Quantitative Finance - The-Learners-Community/RoadMaps-and-Resources GitHub Wiki

ROADMAP

Welcome to the Quantitative Finance Roadmap! This guide is designed to take you from a beginner to an expert in quantitative finance. Each section covers essential topics and skills you need to become proficient and dangerous.

Checkout

PROJECTS - Beginner to Master

Beginner Level

  1. Stock Price Data Collection

    • Collect historical stock price data from APIs like Yahoo Finance or Alpha Vantage.

  2. Moving Averages Strategy

    • Implement simple moving average (SMA) and exponential moving average (EMA) trading strategies.

  3. Portfolio Performance Tracking

    • Build a tool to track the performance of a simple stock portfolio over time.

  4. Monte Carlo Simulation

    • Use Monte Carlo methods to simulate the future price of a single stock.

  5. Sharpe Ratio Calculation

    • Calculate the Sharpe Ratio for a portfolio to assess its risk-adjusted return.

  6. Backtesting Simple Trading Strategies

    • Implement and backtest basic trading strategies like mean reversion or momentum.

  7. Risk and Return Analysis

    • Analyze the risk and return of various stocks or portfolios using historical data.

  8. Black-Scholes Option Pricing Model

    • Implement the Black-Scholes model to price European call and put options.

  9. Bond Pricing Calculator

    • Build a simple tool to calculate the price and yield of fixed-rate bonds.

  10. Efficient Frontier Visualization

    • Create a plot of the efficient frontier for a set of assets.

Intermediate Level

  1. Pairs Trading Strategy

    • Implement and backtest a pairs trading strategy based on cointegration between two assets.

  2. Value at Risk (VaR) Calculator

    • Build a tool to calculate the Value at Risk for a portfolio using historical simulation.

  3. Algorithmic Trading Bot

    • Develop a simple algorithmic trading bot that executes trades based on pre-defined signals.

  4. CAPM Model Implementation

    • Implement the Capital Asset Pricing Model (CAPM) to calculate the expected return of an asset.

  5. Factor Investing Strategy

    • Create a factor-based investing strategy using factors like size, value, and momentum.

  6. Option Greeks Calculator

    • Build a tool that calculates the "Greeks" (Delta, Gamma, Theta, Vega) for various options.

  7. Portfolio Optimization with Constraints

    • Implement mean-variance portfolio optimization with additional constraints (e.g., sector weightings).

  8. GARCH Volatility Modeling

    • Use a GARCH model to forecast stock volatility based on historical returns.

  9. Interest Rate Models

    • Implement an interest rate model like the Vasicek or CIR model to simulate interest rate paths.

  10. Kelly Criterion for Optimal Betting

    • Use the Kelly Criterion to determine the optimal size of trades based on risk and return expectations.

Advanced/Master Level

  1. Quantitative Risk Management System

    • Develop a system to measure and monitor risk across multiple asset classes in real-time.

  2. Machine Learning for Stock Prediction

    • Apply machine learning techniques (e.g., decision trees, neural networks) to predict future stock prices.

  3. Algorithmic Portfolio Rebalancing

    • Build an algorithm to automatically rebalance a portfolio based on changing market conditions.

  4. High-Frequency Trading Simulation

    • Simulate a high-frequency trading system with latency considerations and market impact models.

  5. Stochastic Differential Equations in Option Pricing

    • Use advanced stochastic calculus techniques to price exotic options (e.g., Asian or Barrier options).