Time-Series Modeling on Monthly Returns and Trading Strategies with 6 Portfolios
FMA4200 Final Project: Time Series Modeling for Financial Data
Time-Series Modeling on Monthly Returns and Trading Strategies with 6 Portfolios
The project modeled data distribution and explored arbitrage strategies by implementing fundamental time-series analysis.
The paper also introduced optimal mean-variance method to lower the volatility of each portfolio, and made comparison between the classical algorithm and its variant:
- Least mean-variance algorithm
- Black-Litterman algorithm
Results:
- Prior knowledge (investors’ options, market equilibrium, etc.) brings in extra information (alpha enhancement)
- Lower risk penalty coefficient can improve annualized returns
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