Archive for April, 2008

Post Take-Over Announcement Plays-Part II

Wednesday, April 30th, 2008

Yesterday we looked at buying stocks on take-over companies just after the news of the proposed acquistion was announced. We saw that if one had bought the stock at the closing price on the day of the announcement one could reap an average annual rate of return of around 8.7%. (The data was based on analysis of 57 companies during the period between March through July of last year.) At the end of the article, I wondered if one could do better by buying at the opening price. I crunched through the numbers this morning and here are the results:

You can see that you’ll do better in general by buying at the open, but not because the opening price was lower than the closing price. Actually, the data showed that half the time the opening price was better and half the time the closing value was better. What made the difference were the three times when the opening price was significantly lower than the closing price, by more than 5%. There were three other times when the opening price exactly matched the closing price.

There was one instance where the opening price was significantly lower than the closing price. This happened on May 1st, 2007 when Newscorp announced their take-over bid for Dow Jones. Since take-overs of this type are unusual occurrences, I removed it to see what the numbers would like. The results are indicated by the Special Case in the above table. You can see that the standard deviation becomes a more reasonable value, although the total returns are reduced. But hey, an average annual return of 9.5% ain’t too shabby.

So if you’re looking to play this strategy, the moral of the story is to buy on the open. Another way to play it in shaky markets is to wait a week or two and see if the stock drops. Even take-over targets are subject to market direction and if you think the overall market is due for a breather, sit tight and wait for the price to drop.

But the mo’ bettah play is to hunt for potential take-over targets. That’s where you’ll make the really big bucks. In an upcoming blog we’ll look at the criteria inherent to take-over candidates and see if we can put together a portfolio of potential targets. Ta-ta!

Post Take-Over Announcement Plays

Tuesday, April 29th, 2008

One of the holy grails in trading is to find companies that may be potential take-over targets because if one can correctly identify them, the rewards can be considerable. A take-over announcement can boost the acquiree’s stock price by 10%-50%, although share increases in the 10%-25% range are usually the norm. That’s nice work if you can get it, but it’s in the getting them where lies the rub. Factors that go into trying to figure out what companies are ripe for the picking include low price to book value, companies in sectors that are undergoing consolidation, and technical factors such as unusual options volume which can be a sign that people are trading on inside information. (It’s illegal but it’s done every day.)

Correctly identifying a potential take-over candidate can be very time-consuming and ultimately unrewarding. More often than not you will be wrong which could wind up costing you a lot of money on many failed speculations. But I got to thinking, what about playing stocks after the take-over has been announced? Can one make any decent money on them, or will it only amount to chump change?

To test out my hypothesis, I looked at 62 companies that announced they were being taken-over between March through July of last year. I set up my simulation to buy each stock at the closing price of the day the take-over was announced. Then I checked the date the stock was acquired and the price at which it was sold. The results actually surprised me. Before I present them, I have to say that the data is based on 57 companies. Those are the ones where the acquisition was completed. In two instances, the deals fell through completely. In one case, the merger was extended and is still pending. In the last two cases, the mergers are still pending but are on shaky ground because of regulatory hurdles in one and a reduced financial outlook in the other.

So, without further ado, here’s what I found:

1. The average time for a merger to complete (from announcement to the final take-over date) was about 4 months with a standard deviation of around 2 1/2 months. This means that 68% of most mergers occur between 1 1/2 and 5 1/2 months. (For you statistical wonks out there, the median was around 3 months.)
2. The average gain/loss per stock was +2.9% over the holding period. This result assumes that an equal number of shares of each stock were purchased at the closing price on the day of the take-over announcement. (This value would be different if an equal dollar amount were bought.) The standard deviation of the gain/loss was 2.75% which means that two-thirds of the stocks ended up gaining between 0.15% and 5.65%. There was one stock that gained 17% because the original offer price was subsequently raised. Two stocks actually lost value. One was due to a merger battle, and I couldn’t find a reason for the other.
3. If we assume that the average holding time for each stock is four months, then this results in an average annual return of 8.7% (2.9% x 3).

You may yawn at an 8.7% return, but basically this is done without incurring a lot of risk. So far, only two of the proposed mergers have fallen through, which is a 3% failure rate. Not bad. There aren’t many portfolios out there that can boast a number even close to being that low. A major drawback to this strategy is that M&A activity is at the mercy of the markets. This means that during down markets such as now and especially during the current credit crisis, M&A activity is reduced. During bull markets, this certainly isn’t the best strategy to use to increase your returns, but it’s still not a bad one especially for those of you who are highly risk averse.

Final Note: The above data was derived from the closing prices, but if you pounce on these at the open, you can probably do a bit better. Hey, that’s not a bad idea. For tomorrow, I’ll look into this further and see if there’s a measurable difference in the rate of return between using the opening price and the closing price, so stick around!

Cooking Tools #4: Cup and Handle Bases

Monday, April 28th, 2008

A useful tool that traders use to determine when a stock is breaking out is the Cup and Handle (C&H) base. William O’Neill, the founder of the daily financial newspaper Investor’s Businees Daily (IBD), was the first to coin the phrase in his book How to Make Money in Stocks which is a valuable resource that every serious investor should read. This chart pattern forms the basis of O’Neill’s CANSLIM method. It’s a proven method of identifying stocks that are breaking out and one that deserves a closer look. If you’re unfamiliar with this chart pattern, read on. My point here is to acquaint you with the pattern so that you’ll know what to do should it arise in the chart of one of your stocks or if you see it while perusing the charts of others.

