Uncertainty and risk

Deadly discount rate

Sentiment Indicators

I’ve never been able to model these accurately and robustly, but the idea is intriguing for a contrarian (like I try to be). The question is what indicators to use, what time frame should you look at, how robust is the data, are you measuring coincident indicators/correlation/causation, how do you quantify the predictive value, etc. ETF’s have certainly given us some insight, as does watching the VIX. I was recently sent the following articles about using the Rydex levered bull vs. levered bear ETF’s. The first article looks at daily moves and the second at weekly moves. I have not tested these indicators myself and cannot attest to their validity, but it is something that is worth looking into:

http://www.zerohedge.com/article/rydex-market-timers-amazing

http://thetechnicaltakedotcom.blogspot.com/2010/01/rydex-market-timers-long-term-view.html

These articles seem to be looking at assets, not prices, but I assume you could look at prices as well. Just some food for thought for the modelers out there.

Placing speculative limits is BAD – now if only the Fed will heed it’s own research

In a recent paper published by the New York Fed, Erkko Etula shows that speculators help stabilize commodity markets. To quote:

Taken together, my results highlight the importance of speculative capital for the stability of commodity markets. In this way, the paper not only contributes to the broader literature on limits of arbitrage pioneered by Shleifer and Vishny (1997), but also shows that recent arguments in favor of speculative
trading restrictions have been starkly misguided.

Another interesting outgrowth of this research is that Etula is able to model some of the volatility of commodities based on the flow of funds report. For those trading in the options arena, especially those using quant based approaches, this might point to an interesting factor to test further. For the full report click here.

IMPORTANT NOTICE: Inverse, Leveraged and Inverse-Leveraged Exchange Traded Funds are no longer available for new or additional purchases at UBS

Effective July 27, 2009, UBS is suspending the offering of Inverse, Leveraged and Inverse-Leveraged Exchange Traded Funds (ETFs). You will no longer be able to make new or additional purchases and will only be able to liquidate current positions through UBS at this time. Any attempt to execute a trade of such ETFs will be rejected.

Please contact your Financial Advisor with questions.

Toxic Equity Trading Order Flow on Wall Street

This is a must read for all traders, investors, regulatory officials, and anyone involved in the markets. Themis Trading LLC has blown off the cover of program trading to highlight how algorithmic based programs make money. Everything from automatic bid-spread systems, pinging (searching for hidden liquidity), and liquidity rebates are discussed. These systems are driving volume and volatility and driving false readings and higher costs for the rest of the investing community.

Arnuk and Saluzzi provide two solutions:

1. Orders must be valid for 1 second (which is huge when talking about millisecond moves), and
2. Curb program trading if markets move more than 2% limits.

I have another solutions, which is really simple: hold positions longer! The markets will go where they intend to go anyway, which Arnuk and Saluzzi confirm, however, trading without the advantages of high speed super-computers just costs more because of these algo strategies. Solution: don’t try to compete in a losing game. Hold positions longer and play the time arbitrage. You might pay an extra penny for execution, but if you’re planning on holding the position for longer than a year or even two, then that penny shouldn’t impact your long term IRR.

Toxic Equity Trading Order Flow on Wall Street

Profits Diluted 4% by U.S. Share Sales, Dividend Cuts

June 8 (Bloomberg) — American common equity is increasing for the first time in five years, threatening to dilute corporate profits as companies sell a record amount of stock and cut dividends the most since 1938.

Wells Fargo & Co., ProLogis and more than 150 other companies raised $82.2 billion this quarter, beating the record pace at the height of the technology bubble in 2000, according to data compiled by Bloomberg. The combination of adding shares and restricting dividends will reduce annual equity returns as much as 4.1 percent, the data show.

“The math is inescapable,” said Alan Gayle, the Richmond, Virginia-based director of asset allocation at Ridgeworth Investments, which manages $60 billion. “You’ve got weak earnings, the share price goes down and then, ‘What? They want to raise equity?’ Clearly that isn’t a good thing.”

http://www.bloomberg.com/apps/news?pid=20601087&sid=aCYuw3iBBUmM

Interesting Trade Idea

How about this reversion to the mean trade…

1. Break down the S&P 500 into industry subsectors (http://www2.standardandpoors.com/spf/pdf/index/GICS_500_Scorecard.pdf).
2. Look at the subsectors that have had the most significant changes in weighting over the past 2 years.
3. Go long the subsector that has lost the most ground. If you’re looking to balance it out, then short the subsector that has gained the most ground.
4. Hold for one year, the redo. So, you’re always looking at rolling 2 year changes.

I’d be interested to see if it keeps you out of a lot of trouble. Anyone out there testing this stuff?

Samberg’s Pequot Capital to Close

Sobering.

http://online.wsj.com/public/resources/documents/PequotLetter052709.pdf

Goldman to pay $60 mln in subprime settlement

By the time the dust settles I would expect GS to be neck deep in litigation.

