Which Portfolio Would You Rather Have?

Which portfolio would you rather have?

From 1985 – 2008:

Portfolio A
Return: 11.98%
Volatility: 15.60%
Sharpe Ratio: 0.43
Worst Year: -17.99%

or

Portfolio B
Return: 15.23%
Volatility: 9.55%
Sharpe Ratio: 1.04
Worst Year: -2.70%

Seems simple, right? Portfolio B has returns over 3% higher per year than Portfolio A. Portfolio B is roughly 40% less volatile than Portfolio A. The Sharpe Ratio for Portfolio B is more than double Portfolio A and the worst year is far smaller.

Portfolio A is the S&P 500, and Portfolio B is the Harvard Endowment (and Yale performs even better). Both are fiscal year ending June 30th. Many people are complaining about how terrible the Harvard Endowment is doing this year (down 22% versus stocks down around 40%), but over long time frames, the Harvard Endowment is far superior to a buy and hold of the best performing asset class over this time period. (And I have no idea how accurate Harvard has been in marking their portfolio so yes I understand that 22% figure could be revised.)

And before I get shelled with reader comments, please remember that I do not advocate a buy and hold portfolio but rather a tactical one (which would have done about 12% with 7% volatility and a Sharpe around 1 with no down years over the same time period). I am merely making an observation.

As a comparison, a buy and hold allocation 20% each to US stocks, Foreign Stocks, Bonds, REITs, and Commodities would have done:

Return: 11.76%
Vol: 8.51%
Sharpe 0.76

Better than stocks on a risk-adjusted basis, worse on an absolute basis.

Chart: Endowments vs the S&P500, 1985-2008, fiscal year ending June 30th.

The January Effect After Really Bad Years In Stocks


2008 is shaping up to be a terrible year for stocks with most indices down around 40%. It doesn’t do any good to worry about what has happened, but a better question is: what can I do now?
While our flagship model is a very simple trendfollowing system, I spend a lot of time thinking about other systems based on structural or behavioral phenomena. One well documented effect is the historical outperformance for small cap stocks in January. A simple system of holding the smallest 20% of stocks every January since 1927 results in returns of around 10% a year (and that is without sitting in cash the remaining 11 months of the year which would add an additional 3.5% per annum to returns). That dwarfs the 1.5% return for the largest 10% of stocks in January.
Below is a table of the smallest 10% and 20% of stocks vs. the largest 10% and 20% of stocks in January. (I am using the French Fama data.) Note, if you employed a market neutral strategy (long the small caps and short the large caps -denoted “hedged“ in the table), the returns would still be very respectable with zero market exposure. The table excludes the approximate 3.5% per annum cash return the remaining 11 months.





The below chart adds in cash returns to compare investing in the January small cap strategy vs. investing in the S&P 500 total return. Note how consistent the returns have been for almost a century.











I usually have a hard time getting comfortable with strategies such as this as there needs to be a structural reason for the strategy working. Tax loss selling is a legitimate one as investors sell their losers at the end of the year to capture capital gains losses (and there should be plenty this year).
Another potential problem is data mining. Will the strategy hold up out-of-sample and has the strategy deteriorated over time? Buying the bottom 20% of stocks in January results in nearly 90% up years. 16 of the past 17 years have been positive with average returns of 9.6%. Even better, the strategy would have recorded up years during some of the worst years in the market. 1930: 18.66%. 1931: 23.32%. 2001: up 31.7%. 2002: up 4.8%. The worst January for the strategy would have been around -6%.
Another knock on the strategy is that it would be difficult to implement due the bid-ask spread in small caps. This may have been true historically, but now there are plenty of small cap and micro cap ETFs available the investor can use to implement the trading. The average firm at the bottom decile is about $120 million, but if you back out to the bottom quartile it is a more reasonable $200 million.
What about investing in small cap stocks in January following a terrible year in stocks? In this case I examined all of the years back to 1927, took the 10 worst years in stocks, and examined how small caps (bottom 20% by market cap) performed the following January. The average performance for the S&P 500 the year prior was -21.22%.
The results? An astonishing average performance of 18.17% per January with the worst year being a positive 2.2% (2003). Adding in cash returns the following 12 months and you have returns over 20%.
The average performance of the large caps (top 10%) in January of those years would have been a paltry 3.1%. An investor could either go long a small cap ETF for the month of January, or have a market neutral position with equal amounts long small caps and short large caps. This system (long bottom 20%, short top 10%) would have resulted in average returns of 15% with very little market exposure.
Sample small and microcap funds are PZI, FDM, and IWC. Large cap ETFs include SPY and VTI.

