Explore how Bayesian statistics helps traders update beliefs, build adaptive models, and manage risk. Learn Bayes’ Theorem, Naive Bayes, Bayesian inference, and their applications in algorithmic trading and quantitative finance....
Explore how linear regression powers trading strategies in quantitative finance. Understand OLS, model assumptions, Python code for stock prediction, and real-world use cases for building and evaluating trading models....
Master non-linear regression: Logistic, Quantile, Decision Trees, Random Forests, SVR for finance. Tackle complex patterns, enhance predictive modeling with these machine learning tools....
Master advanced linear regression models in finance: Polynomial, Ridge, Lasso, Elastic Net, LARS. Tackle multicollinearity, feature selection challenges for robust financial modeling. Learn key techniques now!...
To help develop a deeper understanding of statistical analysis by focusing on the methodologies adopted by frequentist statistics and Bayesian statistics....
Linear regression assumptions, limitations, and ways to detect and remedy are discussed in this 3rd blog in the series. We use Python code to run some statistical tests to detect key traits in our models....
Learn to work with historical market data to implement linear regression models on Python and R, with reusable codes....
Episode #3 of our podcast features Vivek Krishnamoorthy (Head of Content and Research at QuantInsti) as our guest. We talk about the Time Series Analysis and how it can be applied to the Financial Markets....