Course Outline

Introduction

Setting up the Development Environment

  • Programming locally vs online: Anaconda and Jupyter

Python Programming Fundamentals

  • Control structures, data types, functions, data structures and operators

Extending Python's Capabilities

  • Modules and Packages

Your first Python Application

  • Estimating beginning and ending dates and times

Accessing External Data with Python

  • Importing and exporting, reading and writing CSV data
  • Accessing data in an SQL database

Organizing Data Using Arrays and Vectors in Python

  • NumPy and vectorized functions

Visualizing Data with Python

  • Matplotlib for 2D and 3D plotting, pyplot, and SciPy

Analyzing Data with Python

  • Data analysis with scipy.stats and pandas
  • Importing and exporting financial data (Excel, website data, etc.)

Simulating Asset Price Trajectories

  • Monte Carlo simulation

Asset Allocation and Portfolio Optimization

  • Performing capital allocation, asset allocation, and risk assessment

Risk Analysis and Investment Performance

  • Defining and solving portfolio optimization problems

Fixed-Income Analysis and Option Pricing

  • Performing fixed-income analysis and option pricing

Financial Time Series Analysis

  • Analyzing time series data in financial markets

Taking Your Python Application into Production

  • Integrating your application with Excel and other web applications

Application Performance

  • Optimizing your application
  • Parallel Computing and Multiprocessing

Troubleshooting

Closing Remarks

Requirements

  • An understanding of finance (securities, derivatives, etc.)
  • A general understanding of probability and statistics
  • Elementary differential and integral calculus
  35 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 09:30 and 16:30.
Open Training Courses require 5+ participants.

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