Statistics for Financial Decisions
Learn to assess evidence and uncertainty in financial research.
- Prerequisite
- Python for Financial Analysis or equivalent.
- Level
- Intermediate
- Includes
- Quantfolio
- Format
- Live online · 1:1 or group
- Schedule & fee
- Agreed on your intro call
Is this for you?
Finance professionals who can work with data in Python and want to judge results with statistical care.
Conclusions are drawn from averages and charts without asking how uncertain they are.
What you’ll be able to do
- Describe return distributions, including fat tails (extreme moves happening more often than a normal distribution suggests).
- Build and interpret confidence intervals.
- Measure correlation and explain why it is not causation.
- Run and interpret a regression, such as a share's beta against the KSE-100 or an international index.
Modules
- Probability and return distributions
- Estimates and uncertainty
- Correlation
- Regression
- Changing market behaviour
- Hypothesis testing and validation
- Reproducible research
The outline can be tailored to your goals.
A reproducible research report.
- Research notebook
- Written report with methods, results and limitations
Tools & data
- Python
- pandas
- NumPy
- SciPy
- statsmodels
- Jupyter
- Quantfolio
PSX and international equity returns · Interest rates and exchange rates, including PKR
Questions
How much mathematics is required?
Comfort with school-level algebra is enough. Concepts are explained with examples and code before formulas.
How is it taught, and what does it cost?
Live online, one-on-one or in a small group. Schedule and fee are agreed with you on a free intro call.
Will this course guarantee trading results?
No. It builds knowledge and skills. It does not guarantee profits.
Portfolio Construction and Risk Analytics
Build the skills to research markets independently.
Talk to us for free. We'll help you choose the right path and give you a preview of Quantfolio.