The premise was simple. Use “big” data analytics and machine learning models to predict the movement of stock prices. However, we had really “dirty” data and our Data Scientists were stuggling to seperate the noise from the signals. In the context of share trading, signal generation is the process of identifying patterns in market data that suggest that a share price is likely to rise or fall in the near future.

This one is better explained with the presentation below. If you want to learn how to run quantitative analytics at scale, it’s well worth a watch.

Built and maintained a client and market side booking service, off order book trade reporting engine and trade manager/repository. A market side booking service is a type of financial service that allows market participants to place orders directly with market makers. This is in contrast to traditional order routing, where orders are routed through a broker or exchange. Market side booking services offer a number of advantages over traditional order routing, including:

I developed an eTrading platform routing client FIX flow to the firm’s Algorithmic Trading platform. The platform was used by traders send orders to the market based on a particular strategy (e.g VWAP). VWAP stands for Volume-Weighted Average Price. It is a technical analysis indicator that is used to measure the average price of a security over a given period of time, taking into account the volume of trades. The VWAP is calculated by adding up the dollar value of all trades for a security and then dividing by the total volume of trades.

Design and development of a real time matching engine to provide insights into liquidity for funding forecasts and regulatory requirements. A matching engine is used in the back office of a bank to match buy and sell orders for securities. It is a software system that receives buy and sell orders from market participants, and it matches these orders based on a set of rules. The rules typically include the price, quantity, and type of order.