The Cup & Handle Pattern
The basic pattern looks like a rounded cup with a smaller handle and represents a triple top. The shape typically looks like a drawn-out, rounded U shape rather than a sharp V. You want to look at the overall cup shape since minor fluctuations within it are usual. The pattern can last anywhere from two months to two years, In general, the longer the cup takes to form, the stronger it will breakout. The usual correction from the top of the cup (point A on the chart below) to the bottom (point B) typically varies from 12%-33%. Downturns greater than that suggests that there is something fundamentally wrong with the stock and should be regarded with caution. The left side of the cup is accompanied by an overall decrease in volume (there may be the occasional volume spike in there due to some sort of news) , and the right side of the cup is formed on gradually increasing volume (point C).
The handle is formed after the base is completed where the price returns at or close to the left side of the cup. Traders see that the price is returning to its resistance level and begin exiting their positions, thus forming the right side of the handle (C to D on the chart). Note that the volume decreases during this period. You should note, too, that the bottom of a true handle should never be more than the low point of the base. It’s okay if the right side of the cup is lower than the left side, but if it’s too much lower, then the subsequent breakout needs to be stronger. The recent daily chart of Volterra Semiconductor (VLTR) illustrates the cup and handle pattern.
How to play it: On daily charts, handles typically take one to two weeks to complete their formation. The way to play this pattern is to wait until the handle has formed and the stock breaks the high point of the cup’s right side (point C) or what O’Neill terms the pivot point. This breakout must occur on heavier than normal volume (at least 50% heavier) for it to be a compelling buy. If the stock breaks out on mega-volume, this is a signal that institutions are pouncing on it and you should be, too.

1. You may have been patiently following the stock and noting its pattern, but it is foolhardly to buy the stock before it reaches its pivot point. Why? Many stocks just do not make it back to their pivots and end up declining in value. You need to wait for the stock to prove its strength before jumping in.
2. Many stocks breakout without ever forming handles. A handle isn’t completely necessary but stocks that form cups without handles are more prone to failure.
Ways to play it: When you see a handle forming, set a price alert at the pivot. When the stock hits that point, you can do any of the following:
1. Buy the stock by entering a quarter or a third of your intended position at the breakout. Wait several days or weeks to gauge the strength of the price movement. If the general trend of the stock is up, keep adding to your position on price dips (such as when it hits a supporting moving average).
2. Buy call options in increments mentioned above. You can also sell out-of-the-money puts to finance your calls.
3. Call ratio backspreads. This is a fancy term for an easy concept. Here, a lower strike call is sold (usually at a strike close to the pivot point) and two (or more) higher strike calls are purchased. I won’t get into the details of this strategy here, but I wanted to mention it because it’s a favorite of many options traders who use it to play breakouts. The beauty of this strategy is that it sometimes can be put on for a credit (or a very small debit) while minimizing margin. Should the stock move a lot in either direction, a profit is realized (if the stock was put on for a credit). Even if the stock doesn’t move, the amount that one risks is usually less than if one had purchased the stock outright. If you’re not familiar with this strategy, you can check it out using the options links on this page.

As always, it’s prudent to paper trade any of these strategies for a few months before putting your own hard-earned cash on the line. For more information, check out Investor’s Business Daily and Bill O’Neill’s book. IBD has daily charts that include stocks that are currently forming cup and handle bases.

Day-trading C&H patterns: The cup and handle pattern isn’t just the province of long-term investors; many day-traders use this pattern on five minute or even one minute charts. Usually when a stock makes a dramatic climb at the beginning of the day, it spends several hours testing its new level. This is when you might see a cup and handle form. If the overall market is still trending up, the stock may make a breakout late in the day. Sometimes the stock will break out right before the close. This is a good time to buy as the odds favor a strong breakout gap when trading resumes the next day.

The Market & The Brokers

Friday, April 25th, 2008

Today we’re stepping out of the ivory tower and wading back into the market moat. I was hoping that today’s market action would be a follow-through on recent upward movement, but unless there’s an end of day rally, it doesn’t look like we’re going to get it.

Last week the volatility index (VIX), a measure of market fear or risk, dropped below its 200dma and has remained there since. That’s a good thing. For my taste, however, it needs to start moving below 20 and stay there before I’ll be convinced that the worst is over. Also, the S&P (SPX) has been toying with its 1400 resistance level, and it will need to break that on heavy volume for me to be a true believer.

There are two high notes. One is that the Dow Transports (DTX), considered to be a leading indicator of market direction, did break through major resistance of 500 last week and has been in an upward trend since the middle of March. In fact, all of the major indices have been trending up since then, as I’m sure you know. The other bright spot is that the Q’s (QQQQ), the Nasdaq 100 tracking stock, also broke its $46 resistance level. I think that if the market can hold through the next Fed meeting on interest rates scheduled for release this coming Wednesday, we may have the beginning of another bull market, albeit a tepid one considering that energy prices continue to rise, unemployment is rising, and the consumer is spending less. These are all factors that will figure into the equation so be careful about backing up your truck because you just might hit a brick wall.

