World Beta Blog

I will be in Chicago next week at the M* ETF Conference Wed Sep 15th – Fri Sep 17th.  Drop me a line if you want to meetup.

I will also be in South America in mid to late November (Santiago, Buenos Aires, and possibly a few other cities TBD).  Again, drop me a line if  you are around!

There are a few more trips lined up (NYC, Denver, Florida) and I will update the blog with dates when confirmed.

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I have recently gone back and reviewed nearly all of the 800 odd posts on WB over the past few years.  I’ll be writing some longer form analysis on some of the topics in our upcoming research newsletters, but below are a few idea I came across that I could be updated short form…

When S&P originally constructed their BuyWrite and PutWrite Indexes they did so with a 1988 start date.  I thought that was a little odd, and you can see some of the conversations I had with them back in 2007. They have now since included data back to 1986.

Below is a table and equity curve with data over the whole period FWIW.

Forgot labels:

SPTR = S&P500 Total Return

BXM = BuyWrite Index

PUT = PutWrite Index

CAGR

StDev

Sharpe

MaxDD

(And by the way, if you REALLY want to get interesting start playing around with these different indexes and some basic timing and volatility trading rules…)

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Another recent post was one on mean reversion after really bad months (like the one in May).  More background here, as well as subsequent performance below:

ETF, May Returns,  July-Aug Returns,  Annualized

VTI,  -7.89%,  1.98%,  12.48%

VEU,  -10.90%,  6.96%,  49.71%

VWO,  -9.18%,  7.40%,  53.44%

Apparently my book came out in Mandarin about a year ago and I didn’t even know it.  Are those gold coins on the front?

Nice Mo review paper by Moskowitz

Also another longer academic paper here Time Series Momentum

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.

And now more on how to exploit momentum while avoiding the reversals…

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.)

And you better believe Wall St is going to capitalize (err take advantage of and extract fees) on the sudden popularity. Some links:

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?

PIMCO Launches Black Swan Protection

DB Tail Risk Hedging and DB ELVIS and DB EMERALD

Is it Possible to Hedge Tail Risk

Talk of the Town

Condor Options

Black Swan movie trailer (Possbily NSFW)

Thom Yorke (Radiohead frontman) song (Definitely NSFW), Black Swan

Boston August 23-24

Washington DC  25-26

Drop me a line if you want to meetup!

Apparently it works, and it works best on the most volatile stocks (whod a thunk it?)

The new paper : “A New Anomaly: The Cross Sectional Profitability of Technical Analysis” and the always great summary from CXO.

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 did some older posts on the subject of the largest company by market cap overall.  The original study was featured in the book “Mosaic: Perspectives on Investing” by Pabrai.)

From Arnott’s letter:

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.

There will be some cool new features and developments coming down the pipe soon for the blog and “other”.  Stay tuned!

Since a large number of readers have requested access to the comments archives/want to continue commenting – I have turned them back on (soon).

Play nice, and if spam gets to be a problem again (or these weird malware issues I had about a week ago) then it will probably revert again.

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.

FX Trends Index Fact Sheet