Tbills Yield Nothing, Gold is in Backwardation, and Shilling Hits it Out of the Park

I spent the past weekend in Colorado (go Broncos!), and looked through my father’s library at some of my old books. I grabbed a copy of Shilling’s Deflation to read on the plane ride home (which is currently listed for $600 since it is out of print – hat tip to reader AC). Shilling has been spot on this year, as his recommendations at the beginning of 2008 show amazing foresight:

In the January 2008 issue of his INSIGHT newsletter, Gary Shilling outlined his 13 investment recommendations for 2008.
1.Sell or sell short homebuilder stocks and bonds.
2.If you plan to sell your home, second home or investment houses anytime soon, do so yesterday.
3.Sell short subprime mortgages.
4.Sell or sell short housing-related stocks.
5.Sell or sell short consumer discretionary spending companies.
6.Sell low-grade fixed-income securities.
7.Sell or avoid most commercial real estate.
8. Short commodities.
9. Sell or sell short emerging market equities.
10. Sell emerging country bonds.
11. Buy the dollar before long.
12. Sell or sell short U.S. stocks in general.
13. Buy long Treasury bonds.

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I also just finished the great book The Ascent of Money, although had I known I may have waited for the DVD out in med-December. (Book review here.)

Interview with Niall Ferguson.

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E-Erian: Resist reblanacing.

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Gold is in backwardation.

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T-bills yield nothing.

AlphaClone Launches!

After a year of hard work, the startup I have been working on with my co-founder Maz Jadallah goes live today!

I will do a few blog posts on the software over the next week or two, but if you want to take a look the tour is here. Sign up for a guest pass to access the free Buffett and Tiger Cub clones, and full site access is $99/month.

Email me any thoughts or suggestions you may have.

The AlphaClone blog starts here.

Long/Short Version of the Model

I get some of the same questions regularly- so when I do the site redesign I am going to include tabs for FAQs as well as timing updates. Those are the two main features people email me for.

Anything else you would like to see added to World Beta?

I was taking a look at an old post from about a year and a half ago that addressed the question of shorting instead of going to cash in the timing model. Normally, I recommend individual investors not short for a few reasons. 1 – most are not familiar with shorting. 2 – individuals do not get short rebates. 3 – the historical returns are lower than long/flat and buy and hold.

For the long short model the return is reduced with increases in volatility and drawdown vs. long/flat. Also not surprising – the correlation to buy and hold drops to 0 (or negative) for the L/S version.

However, if you include 2008, the disparity in performance is so wide between long/short and buy and hold (namely due to everything puking) , that buy and hold and the long short version now have similar return numbers.

If I get around to it I will include a long short section in my 2009 update to the timing paper in January. . .

Being Long Classic Risk Premia Is A Terrible Place To Be This Year

Being long traditional risk factors has been an awful place to be this year. The lesson of the stability of correlations is especially apparent here.

PDF on the all-weather portfolio here.

There used to be a table of Bridgewater’s All-Weather Portfolio performance here, but they asked me to take it down (they were down about 30% for the year as of November 2008).

The Capitalism Distribution PDF

The Capitalism Distribution: Fat Tails in Action

Quick, before you read this post, ask yourself these questions:

1. What percentage of stocks beat their benchmark index over their lifetime?

2. What percentage of stocks have a negative return over their lifetime?

3. What percentage of stocks lose essentially all of their value?

Not sure? The answers to all three questions are below. Want to know why a monkey throwing darts is probably as good as your stockbroker? Read on.

I have been hounding the guys at BlackStar Funds to publish their research in a top academic journal for a long time now, but like most money managers, they are too busy conducting research and managing their funds to be concerned with publishing their research.

I have included some of their research in my upcoming book, and thankfully they finally agreed to do a guest post here. If you have any questions you can reach Eric and Cole directly at their website here or at info@blackstarfunds.com.

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The Capitalism Distribution – The Realities of Individual Common Stock Returns
by Eric Crittenden and Cole Wilcox, BlackStar Funds
(Download the PDF here)

When most people think of the stock market they do so in terms of index results. Popular indexes include the S&P 500 and the Russell 3000. However, most people are not aware of the tremendous differences between winning and losing stocks “beneath the hood” of a diversified index. From 1983 to 2006 over 8,000 stocks (due to turnover and delisting) were at some point members of the Russell 3000. The Russell 3000 Index measures the performance of the largest 3000 U.S. companies representing approximately 98% of the investable U.S. equity market. (Some Russell 3000 statistics here.)