Being wishy-washy is a way to cover one’s butt and there’s a lot of financial pundits out there who are doing just that, but this time I’m giving them a break since the financial crystal ball is very cloudy indeed. One ray of hope that the market may be turning up is to look at the current movement of the major brokerage firms. They’ve been rising stealthily for the past month, and if recent earnings news is any indication, their futures may indeed be bright.

Ever since the four-eyed credit-crunch ogre began to rear its ugly head early last summer, the brokers got whacked, declining 25-50% in value. Most of them put in a double bottom this January and rushed back up only to get beaten down again. Then came March 17th when JP Morgan shocked the investment community by offering a ridiculously low $2/share for Bear-Stearns. The news tanked all of the brokerage stocks, but since then they’ve been staging a rather nice comeback. Three of the major firms, Goldman-Sachs (GS), Morgan Stanley (MS), and Lehman Bros. (LEH), all just reported earnings that beat estimates. Only Merrill-Lynch (MER) reported earnings that were basically in-line. However, that didn’t seem to hurt the stock much as it, too, has been on the rise.

So should you be a buyer of these brokerages? Except for Goldman, I would wait. All of these stocks are still trading below their 200dmas. I’ll be more interested in them when they break overhead resistance on heavier than normal volume: MS at $55, LEH at $50, and MER at $50-$51. I think it was Guy Adami on CNBC’s Fast Money who said about a month ago that Goldman is a screaming buy. (His words.) The company reported good earnings on March 18th and yesterday broke its all-important $180 resistance level. Today, it’s flirting with its 200dma. You go, Guy! (I really wanted to say that.)

Knight Capital (NITE) is my other favorite. The firm surprised Wall Street last week with better than expected earnings, and recently broke its $18 resistance level. The stock is still climbing higher, trading up over a buck since Monday. [Note that most of the major brokerage stocks pay a low dividend except for Knight which pays none.]

What about the online brokers? Most of them have been rising in sync with the institutions, although their charts aren’t quite as compelling. Perhaps this reflects the fact that they didn’t beat earnings estimates as most reported in-line, except for Etrade (ETFC) which reported worse than expected earnings. Right now I’d stay away from this stock, at least until the company can trim the fat and turn around to profitability which analysts think may take at least two quarters. The star of the group is Interactive Brokers (IBKR) which blew out estimates today causing share prices to jump 10%. This is the best banana of the bunch. Both Schwab (SCHW) and TD Ameritrade (AMTD) are rising, but I can’t really say if they’re good buys at this level. Their performance will probably depend on the direction of the overall market.

If you’re like many investors whose portfolios got whacked this year, maybe one way you can get back at your broker is to buy them. Yeah, that’ll show ’em!

MPT-Part IV: Asset Class Correlation & Fund Proxies

Thursday, April 24th, 2008

Today is the final installment of Professor Pat’s dissertation on Modern Portfolio Theory (MPT). In it, he’ll be looking at the correlation among asset classes and will also provide you with fund recommendations that you can use as proxies with which to construct your own portfolio. But before I hand this over to the Professor, I want to thank him for providing us with his insight into MPT and for generating these tables which involved research trips to the local university’s business library and many hours of computer modeling. I am deeply grateful for his valuable time, knowledge, and effort.

Tomorrow we will return to our regularly scheduled programming. Take it away, Pat!

Correlation Among Various Asset Classes
Additional asset classes added for consideration should preferably be uncorrelated or negatively correlated to the other asset classes for best results. The relation between how asset classes or securities move relative to each other is defined by what is known as the Pearson correlation coefficient. The table below shows the Pearson correlation coefficients for each of the asset classes to one another. A value of +1. indicates perfect correlation while a value of -1. would reveal total negative correlation in the sense that when one asset goes up in value the other would go down in the same proportion, and vice versa. A value of zero demonstrates no correlation between the two asset classes; that is, they behave independently. (Note: The Pearson coefficient assumes a Normal distribution of data.)

As expected, large stocks and small stocks are highly correlated to each other. That is, when one class goes up or down in value there is a good chance that the other class also goes up or down commensurately. On the other hand Long Term Government bonds and REITs behave as two uncorrelated processes totally independent of each other. What this table confirms is that there is a sufficient lack of correlation between the various asset classes to present a suitable set of alternatives from which to compile a portfolio that can be counted on to behave according to the precepts of MPT.

Let’s now look at a comparison of the returns and risks of an optimally allocated portfolio with those that contains just one asset class. The table below shows the average annual return and volatility of the individual asset classes over the 1927-2007 time frame for the expanded list of asset classes.

We can see, for example, that a portfolio holding only large stocks would yield an average annual return of 12.3% but do so with a standard deviation (our measure of risk) of 20.0%. Compare that with an optimally allocated portfolio (given in the chart in yesterday’s blog) where the return is 13% but the risk has been reduced to 19.0%. Similarly, a completely conservative portfolio of safe U.S. Treasuries would return an average of 3.8% annually with a standard deviation of 3.1%. We saw yesterday that an optimum conservative portfolio can return a higher 4.2% at an even lower risk level of 3.0% just by adding long-term corporate bonds and some REITs to the mix.

