Machine Learning Based Stock Market Analysis: A Short Survey

Vachhani, Hrishikesh; Obiadat, Mohammad S.; Thakkar, Arkesh; Shah, Vyom; Sojitra, Raj; Bhatia, Jitendra; Tanwar, Sudeep

doi:10.1007/978-3-030-38040-3_2

Cited by 29 publications

(9 citation statements)

References 35 publications

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“…3.2.4 Artificial neural networks technique. Stock market behavior is regarded to be wholly random and substantially nonlinear, according to Vachhani et al (2020). The ANN's capacity to retain specific data for subsequent use makes it the most efficient way for enhancing the ability to analyze the complex structure between interconnections of stock price data.…”

Section: Jm2 193mentioning

confidence: 99%

Predicting daily precision improvement of Jakarta Islamic Index in Indonesia’s Islamic stock market using big data mining

Ledhem,

Moussaoui

2023

JM2

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Purpose This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market. Design/methodology/approach This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared. Findings The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique. Practical implications This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility. Originality/value This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

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Section: Jm2 193mentioning

confidence: 99%

Predicting daily precision improvement of Jakarta Islamic Index in Indonesia’s Islamic stock market using big data mining

Ledhem,

Moussaoui

2023

JM2

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“…Deep Learning algorithms were focused on by the authors of [21] for the same application. e author of [22] did the analysis of the financial market prediction with an ML algorithm. In [23], the author conducted a detailed survey about the optimization algorithm with different parameters and concluded with results and discussion.…”

Section: Related Studiesmentioning

confidence: 99%

Optimization of Virtual Network Mapping Based on Improved Ant Colony Algorithm in Complex Network Environments

Zhang

Sheng²

2022

Scientific Programming

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Financial marketing is a method of risky investment, but in a shorter duration, the individual can expect a profit or loss, depending on the current market rate for the organization. Though it has a higher risk of getting a profit, many individuals are ready to take a chance to benefit. In the current era, much research is going on to provide a better prediction rate. Most researchers prefer Ant Colony Optimization (ACO) as a more trustworthy optimization algorithm among the existing optimization algorithms. In this research work, a novel optimization algorithm is proposed; it is a hybrid algorithm with Ant Colony Optimization (ACO) and financial marketing crisis prediction (FMCP) and is termed ACO-FMCP. This hybrid algorithm was applied to the economic sanctions dataset, and the results were generated. The results were compared with ACO and FMCP algorithms and it was found that the hybrid ACO-FMCP shows improved performance than the other two algorithms.

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“…They are long-term (buy and hold) when executed after many months, years, or even decades (rare). Generally, day trade and swing trade are linked to technical analysis and buy and hold are linked to fundamental analysis [Vachhani et al 2019].…”

Section: Introductionmentioning

confidence: 99%

BovDB: a data set of stock prices of all companies in B3 from 1995 to 2020

Cardoso

Malska

Ramiro

et al. 2022

jidm

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Stock markets are responsible for the movement of vast amounts of financial resources worldwide. This market generates a high volume of transaction data, which after being analyzed are very useful for many applications. In this article, we present BovDB, a data set that was built considering a source of the Brazilian Stock Exchange (B3) with information related to the years between 1995 and 2020. We have approached the events’ impact on the stocks byapplying a cumulative factor to correct prices. The results were compared with public data from InfoMoney and BR Investing, showing that our methods, are valid and follow the market standards, based on the proposed factor. BovDBdata set can be used as a benchmark for different applications and it is available in open access for any researcher on GitHub.

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Machine Learning Based Stock Market Analysis: A Short Survey

Cited by 29 publications

References 35 publications

Predicting daily precision improvement of Jakarta Islamic Index in Indonesia’s Islamic stock market using big data mining

Predicting daily precision improvement of Jakarta Islamic Index in Indonesia’s Islamic stock market using big data mining

Optimization of Virtual Network Mapping Based on Improved Ant Colony Algorithm in Complex Network Environments

BovDB: a data set of stock prices of all companies in B3 from 1995 to 2020

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