What events matter for exchange rate volatility ?

ArXiv ID: 2411.16244 “View on arXiv”

Authors: Unknown

Abstract

This paper expands on stochastic volatility models by proposing a data-driven method to select the macroeconomic events most likely to impact volatility. The paper identifies and quantifies the effects of macroeconomic events across multiple countries on exchange rate volatility using high-frequency currency returns, while accounting for persistent stochastic volatility effects and seasonal components capturing time-of-day patterns. Given the hundreds of macroeconomic announcements and their lags, we rely on sparsity-based methods to select relevant events for the model. We contribute to the exchange rate literature in four ways: First, we identify the macroeconomic events that drive currency volatility, estimate their effects and connect them to macroeconomic fundamentals. Second, we find a link between intraday seasonality, trading volume, and the opening hours of major markets across the globe. We provide a simple labor-based explanation for this observed pattern. Third, we show that including macroeconomic events and seasonal components is crucial for forecasting exchange rate volatility. Fourth, our proposed model yields the lowest volatility and highest Sharpe ratio in portfolio allocations when compared to standard SV and GARCH models.

Keywords: Stochastic Volatility, Macroeconomic Events, Currency Returns, Intraday Seasonality, GARCH

Complexity vs Empirical Score

  • Math Complexity: 7.0/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail
  • Why: The paper employs advanced econometric methods including high-dimensional sparsity-based techniques (spike-and-slab priors) within a stochastic volatility framework, with detailed derivations and statistical theory. It demonstrates strong empirical rigor with high-frequency FX data, rigorous out-of-sample forecasting tests (Diebold-Mariano, horse-race regressions), and a concrete portfolio allocation application with risk-adjusted performance metrics.
  flowchart TD
    A["Research Goal<br>What events matter for<br>exchange rate volatility?"] --> B["Data: High-Frequency<br>Currency Returns &<br>Macro Announcements"]

    B --> C["Methodology:<br>Sparsity-Based Selection"]
    C --> D["Computational Process<br>SV Model with<br>Macro Events & Intraday Seasonality"]

    D --> E["Key Findings"]
    
    E --> F["Identified Macro Drivers<br>& Their Effects"]
    E --> G["Found Intraday Seasonality<br>Link to Global Market Hours"]
    E --> H["Improved Volatility<br>Forecasting"]
    E --> I["Optimal Portfolio Allocation<br>High Sharpe Ratio"]