YahooFinance/Quandl data downloader

Functions related to the resolution of discrete-time Markov Decision Processes.

Least squares spline modeling using shape primitives

Matlab toolbox providing access to X-13 seasonal adjustment programs of the US Census Bureau.

Chapter-by-Chapter MATLAB codes related to the book "Computational Finance. MATLAB oriented modeling"

Mann-Whitney-Wilcoxon non parametric test for two unpaired groups.

Slides and MATLAB^® code for the day-ahead system load and price forecasting case study.

Functions to estimate copula GARCH and copula Vine models.

Demo files from the 2010 webinar "Global Optimization with MATLAB Products"

Repack of Mi(xed) Da(ta) S(ampling) regressions (MIDAS) written by Eric Ghysels and collaborators

Used to retrieve historical stock data for a user-specified date range

density plot

A fuzzy neural network for forecasting time series

Structural Equation Model through Partial Least Squares approach (PLS-SEM)

Provides functions for getting data from both data sources as well as helper utility functions

Retrieve historical stock data from Yahoo! Finance

Dynamic energy demand forecasting using Econometrics (ARIMA/VAR/GARCH)

MATLAB example on how to use Reinforcement Learning for developing a financial trading model

Modification of APPLYHATCH_PLUS, allowing for color and variable thickness for hatch patterns.

SimPowerSystems(SPS) and Simscape are used to calculate losses in a 3-phase, 3-level inverter.

This script file generates a fractal stock price graph.

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.

MATLAB code for the generation asset risk analysis case study

ARMAX-GARCH-K-SK Toolbox

Temporal disaggregation, interpolation and extrapolation of time series. Methods: univariate (with or without indicators) and multivariate.

it use Machine Learning in MATLAB to predict the buying-decision of Stock by using real life data.

TSAF enables you to quickly analyze time series and forecast the future.

This is a case study of forecasting short-term electricity loads for the Australian market.

Plot and analyze live market data from Bloomberg or Yahoo.

How to Build an Event-based Automated Trading System in MATLAB

Algorithm for the analysis of electrodermal activity (EDA) using convex optimization

In this article, it listed some classical time series techniques available in MATLAB, you may try them on your forecasting problem.

Play individual hands of the card game, or simulate a session.

Access historical data, real-time market data, place orders, options chains, and more

Download a google spreadsheet as csv and import into a Matlab cell array.

A single function that calculates 27 different technical indicators

Demo files from (upcoming) webinar on Machine Learning for Algo Trading

Three phase load flow for power distribution systems

Files from the Automated Trading webinar showing X_Trader and QuickFIX/J integration.

Files from the November 18, 2010 webinar.

Compute autocorrelation function

A tutorial and tool using PLS for discriminant analysis.

Text to Binary and Binary to Text conversion

Conditional Value at Risk (CVaR) portfolio optimization with the PortfolioCVaR object

a simulation of the Selective Repeat ARQ protocol

LMP calculation

FAST (Finally An SDDP Toolbox) is an SDDP toolbox for Matlab

Quicksort implementation in Matlab, works in O(n)=n*log(n)

Markov and semi-Markov toolbox

The software solves the power flow problem in rectangular coordinates

Queueing Theory Algorithms for MATLAB

Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations (SDEs)

Software for quantitative portfolio and risk management

A plot which shows the different curves of Intensity - Duration - Frequency of rain events.

This package implements Dual Extended Kalman Filter for time-varying MVAR parameter estimation.

text and comments on solutions available at http://symmys.com/node/170

Retrieves historical stock data from Yahoo Finance by parsing html pages instead of .csv download.

It is comparing the GDP Prediction using ARIMA (Autoregressive Integrated Moving Average) and NAR (Nonlinear Autoregressive Neural Network).