NEW YORK (MarketWatch) — Massachusetts Attorney General Martha Coakley on Monday said her office has reached a $60 million settlement with Goldman Sachs Group Inc. related to the investment bank’s role in securitizing subprime mortgage loans.

http://www.marketwatch.com/news/story/Goldman-pay-60-mln-subprime/story.aspx?guid=%7BD6BD5788%2D41D5%2D49F2%2DA78E%2D0CD9711B0186%7D

Low frequency fundamental value equity strategies…

What’s the deal? I just got off the phone with another strategy builder from one of the big shops looking for a new home. That’s one last week, one this week…Are funds abandoning the low frequency strategies en masse? Is there more time arbitrage for those who can hold on to positions (on both sides) and ignore the noise? Worth following.

Are stocks really less volatile in the long term?

In a recent paper, Professors Stambaugh and Pastor argue that stocks exhibit higher volatility over long horizons. “Evidence of lower long-horizon variance is cited in support of higher equity allocations for long-run investors (e.g, Siegel, 2008) as well as the increasingly popular “life-cycle” mutual funds that allocate less to equity as investors grow older (e.g., Gordon and Stockton, 2006, Greer, 2004, and Viceira, 2008).” The implications touch pension investors or any investors determining allocation based on time horizon (i.e. the vast majority).

For me, one of the most interesting aspect of this paper is that time does not necessarily increase predictability. Assuming that equities are not more volatile over the long term, as the paper suggests, but instead are equally volatile. That would support Mandlebrot’s fractal modeling. Even if volatility is higher, that is, we see the same pattern, but with a certain multiple, using fractals, we should still be able to run simulations and “build” hypothetical returns. Despite our recent foray into genetic algorithms, I find myself continually going back to the work of Mandlebrot…talk about confirmatory bias. Here’s the abstract:

Conventional wisdom views stocks as less volatile over long horizons than over short horizons due to mean reversion induced by return predictability. In contrast, we find stocks are substantially more volatile over long horizons from an investor’s perspective. This perspective recognizes that parameters are uncertain, even with two centuries of data, and that observable predictors imperfectly deliver the conditional expected return. We decompose return variance into five components, which include mean reversion and various uncertainties faced by the investor. Although mean reversion makes a strong negative contribution to long-horizon variance, it is more than offset by the other components. Using a predictive system, we estimate annualized 30-year variance to be nearly 1.5 times the 1-year variance. (Pastor, Lubos and Stambaugh, Robert F.,Are Stocks Really Less Volatile in the Long Run?(February 17, 2009). Available at SSRN: http://ssrn.com/abstract=1136847)

Also, check out this interview with Stambaugh and Jeremy Siegel at Wharton. http://knowledge.wharton.upenn.edu/article.cfm?articleid=2229

Genetic Algorithms cont’d…

It’s interesting how many new inquiries and papers we have been seeing on building these types of algorithms. Here’s another one: Hybrid Evolutionary Techniques for FX Arbitrage Prediction by Tristan Fletcher.

Abstract:     
This paper discusses the need for a missing value technique to fill in gaps in time series representing foreign exchange (FX) prices and assist in the observation of potential arbitrage opportunities. It highlights the requirement for prediction methods to establish the persistence of these opportunities (latency). Naieve missing value and prediction techniques are investigated and then compared with Kalman Filtration, Ensemble Kalman Filtration, Regression and Neural Network techniques. A technique not known to be applied in this domain before, namely NeuroEvolution using Augmented Topologies (NEAT), is then examined in order to asses its ability in filling in missing values and the prediction of arbitrage opportunities in comparison to these other more established techniques. Hybrid functions, incorporating the most successful of the techniques, are constructed in order to ascertain whether combinations of techniques are more successful than their constituents. Data from for various data providers for three markets is used taken over periods representing different levels of market activity (liquidity).

Citation info: Fletcher, Tristan,Hybrid Evolutionary Techniques for FX Arbitrage Prediction(August 31, 2007). Available at SSRN: http://ssrn.com/abstract=1323607

Do Quant Factors Persist Anymore?

http://zerohedge.blogspot.com/2009/04/do-quant-factors-persist-anymore.html

This is an interesting post looking at the persistence of various factors. Not much new info there, but I thought it posed some good generalities.

A Quantitative Approach to Tactical Asset Allocation (Mebane Faber)

In an update to the 2006 paper, Mebane Faber looks at adding a momentum component to asset allocation using 2006-Present as additional virgin data. I particularly appreciated a few key concepts:

1. Use predefined rules to avoid the classic behavioral biases.
2. Use simple rules that aren’t over optimized.
3. Test across multiple asset classes to get a better sense of robustness of underlying hypothesis.
4. Test for predictive value (I think the article could have done a better job on this end).

http://ssrn.com/abstract=962461