Jae Joon Ahn

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This paper is mainly concerned about intelligent forecasting for financial time series subject to structural changes. For example, it is well known that interest rates are subject to structural changes due to external shocks such as government monetary policy change. Such structural changes usually make prediction harder if they are not properly taken care(More)
Suppose that several forecasters exist for the problem in which class-wise accuracies of forecasting classifiers are important. For such a case, we propose to use a new Bayesian approach for deriving one unique forecaster out of the existing forecasters. Our Bayesian approach links the existing forecasting classifiers via class-based optimization by the aid(More)
Finding proper investment strategies in futures market has been a hot issue to everyone involved in major financial markets around the world. However, it is a very difficult problem because of intrinsic unpredictability of the market. What makes things more complicated is the advent of real-time trading due to recent striking advancement of electronic(More)
Recently, Kim and others (2009) proposed a stock market instability index (SMII) and a corresponding p-value using a nonparametric model fitted to a stable period. However, this SMII has failed to explain the 2008 global financial market crisis because its data-driven approach relies excessively on data from the stable period upon which it is based. To(More)
Keywords: Implied volatility Directional forecasting Options market Option Greeks Locally stationary Sliding window Artificial neural network a b s t r a c t This paper examines movement in implied volatility with the goal of enhancing the methods of options investment in the derivatives market. Indeed, directional movement of implied volatility is(More)