A Credit-Based Theory of the Currency Risk Premium (working paper)
With Pasquale Della Corte and Alexandre Jeanneret
Abstract : This paper extends the work of Kremens and Martin (2019) and uncovers a novel component for exchange rate predictability. Our theory shows that currency returns compensate investors for the expected currency depreciation in the case of a severe but rare credit event. We compute this risk compensation - the credit-implied risk premium (CRP) - by exploiting the price difference between sovereign credit default swaps denominated in different currencies. Using data for 16 Eurozone countries over the period 2010-17, we find that CRP positively forecasts the euro-dollar exchange rate return between one-week and six-month horizon, both in-sample and out-of-sample. We also show that currency trading strategies that exploit the informative content of CRP generate substantial out-of-sample economic value.
Learning from Analysts' Forecast: Implications for Asset Prices (work in progress)
Abstract : I derive an asset pricing model in which investors learn about firms’ growth rates using analysts’ forecasts errors. The intensity of investors’ learning process varies depending on the information content of forecasts errors. The model allows to estimate a measure of learning intensity for the panel of US firms. This measure of learning intensity is shown to affects stocks’ excess returns and returns volatility negatively. In addition, it is associated with firms that have high valuations ratios (market-to-book and Tobin’ s q) and with firms with high investment rates, especially in research and development. The empirical analysis sheds light on the fact that high learning intensity is prevalent amongst typical firms of the knowledge economy.