Quantitative analysis
Quantitative finance
Calculus, ODEs/PDEs/SDEs, linear/matrix algebra, probability distributions, statistical inference, Taylor series, transition density functions, Fokker-Planck and Kolmogorov equations, stochastic calculus, Itô’s lemma, martingales, binomial pricing models, Bayesian methods, margin accounts, leverage, macroeconomic event analysis
Quantitative risk and return
MPT, CAPM, portfolio optimisation, Basel III, VaR, collateral and margins, liquidity ALM, GARCH/ARCH, diversification, drawdowns, win rates, position sizing, trend following and mean reversion, profit distribution, MAE/MFE, walk-forward testing
Equities and currencies
The Black-Scholes model, options pricing, delta hedging, advanced Greeks, no-arbitrage principles, derivatives market practice, volatility arbitrage, pairs trading, finite-difference methods, advanced/non-probabilistic volatility models, FX options.
Supervised ML
Regression models (linear, penalised: lasso, ridge, elastic net; logistic, SoftMax), KNN, naïve Bayes, SVM, decision trees, ensemble models (bagging, boosting), hyperparameter tuning, decision trees, multi-AI model strategies, deep learning (NNs, RNNs, LSTMs).
Unsupervised ML
Clustering (K-means, SOMs), dimensionality reduction (t-SNE, UMAP, PCA), autoencoders, NLP, reinforcement learning, AI-based algo trading strategies
Fixed income and credit
Fixed-income products, yield, duration, convexity, stochastic interest rate models, probabilistic methods for interest rates, calibration and data analysis, HJM, LMM, structural models, hazard rate implementations, credit risk and derivatives, XVA (CVA, DVA, FVA, MVA), CDS pricing, market approach, risk of default, copula models
AI/ML in portfolio management
ML/AI in portfolio rebalancing, AI-enabled Markowitz portfolio optimisation, strategies outperforming SPX CAGR/max drawdown, Monte Carlo analysis, training/testing data optimisation to ML/AI strategies, curve fitting, QuantConnect