Technical analysis software

Technical analysis software automates the charting, analysis and reporting functions that support technical analysts in their review and prediction of financial markets (e.g. the ).

The following are the most common features of technical analysis applications. Some software may focus on only one aspect (say back testing) and the combination of more than one software package is often required to build a fully automated trading system.

A graphical interface that presents price, volume and technical analysis indicators through a variety of visual interfaces such as line, bar, candlestick and open-high-low-close (OHLC) charts. The chart data is presented as a time series and users typically have the ability to view historical data with varying interval (sampling) periods. Interval periods range from seconds through to months; short term traders tend to use frequent interval periods, such as 1 minute i.e. the price data is updated every 1 minute, whereas tend to use daily, weekly or monthly interval periods when trying to identify price and technical analysis trends. Some charting packages enable users to draw support and resistance trend line or for example Fibonacci retracements to help establish trending patterns.

Enables traders to test technical analysis investment timing strategies against historical price movement for one or more specific securities. Strategies are compared to each other using diverse performance measurements such as maximum drawdown, annual profit and Sharpe ratio. The objective is to try and develop a trading strategy based on technical analysis indicator criteria, which will generate a positive return. This concept was computerized and introduced to traders by Louis B. Mendelsohn in 1983 with his ProfitTaker Futures Trading Software (see August 2010 issue of Stocks, Futures & Options Magazine).

A process of testing technical analysis indicator parameters, with the view to developing an investment strategy that generates the maximum return based on historical price movement. The optimization process is achieved through the fine-tuning of the associated technical analysis charting parameters. Typically technical analysis indicators have a range of parameters that can be adjusted, such as the interval period and the technical analysis indicator variables. For example, the has four parameters that effect its results: %k, %d, slowing period, interval period. Optimization must be performed carefully to avoid curve fitting. Back testing of an over-optimized system will perform real-time. One way to diminish over-optimization is by carrying out optimization on historical data and then performing future testing (sometimes referred to as 'out of sample') before making a final evaluation of a trading strategy.

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