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Holt-Winters Algorithm to Predict the Stock Value Using Recurrent Neural Network

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Intelligent Automation & Soft Computing 2023年第1期35卷 1151-1163页

作者： M.Mohan P.C.Kishore Raja P.Velmurugan A.Kulothungan Department of Computer Science&Engineering SRM UniversitySonepatHaryanaIndia Department of Electronics&Communication Engineering SRM UniversitySonepatHaryanaIndia Department of Computing Technologies SRM Institute of Science and TechnologyChennaiIndia Department of Computer Science&Engineering SRM Institute of Science and TechnologyModinagarGhaziabadIndia

Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of *** proposed model uses a real time dataset offifteen Stocks as input into the system and based on the data,predicts or forecast future stock prices of different companies belonging to different *** dataset includes approximatelyfifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular company or not;the forecasting is done for the next *** model uses 3 main concepts for forecasting *** one is for stocks that show periodic change throughout the season,the‘Holt-Winters Triple Exponential Smoothing’.3 basic things taken into conclusion by this algorithm are Base Level,Trend Level and Seasoning *** value of all these are calculated by us and then decomposition of all these factors is done by the Holt-Winters *** second concept is‘Recurrent Neural Network’.The specific model of recurrent neural network that is being used is Long-Short Term Memory and it’s the same as the Normal Neural Network,the only difference is that each intermediate cell is a memory cell and retails its value till the next feedback *** third concept is Recommendation System whichfilters and predict the rating based on the different factors.

关键词： Stock market stock market prediction time series forecasting efficient market hypothesis National stock exchange India smoothing observation trend level seasonal factor

S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

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Financial Innovation 2020年第1期6卷 793-811页

作者： Madhavi Latha Challa Venkataramanaiah Malepati Siva Nageswara Rao Kolusu Department of CSE CMR College of Engineering&TechnologyHyderabadIndia Department of Commerce SG Govt.Degree&PG CollegePilerAndhra PradeshIndia Department of Management Studies Vignan Foundation for ScienceTechnology&ResearchGunturAndhra PradeshIndia

This study forecasts the return and volatility dynamics of S&P BSE Sensex and S&P BSE IT indices of the Bombay Stock *** achieve the objectives,the study uses descriptive statistics;tests including variance ratio,Augmented Dickey-Fuller,Phillips-Perron,and Kwiatkowski Phillips Schmidt and Shin;and Autoregressive Integrated Moving Average(ARIMA).The analysis forecasts daily stock returns for the S&P BSE Sensex and S&P BSE IT time series,using the ARIMA *** results reveal that the mean returns of both indices are positive but near *** is indicative of a regressive tendency in the *** forecasted values of S&P BSE Sensex and S&P BSE IT are almost equal to their actual values,with few ***,the ARIMA model is capable of predicting medium-or long-term horizons using historical values of S&P BSE Sensex and S&P BSE IT.

关键词： efficient market hypothesis Bombay stock exchange ARIMA KPSS S&P BSE Sensex Forecasting S&P BSE IT

Carbon trading thickness and market efficiency in a socialist market economy

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Chinese Journal of Population,Resources and Environment 2018年第2期16卷 109-119页

作者： Qian Wang Sitong Wu School of Economics Jilin University

Unlike the European Union emission trade system(EU ETS), China s pilot ETSs implemented diversified policy designs instead of using a uniform framework. Variance ratio test is used to evaluate the efficient market hypothesis(EMH) in China's carbon trading markets. The results of two versions of variance ratio tests indicate that the carbon trading market in Hubei is considered weak form efficient, and the socialist market economy does not necessarily lead to market inefficiency in carbon trading markets. Thin trading activities generate market frictions and bias the efficient market hypothesis(EMH) tests.

关键词： Emission trade system efficient market hypothesis market efficiency

Nonlinearity in Stock Exchange markets: The Case of Bist 100 Indices

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Chinese Business Review 2021年第1期20卷 15-21页

作者： Jamilu Said Babangida Department of Economics Ahmadu Bello UniversityNigeria Department of International Finance Istanbul Commerce UniversityTurkey Department of Economics Ibn Haldun UniversityTurkey

In this paper,using data for the Bist 100 index,we investigate the presence of nonlinearities by employing several nonlinearity *** Brock,Dechert,and Scheinkman(BDS)and runs tests were first applied to the series to show an initial indication of *** findings for the BDS and runs test of randomness were followed by other sets of direct nonlinearity tests developed by White(1989),Terasvirta(1993),Keenan(1985),and Tsay(1986).Also,the Threshold Autoregression(TAR)test is employed as a final test to confirm the existence of nonlinearity in the Turkish stock exchange *** the results of the nonlinearity test,it is concluded that the Bist 100 index is characterised by the presence of nonlinearities and *** finding is in contrast with the efficient market hypothesis(EMH)implying that the Turkish stock exchange market is inefficient.

关键词： stock market nonlinearity efficient market hypothesis Bist 100 index