Making Sense of the DXY

2 days ago

The author, a quant trader, explores quantitative investing in FX markets, contrasting it with equities.
FX markets involve fewer assets (30+ currencies) but are influenced by macro factors like central bank policies, making data translation challenging.
The post outlines steps to build a systematic FX model, starting with data collection and DXY calculation as a market proxy.
Twelvedata is introduced as a data source for FX pairs, with Python API examples provided for data download and storage.
The DXY (Dollar Index) is explained as a weighted geometric average of six major currencies, serving as an FX market benchmark.
A method to calculate DXY from scratch is detailed, including weightings and implementation steps.
The post demonstrates how to compute currency betas (β) against DXY using rolling regressions to understand sensitivity to dollar movements.
Results show EUR's β close to 1 (due to its DXY weight), while TRY and HKD exhibit lower sensitivity, aligning with their unique economic contexts.
Future directions include expanding the model with factors like momentum and commodity sensitivity to explain currency movements.

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