There are many interesting observations to be gleaned from these tables such as the high volatility of REITs and the counterintuitive performance of Long-Term Corporate bonds versus Long-Term U.S. Government bonds where Corporate bond returns display the expected risk premium but the volatility is actually lower. Perhaps a closer examination of the actual composition of the comparative fund holdings might provide an explanation for this.

Asset Class Proxy Recommendations
Earlier, I recommended Vanguard as an excellent family of mutual funds. I do not work for Vanguard and know them only as a satisfied customer. An investor interested in forming a portfolio along the lines of the nine asset classes discussed here will find the following Vanguard funds as suitable proxies for them. Vanguard does not currently offer an International Bond fund so a T. Rowe Price no load fund with a reasonable expense ratio is listed. (Dr.K Note: Vanguard isn’t the only firm offering these type of funds. Check Morningstar for other comparable funds and note transfer fees among fund families.)

The 500 Index Fund (VFINX) for Large Stocks.
The Small Cap Index Fund (NAESX) for Small Stocks.
The Long-Term Investment Grade Fund (VWESX) for Long-Term Corporate Bonds.
The Long-Term Treasury Fund (VUSTX) for Long-Term Government Bonds.
The Intermediate-Term Treasury Fund (VFITX) for Intermediate-Term Government Bonds.
The Treasury Money Market Fund (VMPXX) for U.S. Treasury Bills.
The REIT Index Fund (VGSIX) for U.S Real-Estate Securities.
The Total International Stock Index Fund (VGTSX) for International Stocks.
The T. Rowe Price International Bond Fund (RPIBX) for International Bonds.

In summary, we have shown that diversification provides real measurable benefits and that you, the investor, can use the tools of MPT to quantitatively measure reward versus risk in forming an investment portfolio that is suitable for your circumstances.

Thank you for allowing me to introduce you to the concepts of Modern Portfolio Theory.

Note from Dr. Kris: Pat has expressed a desire to provide one or two future articles on the evolution of MPT into PMPT, or Post Modern Portfolio Theory which challenges some of the assumptions inherent in MPT. (Don’t worry, the information provided here is still valid.) We’ll be looking forward to further installments. Thanks again, Professor Pat!

Modern Portfolio Theory-Part III: Extended Asset Allocation

Wednesday, April 23rd, 2008

Today is the third installment of Professor Pat’s dissertation on Modern Portfolio Theory (MPT). In it, he’ll be including three other uncorrelated asset classes that can be added to a portfolio that will not only increase returns, but lower risk as well. The floor is all yours, Prof. Pat!

Adding international stocks, bonds, and REITS to your portfolio
In Part II of this article (yesterday) I presented some options for optimum portfolios using six basic asset classes. Today we will examine the effects of adding more alternative asset classes to the list of portfolio options. We will see in quantitative terms how broadening the diversification of an investment portfolio not only increases returns but also lowers risk. Any additional asset classes added for consideration should preferably be uncorrelated or negatively correlated to the other asset classes for best results. The following asset classes meet those criteria:

1. Real Estate Investment Trusts (REITs) performance per the Dimensional Fund Advisors (DFA) U.S. Real Estate Securities Index.
2. International Large Company Stocks per the DFA International Value Index portfolio of non U.S. Stocks.
3. International Bonds composed of the DFA Five-Year Global Fixed Income Index Fund.

Using annual total return performance data for each of these asset classes from 1927 through 2007 to match the data as for the other basic six asset classes as described yesterday, I applied the mathematics of MPT to come up with the following table:

In comparing this table to the one from Part II (with fewer asset classes), you can see that the minimum return has been slightly increased with no increase in the standard deviation which is our measure of risk. Actually, for all levels of portfolio return the risk level is the same or reduced. By adding the proper mix of international stocks and bonds to a portfolio measurably decreases risk. In Part II we looked at the 11% return level. You can see the addition of international stocks reduces portfolio risk from 14.9% to 14.1%. Note that there is no downside to this–the lower risk is obtained at no cost or penalty. The portfolio at this level contains about 7% Large-cap US stocks, 21% Small-cap US stocks, 4% Long-Term Corporate bonds, 43% Intermediate-Term Government Bonds, and 25% International stocks. The overall decline in the recommended level of Large U.S. stocks in favor of Small U.S. Stocks and International Stocks is noteworthy.

From the above table we see again that Long-Term Government Bonds are an unattractive component in an investment portfolio. No wonder the 30-year treasury was abandoned!

One thing this table is telling us is that maintaining a component of international stocks or bonds in your portfolio is very beneficial. While they may not be completely uncorrelated with the movement in the US stock and bond markets, they do serve as a currency hedge against a declining dollar.

So, how do you, the investor, take in all this data and decide which level of risk and return and hence which portfolio allocation is suitable for your personal situation? One question to ask yourself is how much draw-down can you tolerate? (Draw-down is the financial term for decline in value.) There are a number of criteria you should consider in answering that question.

