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This lecture covers the stylized facts of asset returns, summary statistics, testing for normality using the Jarque-Bera test, Q-Q plots of S&P 500 returns, and testing for normality using the empirical CDF. It also discusses the efficient market hypothesis, sample autocorrelation, confidence intervals on the sample autocorrelation, irregularity of volatility, and the VIX index. The instructor presents the concepts of machine learning in finance, including supervised learning, reinforcement learning, artificial neural networks, and deep learning methods.
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