The Asian crisis highlighted the vulnerability of emerging market economies faced by sudden capital flow reversals. An important question that has critical implications for crisis management is how negative shocks in capital inflows were transmitted to economic activities, transforming financial...

This paper analyzes Korea’s exchange rate dynamics before and during the crisis of 1997-98 by estimating the long-run fundamental exchange rate and the associated error correction model. The analysis suggests that although Korea’s exchange rate was substantially overvalued before...

Why is Japan a good case study to help Europe overcome the economic and �nancial crisis that started more than �ve years ago? What can Japan learn from Europe's experience? Japan and the EU are both open economies with signi�cant trade and �nancial links; both face in many...

This paper discusses the time-varying degree of flexibility in exchange rate regimes and assesses the extent to which securities markets are integrated in East Asia. The dynamic conditional correlation model developed by Engle (2002) is used to analyze the time-varying characteristics of the...

This paper empirically examines the behaviour of exchange rates in order to identify de facto exchange rate regimes in post-crisis Asian countries. We use the multivariate GARCH model to estimate the conditional correlation among the value of currencies, which include the currencies of Thailand,...

We propose a novel approach that combines random forests and the wavelet transform to model the prediction of currency crises. Our classification model of random forests, built using both standard predictors and wavelet predictors, and obtained from the wavelet transform, achieves a demonstrably...

This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forecasts the short-term crude oil futures prices with good performance. In our study, we confirm that artificial intelligence (AI)-based deep-learning approaches can provide more accurate forecasts of...

This study analyzes the importance of the Tokyo Stock Exchange Co-Location dataset (TSE Co-Location dataset) to forecast the realized volatility (RV) of Tokyo stock price index futures. The heterogeneous autoregressive (HAR) model is a popular linear regression model used to forecast RV. This...

We propose a novel approach that combines random forests and the wavelet transform to model the prediction of currency crises. Our classification model of random forests, built using both standard predictors and wavelet predictors, and obtained from the wavelet transform, achieves a demonstrably...

This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forecasts the short-term crude oil futures prices with good performance. In our study, we confirm that artificial intelligence (AI)-based deep-learning approaches can provide more accurate forecasts of...