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This paper introduces two risk factors which are the covariance between long-run consumption growth and cash flows and the duration of cash flow, and investigates how these factors serve to explain the KOSPI return risk premiums. Based on our empirical results comparing the proposed two-factor cash flow model with the standard benchmark models such as CAPM and Fama-French 3-factor model (FF-3F), using KOSPI equity including de-listed stocks, the cash flow model explains 74.7% of the cross-section of equity risk premium while CAPM and FF-3F model explains 41.9% and 64.1% to the maximum, respectively, showing that the cash-flow model is superior in explaining the risk premium factor structure compared with the benchmark models. Also, the pricing error is only 4% in the two-factor cash flow model, while CAPM and FF-3F are 7.7% and 4.7%, respectively, indicating the cash flow model outperforms the standard benchmark models in pricing error as well. These results can be interpreted that the cross section of the equity risk premium is related to a firm’s cash flow and long-run consumption, and therefore the growth rate of consumption in the long run rather than contemporaneous consumption growth rate has a greater influence on the determination of the risk premium.

This paper estimates a Nelson-Siegel model under the state-space representation in order to circumvent the shortcomings of the conventional Nelson-Siegel model and evaluates the predictive ability of the estimated model. The results indicate that the estimated Nelson-Siegel time-varying three factors have close relations to their counterparts : level, slope and curvature and the inflection of the Korean yield curve is located around the maturity of 55-month. Meanwhile, each factor is found to have unit-root but differenced-factors do not show signs of unit-roots, hence proved I (1) series. In order to assess the efficacy of the estimated model, we compare the yield prediction from our model with several natural competitors : random walk, Fama-Bliss, and Cochrane-Piazzesi. With respect to out-of-sample performance, Fama-Bliss model proves to be the worst in term structure forecasts in Korea. The predictive performance differs between the random walk and the state-space Nelson-Siegel model depending on the forecast horizon lengths. At the shorter horizon, the state-space Nelson-Siegel model outperforms the random walk, but the table is turned in the longer horizon

This study analyzes the impact of Korea ETF market growth on trading costs, information efficiency and corporate valuation focusing on the behaviors of individual component stocks in ETFs.

The empirical analysis exhibits that an increase in the number of stocks held by ETFs has statistically significant effects on the bid-ask spreads of component stocks. In terms of the information efficiency, the correlations between componet stocks and the market, and industry return are statistically significant, suggesting the expansion of the ETF market could be a factor to allow market systematic risks higher.

The impact of ETF on PBR is found to be statistically significant in the positive direction, howing that the growth of the ETF market could be conducive to making the value of component stocks overvalued relative to their fundamentals.

These findings explain that negative side effects may occur from the rapid expansion of the ETF market and suggest special attention and policy considerations are needed to avoid unintended effects resulting from the growth of the ETF market.

We analyze the cross-sectional expected return of KOSPI stocks using equity duration. From 1991 to 2018, we calculate equity durations for the KOSPI listed stocks (including de-listed stocks) and find that the shorter the equity duration, the higher the risk premium. Using the 4-factor model with equity duration added to the benchmark 3-factor model, the explanatory power of the 4-factor model is superior to that of the existing benchmark model in accounting for risk premiums. This is an unusual finding that is not readily explainable by the traditional CAPM or the Fama-French 3-factor model. This can be interpreted that the equity duration is a separate and significant risk factor dissociated from the HML of the 3-factor model.

This paper investigates a retrospective on the Journal of Derivatives and Quantitative Studies (JDQS) on its 30th anniversary based on bibliometric. JDQSs yearly publications, citations, impact factors, and centrality indices grew up in early 2010s, and diminished in 2020. Keyword network analysis reveals the JDQS's main keywords including behavioral finance, implied volatility, information asymmetry, price discovery, KOSPI200 futures, volatility, and KOSPI200 options. Citations of JDQS articles are mainly driven by article age, demeaned age squared, conference, nonacademic authors and language. In comparison between number of views and downloads for JDQS articles, we find that recent changes in publisher and editorial and publishing policies have increased visibility of JDQS.