An Intrinsic Entropy Model for Exchange-Traded Securities

Claudiu Vinte, Ion Smeureanu, Titus-Felix Furtuna and Marcel Ausloos

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Abstract: This article introduces an intrinsic entropy model that can be used as an indicator to gauge investor interest in a given exchange-traded security, along with the state of the general market corroborated by individual security trade data. Although the syntagma of intrinsic entropy might sound somehow pleonastic, since entropy itself characterizes the fundamentals of a system, we would like to make a clear distinction between entropy models based on the values that a random variable may take and the model that we propose, which employs actual stock exchange trading data. The model we propose for intrinsic entropy does not include any exogenous factor that could influence the level of entropy. The intrinsic entropy signals whether the market is inclined to buy the security or rather to sell it. We further explore the usage of the intrinsic entropy model for algorithmic trading, in order to demonstrate the value of our model in assisting investors in the selection of the intraday stock portfolio, along with timely generated signals to support the buy / sell decision making process. The test results provide empirical evidence that the proposed intrinsic entropy model can be used as an indicator to evaluate the direction and intensity of intraday trading activity of an exchange-traded security. The data used for the test consisted of historical intraday transactions executed on The Bucharest Stock Exchange (BVB).

Date: 2022-05
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Published in Entropy 2019, 21(12), 1173 (This article belongs to the Special Issue Disordered Systems, Fractals and Chaos)

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