Senior Lecturer of Finance
Australian School of BusinessUniversity of New South Wales (UNSW)
Kensington NSW 2052, Australia
2007 - 2012 University of Illinois at Urbana-Champaign, Illinois, USA
2006 - 2007 Korea Advanced Institute of Science and Technology (KAIST), Business School, Seoul, Korea
1999 - 2005 Korea Advanced Institute of Science and Technology (KAIST), Daejon, Korea
On the Systematic Volatility of Unpriced Earnings Shocks, with Timothy Johnson (SSRN) (internet appendix)
Some important puzzles in macro finance can be resolved in a model featuring systematically varying volatility of unpriced shocks to firms' earnings. In the data, the correlation between corporate debt and stock market valuations is low. The model accounts for this via the opposing effect of unpriced earnings risk on levered debt and equity prices. The model also explains the low (or nonexistent) risk-reward relation for the market portfolio of levered equity via the opposing effects of unpriced and priced uncertainty (both components of stock volatility) on the levered equity risk premium. Versions of the model calibrated to empirical measures of both types of fundamental risk can quantitatively substantiate these explanations. Variation in residual earning dispersion accounts for a significant fraction of observed disagreement between debt and equity valuations, and of realized stock volatility. The implication that the two components of risk should forecast the levered equity risk premium with opposite signs is also supported in the data. The results are a notable advance for risk-based asset pricing.
Liquidity might be categorized into two types: asset liquidity and funding liquidity. This paper presents a new approach to measure funding liquidity and demonstrates that the estimated funding liquidity can predict future stock market returns. The key idea is that, as capital constraints become more binding, speculators withdraw first from small stocks and then from large stocks. Given that asset liquidity is provided by speculators, the asset liquidity of large and small stocks would covary differently with shocks to speculators' capital depending on their participation in the markets. Based on this intuition, funding liquidity is measured as the difference of rolling correlations of stock market returns with large and small stocks' asset liquidity. The estimated funding liquidity appears positively correlated to aggregate hedge fund leverage ratios, stock market sentiments, and the total number of M&A activities, and negatively to bond liquidity premiums, Moody's Baa-Aaa corporate bond spreads, and the relative prevalence of liquidity mergers. The funding liquidity is able to predict future stock market returns, and its forecasting power is significant in both in-sample and out-of-sample tests. Its forecastability is robust to various equity premium predictors as well as subsample periods.
This paper considers whether the term structure of Treasury bond yields reflects all risk premium factors that affect these bonds' rates of return; that is, whether risk premia factors are spanned by the cross-section of Treasury bond yields. It finds that an important factor determining rates of return is almost fully hidden in the term structure. However, this factor is most apparent in Treasury bill yields and predicts a decrease in the level of the term structure. Survey forecasts of future interest rates appear unaware of this factor. This risk premium in bill yields also predicts economic recessions while the traditional slope factor predicts economic expansions.
Jun - Aug 2009 Barclays Capital, New York, USA
Position: Summer Quant Associate within Fixed Income Research
Built a model to estimate monetary policy interest rate expectation and forward risk premium
Implemented a numerical computation library in C# to calibrate parameters of Svensson Curve
2003 - 2005 NHN Corp., Seoul, Korea
Position: Programmer (Online Game Server)
Designed the server structure and the communication protocol between servers and clients