Continued from Part 6 . . . Assuming Greater Risk
What follows are additional examples of some of the techniques the Bond Geeks use to goose their returns. For clarity, the examples below will use hypothetical data and do not adjust for taxes, inflation, or other trifles that might obscure the larger point.
Longer Dated Bonds Are Riskier: The bond rating agencies (ex: Standard & Poor’s, Moody’s, and Fitch) use unique letter grades to indicate riskiness. Everything else being equal, as a general guideline, longer dated bonds are associated with higher default rates. After all, a 5 year bond has more time to go bad than a 90 day Treasury bill. To offset this risk, in a normal world the longer dated bond would reasonably have a higher (offsetting) yield. If everything goes well, an investor can increase her expected yield by buying longer maturities.
Lower Rated Bonds Are Riskier: A riskier (sub-investment grade) bond would also be expected to pay a higher interest rate than an investment grade bond, even if their maturity dates were the same. If a bond investor requires the higher yield, she will have to accept a greater probability of loss. That’s reflected in the historical data (see chart, below). Graphing the risk structure in this way lets us view the default history on a spectrum of bonds, ranging from investment grade to “high yield” while maintaining the same (in this case, 5 year) maturity date. The default rate is interesting.
Example 5 Year Avg. Default Rates: Corporate Bonds (Moody’s Ratings)
Presume five-year AAA corporate bonds are being offered at a yield of 1.5% (an annual interest payment of $15 on a $1,000 bond). Being investment grade, the bonds are considered to have low risk levels. The expected yield, in this example, is 1.5% minus <1% (i.e., probably an unmeasurable number above zero but beneath the margin of error) for a net-of-risk yield of approximately 1.5%, or $75 over the five year term.
This particular investor, however, cannot abide $75 in exchange for locking up her money for 5 entire years. She’s a woman-of-the-world: she wears a Burberry keffiyeh with her Michael Kor’s and lunches with the girls twice a week. She requires a higher yield because: expenses.
She is considering buying a “B” rated (sub-investment grade) corporate bond currently paying 3%, and scheduled to mature in five years. The bonds are issued by the XYZ Widget Company. Sadly, “B” rated bonds have an anticipated loss of about 20%, meaning that an investment of $1,000,000 is statistically likely to incur a loss of $200,000. For any particular portfolio it might be more or it might be less, but minus 20% is the line of best fit. How might she compare the expected results of purchasing investment over sub-investment grade, or vice versa, over a five year hold?
Why Total Return is Important: An Example of AAA vs B Rated Bonds: A: At a purchase price of $1,000,000, AAA (investment grade) bonds paying 1.5% annual interest will provide $15,000 in interest payments over each of the next 5 years (a total of $75,000 in interest). At the end of those five years the bond matures and the investor receives the return of her principal (the entire $1,000,000 originally invested). Her total return (on her money and of her money), will be $1,075,000.
B: If she bought sub-investment grade B rated bonds instead, that $1,000,000 of B rated issues would certainly be paying a higher interest rate (say, 3%), but would also be subject to a default rate equivalent to 20% of principal. That’s a huge loss, and it leaves only $800,000 to earn interest. At 3% annually the interest comes to $24,000 per year, or $120,000 over the five years. Her total return under this scenario would be $800,000 (return of principal upon bond maturity) plus $120,000 interest. She would receive a total return of $920,000 in exchange for a $1,000,000 investment. Compared to what she could have made on the AAA bonds, that’s a disappointing $155,000 loss ($1,075,000 minus $920,000). Yuck.
The Counter-Party: Somebody Always Makes Money: The person who bought those B-rated issues from our keffiyeh-clad investor was an adventurous bond speculator, recognizable by his gold incisor. He’d just read that the Board of Directors had approved the computerization of XYZ Widget’s sales and inventory system. Up to this point, the company closed for three days every quarter to hand count widgets, but with computerized inventory the counting of widgets could be done almost effortlessly: open the computer, click “Sales and Inventory”, click “Update”. That’s it. No more shutting down 3 working days out of 60 every quarter (ie, 5% of business days) to hand count stuff. Even better, the company could monitor if red widgets were selling faster and determine whether they should take the paint crew off the blue-widget line and put ‘em on the red. Given these (and other) benefits, the company could reasonably be expected to stop hemorrhaging cash and achieve higher profitability.
