Markov Chains for High Frequency Stock Trading Strategies
Tipo
Artigo de evento
Data de publicação
2022
Periódico
Lecture Notes in Networks and Systems
Citações (Scopus)
0
Autores
Alminana C.C.
Orientador
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The price prediction problem for any given stock has been an object of study, deepening and evolution within the past few decades, to achieve the basic goal of positive financial realizations with the smaller risk possible. A known risk minimization strategy is a high frequency trading regime, taking benefit from minor price variations, and achieving small profits multiple times a day. By the hypothesis and the interpretation that prices variations behavior as a Random Walk, it is possible to characterize a Markov (stochastic) process with states and transition probabilities known, allowing to describe price variations through time. Therefore, this study aims to estimate the financial outcome using Markov chains for automated decision making in a high frequency stock trading strategy, and then comparing the computed results with stock’s valuation (or devaluation) within the same analyzed period.