Essays in Empirical Finance

This PhD dissertation is comprised of two substantive chapters in different areas of empirical finance. In the first chapter which is published in the “International Review of Financial Analysis”, I dissect the investing style of different hedge fund strategies, while in the second chapter, I investigate the stock-oil conditional comoments, by employing a battery of modern econometric methods. The following paragraphs provide a summary for each chapter. The first chapter, “Dissecting Hedge Funds' Strategies” (joint with Asmerilda Hitaj), dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds’ return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds’ investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds’ performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market. The second chapter “Stock-Oil Comovements Through Fear, Uncertainty, and Expectations: Evidence from Conditional Comoments", investigates the dependencies and comovements between the S&P 500 and WTI by means of time-varying conditional comoments from April 1983 to December 2021 at the daily level. The conditional comoments mark a new pattern between the two markets' dependencies since the 2008 global financial crisis (GFC). I employ three macroeconomic sentiment measures, including VIX (representing fear), economic policy uncertainty (representing uncertainty), and expected business condition index (representing expectation), to investigate the underlying mechanism for the new emerging stock-oil comovements, using the time-varying parameter vector autoregression (TVP-VAR) to investigate the time-varying impulse responses, and the nonlinear autoregressive distributed lag (NARDL) model to analyze the asymmetries in the short- and long-run effects of the sentiment indices for the pre- and post-GFC periods. The conditional comoments of both markets change direction since the GFC, with crude oil showing a stronger dependence on the S&P 500's return, skewness, and tail events than its counterpart. Overall, the time-varying impulse responses show heightened short-lived responses to the three sentiment indices after the 2008 GFC, with an asymmetric response from the conditional comoments of WTI (negative) and S&P 500 (positive) to the positive shocks in the fear index during the post-GFC period. The NARDL regression results prove that the explanatory power of the three sentiment indices increase largely after the GFC, with strong short-run asymmetries. Further investigations reveal that oil-specific fear index has weaker effect on stock-oil comoments than VIX.

Questa tesi di dottorato è composta da due capitoli sostanziali in diverse aree della finanza empirica.