"Act so as to keep the mind clear, its judgment trustworthy" - Dickson G. Watts, author of Speculation As A Fine Art And Thoughts On Life. [A brief summary here (link)]

Saturday, September 25, 2010

making money in a random market (part 2)


It occurred to me that i should know what the returns and volatility are if one simply holds SPY overnight, every night - regardless of whether or not the market was up intra-day. Interestingly enough, it appears that the positive attributes of the aforementioned strategy whereby one holds overnight when the market was up that day are unrelated to whether or not the market was up that day. In fact, if one simply holds the SPY overnight (every night), then the average daily return is .036%, whereas if one only holds overnight after the market was up intra-day, then the average daily return is only .030%. Furthermore, simply holding overnight, every night, provides for an overall return since 1993 in line with a buy-and-hold strategy with much less volatility.

If I were to fabricate a theory to explain this phenomenon, I'd say it has to do with a liquidity premium related to the idea that many market players (e.g. day traders) are only active during the day and liquidate their positions prior to the market close so as not to have exposure over night. So the strategy of only holding stocks overnight means that one is selling at the open (when others are bidding up the prices) and buying at the close (when others are selling down the prices).

If one wanted an apples-to-apples comparison of the hold-overnight strategy against the buy-and-hold strategy, then one could leverage their investment overnight (via margin borrowing). This means one would be holding more stock in comparison to the amount of their investment and therefore the changing price of that stock in proportion to their investment would be more volatile. Given the data set I'm working with here (i.e. ticker SPY since 1993), if one were to have consistently financed 47.9% of their overnight holdings via margin, then the annualized volatility (standard deviation of returns) would have been 19.8%, precisely the same as for the buy-and-hold strategy. However, the returns from this leveraged hold-overnight strategy would have been 12.88% (annualized), which compares favorably to the 7.33% annualized return provided by the buy-and-hold strategy. For this analysis, I've just assumed the interest rate associated with the margin borrowing was a constant 10%.

Aside from higher returns with equivalent volatility (if leveraged) or equivalent returns with lower volatility (if unleveraged), there is the conceptual risk reduction associated with the fact that one would only be exposed to stock price fluctuations for ~16 hours per day, rather than 24 hours per day. So if something bad happens in the world that triggers a market crash, one would theoretically have a 1 in 3 shot at side stepping the carnage to their portfolio.

So what's the catch? Transaction costs. If one bought everyday at the market close and sold the next morning at the market open, one would lose their entire investment over time to brokerage commissions. This is the case even if one started with $100, 000 and could complete trades for only $10 per 1,000 shares traded.

Nonetheless, this overnight holding phenomenon could be marginally useful information even if one has to incur transaction costs, because if one is using some other system that generates daily trade decisions, one could enter those buy orders at the market close and enter those sell orders at the market open and perhaps realize some additional return over time.

Saturday, September 18, 2010

making money in a random market



i was googling for articles on suggested ways to make money in a random market and i came across an interesting site that articulates the theory of the screw, which is a belief i myself hold and recommend this article to you as worthwhile reading. but aside from that, the author writes in another article about momentum investing. Soooo, i decided to do a simple backtest on the system whereby one buys and holds overnight if the market closed that day higher than it opened. For the test, i pulled historical quotes for the ETF that tracks the S&P500 (ticker: SPY), which has been trading since 2/1993.

what i found is an annualized return of 3.59% with annualized standard deviation of 7.36% over this 17.6-year time period. now, this isn't very compelling if you consider one could obtain an annualized return of 3.50% with annualized standard deviation of only 0.57% over that period by holding 3-mo. t-bills. however, if the stock market would have performed better over that period, this system would have undoubtedly performed better, whereas the same upside potential doesn't exist with t-bills. so perhaps the correct benchmark is the s&p500 itself, which provided a return of 5.36% (annualized) with standard deviation of 15.26% (annualized) over that 17.6-year time period. so for this trading system, the return/volatility was 0.49, which compares favorably to the return/volatility provided by the s&p of 0.35.

now to get a truer picture, i'll have to go back later and model in transaction costs, but the purpose of this test was simply to get a feel for whether or not this system even has any potential. i may have to test this system a bit more, but at first blush, it doesn't appear half bad. i mean look at the chart above since 2001; sure it hasn't made any money, but compare that to the crazy volatility and low returns of the s&p 500.


