Financial Theory Online Book

Here is a structured list of topics that would be covered in a Financial Theory tutorial aimed at preparing for a career as a Quantitative Finance Researcher.

This academic-style tutorial covers essential topics to provide a strong theoretical and practical foundation for someone pursuing a career as a Quantitative Finance Researcher.

Part I: Introduction to Financial Theory

  1. Introduction to Financial Markets and Instruments
  2. Fundamentals of Asset Pricing
    • Time value of money and discounting cash flows
    • Arbitrage and the Law of One Price
    • Fundamental theorem of asset pricing
    • Risk-neutral pricing
  3. Portfolio Theory
    • Mean-variance analysis and Markowitz efficient frontier
    • Risk-return trade-offs
    • Diversification and portfolio optimization
    • Capital Market Line (CML) and Separation Theorem
  4. Capital Asset Pricing Model (CAPM)
    • Assumptions and derivation of CAPM
    • Systematic vs unsystematic risk
    • Security Market Line (SML) and implications for asset pricing
    • Empirical tests and limitations of CAPM
  5. Arbitrage Pricing Theory (APT)
    • Multi-factor models for asset pricing
    • Factor sensitivities and arbitrage opportunities
    • APT vs CAPM: advantages and limitations

Part II: Market Efficiency and Behavioral Finance

  1. Efficient Market Hypothesis (EMH)
    • Forms of market efficiency: weak, semi-strong, and strong
    • Implications of EMH for trading and portfolio management
    • Empirical evidence for and against EMH
  2. Behavioral Finance
    • Limits to arbitrage and market anomalies
    • Behavioral biases: overconfidence, loss aversion, herding
    • Prospect theory and investor behavior
    • Impacts of behavioral finance on asset pricing

Part III: Derivatives and Options Pricing

  1. Introduction to Derivatives
    • Definition and types: forwards, futures, options, and swaps
    • Uses of derivatives in hedging, speculation, and arbitrage
    • Payoff profiles of derivatives
  2. Options Pricing Theory
    • Binomial options pricing model
    • Black-Scholes-Merton model: assumptions, derivation, and formula
    • Greeks: delta, gamma, theta, vega, and rho
    • Implied volatility and volatility smiles
    • Monte Carlo simulations in options pricing
  3. Exotic Options and Complex Derivatives
  • Barrier options, Asian options, and other exotic derivatives
  • Real options and decision-making under uncertainty
  • Pricing of credit derivatives: credit default swaps (CDS)

Part IV: Market Microstructure

  1. Introduction to Market Microstructure
  • Market participants: market makers, dealers, arbitrageurs
  • Limit order books and order matching
  • Price discovery and liquidity
  • Bid-ask spreads and transaction costs
  1. Execution and Trading Strategies
  • Algorithmic trading and high-frequency trading (HFT)
  • Market impact and slippage
  • Trading costs and optimal execution strategies (VWAP, TWAP)
  1. Market Efficiency and Anomalies in Microstructure
  • Information asymmetry and adverse selection
  • Front-running and market manipulation
  • Empirical evidence of market inefficiencies

Part V: Fixed Income and Credit Models

  1. Introduction to Fixed Income Securities
  • Bonds: coupon, zero-coupon, and floating-rate bonds
  • Yield curves and term structure of interest rates
  • Duration, convexity, and bond price sensitivity
  1. Interest Rate Models
  • Deterministic models: Yield to Maturity (YTM) and bond pricing
  • Stochastic models: Vasicek, Cox-Ingersoll-Ross (CIR), and Hull-White models
  • Applications of interest rate models in bond pricing and risk management
  1. Credit Risk Models
  • Structural models: Merton’s model of credit risk
  • Reduced-form models: Jarrow-Turnbull model, CreditMetrics
  • Credit ratings, default probabilities, and credit spreads
  • Pricing and managing credit derivatives (e.g., CDS)

Part VI: Risk Management in Quantitative Finance

  1. Measuring and Managing Risk
  • Value at Risk (VaR) and Conditional Value at Risk (CVaR)
  • Stress testing and scenario analysis
  • Backtesting and risk model validation
  1. Hedging Strategies
  • Hedging with options, futures, and swaps
  • Delta and gamma hedging
  • Static vs dynamic hedging
  1. Liquidity and Funding Risks
  • Measuring liquidity risk
  • Funding liquidity vs market liquidity
  • Strategies for mitigating liquidity risk

Part VII: Advanced Topics in Quantitative Finance

  1. Factor Models in Asset Pricing
  • Fama-French three-factor and five-factor models
  • Momentum, size, and value factors
  • Empirical analysis of factor models
  1. Alternative Investment Strategies
  • Hedge funds and private equity
  • Arbitrage strategies: statistical arbitrage, pairs trading
  • Risk parity and smart beta strategies
  1. Machine Learning in Finance
  • Applications of machine learning in portfolio management and risk modeling
  • Reinforcement learning for trading algorithms
  • Challenges and risks of machine learning in financial markets