iMetrica: Economic and Financial Data Control

The iMetrica software is endowed with a rich and detailed, yet quite easy-to-use module for uploading, downloading, exporting, editing, combining, transforming, building, simulating, and analyzing time series data.  It contains just about anything you’d want to have in an economic or financial time series data control interface while using only simple mouse point-and-click or drag interactions to navigate or download data from the internet. Since the most important aspect of time series analysis is, well, the time series data itself, we created a dedicated data control module to handle the majority of the time series data loading and editing work, before it is exported to any one of the five iMetrica computational modules or financial trading module.

Data Control Interface

We begin this iMetrica blog entry by first giving an overview of the basic components featured in the Data Control module. Figures 1 and 2 show the interface and all the major components labeled. Here, a collection of simulated time series are being plotted together.

Figure 1. The major components of the data control module.

Figure 2. The major components of the data control module, showing the target series editor.

  1. Main plotting canvas. This is where the time series data is plotted. Up to 10 different time series can be loaded into the data control at a time, and all of them can be plotted using the plot control in panel 2. When all the data is plotted together, to highlight a particular series, go to the main Data Control menu in the top left corner and place the mouse on any one the series names, the respective series will then be highlighted.
  2. Plot control panel. The time series that are uploaded into the module can be viewed by toggling their respective check box inside the plot control panel. This is helpful when different time series are scaled different and/or have different means. One can also log-transform the data, rescale the data to have unit standard deviations, or compare data using cross-correlations. Note that the log and rescale check box actions will only apply to the data that is currently being plotted. Furthermore, to plot the cross-correlations, only two time series can be chosen at a time. When one time series is chosen, the auto-correlation plot is drawn. Here, the “Target X(t) indicates a weighted aggregation of the data. To edit this, use the  “Target Series” in 3. To delete all of the data stored in the data control module, simply press the “Delete” button. Careful, there’s no going back once deleted.
  3. Simulated and Target Series Panels. The simulated time series data interfaces to simulate a multitude of different time series. Simulating time series can be helpful when wanting to either learn, practice, or explore the different modules and capabilites of iMetrica, learn more about time series analysis, or learn about the dynamics of time series modules. The different types of models include (S)ARIMA models, GARCH models, correlated cycle models, trend models, multivariate factor stochastic volatility models, and HEAVY models. From simulating data and toggling the parameters, one can visualize instantly the effects of the each parameter on the simulated data. The data can then be exported to any of the modules for practicing and honing one’s skills in hybrid modeling, signal extraction, and forecasting.  Each model has a “parameter” button (see 4) that controls the dimensions, innovation distributions, or parameter values. When changes are made, the simulated series is recomputed automatically and replotted on their respective plotting canvas (see 4).
  4. Simulated Data Control.  Once the parameters have been selected, and a desired simulated series has been achieved to one’s liking, it can be added to the main data control plotting canvas by clicking the “Add” button. The new simulated series is now ready to be exported to any of the modules. One can also change the random seed that controls the “burn-in” of the innovation sequence (random effects that govern the initialization and trajectory of the data). In some of the models, one can “integrate” the data to render stationary data nonstationary.
  5. Parameter Controls.  Once the “Parameters” button has been clicked, an additional panel will pop up where controls for all the model’s parameters can be toggled. Once any parameter has been changed using the sliders, scrollbars, or combo boxes, the simulated data is automatically recomputed and plotted, making it a great tool to understand time series model dynamics.
  6. Target Series Construction. The target series is used to construct a univariate time series that is a weighted sum of one or more time series (given by the X_i(t) for i=1,\ldots,10 series). In modules that only deal with univariate time series data (the uSimX13, EMD, and State Space Modeling), the constructed target series is the series that gets exported for analysis. For the MDFA module, this is the series that is being filtered for constructing a signal, with the other time series acting as the explanatory time series. In the BayesCronos module, this target series is ignored and only the supporting time series data X_i(t) are used.  In these up and down slider controls, one can adjust for the weight associated with that specific series, and the aggregate target series will be automatically recomputed as it is adjusted.
  7. Series Checkboxes. To ignore the series entirely in the computation of the target series, simply click the check box “off” in the associated “computed in target” check box. This will eliminate it from the target sum. In the case one is constructing data for the MDFA module, one has the option of utilizing a series in the target series, but not using it as an explaining time series variable, and vice-versa.

