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A new method is proposed for analyzing complexity and studying the information in random geometric networks using Tsallis entropy tool. Tsallis entropy of the ensemble of random geometric networks is calculated based on the components of…

Statistical Mechanics · Physics 2025-02-20 O. K. Kazemi , S. M. Taheri

Investors and stock market analysts face major challenges in predicting stock returns and making wise investment decisions. The predictability of equity stock returns can boost investor confidence, but it remains a difficult task. To…

Statistical Finance · Quantitative Finance 2025-07-04 Adebola K. Ojo , Ifechukwude Jude Okafor

We show how the Shannon entropy function can be used as a basis to set up complexity measures weighting the economic efficiency of countries and the specialization of products beyond bare diversification. This entropy function guarantees…

Physics and Society · Physics 2021-06-04 Gianluca Teza , Michele Caraglio , Attilio L. Stella

Navigating the intricate landscape of financial markets requires adept forecasting of stock price movements. This paper delves into the potential of Long Short-Term Memory (LSTM) networks for predicting stock dynamics, with a focus on…

Trading and Market Microstructure · Quantitative Finance 2024-03-29 Nisarg Patel , Harmit Shah , Kishan Mewada

The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probability that a system will be in a certain state compared to the…

Information Theory · Computer Science 2019-06-26 Hector Zenil , Narsis A. Kiani , Jesper Tegnér

We develop a complexity measure for large-scale economic systems based on Shannon's concept of entropy. By adopting Leontief's perspective of the production process as a circular flow, we formulate the process as a Markov chain. Then we…

General Finance · Quantitative Finance 2017-07-12 Dave Zachariah , Paul Cockshott

There is a relation between the irreversibility of thermodynamic processes as expressed by the breaking of time-reversal symmetry, and the entropy production in such processes. We explain on an elementary mathematical level the relations…

Statistical Mechanics · Physics 2007-05-23 C. Maes , K. Netocny

R\'esum\'e: Le principal objet de cette communication est de faire une r\'etro perspective succincte de l'utilisation de l'entropie et du principe du maximum d'entropie dans le domaine du traitement du signal. Apr\`es un bref rappel de…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ali Mohammad-Djafari

Financial stock returns correlations have been studied in the prism of random matrix theory, to distinguish the signal from the "noise". Eigenvalues of the matrix that are above the rescaled Marchenko Pastur distribution can be interpreted…

Statistical Finance · Quantitative Finance 2025-08-19 Ixandra Achitouv

This paper develops and empirically evaluates a Sharpe-driven stock selection and liquidity-constrained portfolio optimization framework designed for the Chinese equity market. The proposed methodology integrates three sequential stages:…

Operating Systems · Computer Science 2025-11-18 Thanh Nguyen

In the first chapter of Shannon's "A Mathematical Theory of Communication," it is shown that the maximum entropy rate of an input process of a constrained system is limited by the combinatorial capacity of the system. Shannon considers…

Information Theory · Computer Science 2009-11-20 Georg Böcherer , Valdemar Cardoso da Rocha Junior , Cecilio Pimentel

We study how the Shannon entropy of sequences produced by an information source converges to the source's entropy rate. We synthesize several phenomenological approaches to applying information theoretic measures of randomness and memory to…

Statistical Mechanics · Physics 2007-05-23 James P. Crutchfield , David P. Feldman

Product probability property, known in the literature as statistical independence, is examined first. Then generalized entropies are introduced, all of which give generalizations to Shannon entropy. It is shown that the nature of the…

Statistics Theory · Mathematics 2009-11-13 A. M. Mathai , H. J. Haubold

Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. However, for the effective separation of time series, new entropy…

Machine Learning · Computer Science 2023-05-19 Andrei Velichko , Maksim Belyaev , Yuriy Izotov , Murugappan Murugappan , Hanif Heidari

Stock market is often important as it represents the ownership claims on businesses. Without sufficient stocks, a company cannot perform well in finance. Predicting a stock market performance of a company is nearly hard because every time…

Statistical Finance · Quantitative Finance 2023-05-25 Aadhitya A , Rajapriya R , Vineetha R S , Anurag M Bagde

The main goal of this paper is an application of Bayesian inference in testing the relation between risk and return on the financial instruments. On the basis of the Intertemporal CAPM model we built a general sampling model suitable in…

Applications · Statistics 2008-10-06 Mateusz Pipien

Natural and social multivariate systems are commonly studied through sets of simultaneous and time-spaced measurements of the observables that drive their dynamics, i.e., through sets of time series. Typically, this is done via hypothesis…

Statistical Finance · Quantitative Finance 2020-07-01 Riccardo Marcaccioli , Giacomo Livan

Turnpike theorems state that if an investor's utility is asymptotically equivalent to a power utility, then the optimal investment strategy converges to the CRRA strategy as the investment horizon tends to infinity. This paper aims to…

Portfolio Management · Quantitative Finance 2025-12-02 Hiroki Yamamichi

We obtain the maximum entropy distribution for an asset from call and digital option prices. A rigorous mathematical proof of its existence and exponential form is given, which can also be applied to legitimise a formal derivation by Buchen…

Pricing of Securities · Quantitative Finance 2011-02-03 C. Neri , L. Schneider

Predicting trends in stock market prices has been an area of interest for researchers for many years due to its complex and dynamic nature. Intrinsic volatility in stock market across the globe makes the task of prediction challenging.…

Machine Learning · Computer Science 2016-05-03 Luckyson Khaidem , Snehanshu Saha , Sudeepa Roy Dey