Global FX: Systematic late-cycle hedging with FX options: A machine learning based strategy

We introduce a systematic strategy for identifying signals and selecting late-cycle / recession FX options hedges. 1) we first run Random Forest algorithm to zero in on the most relevant signals for hedging risk-off episodes; then 2) we build a 4-factor model that selectively buys defensive FXO based on model predicted P&L.

• The highest beta to risk-off events is achieved with four signals: m/m change in 1-y z-score of ATM vol, m/m change in 1-y z-score of realized vol, 1-y z-score of 6-month % change in spot, and m/m change in 1-y z-score of fwd pts/vol (i.e. carry/vol).
• We find short-term tenor to be most responsive to adverse episodes, 30%TV digitals to be showing the least decay, and the longer expiry structures tend to hold better during the low vol times. Overall 3M - 6M expires offer a good compromise.
• At current market, our 4- factor model favors high beta G10 digi structures with AUD structures dominating within the top 5: 3M to 6M 30%TV at-expiry digitals in AUD/SGD put, USD/CAD call, EUR/AUD call, GBP/USD put and/or AUD/CHF put.

This podcast was recorded on 20 October 2022.

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