Python: Finance Analytics and Data Science (S-IT0042)

Betribsiwwergräifend Formatioun

U wie riicht sech d'Formatioun?

Anyone who wishes to use Python for finance, financial analysis and algorithmic trading.

Dauer

24,00 Stonn(en)

Sprooch(e) vun der Déngschtleeschtung

EN

Nächst Sessioun

Virkenntnisser

Anaconda, Python and its prerequisites
Knowledge of programming
Knowledge of basic statistics and linear algebra

Ziler

Walkthrough everything you need to know to use Python for finance, financial analysis and algorithmic trading: The basics of Python, the different
base libraries used in it, Py-Finance ecosystem on Spyder as well as the libraries NumPy, Pandas, Matplotlib, Statsmodels, the Quantopian platform for Trading.

Inhalt

  • Python's NumPy library to quickly work with numeric data.
  • Python's Pandas library to analyze and visualize data.
  • Python's Matplotlib library to create custom charts.
  • The statsmodels module for time series analysis.
  • Financial statistics such as daily returns, cumulative returns, volatility,etc.
  • Exponentially Weighted Moving Averages.
  • ARIMA models on time series data.
  • Fundamental Finance Techniques.
  • The Sharpe ratio.
  • Optimizing your financial portfolio management.
  • The financial asset valuation model.
  • Learn more about efficient financial market assumptions.
  • Perform algorithmic trading on Quantopian.

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