three months ended Aug. 31 as trading revenue fell to the lowest since the depths of the financial crisis.

October 17, 2014

October 17th, 2014

Today’s Toronto Stock Exchange Screw-Up regards BCE.PR.K:

BCEPRK_141017
Click for Big

Look that that quote on the Toronto Stock Exchange – which, together with its Venture sibling, comprise Canada’s premier equities markets: 8.55-21.35, a small spread of only $12.80. Since the Exchange refuses to sell me closing quotes, instead selling me “Last” quotes, I’m not sure what the actual closing quote might have been – since I don’t feel like spending extra money to get the detail of the last few minutes. So it might have been a post-4pm bid cancellation, it might be another shining example of how TSX’s Market Maker system maximizes market efficiency. I’ll let youse guys figure it out.

Anyway, HIMPref™ threw up when I tried to tell it the reported bid price, so I have substituted $20.50, which is the bid on Pure.

Meanwhile, Capital Power, proud issuer of CPX.PR.A, CPX.PR.C and CPX.PR.E, issued a profit warning:

Capital Power Corporation (Capital Power, or the Company) (TSX:CPX) provided an update today on its third quarter 2014 financial results and its financial guidance for 2014.

In the third quarter of 2014, Capital Power’s owned plants achieved strong plant availability of 97% which was consistent with expectations. However, due to lower plant availability at the acquired Sundance PPA units, other plant derates, and lower Alberta wind generation, overall electricity generation production was below expectations. Accordingly, the Company expects third quarter net income and funds from operations to be below previous expectations. These non-Capital Power operated plant outages occurred primarily in July coinciding with a period of pricing volatility with Alberta spot power prices averaging $122 per megawatt hour (MWh) in the month compared with $45 per MWh in August and $24 per MWh in September. As a result, with commercial production 100% sold forward in July, the Company was required to cover a short market position that negatively impacted its portfolio optimization position in the quarter.

The Company has updated its outlook for funds from operations for the year, which are now expected at the low end of the forecast range of $360 million to $400 million.

In addition, net income for the third quarter of 2014 was negatively impacted by a non-cash write-down of deferred tax assets of $73 million. The write-down related to the accounting impact of U.S. income tax loss carry forwards that can no longer be recognized for accounting purposes based on the Company’s current long term forecast for U.S. taxable income. The forecast showed a decline in taxable income over the latter years of the forecast. For income tax purposes, these U.S net operating losses do not expire until the 2027 to 2033 period. Accordingly, they retain economic value and could result in the Company recording deferred tax assets in the future. The Company continues to pursue U.S. contracted power opportunities and the U.S. business development pipeline is active. Importantly, the write-down is a non-cash item and has no impact on operations or other key performance measures.

Capital Power will be releasing its third quarter 2014 results on October 24, 2014 after the TSX market closes.

I haven’t seen anything yet from the Credit Rating Agencies as to whether or not they consider this serious.

Advantaged Preferred Share Trust (PFR), which made it into one of my articles, was confirmed at STA-2 (middle) by DBRS:

DBRS has today confirmed the stability rating of STA-2 (middle) to the retractable units (the Units) issued by Advantaged Preferred Share Trust (the Trust).

Proceeds from the Trust’s offerings have been used to enter into a forward agreement with Royal Bank of Canada in order to gain exposure to a diversified portfolio of preferred shares (the Portfolio). The forward agreement provides Unitholders with a return equivalent to a direct investment in the Portfolio. The Portfolio is passively managed by RBC Dominion Securities Inc. (the Administrator).

On August 26, 2010, DBRS assigned a stability rating of STA-2 (middle) to the Units issued by the Trust in accordance with the new methodology for rating structured income funds published in May 2010. The rating was mainly based on the strong credit quality of the Trust’s preferred share portfolio and the limited flexibility of the Administrator to invest in riskier assets. The rating was last confirmed on October 18, 2013, at STA-2 (middle).

Since October 2013, the performance of the Portfolio has been fairly stable. The weighted-average yield of the Portfolio is approximately 5.01% as of September 30, 2014. The Trust’s current net income (including a regular additional payment under the forward agreement to offset operating expenses) covers 98.6% of the distribution paid out to Unitholders. As a result, the rating of STA-2 (middle) on the Units has been confirmed. The main constraints to the rating are the interest rate risk of the Portfolio and the potential for capital losses and reductions in income resulting from underlying securities being called for redemption by their respective issuers.