1. Time horizon and cash needs: These dictate how much time you can allow your portfolio to compound in value. If you won’t need to tap into the assets of your portfolio for many years means that you can take greater risks, but you must also be willing to accept short term declines. If your tolerance for risk is low, then choose a slightly more conservative allocation. Folks nearing retirement should limit their risk and opt for the most conservative allocations. The precise allocation depends on how much money they’ll need to withdraw from their accounts and how long they’ll need their portfolio to last.
2. Standard of living: The size of the portfolio relative to the needs of the investor to maintain their living standard also plays a part in the determination of suitable allocations. A portfolio sized far in excess of the retirement needs of the investor can be more aggressive. Conversely a smaller portfolio that constitutes a safety net or is targeted for specific needs such as a child’s college education or wedding should be allocated more conservatively with greater surety of being intact if or when it will be needed.
3. Current income level: The level of current income outside of the portfolio contributes to the investment allocation decision as well. If the investor is able to earn a living from income without touching the portfolio then again a more aggressive stance can be assumed. The reliability of this income is another contributing element. Those more secure in their employment can assume more risk; those who are unsure should not.
4. Risk tolerance: Your attitude toward risk and your emotional ability to see your nest egg temporarily drop in value is important as well. Investors should ask themselves if they will tend to panic and precipitously sell out when things go south thereby missing out on subsequent recoveries. Again, those with tendencies toward pessimistic gloom and doom should remain conservative and comfortable accepting lower expectations.
5. Investment knowledge: The last criterion is your degree of investment knowledge. Greater knowledge and your ability to understand the various reasons why things go up, why they go down and what to do or not to do about it allows a greater risk tolerance.*

The portfolio allocation decision is as much art as science. MPT has provided the science component but it is ultimately up to you to properly and rationally assess your individual needs and expectations in making the final selections. If you don’t think you have the ability to make these decisions on your own, I would suggest finding a good financial advisor who can help. (If you don’t know any, ask your friends or family members for recommendations.)

The next and final installment of this article will discuss asset class correlation, the validation of optimum allocations over portfolios dedicated solely to individual asset classes, and recommendations for specific mutual funds that can serve as suitable proxies for these asset classes. Hang in there, for the last installment is chock full of good stuff!

*Note from Dr. Kris: Savvy investors with a lot of money in their portfolio can elect to include futures and/or options trading strategies to lower their portfolio risk while increasing returns. For one example, see my April 17th blog on using derivatives to add value while reducing risk in your portfolio.

Modern Portfolio Theory-Part II: Asset Allocation

Tuesday, April 22nd, 2008

Today we continue with the column of guest blogger Professor Pat who provides us with the second installment of his treatise on Modern Portfolio Theory. Yesterday’s blog provided an introduction to Modern Portfolio Theory (MPT) and today he’ll be discussing how to optimize your portfolio using the results of MPT. Although the Professor doesn’t like to toot his own horn, I just want to say that some of the data presented in the table today and in the next installment are derived from historical data run through the Professor’s own MPT algorithms and won’t be found anywhere except for perhaps in brokerage firms. So lead on, Professor Pat!

Portfolio Construction & Optimum Asset Allocation
Last time I introduced the concept of Modern Portfolio Theory (MPT) and described what it was and why it might be of interest to a certain type of investor. This time we will look at some actual data and examine the results.

The core philosophy behind MPT is to construct a portfolio of uncorrelated (or relatively uncorrelated) asset classes. Two assets are said to be uncorrelated if they react differently to market events. For example, the stock market and the bond market are two asset classes that are relatively uncorrelated as bonds usually perform better when the stock market is suffering and vice versa. The point of MPT is to construct a portfolio consisting of relatively uncorrelated assets in ratios that will give the investor the return he expects while minimizing risk.

Ibbotson & Associates, a firm with expertise in asset allocation and recently acquired by Morningstar, publishes a yearbook where they present time series data for six major U.S. asset classes back to the late 1920’s. These classes are:

1. Large U.S. Stocks as currently represented by the S&P 500 Index.
2. Small U.S. Stocks defined by the Dimensional Fund Advisors (DFA) Microcap Portfolio.
3. Long-Term Corporate Bonds measured by the Citigroup High-Grade Corporate Bond Index.
4. Long-Term Government Bonds, currently a 20-year Treasury Bond.
5. Intermediate-Term Government Bonds, a 5-year Treasury Note.
6. 30-day U.S. Treasury Bills.

Using annual total return performance data for each of these individual asset classes from 1927 through 2007 and applying the mathematics of MPT to that data, I was able to construct the following table.

To use this table, you must choose the desired rate of return incorporating your tolerance for volatility or risk. (The standard deviation, the second column in the above table, is the measure of portfolio risk.) You should not merely chase the highest potential return; you should also consider your ability to accept years in which sharp draw-downs in the overall portfolio value may occur. This is the major tenet of MPT.

Investors nearing retirement, when they will start to withdraw investment funds, will need to avoid the possibility of those declines happening just when they will be selling. In that case an aggressive allocation should be converted to a more conservative one. For example, the average return from the most conservative portfolio would be 4.1% which would be achieved with a portfolio of 1.7% Small Stocks, 5.4% Long-Term Corporate Bonds, and 92.9% Treasury Bills. This represents the safest possible portfolio in that it provides the smallest variation in return from year to year. In any one year there is an approximate 68% chance (see the last installment of this article) that the actual return will be within one standard deviation. In this case, the return can be expected to vary between 1.1% and 7.1% (4.1% +/- 3.0%) In other words, the chance of a decline in overall portfolio value over any given year is small.

