The rebate liquidity trading method is one form where the market order flow of information will come under heavier emphasis. In this the flow of information as perceived in the context of both order flow and the real time pricing information would be significant element in decision making (Perlin, 2009). Some strategies that were traditionally used in the past where that of the pinging strategies that of flash orders and more and these are mostly made use of in what are called the crossing venues or the more nontraditional form of trading venues. In these nontraditional styles the form of information, the pressure on the trade, the expected order flow and the flow of information influenced by variables are all points of consideration (Glantz, and Kissell, 2013). Trading strategy has to consider all these elements in order to ensure the investor is profited in some way. Information in the context of rebate-liquidity style trading is therefore retrieved and then analyzed and based on the information analysis some form of a buy or sell style signal is then generation (Deboeck, 1994). In Quantitative Trading, the use of computers, intelligent processing and more will make these information flows processing much faster and more efficient.
In current trends more countries emphasize on this form of a Quantitative Trading as the Quantitative Trading objectives align with that of the creation of fast processing that technology aids it with. “What is meant by this is that the information that can be inferred retrieved, processed, computed, compiled, etc., from market data to generate a buy or sell signal, through the use of quick systems and better computers, infrastructure, location of servers, etc., is colocation, pinging, indication of interests (IOIs) and flash order” (Glantz, and Kissell, 2013, p.276). While some of the advantages of Quantitative Trading like these are seen to be the main reason in their adoption, in countries that are growing to develop their quantitative strategies, the use of some strategies are still a work in progress. Some of the existing strategies are challenged in China because of the extensive back-testing that is required in terms of the execution platforms. Platforms like the Deltix which are US based has been combined with their custom technology in order to create the necessary Quantitative Trading platforms. However, Quantitative Trading is still considered to be relatively new for the country. As an interview with a main stream Quantitative Trading trader and analyst suggests, in the case of China, Quantitative Trading is still very much at the frontier level only. This is because of a social effect (Automated Trader, 2012). People and traders in China might not be that willing to trade in Quantitative Trading or other automated strategies that comes with Quantitative Trading. There are also situations of corruption and more where traders might end up making their money in manipulation, insider information and other unregulated ways and this leads to issues as there is no fair competition or incentive for a trader to be involved in Quantitative Trading (Automated Trader, 2012).