Key findings:

39% of stocks had a negative lifetime total return
(2 out of every 5 stocks are money losing investments)

18.5% of stocks lost at least 75% of their value
(Nearly 1 out of every 5 stocks is a really bad investment)

64% of stocks underperformed the Russell 3000 during their lifetime
(Most stocks can’t keep up with a diversified index)

A small minority of stocks significantly outperformed their peers
(Capitalism yields a minority of big winners that all have something in common)

In this paper we make the case for the Capitalism Distribution, a non‐normal distribution with very fat tails that suggests a small minority of stocks have been responsible for virtually all the market’s gains while most stocks have been below average investments.

Our database covers all stocks that traded on the NYSE, AMEX, and NASDAQ since 1983, including delisted stocks. Stock and index returns were calculated on a total return basis (dividends reinvested). Dynamic point‐in‐time liquidity filters were used to limit our universe to the approximately 8,000 stocks that would have qualified for membership in the Russell 3000 at some point during their lifetime.

(Click on any chart to enlarge.)

Chart 1: Total Lifetime Returns for Individual U.S. Stocks, Jan-1-1983 to Dec-31-2006

The following chart shows the lifetime total return for individual stocks relative to the corresponding return for the Russell 3000. (Stock’s return from X‐date to Y‐date minus index return from X‐date to Y‐date.)

Chart 2: Total Returns of Individual Stocks vs. Russell 3000 Index, Jan-1-1983 to Dec-31-2006

The fat tails in this distribution are notable. 494 (6.1% of all) stocks outperformed the Russell 3000 by at least 500% during their lifetime. Likewise, 316 (3.9% of all) stocks lagged the Russell 3000 by at least 500%.

The next chart shows the lifetime annualized return for individual stocks relative to the corresponding annualized return for the Russell 3000. The left tail in this distribution is significant. 1,498 (18.6% of all) stocks dramatically underperformed the Russell 3000 during their lifetime.

Chart 3: Annualized Returns of Individual Stocks vs. Russell 3000, Jan-1-1983 to Dec-31-2006


The next chart shows the cumulative distribution of the annualized return of all stocks. Notice that the average annualized return for all stocks is negative 1.06%.

Chart 4: Annualized Returns for Individual Stocks, Jan-1-1983 to Dec-31-2006


The next shows how stocks, when sorted from least profitable to most profitable contributed to the total gains produced from all stocks. The conclusion is that if an investor was unlucky enough to miss the 25% most profitable stocks and instead invested in the other 75% his/her total gain from 1983 to 2007 would be 0%. In other words, a minority of stocks are responsible for the majority of the market’s gains.

Chart 5: Attribution of Collective Return, Jan-1-1983 to Dec-31-2006

You may be wondering how the Russell 3000 index can have an overall positive rate of return if the average annualized return for all stocks is negative. The answer is partly a function of the index construction methodology. The Russell 3000 is market capitalization weighted. This means that successful companies (rising stock prices) receive larger weightings in the index. Likewise, unsuccessful companies (declining stock prices) receive smaller weightings. Eventually unsuccessful companies are removed from the index (delisted), making way for small but growing companies. In this way market capitalization weighted indexation is like a simple trend‐following system that rewards success and punishes failure.

It’s also important to point out that stocks with a negative annualized return had shorter life spans than their successful counterparts. The average life span of a losing stock was 6.85 years versus 9.23 years for winning stocks (many of which are still living right now), meaning that losing stocks have shorter periods of time to negatively impact index returns. For these reasons the average annualized return is probably a somewhat deceptive number for the purposes of modeling the “typical” stock, but interesting nonetheless.

The astute reader at this point is probably wondering if outperforming large capitalization stocks explain the observed distributions. Mathematically this would make sense. Small cap stocks certainly outnumber large cap stocks, while large cap stocks dominate the index weightings. However, while large cap stocks (Russell 1000) have outperformed small cap stocks (Russell 2000) over the long term it has been by less than 1% per year, hardly enough to explain our observations.

We identified the best performing stocks on both an annualized return & total return basis and studied them extensively. The biggest winning stocks on an annualized return basis had a moderate tendency to be technology stocks and most (60%) were bought‐out by another company or a private equity firm; not surprising.

Some of the biggest winners on a total return basis were companies that had been acquired. Examples include Sun America, Warner Lambert, Gillette, Golden West Financial and Harrah’s Entertainment. However, most (68%) are still trading today. Not surprisingly, they are almost exclusively large cap companies. However, further research suggests that they weren’t large companies when they were enjoying the bulk of their cumulative returns. Becoming a large cap is simply the natural result of significant price appreciation above and beyond that of the other stocks in the market. We were not able to detect any sector tendencies. The biggest winners on a total return basis were simply the minority that outperformed their peers.

