Essays on the Timing and Combination of Equity Factors

Publication: ThesisDoctoral thesis


This dissertation consists of three chapters that study the properties of the timing and combination of equity risk factors. Even though most results relate to empirical asset pricing, they might nonetheless be important for the practice of equity portfolio management.
The first chapter, TIMING THE FACTOR ZOO, is co-authered with Andreas
Neuhierl, Otto Randl and Josef Zechner.We conduct a comprehensive analysis of the timing success of more than 300 equity risk factors (factor zoo) and a high dimensional set of predictors. Our analysis shows that factor timing is indeed possible, with improvements being highest for profitability and value factors. The most successful individual predictor of factor returns are momentum and volatility signals, however both are dominated by aggregating many predictors using partial least squares. We find that predictability is not concentrated in short subsamples of the data and does not decay in recent time periods.
The second chapter, VOLATILITY MANAGED MULTI - FACTOR PORTFOLIOS, is co-authored with Josef Zechner. We jointly use volatilities of past factor returns and option-implied market volatilities to determine the exposure in multi-factor portfolios. The resulting portfolio performance can be improved significantly, and is much larger in risk regimes characterized by option-implied right-skewed and/or high volatility market returns. We also estimate parameters separately for different regimes and find even higher risk-adjusted portfolio returns. These findings are robust to transaction costs. Using principal component analysis
for a large universe of factors, we show that the results are not driven by a specific set of factors.
In the third chapter, COMBINING FACTORS, we investigate characteristicsbased
scorings to obtain factor portfolios. While it remains largely unexplored how
firm-level characteristics can be combined to obtain optimal factor portfolios, we derive multi-factor portfolios via a combination of stock characteristic scores. These portfolios, which are formed on multiple characteristics are less volatile, and exhibit higher after cost returns compared to the market and single factor portfolios. A major part of the return, risk and turnover preferences are driven by the specification of buy- and sell-thresholds. We further identify optimal weights for individual factor characteristics, but have to recognize the 1/N factor portfolio as a tough benchmark.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Vienna University of Economics and Business
  • Zechner, Josef, 1st supervisor
  • Randl, Otto, 2nd supervisor
Award date31 Aug 2022
Publication statusPublished - 31 Aug 2022

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