This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create...

We establish the out-of-sample predictability of monthly exchange rate changes via machine learning techniques based on 70 predictors capturing country characteristics, global variables, and their interactions. To guard against overfitting, we use the elastic net to estimate a high-dimensional...

This paper employs the post — Least Absolute Shrinkage and Selection Operator (post — LASSO) to make rolling 1-month--ahead currency excess return forecasts using all other currencies' lagged forward discounts as candidate predictors. The trading strategy of buying (selling) quintile...

We compare the out-of-sample predictive accuracy of a mixture of bond yield models with that of the individual models. The individual models considered here are the dynamic Nelson--Siegel model, arbitrage-free Nelson--Siegel model, and random-walk model. Out-of-sample forecasts for U.S. bond...

We present a new, theoretically motivated, forecasting variable for exchange rates that is based on the prices of quanto index contracts, and show via panel regressions that the quanto forecast variable is a statistically and economically significant predictor of currency appreciation. We also...

We study the expectations of individual forecasters in the foreign exchange market. We find that the survey risk premium is less countercyclical than the rational risk premium, primarily because it is not related to the forward premium. We also find that forecasters learn from their own forecast...

We construct mean-variance optimized currency portfolios and analyze the time- series variation of the conditional Sharpe ratio. Returns, volatility and skewness are predictable. Market timing – i.e., trading more (less) aggressively when the conditional risk-return trade-off is more (less)...

We introduce a forecasting method that closely matches the econometric properties required by the theory of exchange rate prediction. Our approach formally models (i) when (and if) predictor variables enter or leave a regression model, (ii) the degree of parameter instability, (iii) the...

This study revisits the Meese-Rogoff puzzle by estimating the traditional monetary models of exchange rate determination in state-space form and comparing the accuracy of these forecasts against the naïve random walk model using a wide range of conventional and alternative measures of...

In this paper we introduce a “power booster factor” for out-of-sample tests of predictability. The relevant econometric environment is one in which the econometrician wants to compare the population Mean Squared Prediction Errors (MSPE) of two models: one big nesting model, and another...