Statistics For Finance 2022

Learn core probability and statistics with Python tools and real applications in finance and business

What you'll learn
Learn the probability foundations of modern statistics
Mean, variance, skewness, and kurtosis, and their significance and application in finance
Apply maximum likelihood estimation and the method of moments to financial models
Master Python tools for handling financial data and carrying out statistical analysis on it

Requirements
No knowledge of statistics or finance is necessary.
Some mathematics background at a business school or high school level is all that is assumed

Description
Level up your statistics skills for your career in finance with this course in core statistics and finance and business applications. Statistics is the core subject providing the foundation for analysis in all areas of finance. This course, designed and produced by a seasoned financial practitioner, and former math professor, delivers you to the forefront of cutting edge quantitative techniques used in the finance industry worldwide.

This course assumes no knowledge of statistics or finance. From a basic foundation of only high school math this course will elevate you to the forefront of quantitative and computational tools for modelling financial markets, analyzing financial products, and managing risk.

What You Will Learn

This course provides a thorough grounding in the probability foundations of statistics. The core topics of statistics, estimation, hypothesis testing, and confidence intervals, are treated in full depth. Modern statistics methods are applied to real problems from finance.

Some of the topics covered in this course include

Discrete and combinatorial probability

The binomial, normal, exponential, and chi-square distributions

Mixed normal distributions

Mean, variance, skewness, and kurtosis

Location, scale, and shape parameters

Law of large numbers

Central limit theorem

Maximum likelihood estimation

Method of moments

Hypothesis testing

Significance level, size, and power of tests

Confidence bounds and intervals

Stationarity and structural breaks in financial time series

Modelling the distributions of financial returns

Includes Python Tools

Python based tools are included for working with probability distributions, for analyzing data, and providing implementations of modern statistical algorithms. All software that is part of this course is released under a permissive MIT license, so students are free to take these tools with them and use them in their future careers, include them in their own projects, whether open source or proprietary, anything you want!

So Sign Up Now!

Accelerate your career by taking this course and advancing your skills in statistics for finance and business. With more than 20 hours of lectures, extensive problem sets, and Python codes implementing modern statistics methods, not to mention a 30 day money back guarantee, you can't go wrong!

Who this course is for
Finance students and working financial professionals who want to level up their statistics skills
Students in any area where statistics are used who would like to learn statistics with an emphasis on applications