Conceptual Charts meets the needs of the trading system developer by being a truly object oriented toolkit. The visual parts of the charts, such as x and y-axes, the different types of indicators and line studies are all objects. Non-visual parts, such as datasets, data access, and data conversion are also designed as objects. This allows a great deal of flexibility and control. Using Conceptual Charts is not like the old style of programming with function libraries. It is a new object oriented development tool for creating trading and investing systems. In addition to other advantages, as the complexity increases, an object oriented approach is much more manageable. Conceptual Charts uses the Component Object Model (COM and ActiveX) and has been developed using C++.
What is an object? In Conceptual Charts, an object is a particular part or piece that performs something useful. For example, an Axis object contains all of the logic and information required for displaying an x or y-axis. Most of the details are hidden, so you can just deal with the axis as a piece of the chart. If you want to change how an object looks or where it is displayed in the chart, an object has methods and properties that allow you to modify the object. If you want to add an object to your chart, you create the object. When you are through with an object, you delete the object.
The following sections give a brief overview of some of the objects included in Conceptual Charts.
The Axis object is used with both x and y-axes. The Axis object has 31 properties, 14 methods, and 20 types of x and y-axes. The different x-axis types support several data sample periods such as intraday, end-of-day, weekly, monthly, quarterly and yearly data. Included are log-based axes, a volume based x-axis, and several other specialized types.
When a chart is first created, it contains a default x-axis and a default y-axis. Using these default types, it is possible to create end-of-day price charts with a minimum of coding.
It is possible to have up to seven x-axes in different positions in a chart. Multiple x-axes are useful when making comparisons between data with different time frames. It is possible to have y-axes in up to seven different positions in a single graph in a chart. If multiple graphs are constructed in a chart, in a stacked fashion, then each graph can have up to 7 y-axes.
The purpose of the DataPlot object is as follows:
The DataPlot object can be used to display data on a graph, or to process input data (i.e. an indicator) and display the results on a graph. Besides including a large set of Technical Analysis indicators, it is also possible to display raw data, or create your own indicator or algorithm, or mix and match inputs and outputs of selected indicators. The DataPlot object can also be used as a black box that does not display the processed data, but allows the output data to be used in your trading program.
The large set of DataPlot types can be used as a toolkit to create custom indicators and trading systems. Combining indicators with custom algorithms is a very powerful feature of Conceptual Charts. The DataPlot object has 51 properties, 10 methods, 87 types, and 91 Technical Analysis indicators. Please click Indicators to view the range of indicator types.
In Conceptual Charts the LinesLabels object is used to construct various types of Technical Analysis Line Studies, labels and different forms of chart annotation. Line Studies are used to analyze and identify patterns such as support, resistance and trends in the charts of stocks, bonds, and commodities, etc. Essentially, they are lines that are drawn on a graph that contains some form of a curve, an indicator, or price bars.
Once the LinesLabels object has been created, the displayed form of line or label may be positioned in the chart using program code or it can be setup to be placed in the chart interactively using the mouse. Annotation tools are used to place comments, or highlight/identify some portion of the graph. They allow the user to mark up the graph with arrows, put a box or circle around a graph pattern, add labels or include comments. Although the annotation tools are not Line Studies, they are created, placed, modified, and used in the same way as Line Studies.
If the graph is moved, resized, zoomed or scrolled; Conceptual Charts will draw the line study or annotation at the correct position in the graph. Line Studies may also be used in graphs displaying real-time input data. The LinesLabels object has 17 properties, 21 methods, and 19 types. Please click Line Studies to view the different types.
Conceptual Charts includes object types that handle zoom and scroll functions for both horizontal and vertical control of the graph display. If multiple x or y-axes are used, a zoom/scroll object may be created for each axis to allow the user to selectively control parts of the displayed graph. The zoom and scroll functionality can be controlled within program code, or it can be tied to scroll bars, and buttons to allow interactive control by the user.
The DataAccess object has 5 properties, and 14 methods. It is used to input data from databases and ASCII data files. Contents of datasets may also be saved to databases. The underlying support for database access is ActiveX Data Objects (ADO). The methods and properties of this interface are designed to simplify the code necessary to input data, while still having the flexibility to connect to the wide range of data stores supported by ADO.
In Conceptual Charts, data is organized in datasets , which are "smart" dynamic arrays. The arrays are dynamic because they automatically increase in size when needed. They are described as "smart" arrays because they also contain logic that handles date, time, and other functions, which removes much of the programming burden. There are two main categories of datasets. In general, datasets are either sampled or non-sampled.
Non-sampled datasets are similar to simple arrays, and they are used in the same way that arrays are used in all programming languages. Sampled datasets are used to store data that have a corresponding time or date for each data element, using a specified sample period. Dataset object types include 17 properties, 8 methods, and 8 types.
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