Juha Joenväärä

Hedge Fund Performance: What Do We Know?

This paper proposes a novel database merging approach and re-examines the fundamental questions regarding hedge fund performance. Before drawing conclusions about fund performance, we form an aggregate database by exploiting all available information across and within seven commercial databases so that widest possible data coverage is obtained and the effect of data biases is mitigated. Average performance is significantly lower but more persistent when these conclusions are inferred from aggregate database than from some of the individual commercial databases. Although hedge funds deliver performance persistence, an average fund or industry as a whole do not deliver significant risk-adjusted net-of-fee returns while the gross-of-fee returns remain significantly positive. Consistent with previous literature, we find a significant association between fund-characteristics related to share restrictions as well as compensation structure and risk-adjusted returns.

The Effect of Investment Constraints on Hedge Fund Investor Returns

This paper examines the effect of investor-level real-world investment constraints, including several which had not been studied before, on hedge fund performance and its persistence. Using a large consolidated database, we demonstrate that hedge fund performance persistence is significantly reduced when rebalancing rules reflect fund size restrictions and liquidity constraints, but remains statistically significant at higher rebalancing frequencies. Hypothetical investor portfolios that incorporate additional minimum diversification constraints, minimum investment requirements, and focus on open funds suggest that the performance and its persistence documented in earlier studies of hedge funds is not easily exploitable, especially by large investors.

Share Restrictions, Risk Taking and Hedge Fund Performance

This paper examines the impact of share restrictions on the risk-taking and on the performance of hedge funds using the Hedge Fund Research (HFR) database. Share restrictions, in the form of longer lockup as well as notice and redemption periods, provide flexibility for the managers. Our results suggest that this flexibility allows hedge fund managers with lockup provision to take an excess risk, which is not compensated, when performance is measured as a unit of the risk taken by the manager. Specifically, we find that typical hedge funds with a lockup provision deliver 5.6-6.6% (3.8-5.4%) lower Fung and Hsieh (2004) appraisal ratios (Sharpe ratios) compared to their peers without a lockup provision. The results remain consistent even after controlling for various database biases, alternative risk and performance measures, and non-linearities in hedge fund returns.

Predicting Hedge Fund Performance with Fund Characteristics

In this paper, we evaluate hedge fund performance by forming hedge fund portfolio strategies that exploit the fund’s characteristics. Speci…cally, we parameterize optimal portfolio weights as a function of the fund’s characteristics such as the manager’s option delta, the fund’s size, and the notice period by applying a method proposed by Brandt, Santa-Clara, and Valkanov (2008). We …nd that the characteristics-based strategy delivers a signi…cant Fung-Hsieh (2004) alpha for a real time hedge fund investor even after controlling for underlying redemption and subscription impediments associated with hedge funds.

Information Content of Hedge Fund Equity Option Holdings

This paper examines the information content of hedge fund equity option holdings via a representative sample of 13F reports that provides information on option characteristics and prices. We find that hedge funds prefer to hold high-embedded leverage, out-of-the-money options with relatively short maturities but without illiquidity or lottery-like skewness. We also establish that the positive returns on various option portfolios that mimic hedge funds’ holdings are unexplainable by option characteristics and common sources of risk. Those positive returns are driven mainly by variation in stock returns and higher for directional (especially call) options. These results are consistent with informed directional trading based on stock-level information. Also consistent with informed trading is our finding that aggregated option holdings contain information that is predictive of stock-level returns. We use portfolio sorts and panel regressions to show that hedge funds’ stock-specific aggregate delta predicts the return on underlying stocks.

Hedge Fund Performance Prediction

This paper studies hedge fund performance and confirms reports of an aggregate decline over the past decade. We test whether a comprehensive set of prediction models can select subsets of individual funds that buck the trend and subsequently outperform. Seven of the predictors reliably pick funds that lower the volatility and raise the Sharpe ratio of a multi-asset class portfolio relative to a stock/bond portfolio over the full 1997 – 2016 sample. Hedge fund allocations reduce volatility across two sub-periods, but fail to improve the Sharpe ratio from 2008 onwards. Potential explanations for the erosion of hedge fund performance are explored.

Hedge Fund Tail Risk: Hedging Mechanisms and Performance

We decompose hedge fund tail risk into two components: Systematic Conditional Tail Risk (SCTR) arising predictably from equity market exposure, and Idiosyncratic Conditional Tail Risk (ICTR) arising from proprietary investment technology. Using option holdings data, we demonstrate that low-SCTR funds mechanically use protective options. Low-ICTR funds seem to pose tail risk hedging skills, because they use protective options heavily only during the times of market stress. Low-ICTR (Low-SCTR) funds (do not) deliver superior performance. Our results hold after controlling for performance measure manipulation, nonlinearities and autocorrelation in fund returns, and cannot be subsumed by existing skill or risk measures.

Frictional Diversification Costs: Evidence from a Panel of Fund of Hedge Fund Holdings

We analyze the diversification choices of fund of hedge fund managers. Diversification is not a free lunch. It is not available for every fund of fund. Instead we find a positive log-linear relation between the number of constituent funds in a fund of hedge fund (n) and the respective assets under management, (AuM ). More precisely it takes the form: n^2 proportional to AuM. This relation is consistent with the predictions from a model of naïve diversification (1/n) with frictional diversification costs such as due diligence costs. Finally, we demonstrate that individual FoFs diversifying more in line with our model’s predictions deliver superior performance and fail less likely.

Effect of Regulatory Constraints on Fund Performance: New Evidence from UCITS Hedge Funds

We economically motivate and then test a range of hypotheses regarding performance and risk differences between UCITS-compliant and other hedge funds. The latter exhibit more suspicious return patterns than do absolute return UCITS (ARUs), but ARUs exhibit higher levels of operational risk. We find evidence of a strong liquidity premium: hedge funds offer investors less liquidity than do ARUs yet exhibit better risk-adjusted performance. Our findings are substantially unchanged under various robustness tests and adjustments for possible selection bias. The liquidity premium for ARUs and their lack of performance persistence have implications for both investors and policy makers.