What Is Financial Toolbox?
Financial Toolbox™ provides functions for the mathematical modeling and statistical analysis of financial data. You can analyze, backtest, and optimize investment portfolios, while taking turnover, transaction costs, semicontinuous constraints, and minimum or maximum number of assets into account. 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.
Published: 30 Oct 2023
Financial Toolbox provides functions for the mathematical modeling and statistical analysis of financial data. With Financial Toolbox, you can perform portfolio optimization, backtest investment strategies, and utilize Monte Carlo simulations.
Standard portfolio optimization methods, such as Mean-Variance, Conditional Value-at-Risk, and Mean-Absolute Deviation, as well as the ability to define custom objectives, are all built into Financial Toolbox. You start with a portfolio object where you can define the necessary information needed to analyze your data. Any constraints or transaction costs can simply be specified within the object. Once you’ve completed the definition, you can use portfolio objects in common applications that are built into Financial Toolbox, such as estimating the efficient frontier, or to evaluate the performance of a custom objective, like minimizing tracking error.
Financial Toolbox’s backtesting framework lets you specify investment strategies, run backtests, and generate performance metrics. Instead of writing extensive complex code, Financial Toolbox simplifies the backtesting process. Using backtest strategy objects, you can define different approaches for making asset allocation decisions. A backtest engine object captures the strategies and parameters to be tested. After running the engine, summary tables and equity curves can be automatically generated to examine the results.
Financial Toolbox uses Monte Carlo and Quasi-Monte Carlo Simulations along with Stochastic Differential Equation tools to build and evaluate stochastic models. This is useful to model phenomena such as fluctuating stock prices and interest rates, which can be integral to inform forecasting and risk management.
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