Study

Understand rate conventions, return calculations, and how annualisation and compounding affect CFA-style performance questions.

Apply present value and cash flow shapes to bonds, mortgages, dividend stocks, and no-arbitrage pricing.

Choose the right measures of central tendency, dispersion, skewness, and kurtosis for asset-return data.

Use scenario trees, conditional expectations, and total probability logic to solve multi-stage uncertainty problems.

Analyze covariance, correlation, portfolio variance, and shortfall risk when combining risky assets.

Distinguish Monte Carlo simulation from bootstrapping and understand lognormal price paths in finance.

Build confidence intervals and connect sample evidence to population conclusions with estimation and inference tools.

Learn null and alternative hypotheses, error types, critical values, and how test decisions are made under uncertainty.

Choose between Pearson, Spearman, and chi-square approaches when testing independence and association.

Interpret regression output, fit simple linear models, and evaluate explained versus unexplained variation.

Get a practical introduction to big data concepts, data science workflows, and modern analytical techniques in finance.