Abstract
We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for 1 to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors, and performs best during extreme markets. We show that the returns to time series momentum are closely linked to the trading activities of speculators and hedgers, where speculators appear to profit from it at the expense of hedgers.
Abstract: Various theories have documented that momentum is followed by reversal in the long term. This paper constructs a new momentum-reversal strategy by avoiding the stocks that are more likely to approach reversals in the winner and loser groups. The results show that the risk-adjusted returns of the new strategy are significantly higher than those of the traditional momentum strategy documented by JT (1993) and Carhart (1997). Such a finding is robust in different time periods and size quintiles. Moreover, the risk-adjusted returns of the new strategy cannot be fully explained by Carhart’s four-factor model and the corresponding timing activities.
From lesbian ballerina sex scenes with Portman/Kunis to a Thom Yorke NSFW song, the phrase black swan is dominating the media. (Trailer and video below.)
Tons of chatter about black swan funds and tail risk funds out there right now (which makes me think a lot of people are going to be sorely disappointed when they lose $ in these funds). We were talking about how someone should launch an ETF on the strategy about 6 months ago. Any public funds yet?
I have a few questions on the study, and a few quibbles (trendfollowing is hardly a new anomaly) but otherwise another nice paper that flies in the face of conventional wisdom for many.
Abstract
In this paper, we document that an application of the moving averages (a popular form of technical analysis) to portfolios sorted by volatility generates investment timing portfolios that outperform the buy-and-hold strategy greatly, with returns that have negative or little risk exposures on the market factor and the Fama-French SML and HML factors. As a result, the abnormal returns, relative to the CAPM and the Fama-French three-factor models, are high, and higher than those from the momentum strategy for high decile portfolios. The abnormal returns remain high even after accounting for transaction costs. While the moving average is a trend following strategy as the momentum, its performance has little correlation with the momentum, and behaves differently over business cycles, default and liquidity risks.
Arnott’s monthly letter is a must read. In the last issue, titled “Too Big To Succeed” he examines how the largest market cap company in each sector performs relative to its peers.
We find the leader in any sector underperforms the average stock in its own sector by 3.5% in the next year … and the next year … and the next year. As Table 1 shows, the damage doesn’t really slow down for at least a decade, as the top dog in each sector lags its own sector by 3.3% per year for the next decade!
From these results, one might conclude that an investor could do rather well by investing in the Russell 1000, minus its 12 sector leaders. Better still, perhaps we should exclude all of the companies that have been sector leaders any time in the past decade because the performance drag for the top dogs tends to persist for a decade or more. These stocks typically comprise about one-fourth of the Russell 1000! If these stocks suffer a 300–400 bps shortfall in most years, one could outperform the index by nearly 100 bps per annum merely by leaving the top dogs out, cancelling the corrosive influence of competitors, populists, and pundits.
Now, Arnott runs billions on indexes that are not market cap weighted, but the arguement is certainly persuasive. He also co-wrote the very good book The Fundamental Index: A Better Way to Invest.
Below are the 9 sector SPDRs and their top holding in each:
There are lots of ways to (try and) reduce risk in a portfolio. Adding (truly) non-correlated asset classes, using risk management and tactical trading models, hedging with derivatives, etc are all possible solutions. In our newest paper we talked about a few different ways to mitigate risk other than just using the trendfollowing methods of the first paper.
However, there is one really simple way to reduce risk further, and that is to simply put less$ at risk in the first place.
That is, invest more in bonds or cash.
Below is the effect of placing part of your portoflio in the simple GTAA strategy with the rest in T-Bills (included in the chart is the effect of leveraging the GTAA strategy which has the opposite effect – much higher returns with increases in vol and maxdd).
As you can see the returns are reduced but the equity curve gets smoother and smoother as more cash is added. The 40% cash bucket still returns 9% compounded over the period (roughly in line with stocks) with 4% volatility and a maxDD of 5%. Not only that, investors willing to enact this strategy over long periods could have picked up some more yield by moving out the yield curve or holding a more diversified fixed income portfolio. Below is the added chart with leverage:
Now, one of the problems enacting that strategy right now (for those learning they now have too much risk in their portfolios) is that T-Bills yield next to nothing and stocks have been underperforming bonds mightily over the past decade. Below is a chart of the 10 year rolling total returns for US stocks and 10 year govt bonds:
While that looks like everyone should short bonds and get long stocks, remember that these conditions can last for awhile…and in Japan’s case it did for nearly a decade:
I have been waiting for a mutual fund or ETF/N to come out on some other currency indexes other than carry, and value and momentum/trend are the two obvious ones.
Below is some info on the FX Trends Index from Alpha Financial Technologies (cousin of the DTI and CTI which have been getting pounded lately). Hopefully a service provider will launch with one of these funds shortly.
I haven’t seen much ink on the new Dodd Bill and potential short sale disclosure requirements, so it came to my surprise when I found this in an email from our fund lawyers:
New Short-Sale Reporting Requirement. The Act directs the SEC to create rules requiring at least monthly public disclosure of the name of the issuer and the title, class and CUSIP number of securities sold short, the aggregate amount of short sales of each security and any additional information that the SEC determines is appropriate. How this requirement will affect advisers who actually sell securities short will depend largely on the rules the SEC adopts. For example, it is unknown whether the rules will apply only to advisers filing Form 13F reports (generally, advisers with investment discretion over accounts holding at least $100 million in section 13(f) securities) or will also apply to other advisers.
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Really interesting new commodity fund from SummerHaven:
The United States Commodity Funds is pleased to announce the launch of the United States Commodity Index Fund (NYSE: USCI), the first 3rd Generation Commodity ETP. USCI seeks to provide clients with diversified commodity exposure while addressing some of the major obstacles of investing in commodity futures.
USCI is based on the SummerHaven Dynamic Commodity Index (SDCI), a rules based commodity index that seeks to identify long-term sources of return in commodity futures based on fundamental signals about the underlying physical commodity markets.
USCI differs from other Commodity ETFs in the following ways:
Commodity Selection – Unlike 1st and 2nd generation commodity indices which are always fully invested in the same commodities, the SDCI is comprised of 14 Futures Contracts that will be selected on a monthly basis from a list of 27 possible Futures Contracts.
Commodity Weighting – Each of the 14 commodities in the SDCI are equally weighted, providing meaningful exposure to each commodity that we believe has the best chance to outperform in the short-run.
Curve Selection – Rather than obtaining all of our commodity exposure at the front month, the SDCI is rules-based and rebalanced monthly. The composition of the SDCI in any given month will be determined by quantitative formulas relating to the prices of the futures contracts as they relate to both price momentum and inventory levels.
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I guess this is what happens when Mint.com gets acquired for $170mm – lots of competitors. Older post here: Why Pay for Beta?
How is Bruce Berkowitz making your mutual fund managers look bad? Easy. By doing all the things they say can’t be done. Most fund companies say you can’t time the market. He has. They say you shouldn’t hold lots of cash in an equity fund. He does. They say you mustn’t put too much money into a few stocks. He does that, too.
It will be interesting to see if he can keep it up with $15b in AUM rather than just $1b….
Below is some nice evidence of the efficacy of using AlphaClone to track value oriented managers. The equity curve below takes his top 10 holdings and rebalances them quarterly five days after the positions are disclosed publicly through 13Fs. As you can see it does a great job of tracking the underlying fund. (Start date is 9/2009 from Yahoo Finance.)
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