A Survey on Stock Market Prediction Using Machine Learning Techniques

Rao, P.Subba; Srinivas, Kudipudi; Mohan, A. Krishna

doi:10.1007/978-981-15-1420-3_101

Cited by 27 publications

(14 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Equation ( 15) contains three terms including the absorbed energy, reflected energy, and transmitted energy. Equation (16) shows the energy absorbed by the product [33].…”

Section: Energy Efficiency and Energy Lossmentioning

confidence: 99%

“…The choice of the hybrid is motivated by the amalgamation having mathematical recompenses, emphasized elsewhere [14,15]. The ANFIS is a governing data-driven and adaptive computational means having the fitness of plotting non-linear and multifaceted data [16]. Conversely, the constraint of ANN is its black box which flops to relation input parameters with the response.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms

et al. 2021

View full text Add to dashboard Cite

The study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of cantaloupe drying using various afore-mentioned input parameters. The results indicated that a rise in microwave power and a decline in sample thickness can significantly decrease the specific energy consumption (SEC), energy loss, exergy loss, and improvement potential (probability level of 5%). The mean SEC, energy efficiency, energy loss, thermal efficiency, dryer efficiency, exergy efficiency, exergy loss, improvement potential, and sustainability index ranged in 10.48–25.92 MJ/kg water, 16.11–47.24%, 2.65–11.24 MJ/kg water, 7.02–36.46%, 12.36–42.70%, 11.25–38.89%, 3–12.2 MJ/kg water, 1.88–10.83 MJ/kg water, and 1.12–1.63, respectively. Based on the results, the use of higher microwave powers for drying thinner samples can improve the thermodynamic performance of the process. The ANFIS model offers a more accurate forecast of energy and exergy indices of cantaloupe drying compare to ANN model.

show abstract

“…Equation ( 15) contains three terms including the absorbed energy, reflected energy, and transmitted energy. Equation (16) shows the energy absorbed by the product [33].…”

Section: Energy Efficiency and Energy Lossmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms

et al. 2021

View full text Add to dashboard Cite

show abstract

“…This research chose data from these three periods for our analysis because this study intended to investigate the effects of short-term, medium-term, and long-term historical data of stock price movements on the efficacy or otherwise of predictive models of stock prices using the GBM Monte Carlo simulation method. Prior research has found seasonality to influence Indian stocks (Rao et al 2020). However, seasonality shows a pattern in the movement of shares, providing a weak form of efficiency for stock markets.…”

Section: Review Of Literature and Hypotheses Developmentmentioning

confidence: 99%

“…Scholars have also used various regression methods in stock price prediction, among which the scholars have found isotonic regression to be more efficient than other regression techniques such as linear regression and least mean squares regression (Chandar 2019). Besides, the machine learning algorithms predict the prices of stocks traded in the Indian stock market with 70 percent accuracy of daily prices, whereas the monthly data of prices do not show any correlation (Rao et al 2020). However, the critical challenge before researchers in using these methods is to account for certain and uncertain components of the movement of stock prices.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Geometric Brownian Motion Method in Predicting Stock Prices: Evidence From India

2022

AJAG

View full text Add to dashboard Cite

This research examines whether stock prices in the Indian stock markets follow a Geometric Brownian Motion (GBM).This study is keen on knowing if one can predict the simulated stock prices accurately against the actual stock prices. One-year, three-year, and five-year data of the historical stock prices of 50 stocks listed on the S&P BSE (Bombay Stock Exchange) Sensex 50 Index were employed as the base data to predict stock prices using the Monte Carlo simulation's GBM method. This study investigates whether there are statistically significant differences between the actual stock prices for three months and the simulated prices of the same period. This research has found that the GBM Monte Carlo simulation effectively predicts future stock prices for three months based on the historical data of stock prices of the past year. This study did not find significant differences between the actual and predicted stock prices when the simulation used the past one year's data. This research is original in the Indian context, as it situates the GBM method of Monte Carlo simulation in the premise of bounded rationality and efficient market hypothesis theories. There is thus the empirical evidence for bounded rationality and that the stock markets are not efficient.

show abstract

“…Since the efficient market hypothesis is not proved, more elaborate techniques have been used trying to exploit the market inefficiencies. Among these techniques, in the literature can be found applications with linear models [16], support vector machines [17], genetic algorithms [18] or more frequently neural networks [19]- [21] and deep learning methods [22]- [24] (for a recent survey on this topic see [25] or [26] for a more general survey).…”

Section: Introductionmentioning

confidence: 99%