Enroll Course: https://www.udemy.com/course/python-fur-finanzanalysen-und-algorithmisches-trading/
Are you looking to leverage the power of Python for sophisticated financial analysis and algorithmic trading? Then look no further than the Udemy course, “Python für Finanzanalysen und algorithmisches Trading” (Python for Financial Analysis and Algorithmic Trading). This comprehensive course is designed for those who already have a grasp of Python fundamentals and are eager to apply their skills in the dynamic world of finance.
As one satisfied student, P. Livadas, raves, “Really well explained! Thank you. You can apply everything immediately! :)” Another student, D. Ebraheim, praises its clarity, stating, “Very clear and structured, TOP!”
The course meticulously guides you through the essential Python libraries that form the backbone of the Py-Finance ecosystem. You’ll start with the basics and delve into powerful tools like Jupyter, NumPy for lightning-fast numerical processing, Pandas for efficient data manipulation and analysis, and Matplotlib for creating insightful data visualizations. The curriculum also covers crucial libraries such as statsmodels, zipline, and more, providing you with a robust toolkit for financial endeavors.
Key topics explored include:
* **Python in Financial Analysis:** Understanding how Python excels in financial contexts.
* **Data Acquisition:** Utilizing pandas-datareader and Quandl to fetch financial data.
* **Time Series Analysis:** Mastering Pandas’ techniques for analyzing time-series data.
* **Financial Metrics:** Calculating stock returns, cumulative daily returns, volatility, and security risk.
* **Statistical Modeling:** Applying Markov Chains, EWMA, ETS, and ARIMA models, along with analyzing autocorrelation and partial autocorrelation plots.
* **Portfolio Management:** Calculating the Sharpe Ratio, optimizing portfolio allocation, and understanding the Efficient Frontier and Markowitz Optimization.
* **Investment Concepts:** Exploring different types of investment funds, order books, short selling, the Capital Asset Pricing Model (CAPM), stock splits, dividends, the Efficient Market Hypothesis, and trading futures.
To get the most out of this course, a foundational understanding of Python programming is essential. While not strictly required, basic statistics and linear algebra knowledge will also be beneficial. The technical prerequisite is the ability to download Anaconda (Python).
Upon completion, you’ll be proficient in using NumPy for rapid numerical operations, Pandas for data analysis and visualization, Matplotlib for custom charting, and statsmodels for time-series analysis. You’ll be able to calculate key financial statistics, implement EWMA and ARIMA models, compute Sharpe Ratios, optimize portfolios, and understand fundamental financial theories like CAPM and the Efficient Market Hypothesis.
This course is highly recommended for anyone who has a solid foundation in Python and wishes to transition their skills into the realm of financial analysis and potentially algorithmic trading. It’s a practical, hands-on learning experience that equips you with the tools and knowledge used by finance professionals.
Enroll Course: https://www.udemy.com/course/python-fur-finanzanalysen-und-algorithmisches-trading/