File Exchange
YahooFinance/Quandl data downloader
Least squares spline modeling using shape primitives
Used to retrieve historical stock data for a user-specified date range
density plot
Matlab toolbox providing access to X-13 seasonal adjustment programs of the US Census Bureau.
Repack of Mi(xed) Da(ta) S(ampling) regressions (MIDAS) written by Eric Ghysels and collaborators
Slides and MATLAB® code for the day-ahead system load and price forecasting case study.
Functions related to the resolution of discrete-time Markov Decision Processes.
Demo files from the 2010 webinar "Global Optimization with MATLAB Products"
Functions to estimate copula GARCH and copula Vine models.
In this article, it listed some classical time series techniques available in MATLAB, you may try them on your forecasting problem.
Use ARIMA Model to predict real life stock data
Many MATLAB routines related to econometrics, statistics and introductory economics teaching.
A framework for systemic risk valuation and analysis.
TSAF enables you to quickly analyze time series and forecast the future.
Modification of APPLYHATCH_PLUS, allowing for color and variable thickness for hatch patterns.
Chapter-by-Chapter MATLAB codes related to the book "Computational Finance. MATLAB oriented modeling"
Download a google spreadsheet as csv and import into a Matlab cell array.
Algorithm for the analysis of electrodermal activity (EDA) using convex optimization
Dynamic energy demand forecasting using Econometrics (ARIMA/VAR/GARCH)
Structural Equation Model through Partial Least Squares approach (PLS-SEM)
Mann-Whitney-Wilcoxon non parametric test for two unpaired groups.
Software for quantitative portfolio and risk management
Provides functions for getting data from both data sources as well as helper utility functions
A tutorial and tool using PLS for discriminant analysis.
Files from the November 18, 2010 webinar.
SimPowerSystems(SPS) and Simscape are used to calculate losses in a 3-phase, 3-level inverter.
MATLAB code for the generation asset risk analysis case study
Application of the Morris method with a reduced risk of factors underestimation
MATLAB example on how to use Reinforcement Learning for developing a financial trading model
Demo files from (upcoming) webinar on Machine Learning for Algo Trading
Toolbox to specify, fit and evaluate SEM models
Files from the Automated Trading webinar showing X_Trader and QuickFIX/J integration.
Similar to csvread, but has a lot more user-friendly options and can deal with non-numeric data.
Quicksort implementation in Matlab, works in O(n)=n*log(n)
GODLIKE combines 4 global optimizers for both single/multi-objective optimizations
Plot and analyze live market data from Bloomberg or Yahoo.
ARMAX-GARCH-K-SK Toolbox
Estimation of parameters and eigenmodes of multivariate autoregressive models.
Connect to MySQL database.
Play individual hands of the card game, or simulate a session.
Compute autocorrelation function
Calculate the RSI for a stock over any time range for any given period
Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations (SDEs)
it use Machine Learning in MATLAB to predict the buying-decision of Stock by using real life data.
Financial stock market prediction
Files for demonstrating how to perform portfolio optimization
Three phase load flow for power distribution systems
Demos from the 'Commodities Trading with MATLAB' webinar - July 25, 2013.
This is a case study of forecasting short-term electricity loads for the Australian market.
artificial potential field path routing
How to Build an Event-based Automated Trading System in MATLAB
This program solves the Dynamic Economic Dispatch by quadratic Programming.
Conditional Value at Risk (CVaR) portfolio optimization with the PortfolioCVaR object
Scripts to build and test Fama & French three-factor model.
GUI for viewing various simple technical analysis indicators of a time series
The software solves the power flow problem in rectangular coordinates
Demonstration of Neoclassic Growth Model in Dynamic Economics
Temporal disaggregation, interpolation and extrapolation of time series. Methods: univariate (with or without indicators) and multivariate.
It is comparing the GDP Prediction using ARIMA (Autoregressive Integrated Moving Average) and NAR (Nonlinear Autoregressive Neural Network).
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