I. Performance Projections - February 2010

The following analysis provides return projections for several hedge fund equity indices for February 2010. By conducting this analysis on a monthly basis, we are essentially creating a synthetic track record for hedge fund index replication. Compared to general back-testing procedures that use historical data, our approach projects the monthly performance before the actual returns are available. Hence, we cannot modify the data to generate more desirable results. Thus, it may be viewed as a “true” projection.

MPI’s analysis projects that the majority of hedge fund strategies will generate positive returns (around 1%) in February 2010. The exception is the emerging market strategy which is projected to produce negative results in February.

II. Review of Last Month - January 2010
Projection results for January 2010 are lower than the actual returns and further research is required at this stage. Although our projections are directionally correct, for most cases, the strategy discrepancies are too large to be explained by random errors. Notably, our projection returns significantly underperformed the actual returns by around 2% for most strategies and index vendors. This pattern prompts us to conduct in-depth research and back-testing to ascertain the cause. MPI will also analyze our February projection numbers to evaluate whether the January results are a singular event.

1. CS/Tremont index was projected without using Nov. 2008 and Feb. 2009 data, as we consider these two data points outliers that would affect the quality of projection. Please refer to our March 2009 projection return for a detailed explanation.

The question many investors are now asking is: Does BRK.B actually belong in the Financial sector? If BRK.B behaves like a Financial, for all practical purposes (including portfolio construction and risk management) it should be treated as a Financial. However, our analysis of BRK.B’s historical returns shows it behaves more like a Consumer Staple stock than a Financial.

BRK.B’s sector classification is of particular importance to both long-only and long-short portfolio managers attempting to manage sector exposure. For example, consider a long-short portfolio manager attempting to construct a sector neutral portfolio. If the portfolio manager is long BRK.B and it behaves like a Consumer Staple and not a Financial, this portfolio will have unintended, potentially large sector tilts towards Consumer Staples and away from Financials.

Based on monthly return correlations, it appears that, in recent years, BRK.B behaves more like a Consumer Staple than a Financial.

As the chart below clearly shows, not only are BRK.B’s returns more closely correlated with Consumer Staples, but the magnitudes of its returns are more similar to Consumer Staples than Financials.

The results from this simple correlation analysis were further supported by more rigorous, quantitative analysis done using MPI’s proprietary Dynamic Style Analysis (DSA) model. When using a multi-factor model comprising of the S&P 500 sectors, Consumer Staples is the dominating factor driving BRK.B’s returns. Since 2001, the exposure of BRK.B’s returns to Consumer Staples is much larger than its exposure to Industrials and Financials combined.

Why does the market treat BRK.B as a Consumer Staple instead of a Financial when, according to Berkshire itself, their primary business is in the insurance and reinsurance sector? We posit that three different considerations, when viewed together, provide a plausible explanation. First, a large chunk of Berkshire’s insurance businesses are viewed as Consumer Staples not Financials. Second, Berkshire’s reinsurance businesses impact BRK.B’s idiosyncratic returns, but do not have a significant impact on its systematic returns. Finally, and most obviously, Berkshire has large public holdings in companies like Coca-Cola and P&G.

Interestingly, looking at the exposure chart above, prior to 2001, BRK.B traded more like a Financial than a Consumer Staple. What explains this apparent shift in how the market perceives Berkshire Hathaway? We will continue our investigation into BRK.B and Berkshire Hathaway in future blog posts.

I. Performance Projections - January 2010

The following analysis provides return projections for several hedge fund equity indices for January 2010. By conducting this analysis on a monthly basis, we are essentially creating a synthetic track record for hedge fund index replication. Compared to general back-testing procedures that use historical data, our approach projects the monthly performance before the actual returns are available. Hence, we cannot modify the data to generate more desirable results. Thus, it may be viewed as a “true” projection.

Based on our analysis, most hedge fund strategies will enter the New Year with a loss in January. According to Table 1, nearly all strategies will post a negative return (more than 1%) with long/short equity and emerging market finishing in last place.

II. Review of Last Month - December 2009
Analysis results for December 2009 are solid as the projected returns are in line with actual returns directionally and  discrepancies are minimal. The only exception is equity market neutral strategy which is a hedge fund strategy that can be hard to replicate and project. The projection difficulty is partly demonstrated by the low R-squared and predicted R-squared in our monthly analysis results.

1. CS/Tremont index was projected without using Nov. 2008 and Feb. 2009 data, as we consider these two data points outliers that would affect the quality of projection. Please refer to our March 2009 projection return for a detailed explanation.

I. Performance Projections - November 2009

The following analysis provides return projections for several hedge fund equity indices for November 2009. By conducting this analysis on a monthly basis, we are essentially creating a synthetic track record for hedge fund index replication. Compared to general back-testing procedures that use historical data, our approach projects the monthly performance before the actual returns are available. Hence, we cannot modify the data to generate more desirable results. Thus, it may be viewed as a “true” projection.

