Financial Toolbox
Analyze financial data and develop financial models
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Financial Toolbox provides functions for the mathematical modeling and statistical analysis of financial data. You can analyze, backtest, and optimize investment portfolios taking into account turnover, transaction costs, semi-continuous constraints, and minimum or maximum number of assets. The toolbox enables you to estimate risk, model credit scorecards, analyze yield curves, price fixed-income instruments and European options, and measure investment performance.
Stochastic differential equation (SDE) tools let you model and simulate a variety of stochastic processes. Time series analysis functions let you perform transformations or regressions with missing data and convert between different trading calendars and day-count conventions.
Technical Indicators and Financial Charts
Compute technical indicators (including moving averages, momentums, oscillators, volume indicators, and rate of change) and create financial charts (including candlestick, open-high-low-close, and Bollinger band charts).
Investment Performance Metrics
Evaluate investment performance using built-in functions for calculating metrics such as Sharpe ratio, information ratio, tracking error, risk-adjusted return, sample lower partial moments, expected lower partial moments, maximum drawdown, and expected maximum drawdown.
Portfolio Optimization Approaches
Perform mean-variance, mean absolute deviation (MAD), and conditional value at risk (CVaR) portfolio optimizations.
Efficient Portfolios and Efficient Frontiers
Estimate the efficient portfolio and its weights that maximize Sharpe ratio, visualize efficient frontiers, and calculate portfolio risks, including portfolio standard deviation, MAD, VaR, and CVaR.
Portfolio Constraints and Transaction Costs
Apply portfolio optimization constraints, including tracking error, linear inequality, linear equality, bound, budget, group, group ratio, average turnover, one-way turnover, minimum number of assets, and maximum number of assets. Incorporate proportional or fixed transaction costs on either gross or net portfolio return optimization.
Strategy Backtesting Framework
Define investment strategies and use the backtesting framework to run backtests, analyze results, and generate performance metrics for your strategies from historical or simulated market data. Incorporate technical indicators, sentiment, and other trading signals into your strategies. The framework also supports custom transaction costs, expanding or rolling lookback windows, margin trading, and long/short portfolios.
Cash Flow Analysis
Use Financial Toolbox to calculate present and future values; determine nominal, effective, and modified internal rates of return; calculate amortization and depreciation; and determine the periodic interest rate paid on loans or annuities.
Fixed-Income Analysis and Option Pricing
Calculate price, yield-to-maturity, duration, and convexity of fixed-income securities. Compute analytics such as complete cash flow date, cash flow amounts, and time-to-cash-flow mapping for bonds. Calculate option prices and greeks using Black and Black-Scholes formulas.
Monte Carlo Simulation
Generate random variables for Monte Carlo simulations based on a variety of SDE models, including Brownian motion, geometric Brownian motion, constant elasticity of variance, Cox-Ingersoll-Ross, Hull-White/Vasicek, and Heston.
Product Resources:
“MATLAB and MATLAB Compiler SDK enabled us to rapidly deliver a sophisticated portfolio analytics web application with confidence that it will return accurate results extremely quickly, ensuring a highly usable and stable platform for our clients.”
Financial Toolbox FAQs
Financial Toolbox provides functions for mathematical modeling and statistical analysis of financial data, enabling portfolio optimization, risk estimation, credit scorecard modeling, yield curve analysis, and investment performance measurement.
Yes, MATLAB's Financial Toolbox is specifically designed for financial applications, offering tools for portfolio optimization, backtesting strategies, and financial data analysis.
Financial Toolbox supports mean-variance, conditional value at risk (CVaR), and mean absolute deviation (MAD) portfolio optimization. It also supports constraints such as turnover, transaction costs, and limits on the number of assets.
Yes, the toolbox includes a backtesting framework for defining investment strategies, running backtests on historical or simulated data, and evaluating performance, with support for transaction costs, management fees, performance fees, and long/short portfolios.
You can price fixed-income securities, calculate yields, duration, convexity, and compute option prices and greeks using Black and Black-Scholes formulas.
Financial Toolbox enables credit risk estimation, credit scorecard modeling, and calculation of portfolio risks, including standard deviation, MAD, VaR, and CVaR, plus performance metrics like Sharpe ratio and maximum drawdown. For more comprehensive risk modeling and validation workflows, see Risk Management Toolbox.
Yes, it includes Monte Carlo simulation capabilities with support for various stochastic differential equation (SDE) models including Brownian motion, geometric Brownian motion, Cox-Ingersoll-Ross, and Heston.
The toolbox computes technical indicators, including moving averages, momentums, oscillators, and volume indicators, and creates financial charts such as candlestick, open-high-low-close, and Bollinger band charts.
