Tong Suk Kim

A Longer Look at the Asymmetric Dependence between Hedge Funds and the Equity Market

This paper reexamines, at a range of investment horizons, the asymmetric dependence between hedge fund returns and market returns. Given the current availability of hedge fund data, the joint distribution of longer-horizon returns is extracted from the dynamics of monthly returns using the filtered historical simulation; we then apply the method based on copula theory to uncover the dependence structure therein. While the direction of asymmetry remains unchanged, the magnitude of asymmetry is attenuated considerably as the investment horizon increases. Similar horizon effects also occur on the tail dependence. Our findings suggest that nonlinearity in hedge fund exposure to market risk is more short term in nature, and that hedge funds provide higher benefits of diversification, the longer the horizon.

Future labor income growth and the cross-section of equity returns

This paper examines the equilibrium relation between future labor income growth and expected asset returns; it proposes revisions in the expectation of future labor income growth as a macroeconomic state variable and suggests a three-factor model, including a factor related to this variable, along with the consumption growth factor and the market factor. The proposed future labor income growth factor is positively associated with the Fama-French factors and subsumes their explanatory power in explaining the cross-section of stock returns. These results provide a possible economic explanation for the roles of the Fama-French factors: they are compensation for higher exposure to the risk related to changes in the value of human capital. This paper also compares the performance of the proposed three-factor model with other competing models and finds that the proposed model specification better captures cross-sectional variation in average returns than any of the competing asset pricing models considered.

Information content of volatility spreads

This study reexamines the determinants of volatility spreads and suggests a new forecast of future volatilities. Contrary to earlier volatility forecasts, the newly introduced forecast is applicable when investors are not risk‐neutral or when underlying returns do not follow a Gaussian probability distribution. This implies that the method is consistent with the presence of risk premia for other risks such as volatility risk. Using S&P 500 index options, we show that the new volatility forecast outperforms other volatility forecasts including risk‐neutral implied volatility and historical volatility in two aspects. First, the new forecast is superior to other estimates in terms of forecasting errors for future realized volatilities. Second, it is an unbiased estimator of future realized volatilities. This is shown using an encompassing regression analysis.

Sovereign Credit Default Swaps, Sovereign Debt and Volatility Transmission Across Emerging Markets

This paper uses daily sovereign credit default swap (CDS) prices to investigate how the credit risks of major Latin American reference entities are interlinked. Our empirical findings suggest that the underlying creditworthiness of nations is reflected in the direction of Granger causality and volatility transmission, and in the degree of volatility persistence. These findings are robust when derived from Latin American government bond credit spreads, yet some important differences emerge which indicate that the sovereign CDS market provides a better forum for diversification of credit risk exposure than does the bond market.

Macroeconomic Conditions and Credit Default Swap (CDS) Spread Changes

We investigate whether the business cycle is an important determinant of credit default swap (CDS) spreads and estimate the expected market risk premium as a proxy for the business cycle. Through portfolio regression, we find that structural model variables, including the business cycle, explain approximately 68% of the differences in CDS spreads. Furthermore, the business cycle variable is strongly significant, and its substantial explanatory power is greater for investment-grade firms than for non-investment-grade firms. This finding is consistent with the recent theory that a structural model incorporating countercyclical risk for macroeconomic conditions can help explain the credit spread puzzle.

Default Correlation Dynamics with Business Cycle and Credit Quality Changes

The distinction between structural and reduced form credit risk models is now well known. Structural models arise from more compelling theoretical principles, but reduced form models are easier to implement in practice. As derivative instruments tied to portfolios of credit–sensitive securities, such as collateralized debt obligations (CDOs) and basket credit derivatives, become more common, the need to understand and model default correlations along with default probabilities also becomes important. But structural models have had a hard time producing the amount of correlation needed to match market prices for these products, partly because default intensities are typically modeled as being constant, or at most, functions of largely firm–specific variables. In this article, Kim and Kim introduce a tractable structural model in which default intensities also depend on broad macroeconomic variables that are assumed to follow correlated diffusions. This joint dependence on macro factors can induce strong default correlations, and can also help to explain certain results from the literature, like the fact that credit risk seems to be more highly correlated among high–grade firms than among low–grade firms, even though the latter have higher individual probabilities of default. The model can also produce a rich dynamic in credit risk exposure.

The Information Content of Changes in Index Composition

This study examines the effect of changes in the KOSPI 200 index to determine the main cause of abnormal return behavior. It tests five prevailing hypotheses individually and simultaneously using both added and deleted stocks during the event window. We find evidence of permanent price effects and no return reversal and of temporary price pressure around the effective date. The results show that the return behavior of added and deleted stocks cannot be explained by a single hypothesis, but the changes in operating performance best explain these effects. The indexing methodology conveys the valuable information that the added stocks showed good performance and better earnings relative to both the market and the same industry average and the deleted stocks showed vice versa. In conclusion, member changes in the KOSPI 200 index are not information-free events.

Dispersion in Analysts’ Earnings Forecasts and Market Efficiency: Dispersion Anomaly and Market Efficiency

Recent studies show that firms with higher analysts’ earnings forecasts dispersion subsequently have lower returns than firms with lower forecasts dispersion. This paper evaluates alternative explanations for the dispersion–return relation using a stochastic dominance approach. We aim to discriminate between the hypothesis that some asset pricing models can explain the puzzling negative relation between dispersion and stock returns, and the alternative hypothesis that the dispersion effect is mainly driven by investor irrationality and thus is an evidence of a failure of efficient markets. We find that low dispersion stocks dominate high dispersion stocks by second‐ and third‐order stochastic dominance over the period from 1976 to 2012. Our results imply that any investor who is risk‐averse and prefers positive skewness would unambiguously prefer low dispersion stocks to high dispersion stocks. We conclude that the dispersion effect is more likely evidence of market inefficiency, rather than a result of omitted risk factors.

Assessing the Proportionality Assumption in Default Rate Forecasting Using the Proportional Hazard Model

The first generation quantitative bankruptcy prediction models are not designed to accommodate the time dimension. To overcome this limitation, various dynamic models based on survival analysis are developed recently. Among them, Cox (1972)’s proportional hazard model has been widely used in various fields because of the advantage of being free of distributional assumptions. The proportionality assumption, however, must be applied precisely when there is a potential structural change. In this paper, we assess the violation of proportionality assumption in the firm failure prediction model built around the Cox’s proportional hazard model and proposed non-proportional hazard model. We also examine the effect of macroeconomic variables to suggested non-proportional hazard model. We perform an investigation using the Korean stock market since the market, which has experienced two well-known structural changes caused by the Asian financial crisis and 2008 Global financial crisis, is well suited for analyzing the impact of the proportionality assumption on the appropriateness and predictability of the Cox’s proportional hazard model. It is shown that a non-proportional hazard model including a change point is a proper alternative, when the proportionality assumption is violated.