Suk Jun Byun
Korea Advanced Institute of Science and Technology · Economics, Econometrics and Finance
About the Lab
Professor Suk Jun Byun's research lab specializes in asset pricing, behavioral finance, and financial econometrics, with a focus on return predictability, market inefficiencies, and investor sentiment. The lab investigates how behavioral biases—such as overconfidence and self-attribution—impact asset prices and trading strategies, particularly through measures like continuing overreaction and lottery-like stock preferences. It also explores advanced volatility modeling, including variance risk premium and stochastic volatility models, using high-frequency data to improve forecasting accuracy. The lab emphasizes both theoretical modeling and empirical testing using extensive market data from U.S. and international equity, currency, and fixed-income markets.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15We study the return predictability of a measure of continuing overreaction based on the weighted average of signed volumes. We find that the strategies of buying stocks with upward continuing overreaction and selling stocks with downward continuing overreaction generate significant positive returns and that our measure of continuing overreaction is a better predictor of future returns than past returns. The results are stronger among stocks primarily held by investors more prone to biased self-a
On the basis of the theory of a wedge between the physical and risk‐neutral conditional volatilities in Christoffersen, P., Elkamhi, R., Feunou, B., & Jacobs, K. (2010), we develop a modification of the GARCH option pricing model with the filtered historical simulation proposed in Barone‐Adesi, G., Engle, R. F., & Mancini, L. (2008). The one‐day‐ahead conditional volatilities under physical and risk‐neutral measures are the same in the previous model, but should have been allowed to be d
The discrepancy between in‐sample and out‐of‐sample predictability of common predictors for asset returns has been widely discussed in the literature. We examine the out‐of‐sample predictability and its economic significance of Variance risk premium (VRP), which recently has shown empirical success in predicting asset returns in‐sample. Extensive analysis indicates strong out‐of‐sample predictability of the VRP for U.S. stock index, currencies, credit index, and equity portfolios. However, we do
Stocks with extreme positive returns underperform the market since they are overpriced due to investors’ preference towards lottery-like stocks, stocks with a low probability of an extremely high payoff. Using data from the South Korean stock market, we show that the underperformance of such stocks is pronounced following periods of low investor sentiment. This suggests that low investor sentiment coincides with economic downturn when stocks with extreme positive returns experience increased sal
Purpose The purpose of this paper is to examine whether the superiority of the implied volatility from a stochastic volatility model over the implied volatility from the Black and Scholes model on the forecasting performance of future realized volatility still holds when intraday data are analyzed. Design/methodology/approach Two implied volatilities and a realized volatility on KOSPI200 index options are estimated every hour. The grander causality tests between an implied volatility and a reali
Momentum strategies suffer from occasional large drawdowns referred to as momentum crashes when the market rebounds. We find that a surge of investor speculation toward stocks far from their 52-week highs can partially explain the momentum crashes. If a momentum strategy is revised to be neutral on a 52-week high effect, momentum crashes are significantly attenuated and the revised strategy does not exhibit procyclical returns. Furthermore, the revised strategy generates a higher Sharpe ratio in
Research Areas
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