We’re always hearing about Chinese property buyers in Vancouver, but they’re all over the States as well:

This flood of money, arriving from China despite strict currency controls, has helped the city build a $20 million high school performing arts center and the local Mercedes dealership expand. “Thank God for them coming over here,” says Peggy Fong Chen, a broker in Arcadia for many years. “They saved our recession.” The new residents are from China’s rising millionaire class—entrepreneurs who’ve made fortunes building railroads in Tibet, converting bioenergy in Beijing, and developing real estate in Chongqing. One co-owner of a $6.5 million house is a 19-year-old college student, the daughter of the chief executive of a company the state controls.

Arcadia is a concentrated version of what’s happening across the U.S. The Hurun Report, a magazine in Shanghai about China’s wealthy elite, estimates that almost two-thirds of the country’s millionaires have already emigrated or plan to do so. They’re scooping up homes from Seattle to New York, buying luxury goods on Fifth Avenue, and paying full freight to send their kids to U.S. colleges. Chinese nationals hold roughly $660 billion in personal wealth offshore, according to Boston Consulting Group, and the National Association of Realtors says $22 billion of that was spent in the past year acquiring U.S. homes.

It was a strong day for the Canadian preferred share market, with PerpetualDiscounts gaining 6bp, FixedResets winning 32bp and DeemedRetractibles up 11bp. Volatility was high, highlighted by losing Floating Rate issues and winning FixedResets. Volume was well above average (so there, prefQC!).

HIMIPref™ Preferred Indices
These values reflect the December 2008 revision of the HIMIPref™ Indices

