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Using Implied Volatility to Modulate Currency Trend Following

Article arXiv papers · Author: Ted Theodosopoulos et al.
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Summary

The document presents a hybrid dynamical model for studying trend-following behavior in currency markets. It generates symbolic dynamics from a lognormal diffusion model of the at-the-money implied volatility term structure, using information from derivatives to characterize properties of the underlying exchange-rate returns. The application uses the JPY-USD exchange rate and associated one-month, three-month, six-month, and one-year implied volatilities.

The reported result is that modulating autoregressive trend following with derivative-based signals significantly improves the model’s fit to the distribution of times between successive sign changes in the exchange rate series. This is a distribution-fitting result, not evidence of higher trading returns or reduced risk. The description does not provide the model’s detailed rules, data period, comparison metrics, or out-of-sample validation, limiting conclusions about practical performance.

Key ideas

  • The model uses implied volatility term structure data to inform currency return dynamics.
  • It applies lognormal diffusion to at-the-money implied volatilities across several maturities.
  • Derivative-based signals are used to modulate an autoregressive trend-following process.
  • The reported improvement concerns fitting intervals between return sign flips, not trading profitability.

Tags

ForexOptionsTrend followingVolatility
Full text
# Hybrid dynamics for currency modeling


# Hybrid dynamics for currency modeling









We present a simple hybrid dynamical model as a tool to investigate behavioral strategies based on trend following. The multiplicative symbolic dynamics are generated using a lognormal diffusion model for the at-the-money implied volatility term structure. Thus, are model exploits information from derivative markets to obtain qualititative properties of the return distribution for the underlier. We apply our model to the JPY-USD exchange rate and the corresponding 1mo., 3mo., 6mo. and 1yr. implied volatilities. Our results indicate that the modulation of autoregressive trend following using derivative-based signals significantly improves the fit to the distribution of times between successive sign flips in the underlier time series.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.