The strategy trades USD/EUR using a model predicting appreciation or depreciation based on past volatility, skewness, VIX, and interest rate differentials, rebalancing daily based on probability estimates.
ASSET CLASS: CFDs, futures | REGION: Global | FREQUENCY:
Daily | MARKET: currencies | KEYWORD: Interest Rate
I. STRATEGY IN A NUTSHELL
This strategy trades the USD/EUR pair using a model where log returns follow a multiplicative heteroscedastic process. Innovations are modeled with a standardized sinh-arcsinh distribution, with skewness (ε) and kurtosis (δ) estimated via maximum likelihood. Skewness follows an ARMAX(2) process dependent on lagged ε, VIX, and LIBOR interest rate differentials. The model computes the probability of currency appreciation: >0.5 → long USD/EUR, <0.5 → short. Positions are rebalanced daily.
II. ECONOMIC RATIONALE
The strategy exploits predictive signals from interest rate differentials, VIX, and past shocks to dynamically adjust exchange rate skewness. IRDs indicate potential appreciation but raise crash risk, while VIX signals USD strength yet increases downside risk in high-volatility periods. Incorporating these variables allows the model to anticipate asymmetric returns, producing robust in- and out-of-sample performance.
III. SOURCE PAPER
Interest Rate Differentials and the Dynamic Asymmetry of Exchange Rates [Click to Open PDF]
Julien Hambuckers; Maren Ulm
<Abstract>
In this paper, we revisit the predictive content of interest rates for daily exchange rate returns using an improved econometric strategy. The novelty of our approach is to take into account dependencies of higher orders by allowing for a time-varying asymmetry in the distribution of exchange rates. Using data on USD/EUR currency pair over the period 1999-2019, we find the dynamic asymmetry component to be significant and driven by interest rate differentials, but also by general uncertainty and past unexpected shocks. In line with recent currency crash theories, our study suggests that the larger the difference between interest rates, the more likely the high yield currency is to appreciate but also to experience currency crashes. To assess the economic significance of our results, we introduce a directional forecasting approach derived from our model. We show that a trading rule based on these forecasts provides better in-sample and out-of-sample economic performance compared to benchmark models.
IV. BACKTEST PERFORMANCE
| Annualised Return | 5.32% |
| Volatility | 10% |
| Beta | N/A |
| Sharpe Ratio | 0.53 |
| Sortino Ratio | N/A |
| Maximum Drawdown | N/A |
| Win Rate | N/A |