Once the Board’s decision becomes generally known, the speculator anticipates that XYZ bonds will be rated more highly and thus sell at a materially lower yield, for a strong net gain to him.
- Know thyself.
- An investor who speculates can lose her keffiyeh.
- On the other hand, a speculator who knows what he’s doing can occasionally do quite well.
Speculating is Not Investing
A day or two ago someone was browsing at Barnes & Noble and while passing through the “Business” section noticed a young man of a transitional age, old enough to have graduated but not yet old enough to have done anything useful, engrossed in a book on day trading. Day trading is where the speculator both buys and sells his position on the same day. There are different approaches to day trading. One is to rely on monetizing small changes (up or down) in the price of the underlying asset. Usually (but not always) the day trader takes advantage of leverage to maximize his gain, if leverage is available. Sometimes several purchase / sales (round trips) are made during the day, but typically they are all closed out by the end of market hours. It’s a highly speculative process, so sensitive to small changes that it’s deemed excessively risky to keep a position overnight. Something may happen in a foreign market that adversely affects the domestic market. Hence, “day trading”. A day trader’s grail is to use high leverage when buying low and to sell after lunch at a huge profit.
Day trading is not the exclusive preserve of the risk-seekers. The investment divisions of large banks also do a lot of trading, some of it very short term. Some bank trading desks will buy an asset on one market (say, the New York) and immediately arbitrage it on another market (say, the Hong Kong). The gain is tiny but “riskless”, and large positions are taken. It all adds up. A major bank or private investment fund, with liquid assets and institutional memory, can do things beyond the ability of most individual day traders.
George Soros “broke the bank of England” in 1992 when he made $1 billion by selling the British pound short.
Andrew Krieger was trained at Solomon Brothers before taking a position at Banker’s Trust in 1986. Over the next year he proved himself to his employer’s satisfaction, and his trading capital limit grew enormously, to $700 million. (For reference, the standard capital limit was $50 million). Krieger used 400:1 leverage to short the New Zealand dollar. At one time, his short position was bigger than the entire New Zealand money supply. He closed out the trade with a gain of $300 million dollars.
Soros and Krieger are examples of wealth gained by leveraged trading positions. There have also been gobsmacking losses. In 2012 the London branch of JPMorganChase lost $9 billion by being on the wrong side of credit default swaps.
Barings Bank was formed in London in 1792, originally to service the wool trade. The bank prospered and in 1802 lent the money for the Louisiana Purchase, adding 828,000 square miles of territory to the young United States. Barings Bank collapsed in 1995, brought low by the losses of their derivatives trader, Nick Leeson, of the Singapore office.
Sometimes, the day trading mentality infects otherwise responsible people. Years ago, I was told the story of an elderly widow whose husband left her much money. This was before the expansion of low cost index funds and sector investments that made expensive mega brokerage houses largely redundant. Back then, it was considered prudent to have one’s portfolio managed by a ranking executive in a reputable stock brokerage. And that was this widow’s situation. She had a large part of her money run by one of the promising young vice-presidents of a major house. One day, he took her to lunch and told her that holding stocks for the long term was foolish. The real money was made elsewhere: she should become a short-term trader. “I know what will happen tomorrow”, he said, “I do not know what will happen in ten years.” When the widow returned home she closed her account. That broker’s single sentence caused her to realize that he had the risk-seeking soul of a day trader and was only pretending to advise on investments. And the fact that the broker’s commission checks would benefit mightily if she made her account churnable was not totally lost on the widow.