Based on our analysis, November 2009 is projected to be another solid month for the majority of hedge fund strategies. Hedge fund composite indices are projected to post positive 1-2% returns and a strong rebound is expected for emerging market indices in November.

II. Review of Last Month - October 2009
We successfully projected the correction that occurred in October for most hedge fund strategies, particularly the downward performance of long/short equity strategy. There is some discrepancy between the actual and projected returns for event driven and convertible arbitrage strategies. Technically, this under projection is due to a sudden drop of the Merrill Lynch convertible bond index which is used for the analysis. Note that further research is being conducted into these strategies.

1. CS/Tremont index was projected without using Nov. 2008 and Feb. 2009 data, as we consider these two data points outliers that would affect the quality of projection. Please refer to our March 2009 projection return for a detailed explanation.

First, we expanded the time period from our previous post. The chart below now includes excess return information for five full years from 2004 where we’ve highlighted three months: July ’07 and ’08, which have come under heavy scrutiny for alleged insider trading and July ’06, where outperformance was notably higher than both July ’07 and July’08. Over the five year period (2004-2008) these three months were the only months when the Galleon fund significantly outperformed its peers—an average technology hedge fund in the index.

Clearly, July performance numbers for each of the three years are deemed as statistical outliers (regardless of the legal connotation) which potentially could distort any further analysis of Galleon returns. In addition, the complaint mentions July 2007 $4M gain from trading Hilton—not a technology stock—which could also “contaminate” our analysis. Given the facts above we decided to remove all three July observaions as outliers.

Next, we proceed with a dynamic forensic analysis of the Galleon Technology fund’s returns similar to the one performed in our previous post using MPI Stylus™ and its DSA engine. The results of this analysis are presented in an exposure chart below. Note that this chart does not show actual holdings, but allocations to different factors that best explain the returns of the fund.

We note quite stable long exposure to several Dow Jones technology sectors. The exposure to foreign technology companies is represented by the MSCI All Country ex. US Tech index, indicating positions in ADRs, foreign stocks, or simply sensitivity to foreign markets through investing in U.S. stocks. Short exposure to PowerShares QQQ ETF is supported by the fund’s SEC filings according to which the fund maintained at times a significant position in QQQ put options. Both the cash exposure (about 60%, an indication of net 40% market exposure) and the size of the short position (30-40%) are similar to our earlier results. At the same time, these results are slightly different from the ones in the previous post, which is expected given that we removed three very large outliers.

It should be noted that because of the removal of outliers the statistical quality of the analysis improved significantly. The R-squared statistic determining the quality of fit is 89% and the Predicted R-squared, MPI’s proprietary cross-validation statistic, is 79%. Such a high quality regression is more typical for a large, diversified mutual fund. The quality of fit is also illustrated in the performance chart below where an exposure-weighted portfolio made of factor indexes (called a “Style” or “Tracking” portfolio) closely tracks the fund’s actual performance in-sample (“Total”).

Note that the tracking is exceptionally good through the middle of 2006 where the fund and the tracking portfolio lines begin to deviate slightly despite the removal of outliers. Nevertheless, both the pattern of performance and its magnitude are captured very well throughout the entire five-year history.

While the results of this analysis are very intriguing and somewhat unexpected, the study itself carries very important lessons for investors. First, it shows that analysis of hedge fund returns is a delicate, iterative process requiring careful examination of residuals. If outliers cannot be explained by any available portfolio information they could warrant removal or winzorisation. More importantly, removal of several large “alpha” outliers allowed us to show that in the remaining periods this quintessential high-turnover arbitrageur behaved more like a diversified mutual fund, with returns mimicked by a few long-term directional bets. And while massive computer-generated trading of Renaissance RIEF resulted in such an immediately apparent pattern, in the case of Galleon, the long-term directional pattern became visible only after identification and removal of several exceptional returns.

Daniel Li, PhD contributed to this research.

I. Performance Projections - October 2009

The following analysis provides return projections for several hedge fund equity indices for October 2009. By conducting this analysis on a monthly basis, we are essentially creating a synthetic track record for hedge fund index replication. Compared to general back-testing procedures that use historical data, our approach projects the monthly performance before the actual returns are available; hence, we cannot modify the data to generate more desirable results. Thus, it may be viewed as a “true” projection.

Investor sentiment negatively changed in October–a move which is also reflected in the projected performance of hedge fund indices. For all six indices, we project that only emerging market and composite indices will post positive returns (not greater than 1%.) Note that the convertible arbitrage index is projected to produce a negative return for the first time since January 2009.

