Predicting the Short-Term Market Reaction to Asset Specific News: Is Time Against Us?

The efficient market hypothesis states that investors immediately incorporate all available information into the price of an asset to accurately reflect its value at any given time. The sheer volume of information immediately available electronically makes it difficult for a single investor to keep abreast of all information for a single stock, let alone multiple. We aim to determine how quickly investors tend to react to asset specific news by analysing the accuracy of classifiers which take the content of news to predict the short-term market reaction. The faster the market reacts to news the more cost-effective it becomes to employ content analysis techniques to aid the decisions of traders. We find that the best results are achieved by allowing investors in the US 90 minutes to react to news. In the UK and Australia the best results are achieved by allowing investors 5 minutes to react to news

Modeling moneyness volatility in measuring exchange rate volatility

The implied volatility (IV) is widely believed to be the best measure of exchange rate volatility. Despite its widespread usage, the IV approach suffers from an obvious chicken-egg problem: obtaining an unbiased IV requires the options to be priced correctly and calculating option prices accurately requires an unbiased IV. We contribute to this literature by developing a new model for exchange rate volatility which we term as the “moneyness volatility (MV)”. Besides eliminating the chickenegg problem of IV, the MV approach outperforms the IV in forecasting ability in both in-sample and out-of-sample tests. The F-test, Granger-Newbold test and Diebold-Mariano test results consistently reveal that MV outperforms IV in estimating as well as forecasting exchange rate volatility. Furthermore, test results reveal that our approach works well for the six major currency options. Our pioneering approach in modeling exchange rate volatility has far-reaching implications for academicians, professional traders and risk managers