Simulation of tail risk noise and asset price
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Updated
Aug 28, 2024 - Jupyter Notebook
Simulation of tail risk noise and asset price
Analyze cryptocurrency return dynamics, volatility, and risk from 2010–2025.
Regime detection using Hidden Markov Models with Swan Beta features to identify tail-risk market states.
Predicting the probability of equity market crash events using historical return-based features, with a fixed crash definition and a focus on tail risk. The model is evaluated using the SPDR S&P 500 ETF (SPY) as a proxy for the S&P 500 Index, with data sourced via the yfinance API.
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