Paper: arXiv 2410.09062

Abstract

Predicting volatility in financial markets, including stocks, index ETFs, foreign exchange, and cryptocurrencies, remains a challenging task due to the inherent complexity and non-linear dynamics of these time series. In this study, I apply TimeMixer, a state-of-the-art time series forecasting model, to predict the volatility of global financial assets. TimeMixer utilizes a multiscale-mixing approach that effectively captures both short-term and long-term temporal patterns by analyzing data across different scales. My empirical results reveal that while TimeMixer performs exceptionally well in short-term volatility forecasting, its accuracy diminishes for longer-term predictions, particularly in highly volatile markets. These findings highlight TimeMixer’s strength in capturing short-term volatility, making it highly suitable for practical applications in financial risk management, where precise short-term forecasts are critical. However, the model’s limitations in long-term forecasting point to potential areas for further refinement.

Complexity vs Empirical Score

  • Math Complexity: 8.0/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper employs advanced mathematical concepts including multiscale decomposition and specific neural network blocks (PDM/FMM), indicative of high complexity. It is backed by empirical results across multiple asset classes (stocks, ETFs, FX, crypto) and discusses performance metrics, showing significant data and implementation efforts.

Research Flowchart

  flowchart TD
  A["Research Goal: Predict Volatility<br>in Global Financial Markets"] --> B["Data Collection<br>Multi-asset Time Series"]
  B --> C["Methodology: Apply TimeMixer<br>Multiscale-Mixing Approach"]
  C --> D["Computational Process<br>Capture Short & Long-Term Patterns"]
  D --> E{"Key Findings / Outcomes"}
  E --> F["Strong Performance in<br>Short-Term Forecasting"]
  E --> G["Limitations in<br>Long-Term Forecasting"]
  F --> H["Application: Financial<br>Risk Management"]