A more aggressive investor with a longer time horizon, such as a person in his 20s -30s, might choose a higher yielding allocation but he must also be willing to accept the risk of short-term market declines or intermediate-term lackluster returns. He must do this so that he will be properly invested during those times where the previously underperforming assets become out-performers.

Small stocks have historically produced the highest overall returns over the long haul as indicated by the table. We can see that an average annual return of 17.3% can be achieved by a portfolio that is 100% invested in small-cap stocks. This return, though, is realized at the cost of very high volatility. In 1973, for example, the loss in the small stock asset class was about 31% followed in the next year by another 20% hit. The following nine years, however, saw a nice recovery with a whopping average annual appreciation of 36%. Regardless of your risk tolerance, the table does indicate that some exposure to small-cap, high-growth stocks is advantageous.

It is interesting to note that the above table recommends that Long-Term Government Bonds are not an attractive investment to hold in any portfolio. Who knew?

Most investors will want to choose an allocation that moderates the volatility risk while still providing a healthy average return. One such selection is at the 11% level. For such a return there are chances of small declines in any one year but reliable gains over time for most years. The portfolio would consist of approximately 27% Large stocks, 30% Small stocks, 16% Long-Term Corporate Bonds, and 26% Intermediate Term Government Bonds. This allocation has the advantage of including one additional asset class over the 10% level for greater diversification.
If the reader is interested in following a course of action along the lines of MPT using these asset classes I recommend the Vanguard family of funds for their low expense ratios and respectable performance. (Note: I have no affiliation with Vanguard other than being a satisfied customer.) It’s also good to note that index funds have very low to no year-end capital gains distributions which means your taxes on them will be minimal to none.

In my next installment, I’ll discuss the effects of expanding the number of asset classes to include international stocks and bonds as well as real-estate investment trusts (REITs). See you tomorrow!

Modern Portfolio Theory: An Introduction

Monday, April 21st, 2008

In last Thursday’s blog we looked at the concepts of alpha and beta in terms of maximizing portfolio returns while minimizing risk. Those concepts are an integral part of a larger subject known as Modern Portfolio Theory, or MPT. This theory determines how investors should allocate their holdings to achieve a specified return with the least amount of risk. Since my knowledge of MPT is minimal, I thought I’d turn over today’s blog to Professor Pat, a colleague of mine who is well acquainted with MPT and uses it to allocate his own investment portfolio. For the record, Pat is not technically a professor in the usual sense of the word. He doesn’t teach MPT on the university level but his knowledge on the subject is so vast that he probably could. I’m using the term here in its second definition as one who professes or instructs. So, without further ado, I’ll let Professor Pat take it away and perhaps we’ll all learn something from his elegant discourse.

Modern Portfolio Theory (MPT): The Background
Thanks, Dr. K, for letting me present the ideas behind MPT. Since this is such a large subject, I’m going to split it up into several segments. Today, I want to describe the theory in general and its importance to you, the investor. In subsequent columns, I’ll present concrete strategies using results that have not been published anywhere that you can easily implement in constructing your own investment portfolio.

Modern Portfolio Theory (MPT) was first conceived by Harry Markowitz in 1952. For his inspiration and hard work he was awarded the 1990 Nobel Prize in Economics. Markowitz proposed that investors should be concerned not just with investment returns but also with investment risk, and put forth a strategy on how to achieve optimum performance using a mathematically derived allocation of asset classes.

MPT asserts that investors could and should balance the returns they receive on their investment portfolios with the risks those investments present. As such, and for the first time, a way to actually quantify the notion of risk was available. The new idea was that risk could be equated with volatility or the variation in returns from one time period to the next. The beauty of MPT is that it was also now possible to take this one step further and mathematically determine an optimum investment portfolio that delivers the desired long-term rate of return while simultaneously minimizing risk. The benefits of portfolio diversification in terms of risk reduction could now be mathematically derived. [Note from Dr. K: The math used in MPT is quite hairy and is beyond the scope of this discussion. For those of you who are mathematically inclined, you can research this further. Wikipedia gives a good overview of the math used in MPT. Good luck!)

An investment portfolio consists of various asset classes, some of which appreciate and some of which may depreciate within any specified time interval. The rate of change, or volatility, in the value of each class varies as well. Some investments move up and down together, some move up when others move down, while others are completely uncorrelated to each other. MPT takes advantage of this fact to determine not only which investments to invest in but how much of each you should hold relative to one another.

MPT can also be thought of as a type of portfolio insurance. As an investor, you hope that all of your investments will increase but you also know that this is an unrealistic expectation. MPT insures your portfolio against unreasonable losses by holding asset classes that can counteract losses in one class with gains in another. The way to achieve this is to select investment vehicles that are uncorrelated with each other. (More on that later.) A properly diversified portfolio also includes relatively low yielding assets (like treasuries) that can be counted on to produce steady and reliable gains. An important assumption of MPT is that the future will, on average, be just like the past.