II. Review of Last Month - September 2009
Our September index projections continue to be accurate as compared to the actual returns reported by data vendors. Large positive returns for emerging market, event driven and convertible arbitrage indices were successfully projected. For long/short equity and composite indices, our projections were directionally correct but underperformed the actual returns close to 1%. We believe that this outcome is due to the lagging effect of our projection; as we used the previous month’s estimated asset loadings to project current month’s index returns (essentially assuming buy and hold between the two months).

1. CS/Tremont index was projected without using Nov. 2008 and Feb. 2009 data, as we consider these two data points outliers that would affect the quality of projection. Please refer to our March 2009 projection return for a detailed explanation.

Daniel Li
Michael Markov

In the recent insider trading scandal involving the founder of Galleon Group, Raj Rajaratnam, the government used wiretaps to secretly record his phone conversations and those of his alleged accomplices. In the complaint, government prosecutors present an insider trading case against Rajaratnam and several other executives for illegally profiting from trading stocks and options of Hilton, Google, Akamai and others.

The full text of the complaint is available on the DOJ website and reads like a detective story.

There is little doubt that wiretapping is a highly effective investigative tool, but we decided to try some less intrusive methods. With $20M in profits allegedly pocketed in the scheme, we thought that there might be a possibility that the effect of these transactions could show up in Galleon’s hedge fund returns.

As a first step, we take a closer look at the actual numbers in the complaint. Below are the facts of the alleged profit from trading in 2007-2008. The rest of trading (e.g., AMD) hasn’t produced meaningful profit.

• July 3-5, 2007 trading in Hilton stock resulted in a profit of about $4M (pp.15-16 of the complaint)
• July 17-19, 2007 trading in Google stock and options resulted in profit of $8M (pp.17-19)
• July 31–Aug 6, 2008 trading in Akamai stock and options resulted in profit of $3.5M (pp.23-25) A detailed analysis of Akamai stock prices and positions listed in the complaint point to about $4.5M P&L gain booked on July 31, when Akamai stock dropped 25%. The realized gain could differ as positions were closed in early August when the stock price was steady.

The October 20th article in The New York Times puts the current assets of the Galleon Technology Fund at $350M. Assuming that the technology fund lost about 50-60% in assets over the past two years, and given the profits shown in the trades above, one should observe spikes of about 1-2% per month over the fund’s systematic, market driven return.

First, we examine the fund’s monthly returns over two years, 2007-2008, where we highlighted the periods of alleged fraud in 2007 and 2008.

One can observe a 5% return in July 2007 and 2% in July 2008 but there’s no conclusive pattern of anything questionable going on during these periods. Essentially, the pattern of the fund’s monthly returns seems random.

The next obvious step would be to distill or filter out systematic market or strategy-driven return. Once that is done, the remainder would more likely reflect security selection picks. A reasonable choice for such a procedure would be to subtract the monthly returns of an appropriate benchmark from the monthly returns of the Galleon Technology fund. In the chart below we show the return differential between the fund and the CISDM Technology Index (representing average returns of hedge funds in the Technology category). The results are striking: the only two periods when the Technology fund significantly outperformed the index are the two months mentioned in the complaint.

Of course, the magnitude of excess performance spikes is 2-3 times higher than what we expected to see and the results are completely dependent on the choice of index. Still, this qualifies as a good initial sanity check.

However, what if a fund had an obscure strategy and a reasonable benchmark wasn’t easily available? In such a case, a forensic analysis of the hedge fund returns could provide an answer. Using MPI Stylus™ and its Dynamic Style Analysis model (”DSA”) we attempted to reverse-engineer the Galleon Technology fund’s returns.¹ After an exhaustive search of thousands of potential combinations of factors and sector indices, the model selected only a handful of relevant factors that best mimic the return behavior of the fund over a two-year period from 2007-2008. The results of this analysis are presented in exposure chart below. Note that this chart does not show actual holdings, but allocations to different factors that best explain the returns of the fund.

The apparent exposure to the Tech and Biotech Dow Jones sector indices, as well as the amount of leverage determined by MPI’s DSA model, are supported by the scant information about the fund’s strategy. It is widely known that the fund made long and short bets on software and hardware companies and maintained a moderate short position of 30-40%. The latter is confirmed by our analysis showing average negative exposure of about 40%. The credibility of the above analysis is also supported by MPI’s proprietary cross-validation statistics. The cash position of roughly 70% could indicate either hedging or margin position. In more generic terms it tells us that the fund had about 30% net long exposure.

Note that the factor exposures are exceptionally stable and an exposure-weighted portfolio made of these indexes (called a “Style” or “Tracking” portfolio) closely tracks the fund’s actual performance in-sample as shown in the cumulative growth chart below.

