Geometric brownian motion: an alternative to high-frequency trading for small investors
Autor: | Aline Cristina Rodrigues de Faria, Davi Franco Moreira, Eder Oliveira Abensur |
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Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
Geometric Brownian motion
050208 finance 021103 operations research business.industry financial engineering Risk measure 05 social sciences high-frequency trading 0211 other engineering and technologies algorithmic trading 02 engineering and technology Market liquidity Financial management statistical inference 0502 economics and business Econometrics Stock market Business High-frequency trading Stock (geology) Statistical hypothesis testing |
Zdroj: | Independent Journal of Management & Production; Vol. 11 No. 3 (2020): Independent Journal of Management & Production; 1434-1453 Independent Journal of Management & Production Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP) instacron:IJM&P Independent Journal of Management & Production; Vol 11, No 3 (2020): Independent Journal of Management & Production; 1434-1453 |
ISSN: | 2236-269X |
Popis: | High-frequency trading (HFT) involves short-term, high-volume market operations to capture profits. To a large extent, these operations take advantage of early access to information using fast and sophisticated technological tools running on supercomputers. However, high-frequency trading is inaccessible to small investors because of its high cost. For this reason, price prediction models can substitute high-frequency trading in order to anticipate stock market movements. This study is the first to analyze the possibility of applying Geometric Brownian Motion (GBM) to forecast prices in intraday trading of stocks negotiated on two different stock markets: (i) the Brazilian stock market (B3), considered as a low liquidity market and (ii) the American stock market (NYSE), a high liquidity market. This work proposed an accessible framework that can be used for small investors. The portfolios formed by Geometric Brownian Motion were tested using a traditional risk measure (mean-variance). The hypothesis tests showed evidences of promising results for financial management. |
Databáze: | OpenAIRE |
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