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This study examines the empirical performance of emission allowance option pricing models, concentrating on the EU-ETS markets. For option pricing, we use parameters estimated from option market data whereas few papers in the extant literature use parameters from underlying asset data. As results, it is shown that the most appropriate is the one-factor model in which the EUA logarithmic spot prices follow the mean-reverting process of Ornstein-Uhlenbeck type. Also, the addition of jumps is not shown to make any significant improvement in the model performance. These results are quite striking in the sense that existing papers report the addition of jumps is necessary to improve option pricing on the EU-ETS markets. In sum, this paper is meaningful in the sense that it extends the growing empirical literature on the behavior of emission allowance spot prices

The term structure of KTB (Korea Treasury Bond) is empirically implemented and forecasted by the extended 2-factor CIR model. Pearson and Sun model. MLE is applied to estimate parameters. Using KTB prices forecasted by the model, strategies of trading and hedge between KTB, KTF (Korea Treasury Futures) are established. In this article we can see that Pearson and Sun model appropriately explains the term structure of KTB but does not fit forecasting KTB prices. However, the model well forecasts the direction of interest rate moving up or down. Through such a forecast‘ profit via trading KTB and KTF can be realized.

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.

This paper aims to replicate 148 anomalies and to examine whether the performance of the Korean market anomalies is statistically and economically significant. First, the authors observe that only 37.8% anomalies in the universe of the KOSPI and the KOSDAQ and value-weighted portfolios have t-statistics that exceed 1.96. When the authors impose a higher threshold (an absolute value of t-statistics of 2.78), only 27.7% of the 148 anomalies survive. Second, microcaps have large impacts. The results vary significantly depending on whether the sample included stocks in the KOSDAQ and whether value-weighted or equal-weighted portfolios are used. The results suggest that data mining explains large portion of abnormal returns. Any tactical asset allocation strategies based on market anomalies should be applied very cautiously.