MPT: The Theory
The techniques that are used in MPT to solve the optimum asset allocation problem is a branch of mathematics known as quadratic programming. There are two inputs to this program: 1. The actual historical returns of the various candidate assets input as a time series, and 2. The desired average rate of return that portfolio is expected to produce. The output of the calculations is the percentage to be ascribed to each asset class so that the entire portfolio will produce the input return while minimizing risk. MPT quantifies that level of risk with a number called the standard deviation.

The standard deviation, denoted in statistical terms by the Greek letter σ, is a number that provides a bracket range for the desired return. One standard deviation represents approximately 68% of the values around the the expected outcome. A basic assumption in MPT is that investment returns follow a pattern known as a normal distribution commonly found in natural processes.* Graphically, it forms a shape that looks like a bell as depicted in the illustration below. For example, if the desired annual rate of return is 10%, MPT might reveal a certain asset allocation strategy that would result in a minimum standard deviation of 11.7%. This means that approximately 68% of the time the actual return in any one year would fall in a range from -1.7% to +21.7%. (10% +/- 11.7%) The normal distribution also tells us that about 95% of the time the return will be the average return plus or minus two standard deviations, or between -13.4% to 33.4% in this example. The image below depicts these concepts. The dark blue region is one standard deviation,and the light blue region extends to two standard deviations. The symbol μ on the image is the average rate of return, or 10% in our example.

MPT is a useful tool for investors who prefer to remain somewhat passive in their investment activities. That is, they are not concerned with market timing. The optimum asset allocation technique tells them that they can remain comfortable with fluctuations in the market and limit their activities to quarterly rebalancing to preserve the correct allocations following increases or decreases in the value of individual assets held.

When we get to presenting the reality of these results, the data will confirm what everyone already knows: there is no such thing as a free lunch. That is, the higher the rate of return you wish to achieve, the more risk you have to be willing to take on. But we will see with numbers just how much more risk we’ll have to take to achieve those higher returns or how much return we need to give up to achieve more safety.

The next installment in this series will present actual results using common investment classes and will show you how to assemble a portfolio needed to achieve your desired rate of return. Stay tuned!

*Dr. K Note: Post-Modern Portfolio Theory (PMPT) challenges this assumption, but for right now, it’s a good-enough one.

REIT Covered Call Portfolio-Update

Friday, April 18th, 2008

In my blog on March 17th, I constructed a portfolio of six high-paying dividend stocks and wrote the April covered calls against them. Since today is options expiration, I want to examine the portfolio and see how we did.

The stocks I chose all had to have dividend yields greater than 3%, pay a dividend between then and today, be optionable, and not be in a down-trend. All of the candidate stocks were REITs (real-estate investment trusts): Avalon Bay (AVB), Cali Realty (CLI), Developers Diversified (DDR), Entertainment Properties (EPR), Essex Property Trust (ESS), and UDR (UDR). I constructed a virtual portfolio of all of these stocks by buying 500 shares of each at the March 17th closing price and writing 5 call contracts on each at the option closing price. The call strikes were either at-the-money (ATM) or slightly out-of-the-money (OTM).
Fortunately, all of the stocks selected did quite well, gaining between 5-15% in value since then. I did make one mistake in selecting UDR. The information that was given to me from a person who shall remain nameless (Dimitri) stated that the UDR dividend was to be paid on April 15th. That was inaccurate as the dividend pay date is April 30th. Since the pay date is later than today, the day of options expiration, I’m not going to include it in this discussion. But if I had owned the stock, it would have returned over 5% with the covered call strategy which is not too shabby.
Here’s how I set up the portfolio:
1. Used end of day data on 3/17 for the stock and options prices.
2. Used middle of the day data today (4/18) for the stock prices (I’m writing this before the close.)
3. Bought 500 shares of each stock and sold 5 April call contracts.
4. Commissions are included ($10/stock trade; $15/options trade).
The following is a chart of the parameters that were used. Note that all prices are on a per-share or per-contract basis.
Since all of our options expired in the money, all of our stocks will be assigned. That means that if we want to own them again, we’ll have to go out and buy more. It also means that we didn’t get to participate in any price movement above the strike price which is unfortunate since all of the stocks did very well.
The next chart shows you the difference in portfolio performance. The first column shows the returns on a portfolio with no covered calls, assuming that you would have sold your stocks today to realize these gains. The second is the covered call portfolio. Note that although the total return is a nice 7% gain, it’s 4% short of the uncovered portfolio.
So what have we learned from this lesson? That covered calls aren’t such a good idea? Well, yes and no. We would have done a lot better if we had waited to sell calls when the stock was making a new high, but if course one never knows when a stock is at a local high or is poised to go higher. Certainly, when the stock is taking a breather is not the best time to cover.
Perhaps a better strategy is to combine the two. That is, when your stocks and the market are moving up, you refrain from covering. During this time you’ll own the stock and collect the juicy dividends. After your stocks have enjoyed a long run-up is when you might consider writing calls. This will offer you some downside protection just in case things start to unravel without digging into your profits.

The point I really want to make here is that paper trading your strategies will allow you to make better investment decisions when you do decide you’re ready to put them into practice. I hope this exercise has done just that.

