Python Programming for Finance (New York Institute of Finance)

Colleagues, the “Python Programming for Finance” program from NYIF will teach you the essential elements of Python to build practically useful applications and conduct data analysis for finance. Prerequisite knowledge: Basic probability and statistics, familiarity with financial securities and derivatives, and elementary differential and integral calculus. You will gain high-demand skills in the basic elements of programming in Python, learn essential data analysis concepts and techniques for finance, and build realistic applications for finance using Monte Carlo methods and other useful techniques. Training modules include: 1) Introduction to Python - Anaconda Python distribution, interactive programming: IPython and Jupyter notebooks, programming: control structures, data types, functions, data structures, modules and Packages; 2) Essential Python Toolkit - date and time management : format, measuring time lapse, etc., build and run a standalone application, parse command line arguments, importing/Exporting files, reading and writing in CSV format, accessing SQL databases, multiprocessing, using a dictionary for explicit indexing; 3) Arrays, Vectorization and Random NUmbers - NumPy: array processing, vectorized functions, random number generation; 4) Scientific Computing with Python - Matplotlib: 2D and 3D plotting, using pyplot, SciPy: scientific computing, root finding, interpolation, integration and optimization; 5) Data Analysis with Python - data analysis with scipy.stats and pandas data structures: series and data frames, importing and exporting data from/to MS Excel, importing data from websites, 5) Python Applications - Monte Carlo simulation basics, simulating asset price trajectories, smoothing using Kalman Filter, Project: Stock Correlation Prediction; and 6) Python Applications - Time Series Analysis using Advanced Python Libraries, Value-At-Risk (VAR), and Calculation using Var/Cov Model.

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