Editor’s Letter

This issue of The Journal of Alternative Investments starts with an interesting perspective piece by Zura Kakushadze and Ronald P. Russo, Jr., who discuss several applications of the blockchain technology outside of cryptocurrency and initial coin offerings. In “Blockchain: Data Malls, Coin Economics, and Keyless Payments,” the authors focus on three main areas: the role of blockchain-based coins for “data malls” (specialized data marketplaces), data provenance (a historical record of data and its origins), and “keyless payments,” which are made without having to know other users’ cryptographic keys. As an example, they note that data provided by a prediction market can be connected to a blockchain where participants are rewarded or penalized for their predictions.

The next article covers an unexplored aspect of the emerging area of factor investing. Since factor investing requires a factor investor to hold portfolios with weights that deviate significantly from the market cap of those securities, nonfactor investors must be willing to hold the other side of the trade. For instance, if a large group of investors decides to allocate to high beta/volatility portfolios because they cannot use leverage, other investors must have an “abnormal” allocation to low-volatility portfolios. One can naturally ask, “Who are these investors and are they compensated for the risk they are taking?” In “Are Hedge Funds on the Other Side of the Low-Volatility Trade?” David Blitz explores this question. The low-volatility anomaly is often attributed to limits to arbitrage, such as leverage, short-selling, and benchmark constraints. Therefore, Blitz argues that one would expect hedge funds, which are typically not hindered by these constraints, to be the smart money that can benefit from the anomaly. He finds that the return difference between low- and high-volatility stocks is indeed a highly significant explanatory factor for aggregate hedge fund returns, but with the opposite sign; that is, hedge funds tend to bet against the low-volatility anomaly, rather than on it. This finding suggests that limits to arbitrage are not the key driver of the low-volatility anomaly and that concerns about low-volatility having become an “overcrowded” trade may be exaggerated.

“Reconsidering Hedge Fund Contagion,” challenges that idea that hedge funds act as a negative, disruptive force in financial markets due to “contagion.” Hedge funds are often viewed as culprits in both the 2007–2008 financial crisis and the 2007 quant crisis, for example. Richard Sias, H.J. Turtle, and Blerina Zykaj evaluate existing and new evidence of: 1) hedge fund contagion, 2) hedge fund crowding, 3) hedge funds’ role in the 2007–2008 financial crisis, and 4) hedge funds’ role in the August 2007 quant crisis. Contrary to conventional wisdom, the popular press, and most academic work, they find little evidence to support the view that hedge fund contagion has widespread negative effects on markets and mispricing.

Many essential portfolio management tasks incorporate the development of views on the future correlation between assets. To the extent that such views are formed by analyzing historical data, they are associated with estimation errors. In “Hedging and Constructing Portfolios of Active Strategies: Strategy Time Horizon and Estimation Errors,” Alexander Rudin and William Marr discuss estimation errors for active strategies and describe how such errors affect hedging and portfolio construction decisions. They point out that for active strategies with time horizons extending over multiple data points within the historical sample, the number of independent observations is not provided by the number of data points in such a sample, but is considerably smaller instead. This leads to a situation where the correlation estimation error scales down with the sample size much more slowly than it does over the square root of the sample size, the rate usually suggested by traditional thinking. A t-statistic reflecting this intuition is offered for a single strategy hedging problem. Implications for hedging and construction of hedge fund and risk premia portfolios are then discussed briefly.

A wide range of research has suggested that informed trading in options markets may effectively signal subsequent changes in equity prices. In “Option Informed Stock Picking,” Edward Szado, Hossein Kazemi, and Thomas Schneeweis analyze the performance of long/short strategies based on a number of signals from options markets. In addition, they create an easily implemented long-only strategy based on a subset of the signals (volatility risk premium, option/stock volume ratio, implied volatility skew, and realized volatility). The analysis of the period from 1996 through mid-2015 shows significant outperformance of a long-only, equal-weighted portfolio relative to the S&P 500 and the equal-weighted S&P 500. A return attribution analysis confirms that the outperformance is provided by individual stock selection rather than sector selection.

Market efficiency is one of the cornerstones of financial theory with immense implications for the asset management industry. It is widely accepted that major global equity markets such as those found in the United States, the United Kingdom, Japan, France, and Germany are highly efficient and that simple trading rules are unlikely to generate consistent abnormal returns. In “Return Predictability and Efficient Market Hypothesis: Evidence from Iceland,” Massoud Metghalchi, Massomeh Hajilee, and Linda Hayes examine whether technical analysis has predictive power in the case of the OMX Iceland All-Share Index. They study whether such trading rules could be employed by a trader to outperform a buy-and-hold strategy of the index after corrections for transaction costs. They first examine the evidence and assert that trading rules have predictive power. They then design four strategies for each trading rule and conclude that it is possible to exploit the predictive power of these rules.

The final article of this issue, “Do Implicit Phenomena Matter? Evidence from China Stock Index Futures” by Min-Yuh Day, Paoyu Huang, Yensen Ni, and Yuhsin Chen, deals with potential market inefficiency in China Stock Index Futures. The authors observe that the CSI 300 Futures Index rises (falls) implicitly in five consecutive minutes. The authors explore whether investors would profit when the implicit rising (falling) phenomena occur. The study reveals that this observation precedes a rise (fall) of the underlying index, the CSI 300 Futures Index, which could be used to generate abnormal profits. The authors suspect that this observation is likely to be an indication of market manipulation attempts by some types of investors.

We hope that you will enjoy this issue of The Journal of Alternative Investments, and, as always, we welcome your comments.

Hossein Kazemi

Editor-in-Chief

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