A Trade Gap Scalability Model for the Forex Market

The Foreign Exchange Market is characterized by the management of bandwidth and data memory. The Forex brokers manage the server side while the client side is managed by traders or the trading system. To handle the data memory and bandwidth overheads, leading Forex brokers must put measures in place to cope with increasing loads while traders pay for increased bandwidth to maintain multiple trading systems on virtual private servers. Research communities have concentrated on Forex prediction and profitability systems and models while neglecting the bandwidth and data memory overhead issue. In this paper, we propose trade gap scalability and profitability client-side model for the Forex market, to address this problem. The model was implemented and tested by integrating it into an expert advisor. Preliminary results showed that trade gap scalability model produced an increased profit gain of about 81%, reduced the volume of data broadcasted by the client to the broker's server and saved 39% of the server time.