Ardia, David

2017-4, Ardia, David, Gatarek, Lukasz, Hoogerheide, Lennart

2013, Ardia, David, Boudt, Kris

There is extensive empirical evidence that funds of hedge funds (FoHFs) quickly change their investment bets as a function of the changing market conditions. In this chapter, we first analyze the stability of risk exposure and performance of FoHFs during the period January 2005–June 2011. We then study the short-run persistence of performance in the FoHFs industry. Past performance is measured using the 1-year trailing return as well as risk-adjusted measures such as the Sharpe ratio and the fund’s alpha based on the Carhart (1997) or Fung and Hsieh (2004) factor models. Over the examined timeframe, we consistently find that using risk-adjusted return measures improves the risk-adjusted performance of the momentum investment strategy. This finding holds for the financial crisis period as well as the pre- and post-crisis periods.

2014, Ardia, David, Hoogerheide, Lennart

We analyze the impact of the estimation frequency - updating parameter estimates on a daily, weekly, monthly or quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily returns for constituents of the S&P 500 index. We assess the implication for one-day ahead 95% and 99% Value-at-Risk (VaR) forecasts with the test for correct conditional coverage of Christoffersen (1998) and for Expected Shortfall (ES) forecasts with the block-bootstrap test of ES violations of Jalal and Rockinger (2008). Using the false discovery rate methodology of Storey (2002) to estimate the percentage of stocks for which the model yields correct VaR and ES forecasts, we conclude that there is no difference in performance between updating the parameter estimates of the GARCH equation at a daily or weekly frequency, whereas monthly or even quarterly updates are only marginally outperformed.

2014, Ardia, David, Boudt, Kris, Mullen, Katharine, Peterson, Brian