Alpha & Beta: It’s All Greek to Me!

Thursday, April 17th, 2008

If you watch CNBC or read some of the financial journals, you’ve probably stumbled across the word alpha. Most non-institutional investors don’t know what it means but they should since the attainment of alpha is the goal of every investor, whether he or she realizes it or not. So what is alpha? Alpha is nothing more than the excess return of a stock, portfolio, or fund over a given benchmark. I won’t bore you with the mathematical equation for alpha, but it takes into account the price risk, or volatility of the stock or fund and compares its risk-adjusted performance to a benchmark, usually the S&P 500. The price risk is given by a coefficient named beta. Sometimes you’ll see the beta of a stock listed under the company’s profile. Beta is a measure of a stock price’s volatility as compared with the overall market. Since the S&P is the typical benchmark, it has a beta of 1. A beta of 2.50 represents price movement that is 150% more volatile than the market; a beta of 0.50 represents a movement that is half as volatile as the market. Beta can be viewed as a measure of risk so that riskier stocks such as high-tech stocks typically have beta’s greater than 1 while less risky stocks like utilities have betas less than 1. With me so far? Good.

Now let’s get back to alpha. In the hedge fund world, alpha is of primary importance. Hedge fund managers are rated according to how much alpha their fund generates. (They’re also rated according to their Sharpe ratio which is defined below.) A positive alpha of 1.0 means that the fund outperformed its benchmark index by 1%, and a negative alpha of -1.0 means that it underperfomed it by 1%. Alpha can be viewed as a measure of the fund manager’s ability to generate profits in excess of market returns. This isn’t that easy to do and sometimes the process of seeking alpha requires taking substantial risks which is why a lot of hedge funds that have invested heavily in mortgage-backed debt are in serious trouble right now.

Fund managers are usually paid in accordance to how much alpha their fund generates. The higher the alpha, the higher their fees (usually). Hedge fund managers with stellar alphas and high Sharpe ratios can take up to 50% of the profits! That’s why many of them have homes in the Hamptons worth tens of millions of dollars, bid up oil paintings to ridiculous prices at Sotheby’s, and flitter to and fro on private jets. But hey, if you’re a high net worth individual with money in their funds, you’re probably hob-nobbing with them, too.

If you’re not a part of the jet-set, is there a way that an individual investor can increase alpha without increasing portfolio risk? Yes, via the theory known as “portable alpha.” In essence what this means is that an investor would invest some of his portfolio in securities (or other instruments) that have no correlation with the existing portfolio. (They’re separating beta from alpha.) This typically involves leveraging part of the portolio using futures. I know that most people shy away from futures, but it’s not as formidable as it sounds. Really. Let’s look at an example.

Adding Alpha without Adding Risk
Let’s say you have a portfolio of $200,000 invested in Treasury bonds (which are essentially risk-free) that are currently yielding 4%. You’re not happy with that rate of return and would like to increase it without adding risk. You think that although the S&P has been lousy, things might be looking up and you’d like to invest 30% of your portfolio into the index. You believe that a 10% return on the S&P for this year is reasonable, if not even a bit conservative. So, instead of investing $60,000 into an S&P index fund, a better approach is to buy $60,000 worth of the S&P Emini futures. Although margin requirements for buying futures varies among brokers, we’ll use 10% here. (My broker charges about 7%.) What this means is that you’ll only need $6000 to buy the futures. So what do you do with the leftover $54,000? You buy more treasuries.

These leaves us now with a portfolio of $194,000 in treasuries and $6000 allocated to margin for the futures. At the end of the year assuming everything works out as planned, your rate of return will be 6.9% instead of 4% had you only owned treasuries. (4% x $194000 + 10% x $60000) You’ve increased your return by nearly 3% without adding portfolio risk. (Actually, your return will be slightly less since there’s a built-in premium to futures contracts.)

However, you do take on another risk–that of event risk. If the stock market takes a nasty drop, you might be faced with a margin call in your futures account. In the event that this happens, you’ll need to deposit more money into your margin account. To do this will require you selling some of your T-bonds to make up the difference. If the market corrects and you have now excess capital in your margin account, you can reinvest that into treasuries. Your new projected rate of return will be different and probably less than expected depending on the going T-bill rates.

That’s it for the example. I want to emphasize that I’ve only scratched the surface on the discussion of alpha and beta. People have won Nobel prizes developing these concepts, so take heart if you don’t quite understand them, but be assured that institutions do.

Portable alpha is used regularly by fund managers to add alpha to their funds without increasing risk. They do this by using futures to generate money that they can use to purchase other instruments they feel will generate positive returns, thus increasing alpha. And now, so can you!

The Sharpe Ratio
The Sharpe ratio is a measure of risk-adjusted return. Essentially, the Sharpe ratio tells us whether returns are due to smart investment decisions or are a result of excess risk. The higher the ratio, the safer the strategy. (Sharpe ratios greater than one are considered to be good.) It can viewed as a measure of the fund manager’s consistency. Two funds may have the same alpha, but the one with the higher Sharpe ratio has better risk-adjusted performance. If you’re comparing funds with similar focus and performance, look at their Sharpe ratios. The ones with the highest ratios will be the safer investments, although past performance is no guarantee of future results…