Welcome to my personal website.
I am Chunjie Wang. I am an assistant professor in finance at KU Leuven. I obtained PhD in finance at Stockholm School of Economics. My research interest lies in empirical asset pricing, and machine learning applications.
You can reach me by my social accounts or by email: chunjie.wang@kuleuven.be
Working Paper
Asset pricing, not equity pricing
job market paper
This paper demonstrates that building characteristics-managed factors using firms' asset returns greatly reduces the number of factors necessary to explain the cross-section. A 5-factor model based on asset returns explains 62.4% of the variation in 100 factors, whereas an 88-factor model using equity returns explains only 38.6%. Out-of-sample, the asset-based implied mean-variance-efficient (MVE) portfolio achieves a Sharpe ratio of 1.2, compared with 0.75 for its equity-based counterpart. The parsimonious asset-based model explains equity returns better than the equity-based model, as it reduces the number of equity anomalies to 15 compared with 23 for the latter. The nonlinear transformation of returns caused by leverage increases the loadings of firms with high leverage on the equity-based factors, exposes these factors to firm-level systematic risks that would not arise in asset-based factors, and contributes to the factor zoo.
Betting on Stocks with Options?
with Adrien d’Avernas, Christian Schlag, Tobias Sichert, and Martin Waibel
We examine whether expected stock returns translate into expected option returns as predicted by standard theory. Using machine-learning estimates of expected stock returns, we uncover a pronounced U-shaped relation between expected returns and volatility, whereby both high and low expected stock returns coincide with elevated volatility, which increases option prices and largely offsets the expected payoff differential. We derive a model-free lower bound on expected option return spreads and show it is strongly violated in the data; as a result, equity options are an inefficient instrument for harvesting stock risk premia. A calibrated Black–Scholes model reproduces these empirical patterns.
