In this paper, we propose a method for finding policy function improvements for a single agent in high-dimensional Markov dynamic optimization problems, focusing in particular on dynamic games. Our approach combines ideas from literatures in Machine Learning and the econometric analysis of games...

We assess the performances of alternative procedures for forecasting the daily volatility of the euro's bilateral exchange rates using 15 min data. We use realized volatility and traditional time series volatility models. Our results indicate that using high-frequency data and considering their...

We use Generalized Andrews-Ploberger (GAP) tests to examine the random-walk behavior of 17 OECD countries' euro exchange rates at daily frequencies. The GAP tests reject the hypothesis of random-walk behavior less often than do traditional tests. Moreover, the random-walk hypothesis cannot be...

This paper focuses on forecasting volatility of high frequency Euro exchange rates. Four 15 minute frequency Euro exchange rate series, including Euro/CHF, Euro/GBP, Euro/JPY and Euro/USD, are used to test the forecast performance of six models, including both traditional time series volatility...

Using the most comprehensive weekly dataset of ‘A’ shares listed on the Chinese stock market, this paper examines short-term contrarian strategies under different market states from 1995--2010. We find statistically significant profits from contrarian strategies, especially during the period...

We compare volatility forecasts using daily data and intraday data at different frequencies from the Chinese commodity futures market. Focusing on aluminium, copper and fuel oil futures contracts with 3 months to maturity, our empirical results suggest that in the out-of-sample forecasting...