Loading Data from Files

Within this main data control hub, one can import univariate or multivariate time series data from a multitude of file formats, as well as download financial time series data directly from Yahoo! finance or another source such as Reuters for higher-frequency financial data.  To load data from a file, simply click on the “Data Input/Export” menu when in the Data Control module and select one of the “Load” data options. The “Load Data” option pop up a “file select” panel and from there, the data file can be selected. The format of the data in this “Load Data” case is simple: a single column of data for each series. If more than one series is present, the data column must be separated by a space.  In the “Load CSV” data, this assumes the file is stored in a CSV format. See Figure 3 for the menu options of the Data Control module.

Figure 3. Showing the different options for importing data into the data control module.

Downloading Financial Data 

The other option for loading data into the module is through the “Load Market Data” interface. Rather than loading data from a file that is sitting in your directory, you also conveniently have the option to download data directly from the internet or financial time series database, such as Reuters.  As a fast and easy way to download financial data into iMetrica, when the “Load Market Data” is selected, a pop-up panel interface will surface that gives access to controlling the download of financial market data. This is shown in Figure 4.  The options on this interface are described below.

Figure 4. The “Load Market Data” interface to download market data directly from Yahoo!. Here the daily log-returns and volume of Google (GOOG) and Apple (AAPL) are being downloaded.

  • Symbols(s) – In this text box, type the market ticker symbol of the desired financial series in all CAPS. Each ticker symbol must be seperated only by one space and nothing else. Up to 10 ticker symbols can be entered.
  • Start Date – This indicates the year, month, and day from which the financial time series begins. This date must obviously be in the past. If the day falls on a non-traded day such as a weekend or holiday, the nearest date after that date will be chosen. The time series will then be loaded to the most recent date available for that asset.
  • Hours –  This indicates the time period in which the frequency of the data is selected. In most cases, this should simply be set to “US Market Hours”.
  • Frequency – The frequency of the data. The options are Second, Minute, 3,5,10,15,30-Minute, Hourly, Daily, Weekly, Monthly.
  • New Data Set – Deletes all the data already stored in the data control module and uploads as new data.
  • Log Returns – Download the data in log-return format. This is usually the case when using the data to build financial trading strategies using the MDFA module. However, in addition to the log-return data, it will also download the log-transformed raw time series data of the first asset in the Symbols(s) box. This is generally used for gauging financial trading accounts in the financial trading interface of iMetrica. When Financial Trading is turned on in the data control menu this is automatically set on.
  • Volume Data – In addition to the asset time series data, the volume (of trades) data associated for the given frequency will also be downloaded for each market ticker symbol given in Symbols(s).
  • Yahoo! Source – The financial data will be downloaded from Yahoo! finance (thus you need an internet connection). If this box is not checked, then the downloader will assume a Reuters financial database (but of course for this you need an account with Reuters).

Once the settings are made in the interface, click “Download Market Data”. If no errors are present in the settings, then all the data should be automatically available in the plot canvas after a few seconds of downloading time. Figure 5 gives the results of the data download from the example in Figure 4. Here, the daily log-returns of Google (GOOG) and Apple (AAPL) along with their daily volumes from 6-4-2011 to today (11-14-2012) have been downloaded into the data control module and ready for use. Notice the scaling of the volume data (final two series) have been adjusted using the simple slider bars in the “Target Series” panel to more-or-less fit the scale of the log-return data.

Figure 5. The daily log-returns of Google (GOOG) and Apple (AAPL) along with their respective volumes loaded into the data control module and plotted on the canvas. The data was uploaded by using the “Load Market Data” interface panel.

If there were errors, then no data will be uploaded to the canvas and you have to try again. Common errors are either no internet connection, the symbols are either incorrect or not in CAPS, or the starting date is bogus. Once the data is available to be plotted, simply click the check boxes associated with each plot. edit, scale, export, analyse, compute, and/or trade away!

More options for downloading data will constantly be added to the iMetrica software. Check back to the blog regularly for more updates and additions as they come.  Of course, suggestions are always welcome.


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