Technical Notes:
1. if you want to buy and hold overnight, you must buy prior to the close (unless you buy in the after-market), but i'm just assuming one can buy a few minutes prior to the close and almost always hit a bid very close to the closing price assuming there are no huge moves during the last few minutes.

2. i did not take the time to model in transaction costs, which would dilute the returns of this system.

Sunday, September 12, 2010

no free lunch here


I was wondering if folks who ordinarily have some portion of their portfolio allocated to bonds might be better off to instead utilize a mix of stocks and cash. The idea is the stocks and cash would be proportioned so as to achieve the same volatility as bonds while potentially achieving a higher return.

To investigate, I pulled historical data from yahoo! finance going back to the early 1960s for 3-month treasury bills (proxy for cash returns), 10-year treasury notes (proxy for bond returns), and the S&P 500 (proxy for stock returns). Then I solved for the stock/cash proportions (54.7% / 45.3% with monthly rebalancing) that would provide for the same volatility (8.3% annualized standard deviation in returns) provided by the 10-year treasury notes.

What I found is that the stock/cash portfolio provides a slightly lower return than the 10-year treasury notes. Perhaps next week I'll try to get my hands on some corporate bond data and see if the idea pans out better there.

congrats to jmu dukes

Money Quote: "It was the first time Virginia Tech Coach Frank Beamer has lost to a division I-AA opponent since taking over the program in 1987. It also was only the second time a division I-AA team defeated a ranked division I-A team, the first being when Appalachian State shocked No. 5 Michigan in 2007." Full story here.

Also, intriguing bit of motivation here: "Asked during the week about Saturday' s matchup with No. 13, Virginia Tech, Matthews [JMU coach] had a simple summation for his team's chances against a major-college, in-state school located a couple of hours south off I-81 from his Harrisonburg campus:

"When you get right down to it, they didn't want any of our guys. It's kind of comical to think you're going to go down there and beat them."

Thursday, September 9, 2010

Saturday, September 4, 2010

model portfolio (1-year in)




Between reading loan documents for work and preparing for my fantasy football draft on Monday, I won't be doing a real post this weekend. However, the charts above show the model portfolio performance after the completion of one full year of history.

As a recap, from 9/2009 thru 4/2010, the model portfolio slowly but steadily got out to a lead over the benchmarks, in my opinion due mainly to the low beta stock selection, economic sector diversification, and minimization of financial sector exposure. From 4/2010 thru 6/2010 I pruned the portfolio to lower the beta even more and allocated 1/3 to low beta foreign stocks in an effort to further lower the covariance with the S&P 500. In 6/2010, I turned bearish based on the weakening economic fundamentals, mainly retail sales, and allocated 1/3 of the portfolio to the ETF that moves inversely to the S&P 500 (ticker: SH). Since then, the portfolio volatility has been very low while the equity markets as a whole have essentially been unchanged from then to now, but with a lot more volatility along the way.

Overall, I am pleased with the results, while realizing this could well be 100% luck. The markets are so volatile in comparison to the magnitude of the model portfolio outperformance, that one could reasonably attribute this outperformance to statistical noise. As I told my son last month while explaining the basics of investing to him, one should try to select an advisor that can demonstrate this type of outperformance consistently over say 10 years. Further, even such a track record of outperforming 9 of 10 years would be insufficient if the one year of underperformance is so awful as to make the cumulative return lag the market benchmark. Still, if an advisor is found who can truly meet this standard, it could still be luck, but intuitively I believe such a track record would provide for a better chance of outperformance in coming years as compared to an advisor without such a record.

Otherwise, if one can only find advisors for whom the prospect of outperformance is essentially a gamble, why not save the management expense and gamble on your own? I don't mean go crazy and put 100% of your savings into the latest hot stock, but I do think most folks would do well to (i) minimize their management expenses via a low cost platform like folioinvesting.com and (ii) minimize portfolio volatility via sector diversification, geographic diversification, and low beta stock selection. For the technically inclined, disciplined market timing strategies based on quantitative rules can help minimize portfolio volatility as well.