Trade Analysis: Experts In Medium & High Frequency Data
Financial markets are increasingly benefiting from the use of Artificial Intelligence based trading strategies and platforms. The adoption of AI by financial markets means that less biased decisions are being made by the several players and also that traditional approaches are being shown to be ineffective and suboptimal when it comes to performance. Financial institutions that do not adopt AI in their processes are bound to underperform the market in the long run.
Quants at DataSpartan specialise on the mathematical modelling of different aspects of the market and have experience on the analysis of market data in the medium and high frequency ranges. In this use case, the client had an in-house proprietary trading platform and wanted to increase the range of trading strategies available. The research work included both public and proprietary data feeds for each symbol which allowed the quants to conduct in depth research.
Our quant team followed a rigorous approach that starts from analysing existing research related to the desired strategy outcome. Continuous work from a multidisciplinary team found Ideas from a wide rage of fields such as physics, psychology and mathematics. Strategy ideas were backtested on real data using the existing client’s platform and those profitable were promoted for production use.
After months of research and backtesting, multiple strategies with competitive returns and Sharpe Ratios were found and promoted to live use. Our new strategies have increased the returns of the assets under management of the firm. Work continues to improve returns and to expand to different asset classes.