Random Walk Algorithms: Definitions, Weaknesses, and Learning Automata-Based Approach

Saghiri, Ali Mohammad; Khomami, M. Daliri; Meybodi, Mohammad Reza

doi:10.1007/978-3-030-10883-0_1

Cited by 2 publications

(1 citation statement)

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“…Although the theory of random-walk processes is continuously acceptable, the theory has started to be criticized. The weakness of random walk algorithms is stated by (Saghiri et al 2019). The non-intelligent random walk models may not be a problem-solving method in real-world problems since some complex systems such as biological networks or social networks work as a "learning mechanism".…”

Section: The Origin Of Quantum Distributionsmentioning

confidence: 99%

Applying Quantum Mechanics for Extreme Value Prediction of VaR and ES in the ASEAN Stock Exchange

Chaiboonsri

Wannapan

2021

Economies

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The advantage of quantum mechanics to shift up the ability to econometrically understand extreme tail losses in financial data has become more desirable, especially in cases of Value at Risk (VaR) and Expected Shortfall (ES) predictions. Behind the non-novel quantum mechanism, it does interestingly connect with the distributional signals of humans’ brainstorms. The highlighted purpose of this article is to devise a quantum-wave distribution methodically to analyze better risks and returns for stock markets in The Association of Southeast Asian Nations (ASEAN) countries, including Thailand (SET), Singapore (STI), Malaysia (FTSE), Philippines (PSEI), and Indonesia (PCI). Data samples were observed as quarterly trends between 1994 and 2019. Bayesian statistics and simulations were applied to present estimations’ outputs. Empirically, quantum distributions are remarkable for providing “real distributions”, which computationally conform to Bayesian inferences and crucially contribute to the higher level of extreme data analyses in financial economics.

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Section: The Origin Of Quantum Distributionsmentioning

confidence: 99%