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Real-time computing method and system for nonrandom informational probability in continuous game data streams

A real-time computing and data flow technology, applied in the computer field, can solve the problems of not being able to reflect the real-time status of non-random information probability, inconvenient and timely updating, etc.

Active Publication Date: 2016-06-29
SHANGHAI LEITON CAPITAL MANAGEMENT CO LTD
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Problems solved by technology

[0003] However, the currently commonly used non-random information probability estimation method is based on the statistical method of maximum likelihood method for some unobservable parameters, which inevitably requires artificial assumptions for parameter estimation, and the results of parameter estimation are not consistent. It is convenient to update in time, so it cannot reflect the real-time status of the non-random information probability in the feature data stream

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  • Real-time computing method and system for nonrandom informational probability in continuous game data streams
  • Real-time computing method and system for nonrandom informational probability in continuous game data streams
  • Real-time computing method and system for nonrandom informational probability in continuous game data streams

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[0050] In the following, the technical solutions of the present invention will be further described in detail in combination with specific embodiments. The following examples are implemented on the premise of the technical solutions of the present invention, and detailed implementation methods and processes are given, but the protection scope of the present invention is not limited to the following examples.

[0051] For the non-random information probability in the continuous game data stream, by constructing such as figure 1 The micro-trading model shown is used to illustrate, where α is the probability of information event generation, μ is the transaction order rate of an informed (i.e., non-random information) trader, and ε is the transaction order of an uninformed (i.e., random information) trader rate. Thus, the probability PIN of informed transaction information (that is, the probability of non-random transaction information) can be expressed as follows:

[0052] ...

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Abstract

The invention discloses a real-time computing method and system for nonrandom informational probability in continuous game data streams. The real-time computing method comprises the steps of maintaining a current trading volume data bucket by virtue of a series of input time series data, simultaneously maintaining a queue with a length equal to the number n of sampled data buckets, adding VtauB and VtauS computed in the current trading volume data bucket into the head of the current queue whenever the current trading volume data bucket is full, and computing the nonrandom informational probability according to n latest VtauB and VtauS by virtue of a sliding window analogue method. According to the real-time computing method, the online rolling real-time computation can be realized, furthermore, the stability and the adaptivity are relatively good, obstacles for estimating unobservable parameters are eliminated, and defect of inaccuracy of a time dimension algorithm during real-time trading and particularly high-frequency trading is overcome.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a data analysis method and system. Background technique [0002] Continuous games, such as auctions, bidding systems, real-time transactions, etc., form data streams. Due to factors such as information asymmetry and irrational decision-making among the players participating in the game, the data streams are mixed with random decision-making information of a large number of players. Calculating the random decision probability in the feature data stream, or calculating the non-random information probability in the feature data stream can make better use of the effective information in the game data time series, thus helping to solve many practical problems, such as predicting Market volatility, prevention of market risks, etc. [0003] However, the currently commonly used non-random information probability estimation method is based on the statistical method of maxim...

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Application Information

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IPC IPC(8): G06F19/00
CPCG16Z99/00
Inventor 沈天瑞王琦涂世涛
Owner SHANGHAI LEITON CAPITAL MANAGEMENT CO LTD
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