Soohun KimPhd Candidate in Finance (Expected 2013)
Kellogg School of Management
2001 Sheridan Rd #433, Evanston, IL, 60208
Research Interests: Asset Pricing, Financial Econometrics
Job Market Paper
Asset Prices in Turbulent
Markets with Rare Disasters (2012)
I propose a parsimonious econometric model for the stochastic process governing the evolution of per capita consumption and stock market dividend over time. The model features stochastic volatility of consumption and dividend growth rates, and time-varying likelihood of rare disasters. I embed this time-variation of risk in an endowment economy with a representative agent and estimate parameters from U.S. stock market data using Maximum Likelihood. Allowing for time-varying likelihood of rare disasters improves the model's performance. My model successfully explains a number of empirical puzzles: the high equity risk premium, excessive volatility of equity return, predictability of market returns through the dividend-to-price ratio, and the cyclical patterns observed in the term structure of the yield on dividend strips.
Tail Risk in Momentum Strategy Returns (2012) with Kent Daniel and Ravi
Price momentum strategies have historically generated high positive returns with little systematic risk. However, momentum strategies incur periodic but infrequent large losses. During 13 of the 978 months in our 1929:07-2010:12 sample, losses to a US-equity momentum strategy exceeded 20 percent per month. We characterize these risk-spikes with a two state hidden Markov model, with turbulent and calm states. These states are persistent and forecastable using ex-ante instruments. Each of the 13 months with losses exceeding 20 percent per month occurs during a turbulent month, meaning a month when the predicted probability of the hidden state being turbulent exceeds 50%. During turbulent months, momentum returns are more volatile, and average -0.47%/month. A dynamic momentum strategy that avoids turbulent months has a monthly Sharpe Ratio 0.30 -- double that of the static momentum strategy. The predictability of momentum tail-risk renders momentum an even stronger anomaly.