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A custom-built pairs trading simulator in R to analyze different ways of coducting this type of trade on US Sector SPDRs. We assessed both commonly-used price and return correlations between assets as well as using model residuals for both ARIMA and GARCH (volatility) type time series modelling.
Script to fit the Heston-Nandi GARCH(1,1) model. Includes MLE of parameters, future path simulation, Monte Carlo simulation for option price and computations of pdf and cdf.
Analyze NASDAQ100 stock data. Used ARIMA + GARCH model and machine learning techniques Naive Bayes and Decision tree to determine if we go long or short for a given stock on a particular day