Alpha generation: The search for the unexplainable

Equity market neutral strategies stripped


We began this research effort on the hypothesis that one can use an equity market neutral strategy to either a) isolate exposure on idiosyncratic risks or b) isolate exposure to equity factors like value or momentum. The latter is steeped with academic research and readily available as long-short risk premia products from investment banks. The former is filled with the unknown and is highly desirable for portfolio diversification, but as one can imagine, is difficult to generate for hedge fund managers.

A relatively simple definition of alpha is the return driven in an unrelated fashion to one’s benchmark. Capital allocators have greater access to cheap strategies, markets, and risk types due to the boom in passive investing products. Although these make reducing returns down to the bare bones much easier as we can strip out more risk exposures, the transparency makes the active manager’s job significantly more challenging. The goal of all active managers is to provide, from a quantitative perspective, alpha. This represents the unexplainable returns once stripped of various loadings.

Allocators look for a large portion of a fund’s return to be alpha. Otherwise, why pay high active management fees?

In this short research note, we analyse the returns of equity market neutral hedge fund managers, both systematic and discretionary, to study how much alpha they are generating and whether we can explain what is driving their returns.

Systematic equity market neutral performance stripped

We are using a proprietary data set of equity market neutral hedge funds (EMN) that are classified as either discretionary or systematic based on the funds’ descriptions. A significant number of these funds either stopped existing or are no longer reporting returns, which means the data set features survivorship bias.

For this analysis, we conducted a two-stage return decomposition. First, we regressed the systematic EMN index’s returns against the returns of the S&P 500 and removed the market beta; we call this the net of market beta index. We then ran a multiple linear regression using common equity factors, namely value, momentum, quality, size, and low volatility against this index. This then leaves us with what we call the Alpha Index and represents the unexplained returns. Stated differently, it is the alpha generated by the hedge fund managers’ net of market beta and equity factors.

Intuitively, we would expect the equity market neutral index to have no relationship with market beta given their objective of offering uncorrelated returns. Capital allocators would hope to find the majority of returns coming from equity factors given that these are systematic funds, or better, represent true alpha.

As shown in previous research notes we have published, the EMN index has generated a significant portion of its returns from simply providing exposure to the stock market. At its peak in 2018, alpha accounted for a little under a third of the EMN index’s returns. However, the alpha generation turned negative thereafter and essentially was zero over the entire period between 2011 and 2020.


Source: ACE Capital Investment, FactorResearch

Discretionary equity market neutral performance stripped

The Discretionary EMN Index was run through the same process as its systematic brethren to calculate its Net of Market Beta and Alpha indices.

Once again, undesirably, we observe that market returns contributed a large portion to the Discretionary EMN Index returns. Furthermore,  equity factors explain even more of the returns than for systematic funds, which is somewhat ironic given that discretionary managers do not tend to invest quantitatively. The total alpha generated across the observation period of almost a decade was zero.

chart, line chart

Source: ACE Capital Investment, FactorResearch

Performance analysis

To further analyse the performance of the EMN indices, we break down the factor loadings of the return stream to get a sense of what specifically has been driving each index.

Intuitively, we would expect a greater relationship with equity factors for systematic hedge fund managers over discretionary managers given the more academic-centred and data­ driven investment process. After running factor loadings on the Net of Market  Beta Index for each investment process, we found that this theory is true with Value, Momentum, and Quality having roughly double the weighting for systematic managers versus discretionary managers.

Given that Value has significantly underperformed over the last decade and systematic managers had a high exposure to that factor explains a significant part of their poorer performance relative to the discretionary managers.

chart, waterfall chart

Source: ACE Capital Investment, FactorResearch

Although the alpha generation was essentially zero, these hedge fund strategies can still be valuable if they provide greater risk-adjusted performance than the alternative.

Therefore, we calculated the Sharpe ratio of the various indices for the period from 2011 to 2020. The discretionary managers provided better risk-adjusted performance than the S&P 500 while the systematic managers produced a worse risk-adjusted Sharpe than the S&P 500, which can primarily be contributed to the divergence in performance in 2020. Given that the alpha was zero for either type of fund manager, the Sharpe ratios are zero.

chart, bar chart

Source: ACE Capital Investment, FactorResearch

Index replication

Given the explanatory power of both the S&P 500 and equity factors on the EMN indices, we can create replication indices using the betas. The first replication index allocates 15% to the S&P 500 and 85% to an equal-weighted long-short multi-factor equity portfolio while the second one allocates 15% to the S&P 500 and 85% to cash.

We observe that these simple replication indices exhibited the same performance trends as the Systematic and Discretionary EMN indices, which questions the diversification benefits and alpha generation that these hedge fund managers aim to provide. Capital allocators can replicate these indices easily themselves and avoid paying management and performance fees as well as the complexity of hedge fund due diligence and monitoring.

chart, line chart

Source: ACE Capital Investments, FactorResearch

Further thoughts

It is worth mentioning one caveat to the research above: the analysis is based on indices and therefore we are just looking at the average hedge fund’s performance. There will be both winners and losers within the indices that produce more and less alpha versus what the average fund does.

We have previously shown that neither discretionary and systematic hedge fund managers offered performance consistency when contrasting in-sample and out-of-sample returns. However, capital allocators continue to invest billions in a few highly successful hedge funds like Citadel and Millennium. It would be interesting to explore their returns and understand what has been driving them. Is it alpha, or just market beta and factor exposure again?

A further interesting area of research is the relationship between alpha generation and stock market volatility. Fund managers frequently comment that they require volatility to generate alpha, but that does not seem to be supported by the data. In contrast, when volatility spiked during the COVID-19 crisis in early 2020, both types of equity market neutral strategies lost money. Naturally, this is not desirable to capital allocators as that is when portfolio diversification is needed the most.

Nicolas Rabener is founder and CEO of Factor Research and Karl Rogers is founder of ACE Captial Investments

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