Education
Markets and Strategies
Equities, rates, credit, options, and energy, and the strategy types that trade them: momentum, relative value, volatility, and event-driven.
Coding and Problem Solving
Python and pandas for research, Green Book problems, and market-making games.
Strategy Infrastructure
Building a strategy from the ground up: data pipelines, backtesting engines, execution through market APIs, and automation.
Math and Probability
Probability, statistics, regression, time-series methods, and option pricing.
Modules
Topics
- Stocks, bonds, futures, options, swaps, and ETFs
- Long and short positions, leverage, and margin
- Bid, ask, spreads, liquidity, and order types
- From hypothesis to signal, execution, profit and loss, transaction costs, and risk
Topics
- Random variables and common probability distributions
- Expected value, variance, and standard deviation
- Conditional probability, independence, covariance, and correlation
- Introductory Monte Carlo simulation and interpreting uncertainty
Topics
- Repositories, branches, commits, and pull requests
- GitHub issues, code review, and collaborative workflows
- Reproducible project structure, documentation, and secure credential management
- Responsible use, verification, and disclosure of AI-assisted work
Topics
- Economic hypotheses and potential market inefficiencies
- Signals, entry and exit rules, and holding periods
- Benchmarks, transaction costs, and basic backtest interpretation
- Defining the evidence that would support or invalidate a strategy
- Python and pandas fundamentals
- Loading, cleaning, and organizing financial data
- Timestamps, missing values, duplicate records, and return calculations
- Basic rolling statistics, visualizations, and data-quality checks
Topics
- Calls, puts, strike prices, expiry, and moneyness
- Implied versus realized volatility
- Delta, gamma, vega, and theta
- Long- and short-volatility positions, volatility risk premium, and tail risk
- Linear and logistic regression
- Features, targets, and baseline models
- Time-ordered training, testing, and leakage prevention
- Overfitting, regularization, and predictive versus trading performance
Topics
- Earnings surprises and market expectations
- Post-earnings announcement drift
- Pre-earnings volatility and implied-volatility crush
- Event-study interpretation and directional versus volatility-based trades
- Lags, autocorrelation, and basic stationarity
- Correlation, prediction, causality, and confounding
- Causal graphs and introductory Granger causality or PCMCI
- Synthetic-data validation and false-discovery risks
Topics
- Present value, discounting, bonds, and yields
- Yield curves, duration, and DV01
- Interest-rate swaps and credit spreads
- Funding, liquidity, and hidden risks in apparent arbitrage opportunities
- Backtest architecture and execution timing
- Look-ahead bias, survivorship bias, and data leakage
- Transaction costs, slippage, and train-test separation
- Sharpe ratio, drawdown, turnover, and benchmark comparison
Topics
- Time-series and cross-sectional momentum
- Trend, reversal, and regime dependence
- Underreaction, herding, crowding, and market microstructure
- Transaction costs, market impact, capacity, and edge decay
- Project-specific option-pricing or fixed-income module
- Black–Scholes and Greeks, or bond pricing and DV01
- Basic numerical methods and sensitivity calculations
- Testing financial functions and important boundary cases
Topics
- Leading and lagging economic indicators
- Data-release timing, revisions, and look-ahead concerns
- Correlation, prediction, causality, and economic mechanisms
- Assessing whether a macroeconomic signal is stable and tradable
- Research code versus production code
- Broker and market-data APIs
- Paper trading, order simulation, logging, and error handling
- Risk controls, monitoring, and kill switches
Topics
- Position sizing and volatility targeting
- Correlation, diversification, concentration, and exposure
- Drawdowns, stress testing, and kill conditions
- Final strategy defense and development handoff
- Project-specific implementation-support sprint
- Pull requests, peer review, and unit tests
- Documentation, reproducibility, and known limitations
- Final demonstration and project-team handoff