Our client lacked the in-house talent required to develop a generic trading platform for back testing strategies. DataSpartan was brought in to resource and manage the project.
The backtesting system was built in Java and used Spark Streaming, Kafka and HDFS to build a continuous exchange-transform-load (ETL) pipeline for gathering the data feeds of stock prices and in particular streaming social media data in order to produce short term predictions of the stock price.
The system has been fully built and currently DataSpartan quants are building on top of the system in order to identify profitable strategies in both the high frequency and medium frequency space for market making. Currently, a market-impact tested strategy of Sharpe ratio 1 has been found and is being put into production.