Название: MATLAB Financial Toolbox User's Guide (R2021a)Автор: MathWorks
Издательство: The MathWorks, Inc.
Год: 2021
Страниц: 3028
Язык: английский
Формат: pdf (true)
Размер: 13.8 MB
Analyze financial data and develop financial models.
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.
In general, this guide assumes experience working with financial derivatives and some familiarity with the underlying models. In designing Financial Toolbox documentation, we assume that your title is like one of these:
- Analyst, quantitative analyst
- Risk manager
- Portfolio manager
- Asset allocator
- Financial engineer
- Trader
- Student, professor, or other academic
We also assume that your background, education, training, and responsibilities match some aspects of this profile:
- Finance, economics, perhaps accounting
- Engineering, mathematics, physics, other quantitative sciences
- Focus on quantitative approaches to financial problems
Contents:
Getting Started
Performing Common Financial Tasks
Portfolio Analysis
Mean-Variance Portfolio Optimization Tools
CVaR Portfolio Optimization Tools
MAD Portfolio Optimization Tools
Investment Performance Metrics
Credit Risk Analysis
Regression with Missing Data
Solving Sample Problems
Financial Time Series Analysis
Using Financial Timetables
Using Financial Time Series
Financial Time Series App
Financial Time Series User Interface
Trading Date Utilities
Technical Analysis
Stochastic Differential Equations
Functions
Bibliography
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