To invest successfully, a person needs to know both (a) what will happen and (b) when it will happen. It is not terribly difficult to know what will happen: very simply, things that are now low will cycle high; high things will cycle low. That is the nature of things. But knowing what will happen is seldom sufficient to warrant an investment if when is uncertain. What to invest in and when to do it: if a person could consistently get these two things right they’d be rich enough to no longer be a broker: they’d be someone’s favorite client.
When does not have to be calendar specific, like the maturity date on an investment grade bond. When can be general, as in “Interest rates are at a 40 year peak, so over time I expect they will decline and my investment will become more valuable”, or even “this asset historically rises with inflation”.
The brokerage vice-president thought of “when” as being with the present news cycle, and sometimes that works. But a lot of times it doesn’t. The widow’s advantage was that she saw “when” not as a fixed point in the future but as a trend line. “Over time, the line will go up. This investment will compound better than the available alternatives”. While she seldom bought individual companies anymore, sometimes she bought shares in the two or three top companies in a given sector. As an example only, years ago when it became clear that computization was the future, she bought both Microsoft and Apple. After the Great Recession of 2008-09, when it became obvious that the Federal Reserve would save the economy almost no matter what, she bought shares in each of the largest three or four domestic banks. She could not imagine an economy without banking services, so she thought her purchase was a safe investment. And when she had investible funds but no individual stocks were particularly compelling, she bought the S&P Index Fund when she thought it was favorably priced.
The S&P 500 is an index of the largest publically held companies in America, and is a simulacrum of the market as a whole. The data are persuasive. Over the last forty-five years or so, the Price / Earnings Ratio of the S&P 500 has run from 7.22 (Oct-Dec 1976) to 122.14 (Apr-Jun 2009), and back to 13.72 in the third quarter of 2011.
Some of this extraordinary spread was for cause. In the Apr-Jun period, 2009, the market’s P/E ratio was an unusual 122.14 due to the housing crash and consequently low corporate earnings while share prices remained elevated. By 2011 the ratio of stock prices to corporate earnings had recovered to 13.72.
Parsing the historical data offered by the S&P, a grid can be developed that reflects a relationship (example below) between the P/E ratio of the S&P and annualized returns for the following 10 years: the lower the P/E Ratio, the higher the returns. This relationship, being consistent, is probably more robust than the actual numbers, which are unlikely to be repeated.
|Market P/E Ratio||Annualized Return Next 10 Yrs|
|8.6 – 11.9||12%|
|12 – 15||9.4%|
|15.1 – 19||8.5%|
|19.1 – 26.9||4.8%|
Note: The past is no indication of future performance.
Excluding the second quarter of 2009, which was unusual due to the housing crash (a P/E of 122!), assets historically purchased when the S&P 500 Price/Earnings ratio is over 19 tend to appreciate very little over the following decade. Assets purchased at a P/E below 15 historically generate a 10 year annualized return of 9% or thereabouts.
Uber-low P/Es across the entire market don’t happen very often. They are seen with individual stocks, of course, but individual stocks could be priced low for a reason. It is unusual to find entire markets priced well below their mean.
The widow liked to add to her S&P 500 Index fund when the market was less than 15 P/E. When that happened, she expected an annual return over the following decade of 10% or so. Ten percent per year means that portion of her portfolio invested in the S&P 500 Index would double every seven years. Twenty-eight years would provide for four doublings: $100,000 invested for the first seven years would grow to $200,000; after 14 years it would be $400,000, 21 years equals $800,000, and twenty-eight years along the initial investment of $100,000 could be projected to grow to $1,600,000.
What is important here is that she stopped investing for herself a long time ago. For the last few decades she’s been investing for her posterity. She wished her own grandparents had been as thoughtful.
This article is for informational purposes only and is not intended as professional advice. For specific circumstances, please contact an appropriately licensed professional. Klarise Yahya is a Commercial Mortgage Broker specializing in difficult-to-place mortgages for any kind of property. If you are thinking of refinancing or purchasing real estate Klarise Yahya can help. For a complimentary mortgage analysis, please call her at (818) 414-7830 or email info@KlariseYahya.com.