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Quantitative Finance Club @ UCF
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Financial Time-Series Models Workshop

Build and evaluate time-series forecasts for financial data using a walk-forward process.

Prerequisites: Python experience; familiarity with calculating returns from price data, autocorrelation, and time-based train-and-test splits

  • Dependence, stationarity, and autoregressive models
  • Moving-average models, ARIMA, and GARCH
  • Return and volatility forecasts against a naive benchmark
  • Rolling and expanding evaluation windows