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Hedge Fund Replication: A Model Combination Approach

Review of Finance 2017 21(4), 1767-1804
Recent years have seen increased demand from institutional investors for passive replication products that track the performance of hedge fund strategies using liquid investable assets such as futures contracts. In practice, linear replication methods suffer from poor tracking performance and high turnover. We propose a model combination approach to index replication that pools information from a diverse set of pre-specified factor models. Compared with existing methods, the pooled clone strategies yield consistently lower tracking errors, generate less severe portfolio drawdowns, and require substantially smaller trading volume. The pooled hedge fund clones also provide economic benefits in a portfolio allocation context.

Does It Pay to Bet Against Beta? On the Conditional Performance of the Beta Anomaly

Journal of Finance 2016 71(2), 737-774
Prior studies find that a strategy that buys high‐beta stocks and sells low‐beta stocks has a significantly negative unconditional capital asset pricing model (CAPM) alpha, such that it appears to pay to “bet against beta.” We show, however, that the conditional beta for the high‐minus‐low beta portfolio covaries negatively with the equity premium and positively with market volatility. As a result, the unconditional alpha is a downward‐biased estimate of the true alpha. We model the conditional market risk for beta‐sorted portfolios using instrumental variables methods and find that the conditional CAPM resolves the beta anomaly.

Stocks for the long run? Evidence from a broad sample of developed markets

Journal of Financial Economics 2022 143(1), 409-433
We characterize the distribution of long-term equity returns based on the historical record of stock market performance in a broad cross section of 39 developed countries over the period from 1841 to 2019. Our comprehensive sample mitigates concerns over survivor and easy data biases that plague other work in this area. A bootstrap simulation analysis implies substantial uncertainty about long-horizon stock market outcomes, and we estimate a 12% chance that a diversified investor with a 30-year investment horizon will lose relative to inflation. The results contradict the conventional advice that stocks are safe investments over long holding periods.

Tax uncertainty and retirement savings diversification

Journal of Financial Economics 2017 126(3), 689-712
We investigate the optimal savings decisions for investors with access to pre-tax (traditional) and post-tax (Roth) versions of tax-advantaged retirement accounts. The model features a progressive tax schedule and uncertainty over future tax rates. Traditional accounts are valuable for hedging retirement account performance and managing current income near tax-bracket cutoffs, whereas Roth accounts allow investors to mitigate uncertainty over future tax schedules. The optimal asset location policy for most households involves diversifying between traditional and Roth vehicles. Contrary to conventional advice, the substantial economic benefits from Roth investments are not limited to investors with low current income.

On the performance of volatility-managed portfolios

Journal of Financial Economics 2020 138(1), 95-117
Using a comprehensive set of 103 equity strategies, we analyze the value of volatility-managed portfolios for real-time investors. Volatility-managed portfolios do not systematically outperform their corresponding unmanaged portfolios in direct comparisons. Consistent with Moreira and Muir (2017), volatility-managed portfolios tend to exhibit significantly positive alphas in spanning regressions. However, the trading strategies implied by these regressions are not implementable in real time, and reasonable out-of-sample versions generally earn lower certainty equivalent returns and Sharpe ratios than do simple investments in the original, unmanaged portfolios. This poor out-of-sample performance for volatility-managed portfolios stems primarily from structural instability in the underlying spanning regressions.