TL;DR
This paper compares classical econometric and mathematical approaches to modeling FX market volatility, demonstrating that both methods show promising results across major currency pairs and high-frequency data.
Contribution
It introduces the application of singular spectrum analysis and dynamical systems stability analysis to FX volatility modeling, highlighting their potential alongside traditional econometric methods.
Findings
Both approaches perform well on major currency pairs.
Mathematical tools show promising results in volatility modeling.
Both methods are underexplored in econometric discourse.
Abstract
This paper aims at solving FX market volatility modeling problem and finding the most becoming approach to this task. Validity of two competing approaches, classical econometric generalized conditional heteroscedasticity and mathematical (singular spectrum analysis and dynamical systems stability analysis) are tested on major currency pairs (EUR/USD, USD/JPY, GBP/USD) and unique high-frequency USD/RUB data. The study shows that both mathematical tools, understudied in econometric discourse, have a great potential in scope of discussed problematic, as for all experiments covered in this research, both of them show promising results.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Financial Risk and Volatility Modeling · Market Dynamics and Volatility