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
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!
