My first open-source release of iMetrica for Linux Ubuntu 64 can now be downloaded at my Github, with a Windows 64 version soon to follow. iMetrica is a fast, interactive, GUI-oriented software suite for predictive modeling, multivariate time series analysis, real-time signal extraction, Bayesian financial econometrics, and much more.
The principal use of iMetrica is to provide an interactive environment for the numerical and visual analysis of (multivariate) time series modeling, real-time filtering, and signal extraction. The interactive features in iMetrica boast a modeling and graphics environment for analysts, practitioners, and students of econometrics, finance, and real-time data analysis where no coding or modeling experience is necessary. All the system needs is data which can be piped into the system in many forms, including .csv, .txt, Google/Yahoo Finance, Quandle, .RData, and more. A module for connecting to MySQL databases is currently being developed. One can also simulate their own data from a one or a combination of several different popular data generating models.
With the design intending to be interactive and self-enclosed, one can change modeling data/parameter inputs and see the effects in both graphical and numerical form automatically. This feature is designed to help understand the underlying mechanics of the modeling or filtering process. One can test many attributes of the modeling or filtering process this way both visually and numerically such as sensitivity, nonlinearity, goodness-of-fit, any overfitting issues, stability, etc.
All the computational libraries were written in GNU C and/or Fortran and have been provided as Native libraries to the Java platform via JNI, where Java provides the user-interface, control, graphics, and several other components in a module format, and where each module specializes in a different data analysis paradigm. The modules available in this open-source version of iMetrica are as follows:
1) Data simulation, modeling and fitting using several popular econometric models
- (S)ARIMA, (E)GARCH, (Multivariate) Factor models, Stochastic Volatility, High-frequency volatility models, Cycles/Trends, and more
- Random number generators from several different types of parameterized distributions to create shocks, outliers, regression components, etc.
- Visualize in real-time all components of the modeling process
2) An interactive GUI for multivariate real-time signal extraction using the multivariate direct filter approach (MDFA)
- Construct mulitvariate MA filter designs, classical ARMA ZPA filtering designs, or hybrid filtering designs.
- Analyze all components of the filtering and signal extraction process, from time-delay and smoothing control, to regularization.
- Adaptive real-time filtering
- Construct financial trading signals and forecasts
- Includes a real-time/frequency analysis module using MDFA
3) An interactive GUI for X-13-ARIMA-SEATS called uSimX13
- Perform automatic seasonal adjustment on thousands of economic time series
- Compare SARIMA model choices using several different novel signal extraction diagnostics and tools available only in iMetrica
- Visualize in real-time several components of modeling process
- Analyze forecasts and compare with other models
- All of the most important features of X-13-ARIMA-SEATS included
4) An interactive GUI for RegComponent (State Space and Unobserved Component Models)
- Construct unobserved signal components and time-varying regression components
- Obtain forecasts automatically and compare with other forecasting models
5) Empirical Mode Decomposition
- Applies a fast adaptive EMD algorithm to decompose nonlinear, nonstationary data into a trend and instrinsic modes.
- Visualize all time-frequency components with automatically generated 2D heat maps.
6) Bayesian Time Series Modeling of ARIMA, (E)GARCH, Multivariate Stochastic Volatility, HEAVY models
- Compute and visualize posterior distribtions for all modeling parameters
- Easily compare different model dimensions
7) Financial Trading Strategy Engineering with MDFA
- Construct financial trading signals in the MDFA module and backtest the strategies on any frequency of data
- Perform analysis of the strategies using forward-walk schemes
- Automatically optimize certain components of the signal extraction on in-sample data.
- Features a toolkit for minimizing probability of backtest overfit
Tutorials on how to use iMetrica can be found on this blog and will be added on a weekly basis, with new tools, features, and modules being added and improved on a consistent basis.
Please send any bug reports, comments, complaints, to firstname.lastname@example.org.