Quantitative Analysis
Learning Outcomes:
- Explain statistical and probability concepts relevant to financial data
- Apply probability distributions, sampling methods, and estimation techniques
- Apply hypothesis testing, regression analysis, time-series analysis and multifactor models using Stata
- Explain the application of machine learning, big data, and risk models in finance.
Topics:
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Statistical Concepts: Organizing, Visualizing, and Describing Data
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Probability Concepts & Distributions
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Sampling and Estimation Techniques
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Hypothesis Testing: t-test, z-test, chi-square test
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Introduction to Linear & Multiple Regression
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Classic Assumption Testing and Application of Regression in Finance
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Time-Series Forecasting: Trend, Seasonality, ARIMA
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Multifactor Models in Finance: CAPM, Fama-French
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Introduction to Machine Learning in Finance & Big Data Use Cases
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Measuring and Managing Market Risk (e.g., VaR, volatility
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