Algorithmic trading is becoming all the more common to the everyday investor.
Companies likes Metaquotes and TradeStation provide MetaEditor and EasyLanguage, respectively, which allow traders, with a basic programming background, to create algorithmic trading strategies. Traders can add a few technical indicators to their charts, look for patterns and build a strategy to test their hypothesis.
But what if you could take it a step further? What if, instead of adding indicators to charts and looking for patterns, the algorithms themselves looked for the patterns on the chart and you decided whether it was a good opportunity or not. Sound confusing? Let’s step through an example to make it clearer. Generally, a trader brings up a chart of the asset they would like to trade and they add a few indicators. To make it easy let’s pretend the trader is looking at the EUR/USD with a 200 and a 50 period moving average. While the more discretionary traders look to see if the 50 period moving average is above or below the 200 period moving average, more sophisticated traders will export the data to Excel, MatLab, Stata, R, etc… and analyze price movements before and after crosses, on certain days, at certain times, based on the distance between the two averages, etc… They will then refine the conditions that need to be met in order to trade; this includes applying market filters like volatility or volume parameters, excluding trades during news events, or not trading on Friday afternoons. Traders then code up their strategy, select a date range, take profits and stop losses and backtest the strategy. Finally, they paper trade it (hopefully) before trading it live. If this sounds immensely time consuming, that is because it is.
What MetaTrader and TradeStation are trying to do is decrease the time it takes to code, backtest and paper trade a strategy so traders can more quickly get to the fun stuff; live trading. What more sophisticated traders, professional money managers, quantitative hedge funds and the like do is a bit different. They have access to computer scientists, mathematicians, statisticians and experienced traders. They can use intelligent algorithms to do the heavy lifting and search for patterns in the data. Instead of staring and scrolling through their charts and pouring time into Excel, Matlab, Stata and R, they allow an algorithm to do the pattern recognition for them.
Inovance Financial Technologies is creating a platform for traders to do the same analysis, but without any programming or math knowledge required. Traders input the indicators that they think influence price changes and machine learning algorithms find patterns in the data. The simple point-and-click interface allows the trader to select an asset, indicators and an intelligent algorithm and search for patterns over a specified date range. Additionally, traders can drill down into each trading opportunity to see what the patterns are before simulating or trading their strategy live. The platform doesn’t come up with a strategy for you, but it does mitigate the time a trader spends analyzing data. Traders can create an algorithmic strategy in just a few minutes. Inovance, in its private beta, offers their platform on spot FX and plans to soon expand to stocks, futures, and options.