巴黎银行-全球-外汇策略-G10外汇季节性指南-20190626-11页_1mb

G10 FX Seasonality Guide Summary

Core Content

This document provides an analysis of seasonal patterns in G10 FX (Foreign Exchange) markets based on historical data from 2008 to 2019. It examines spot rates, FX investor positioning, and 3-month implied volatility to identify recurring trends and patterns in currency movements.

Main Signals

Spot Seasonality

• January: High-beta currencies like AUD and NZD tend to appreciate against the USD, with AUDUSD showing appreciation 80% of the time by an average of 1.9 z-scores (1.5%). USDJPY declines by 1.7 z-scores (1.0%) in the beginning of January.
• April: NOK and SEK tend to strengthen versus the EUR. GBPUSD appreciates by 2 z-scores (1.1%) at the end of April and into May.
• May: High-beta currencies (AUD, NZD) decline versus the USD, with NZDUSD showing the most pronounced weakening. EUR and GBP also weaken against the USD.
• November: USD strengthens broadly, especially against EUR, JPY, and CAD. EURUSD declines by 2.1 z-scores (1%), USDJPY by 2.7 z-scores (1.6%), and USDCAD appreciates 90% of the time.
• December: EURNOK tends to appreciate by 2.1 z-scores (1.0%) in the final weeks of the year.

FX Positioning Seasonality

• January: Investor willingness to change FX exposure is high, second only to May. NOK and JPY positioning turns more positive.
• April: NOK and JPY positioning turns more positive in line with spot movements. CAD positioning tends to turn more negative.
• May: Overall G10 FX positioning is reduced. Positioning in AUD, NZD, EUR, SEK, and NOK turns more negative, while USD positioning turns more positive.
• June: EUR strengthens versus NOK and SEK, and weakens versus CHF. EURCHF declines 90% of the time.
• July: G10 FX volatility declines after being elevated in June.
• August: USD strengthens broadly, particularly versus EUR and GBP.
• November: FX investors turn more positive on the USD, with overall G10 FX positioning reduced. USD strengthens against EUR, JPY, and CAD.
• December: No strong seasonal patterns in FX positioning, but high volatility is observed.

Implied Volatility Seasonality

• January and February: Show the highest G10 FX volatility on average, with monthly volatility exceeding the yearly average.
• April: Volatility for the first half of the year tends to bottom out.
• November: Volatility picks up broadly.
• December: Characterized by high G10 FX volatility.

Key Patterns

• High-beta currencies (AUD, NZD) tend to appreciate in January and weaken in May.
• EUR shows consistent patterns: weakens against USD in November, strengthens against NOK and SEK in June, and depreciates against GBP in late July.
• NOK appreciates in mid-April and in the final weeks of December.
• SEK tends to outperform versus EUR at the end of Q4.
• JPY shows no significant seasonality at the close of the Japanese fiscal year (31 March).
• Volatility peaks in January and February, and again in November and December, while it tends to bottom out in April.

Methodology

• Spot Analysis: Weekly FX spot rates are analyzed, with outliers removed (|z| > 2.5). Rolling 2-week sums are used to capture inter-month movements. Z-scores are calculated to standardize currency moves across time.
• Positioning Analysis: Uses BNP Paribas FX Positioning Analysis to assess investor willingness to add or reduce FX positions. Monthly changes in positioning are calculated and averaged to determine seasonal trends.
• Volatility Analysis: Uses 3-month implied volatility data to measure average monthly volatility. Ratios of monthly volatility to yearly average are calculated to provide a proxy for G10 FX volatility.

Important Notes

• This analysis is descriptive, not explanatory, and does not claim to be an exhaustive study.
• The document may be subject to conflicts of interest due to interactions with sales and trading.
• It is classified as non-independent research and marketing communication under MiFID II regulations.
• The content may include "Research" as defined under MiFID II unbundling rules, intended for specific firms that have signed up to BNPP's research packages.
• All information is subject to change and not guaranteed in accuracy or completeness.
• Past performance is not indicative of future results.
• Simulated performance may not reflect real-world market conditions, including liquidity constraints and transaction costs.

Conclusion

The guide identifies consistent seasonal patterns in G10 FX, highlighting the influence of investor positioning and implied volatility on currency movements. These insights can help traders and investors anticipate market behavior, though they should be used with caution and in conjunction with independent analysis.