Values are provisional and are finalized monthly
Index Mean
Current
Yield
(at bid)
Median
YTW
Median
Average
Trading
Value
Median
Mod Dur
(YTW)
Issues Day’s Perf. Index Value
Ratchet 3.13 % 3.12 % 22,087 19.40 1 -1.2768 % 2,668.1
FixedFloater 0.00 % 0.00 % 0 0.00 0 -1.8156 % 3,987.2
Floater 2.99 % 3.19 % 63,568 19.26 4 -1.8156 % 2,677.3
OpRet 4.04 % 2.55 % 102,222 0.08 1 0.0394 % 2,733.6
SplitShare 4.31 % 4.10 % 85,562 3.82 5 -0.4050 % 3,143.0
Interest-Bearing 0.00 % 0.00 % 0 0.00 0 0.0394 % 2,499.6
Perpetual-Premium 5.49 % 0.14 % 72,621 0.08 18 0.1977 % 2,452.7
Perpetual-Discount 5.33 % 5.15 % 95,278 15.11 18 0.0647 % 2,587.0
FixedReset 4.22 % 3.69 % 169,202 16.44 75 0.3170 % 2,550.3
Deemed-Retractible 5.03 % 2.54 % 102,803 0.44 42 0.1062 % 2,557.9
FloatingReset 2.55 % -4.24 % 62,578 0.08 6 0.1830 % 2,550.8
Performance Highlights
Issue Index Change Notes
BAM.PR.C Floater -2.83 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 16.48
Evaluated at bid price : 16.48
Bid-YTW : 3.20 %
BAM.PR.B Floater -2.59 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 16.53
Evaluated at bid price : 16.53
Bid-YTW : 3.19 %
BAM.PR.K Floater -2.25 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 16.53
Evaluated at bid price : 16.53
Bid-YTW : 3.19 %
BAM.PR.E Ratchet -1.28 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.56
Evaluated at bid price : 23.97
Bid-YTW : 3.12 %
PVS.PR.B SplitShare -1.20 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2019-01-10
Maturity Price : 25.00
Evaluated at bid price : 24.80
Bid-YTW : 4.71 %
FTS.PR.H FixedReset 1.24 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 20.36
Evaluated at bid price : 20.36
Bid-YTW : 3.72 %
POW.PR.G Perpetual-Premium 1.27 % YTW SCENARIO
Maturity Type : Call
Maturity Date : 2021-04-15
Maturity Price : 25.00
Evaluated at bid price : 26.23
Bid-YTW : 4.75 %
MFC.PR.F FixedReset 1.31 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 22.35
Bid-YTW : 4.50 %
SLF.PR.I FixedReset 1.36 % YTW SCENARIO
Maturity Type : Call
Maturity Date : 2016-12-31
Maturity Price : 25.00
Evaluated at bid price : 26.15
Bid-YTW : 2.21 %
IFC.PR.A FixedReset 1.84 % YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2025-01-31
Maturity Price : 25.00
Evaluated at bid price : 23.83
Bid-YTW : 4.19 %
FTS.PR.K FixedReset 2.04 % YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.22
Evaluated at bid price : 25.03
Bid-YTW : 3.55 %
Volume Highlights
Issue Index Shares
Traded
Notes
TD.PR.O Deemed-Retractible 331,587 TD crossed blocks of 300,000 and 13,400, both at 24.98, and sold 15,000 to Nesbitt at the same price.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2014-11-30
Maturity Price : 25.00
Evaluated at bid price : 24.98
Bid-YTW : 4.00 %
BMO.PR.W FixedReset 231,516 RBC crossed 50,000 at 25.02. Nesbitt crossed blocks of 50,000 and 100,000 at the same price.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.21
Evaluated at bid price : 25.16
Bid-YTW : 3.64 %
MFC.PR.M FixedReset 182,128 Nesbitt crossed 33,200 at 25.35; TD crossed 99,900 at the same price.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2019-12-19
Maturity Price : 25.00
Evaluated at bid price : 25.33
Bid-YTW : 3.78 %
TD.PR.S FixedReset 171,393 Nesbitt crossed 45,000 at 25.15; RBC crossed 105,400 at the same price.
YTW SCENARIO
Maturity Type : Hard Maturity
Maturity Date : 2022-01-31
Maturity Price : 25.00
Evaluated at bid price : 25.16
Bid-YTW : 3.14 %
CU.PR.D Perpetual-Discount 155,587 Desjardins crossed 153,400 at 24.04.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.66
Evaluated at bid price : 24.04
Bid-YTW : 5.15 %
RY.PR.I FixedReset 151,473 Nesbitt crossed 33,000 at 25.57, then another 111,100 at 25.63.
YTW SCENARIO
Maturity Type : Call
Maturity Date : 2019-02-24
Maturity Price : 25.00
Evaluated at bid price : 25.58
Bid-YTW : 3.09 %
NA.PR.W FixedReset 133,285 Scotia crossed 50,000 at 24.75, then bought 12,100 from National at the same price.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.05
Evaluated at bid price : 24.75
Bid-YTW : 3.73 %
TD.PF.B FixedReset 100,325 RBC crossed blocks of 29,900 and 32,000, both at 25.04.
YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 23.23
Evaluated at bid price : 25.15
Bid-YTW : 3.63 %
There were 40 other index-included issues trading in excess of 10,000 shares.
Wide Spread Highlights
Issue Index Quote Data and Yield Notes
PWF.PR.P FixedReset Quote: 22.16 – 22.75
Spot Rate : 0.5900
Average : 0.3901

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 21.71
Evaluated at bid price : 22.16
Bid-YTW : 3.56 %

BAM.PR.B Floater Quote: 16.53 – 16.99
Spot Rate : 0.4600
Average : 0.2650

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 16.53
Evaluated at bid price : 16.53
Bid-YTW : 3.19 %

BAM.PR.C Floater Quote: 16.48 – 16.91
Spot Rate : 0.4300
Average : 0.2626

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 16.48
Evaluated at bid price : 16.48
Bid-YTW : 3.20 %

CIU.PR.C FixedReset Quote: 20.42 – 21.23
Spot Rate : 0.8100
Average : 0.6474

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 20.42
Evaluated at bid price : 20.42
Bid-YTW : 3.65 %

SLF.PR.I FixedReset Quote: 26.15 – 26.55
Spot Rate : 0.4000
Average : 0.2442

YTW SCENARIO
Maturity Type : Call
Maturity Date : 2016-12-31
Maturity Price : 25.00
Evaluated at bid price : 26.15
Bid-YTW : 2.21 %

TRP.PR.C FixedReset Quote: 20.63 – 21.20
Spot Rate : 0.5700
Average : 0.4149

YTW SCENARIO
Maturity Type : Limit Maturity
Maturity Date : 2044-10-17
Maturity Price : 20.63
Evaluated at bid price : 20.63
Bid-YTW : 3.80 %