What if you could develop a trading strategy that dynamically adjusts itself as market conditions change and continually runs back tests to calculate optimal trading parameters? Using artificial intelligence and machine learning, financial trading startup, Inovance Financial Technologies is aiming to do just that. Inovance’s offering is based on its TRAID platform. The platform provides users a wide array of quantitative trading strategies that mimic tactics used by institutional and professional traders. Similar in a way to social and auto trading products where users elect to copy signals or other traders, TRAID differs in that users create a portfolio of strategies for each symbol they are trading. The platform then adjusts the weighting of each strategy based on its recent performance and overall market conditions.
Explaining the process, Justin Cahoon, Director of Business Operations at Inovance, stated to Forex Magnates that the idea behind TRAID was to “create a platform that would use real algos used by Wall Street traders. TRAID back tests the algos to create a model that weighs the strategies for optimal efficiency.” He added that, “With each new data point, the model is retrained and better algorithms stay and weaker performers become under weighted.”
The platform is operated by first choosing a currency and creating a portfolio model by adding algorithmic strategies. According to Cahoon, algos are based on 100’s of different technical indicators as well as ones that use fundamental and sentimental data. After creating a model, users enter risk management criteria, such as for max daily drawdowns of any single strategy and position sizes. Trading criteria can also include periods of when trading should be suspended, such as before or after important economic releases, times of the day, and during holiday periods. TRAID then back tests results to create a model that takes into account both performance and risk. As mentioned above, once optimized, models are continually adapted to recalculate weighting of the portfolio’s algorithm.
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Beyond only providing dynamically changing black box strategies, Inovance is also working on implementing greater transparency of algorithms. The goal being to allow users with quant backgrounds to use TRAID to develop their own strategies using the program, as well as providing non-quants with more transparency about the algorithms they are using.
Having received a demo of the product, currently TRAID is best described as suitable for experienced traders who have an understanding of using algorithms and the overall market. In this regard, Inovance is currently aiming to appeal to professional traders and small hedge funds. Overall, Cahoon mentioned that, “Our goal is to replace a firm’s quant team with our TRAID platform.”
In addition to company’s high-end user target, Inovance plans on using its machine learning product to create tools for the retail market. Ideas include rating of MetaTrader EAs to determine their risk soundness and provide suggestions to improve results and third party ratings of signal providers.
Currently, Innovance is interested in receiving feedback about TRAID and is actively seeking beta testers for the product.