Collecting Tick Data instead of book data in the financial market by Srikant Krishna NJ

Tick data represents those principal components of capital market. This shows the actionable quotes and the different transpired trades for a certain trader. And according to Srikant Krishna NJ which is an expert in proprietary automated trading it is more important that book data. The trader is able to derive a lot of important data out of tick data. They are able to measure volume, spreads, quoting frequency, moving averages, VWAPs and volatility. These types of data used to be very hard to procure from the U.S. equity market. This information used to be only available for hedge funds and investment banks or those who can afford to have a team to work on gaining that information.

Today there are programs that enables individual to gain access to the information that they need. Through CTS/CQS Srikant was able to gain about 30GB or more information. He gathers all the data through multicast UDP. He makes sure that he fires an event to strip off the network buffer because he wants to throw the information on a separate queue in the memory. This will insure all the data are captured even with long period of time. He then classifies information that he gets as either a trade or quote.

Srikant Krishna NJ usually records it for 7 hours a day and he will get about 20-30GB of information which he then will compress into a zip file for him to easily upload and share to his other storage. He usually downloads information weekly. With the help of C#/.NET he can replay all the tick data that he saved. With this information he is able to have a good idea on how the market is and what is going to be a good trade to have. He is planning to improve his system by moving the back testing apparatus to his Microsoft Azure platform. This can save him time and will provide him with unlimited resources. If he also have an access to a bigger storage he would also be able to load a month’s worth if tick data into the memory.

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Created on Dec 31st 1969 18:00. Viewed 0 times.

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