Master Financial Econometrics for Time Series Analysis
Learn financial time series analysis! Beginner-friendly course covering theory, math, Excel, and practical applications. Model & analyze data from scratch.
Course Content
Master Financial Econometrics for Time Series Analysis is a beginner-level Udemy course taught by Shaun McDonogh. It runs 7h 40m, is taught in English, and includes a certificate of completion. Learners rate it 4.7 out of 5 from 48 reviews, with 352 students enrolled. It is a paid course, first published February 2025.
Embark on a comprehensive journey into financial econometrics and time series analysis with this practical course. Master essential techniques for understanding and predicting financial data, leveraging the power of Excel for real-world applications.
Key Skills You'll Gain:
- Data Acquisition & Preparation: Learn to source financial data from platforms like Kaggle and direct exchanges. We'll focus on utilizing provided datasets for a consistent learning experience.
- Statistical Foundations: Develop a strong understanding of core statistical measures including mean, variance, and standard deviation. Explore probability distributions (normal, discrete, continuous) and random variables.
- Data Transformation & Visualization: Transform raw data into actionable insights through techniques like log returns and standardization. Master QQ plots for visual distribution comparison and utilize Z-scores to scale empirical PDFs.
- Statistical Modeling: Explore fundamental statistical models including linear regression (simple & multiple) using Ordinary Least Squares (OLS). Understand ANOVA metrics (RSS, TSS, ESS, R-squared) and develop proficiency in hypothesis testing with t-tests and p-values. Learn Maximum Likelihood Estimation (MLE).
- Time Series Analysis: Dive deep into time series models like AR, MA, ARMA, and ARIMA. Understand stationarity (strict & weak), unit roots, and utilize ACF and PACF plots for data analysis. Apply Dickey-Fuller tests to assess stationarity and explore cointegration with the Engel-Granger test and Error Correction Models (ECM).
- Volatility Modeling: Model financial volatility using GARCH and AGARCH models.
- Multivariate Analysis: Explore bivariate joint PDFs and copulas (particularly the Gaussian copula) to model dependencies between random variables.
Practical Application with Excel:
- Hands-on Excel Implementation: Apply all learned models and calculations using the familiar interface of Excel.
- Software Proficiency: Develop critical thinking skills to evaluate software assumptions and ensure result accuracy.
- Ready-to-Use Templates: Utilize provided Excel templates and example files to guide your learning and compare your results.
This course provides the theoretical knowledge and practical skills necessary to excel in financial econometrics and gain valuable insights from financial time series data. Transform data into actionable strategies!
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