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Covers the Black-Scholes formula for European options with Python implementation. Topics include derivation, the Greeks, put-call parity.
Derive the Black-Scholes-Merton PDE with Itô's lemma, delta hedging, and no-arbitrage assumptions, then connect the equation to option pricing.
Covers the no-arbitrage principle, replicating portfolios, and risk-neutral probabilities.
Covers Itô's Lemma with complete derivations and Python simulations. Topics include stochastic calculus, geometric Brownian motion.
Build mathematical models for random price movements. Topics include simple random walks, Brownian motion properties.
Examines heavy tails, volatility clustering, and the leverage effect in financial returns, with their implications for risk modeling.
Covers convertible bond valuation and analysis. Topics include conversion ratios, pricing models, warrants, preferred stock, and hybrid security structures.
Covers CDO mechanics, cash flow waterfalls, and correlation risk. Topics include tranche valuation, the Gaussian copula model, and lessons from the 2008 crisis.
Covers CDS pricing using hazard rates and survival probabilities. Topics include credit risk valuation, implied default probabilities, and spread calculations.
Covers interest rate swap fundamentals: cash flow mechanics, day count conventions, LIBOR to SOFR transition, hedging strategies, and market structure.
Covers option fundamentals including calls, puts, intrinsic value, time value, and put-call parity. Topics include payoff diagrams and basic trading strategies.
Covers forward and futures pricing with cost-of-carry models. Topics include no-arbitrage strategies, basis risk, minimum variance hedge ratios.
Covers FX market structure, currency forward pricing via covered interest rate parity, and hedging strategies. Topics include cross rates and forward valuation.
Covers option strategies by combining basic building blocks. Construct spreads, straddles, and iron condors to visualize payoffs and manage risk.
Covers commodity futures pricing with cost of carry models, convenience yield, contango and backwardation analysis, and optimal hedging strategies.
Covers forward and futures contracts: payoff structures, margin requirements, daily settlement, and hedging strategies for effective risk management.
Measure and manage bond interest rate risk using duration, convexity, and immunization. Topics include portfolio hedging and liability-driven investing.
Covers yield curve construction through zero rates, forward rates, and bootstrapping. Interpret curve shapes and build production-quality curves.
Covers financial data handling with pandas, NumPy, and Numba. Topics include time series operations, return calculations, and visualization for quant finance.
Covers bond pricing through present value calculations, yield to maturity analysis, and price-yield relationships. Topics include fixed income fundamentals.
Covers equity market fundamentals including stock ownership, order book mechanics, trading execution, and key valuation metrics for quantitative finance.
Covers root-finding, interpolation, and numerical integration for finance. Compute implied volatility, build yield curves, and price derivatives.
Covers continuous compounding, present value calculations, and differential equations. Essential tools for derivative pricing and financial modeling.
Covers derivatives, gradients, and optimization techniques essential for quantitative finance. Topics include Greeks, portfolio optimization.
Covers vectors, matrices, and decompositions for portfolio optimization, risk analysis, and factor models. Essential math foundations for quant finance.
Covers moments of returns, hypothesis testing, and confidence intervals. Essential statistical techniques for analyzing financial data and quantifying risk.
Covers probability distributions essential for quantitative finance: normal, lognormal, binomial, Poisson, and fat-tailed distributions with Python examples.
Covers probability distributions, expected values, Bayes' theorem, and risk measures. Essential foundations for portfolio theory and derivatives pricing.
Covers time value of money concepts: compounding, discounting, present value, annuities, and interest rate conventions essential for quantitative finance.
Compare TWAP, VWAP, and Almgren-Chriss execution algorithms. Covers the tradeoff between market impact and timing risk, implementation, and evaluation.
Covers interest rate swap valuation through bond portfolio and FRA methods. Topics include curve bootstrapping, DV01 risk measures, and hedging applications.
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Why
I created this space so readers can learn together, ask questions, and make sense of difficult ideas.