It should be noted that even though the fund’s strategy was primarily short-term arbitrage, a significant portion of its returns could be explained by directional sector bets and easily replicated with a handful of ETFs if anyone wanted to.

Finally, we compute the return differential between the fund and its dynamic in-sample tracking portfolio (“Style”). These returns are shown in the chart below and are called “Selection” returns as they could be attributed to non-systematic factors such as skill, luck or… insider trading.

We readily observe that both July’07 and July’08 returns are outliers on the positive side. Their magnitude is in the range of what one would expect to see based on the information presented in the complaint. Interestingly, if these two months are taken out of consideration, our analysis shows that the fund manager had unimpressive stock selection results in 2008. Obviously, not every spike in selection return is a suspect of insider trading and the prosecution is yet to prove their case. At the same time, this case adds another important dimension to routine analysis of a portfolio manager’s selection skill: what if it’s neither luck nor skill but something else? An analysis like this one helps investors to frame their questions and precisely position them in time.

What was presented in this quick analysis of a suspect fund obviously cannot be used as evidence in court. Clearly, wiretapping as a prosecutor’s tool wins here hands down. But, for investors with no access to their investments’ positions (forget about wiretapping!) and struggling to reconcile their funds’ performance with common sense and market moves (Performance is too good to be true? Why are the returns so smooth? Why the fund is up when everyone else is down? etc.) a quantitative forensic analysis remains the only viable option. Investors should be and can be smarter than wiretaps.

1. For those unfamiliar with our methodology we refer to the Research Center and other posts in this blog for details.

http://online.barrons.com/article/SB125513241806577275.html

In the article, the author notes that the manager of the flagship Legg Mason Value Trust fund is at the top of its relative peer group for 2009, delivering a 37% YTD return compared to 19% return for the S&P 500 index. The article attributes the fund’s poor performance in 2007-2008 to both sector bets in financials along with poor security selection in names such as Lehman Brothers and JPMorgan. This year, the author concludes, the manager must be doing something right.

Several years ago we performed a detailed analysis of Mr. Miller’s fund to better understand the sources of its well documented 15-year winning streak through 2006.

This time around however our goal was to take a very top level look at the performance drivers behind the fund’s turnaround in 2009. We wanted to identify whether Mr. Miller had “passively” benefited from the market rebound or actively employed new strategies to help lift the fund’s return (or a combination of both).

We started the analysis by analyzing the fund’s monthly returns from January 2007 through September of 2009. The chart below illustrates the fund’s returns-based style analysis factor exposures using S&P 500 sector indices.

There are two immediate observations: (a) Legg Mason Value Trust has had considerable overweights in financials and technology relative to their benchmark S&P 500 index; and (b) overweights in these sectors have remained relative stable throughout the period. From an RBSA perspective, there were virtually no notable structural changes in the fund and that Mr. Miller maintained the fund’s sector composition going into 2009.

Performance attribution analysis in the chart below decomposes the fund’s excess return into timing and selection components. Mr. Miller’s 17% excess return over the index in 2009 can be attributed to both “timing” and “selection” in almost equal proportion. Sector bets accounted for roughly fifty-percent of the fund’s “turnaround” with the other half attributed to security selection within those sectors.

The attribution chart above shows that timing and selection components had roughly equal share in the fund’s underperformance in 2007 and 2008 by 12% and 18% respectively. Mr. Miller’s overweight in financials and associated names such as Lehman Brothers created serious problems for the fund in 2008.

This analysis is very top level and we will post a more comprehensive Performance Attribution Report shortly.

Wall Street Journal’s print edition on October 5, 2009 also featured Mr. Cinnamond as placing second in the Winner’s Circle contest for the 12-month period through September 2009 (posting a 29% return).

We decided to take a closer look using daily data and returns-based style analysis (RBSA), and found Mr. Cinnamond’s selection skills over the past eighteen months have been strikingly strong relative to other small capitalization mutual funds.

We were surprised to find “timing contribution” was only incremental given Mr. Cinnamond’s sizeable moves into cash and other sectors over this period of high market volatility. Most of the excess performance as determined by the sector specific returns-based style analysis model was generated through “selection” as shown in the chart above. Together, the combination of both timing and selection skill led to dramatic excess outperformance of 23.0% over the Russell 2000 Index for the period March 2008 to September 2009.

MPI clients: For a more in-depth Performance Attribution report, please click here. To obtain the mpi Stylus Pro daily attribution template, please contact support@markovprocesses.com. Facilitated and interactive Case Study Webcasts on Intrepid Small Cap and other investment product are available to clients on an ongoing basis. Schedule and sign-up requests can be accessed here.

Non-subscribers: For a more in-depth performance attribution report, please complete this online form and the analysis will be sent to you shortly.