Applied Finance in Python

อัปเดตแล้ว 03/2569

Enhance your Python financial skills. Learn how to evaluate portfolios, calculate credit risk, and create GARCH models to forecast volatility.

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คำอธิบายแทร็ก

Applied Finance in Python

Enhance your Python financial skills and learn how to manipulate data and make better data-driven decisions.You’ll begin this track by discovering how to evaluate portfolios, mitigate risk exposure, and use the Monte Carlo simulation to model probability. Next, you’ll learn how to rebalance a portfolio using neural networks. Through interactive coding exercises, you’ll use powerful libraries, including SciPy, statsmodels, scikit-learn, TensorFlow, Keras, and XGBoost, to examine and manage risk. You’ll then apply what you’ve learned to answer questions commonly faced by financial firms, such as whether or not to approve a loan or a credit card request, using machine learning and financial techniques. Along the way, you’ll also create GARCH models and get hands-on with real datasets that feature Microsoft stocks, historical foreign exchange rates, and cryptocurrency data. Start this track to advance your Python financial skills.

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Course
1
Introduction to Portfolio Risk Management in Python
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Course
2
Quantitative Risk Management in Python
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Course
3
Credit Risk Modeling in Python
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Course
4
GARCH Models in Python
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.