Both the biggest winners on annualized return and total return basis tended to have one thing in common while they were accumulating market beating gains. Relative to average stocks they spent a disproportionate amount of time making new multi-year highs. Stock ABC can’t typically travel from $20 to $300 without first crossing $30 and $40. A stock that’s going from $20 to $300 is likely going to spend a lot of time making new highs. Likewise, the worst performing stocks tended to spend zero time making new multi-year highs while they were accumulating losses. Rather, relative to average stocks they tended to spend a disproportionate amount of time at multi‐year lows.

Mathematically it makes perfect sense. Stocks that generate thousands of percent returns will hit new highs hundreds of times, usually over the course of many years.

Could it be this simple; long term trend following on stocks? That’s our conclusion. For detailed results of the trading system that was inspired by this research see the paper, “Does trend following work on stocks?

-Eric Crittenden and Cole Wilcox

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Meb’s note:

I mentioned their trendfollowing paper in my research paper as well as my book. It is a great example of a simple approach to risk management for investing in stocks. Setting a trailing stop ould have kept you from holding dogs like AIG, Bear Stearns (BSC), Lehman (LEH), Office Depot (ODP), Sears (SHLD), Beazer (BZH), and Citigroup (C) all the way into the ground. Not only does the system protect your portfolio, but it also saves you the emotional distress and uncertainty from watching Citigroup go from $50 to $5.

Ditto for historical blowups like Enron, WorldCom, Adelphia, and New Century Financial.

So what stocks are going up? A partial list of stocks near all time highs includes, gasp, some financials!

(Disclosure: Blackstar is probably long any stock that is near an all-time high.)

NuVasive (NUVA)
Flowers (FLO)
Stericycle (SRCL)
Heartland Express (HTLD)
Stanley (SXE)
Exponent (EXPO)
First Financial Bankshares (FFIN)
Laclede Gas (LG)
WGL Holdings (WGL)
New Jersey Resources (NGR)
Peoples Bank (PBCT)
Southside Bancshares (SBSI)
Trico Bancshares (TCBK)
UST (UST)
Allegiant Travel (ALGT)
Strayer Education (STRA)
Piedmont Natural Gas (PNY)
California Water Serv Group (CWT)
Emergent BioSolutions (EBS)

AlphaClone Beta Launch!

Take the tour here!

Free Warren Buffett clone example here. Beats the market by 10% a year since 2000, including outperforming the market by 20% in 2008. (Those number agree with the historical numbers found in this academic study.) Top holdings include WFC, KO, PG, COP, BNI, AXP, KFT, JNJ, USB, and WSC.

Screenshot of Buffett clone below:

Free Tiger Cubs clone here. This clone selects the most popular holdings from 20 funds that are progeny of Julian Robertson’s Tiger Management. Beats the market by 12% a year since 2000. Top holdings include QCOM, V, MA, AMX, PCLN, TDG, SD, SBAC, AMT, XTO.

To keep updated on the full launch (early December), sign up here.

Email me any thoughts or suggestions you may have.

Have a great Thanksgiving!!

Market Timing is Impossible

That was the response of a certain Nobel Laureate when I tried to get him to read my paper “A Quant Approach to Tactical Asset Allocation.” He refused to even take a look at it.

This year has certainly been the perfect storm for buy and hold investors. Everything has gone down – Sotcks, Foreign Stocks, REITs, Commodities, and (some) bonds. This has been an instructive year to showcase the benefits of a market timing solution, namely, risk management and avoiding large losses. I have no idea how big this decline will be or when it will end, but it is instructive to take a look at some historical relative performance of the timing model vs. buy and hold investing.

October 1974 ended a period where buy and hold had its highest drawdown ever at around -20%. That has now been eclipsed by the current -30%+ drawdown. (The max timing drawdown is around -10%.)

Below is a chart for the relative returns of buy and hold vs. the timing model. Readers know that both have similar compounded returns over the past 36 years, but that the timing model has much lower volatility and drawdowns. Usually one outperforms the other by a maximum of around 10% before mean reverting. (Click on the chart to enlarge)

However, in times of severe market stress (now), the timing model can outperform by far greater amounts. As of the end of October it was outperforming by about 27%. Has there ever been a period comparable?

By October of 1974 the timing model was outperforming as most asset classes were declining severely (with the exception of commodities). The timing model ended the year with a gain of around 13% vs. a loss of -12% for buy and hold. However, buy and hold mean reverted over the next year, and returned about 20% for 1975 while the timing model would have done about 2%.

The million dollar question is, how bad is it gonna get?
(Stay tuned to a follow up post on some thoughts I have here.)

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