Kenya Nairobi Securities Exchange (NSE) All Stocks Prices 2023-2024

Published: 18 November 2024| Version 1 | DOI: 10.17632/ss5pfw8xnk.1
Contributor:
Barack Wanjawa

Description

This compilation of historical daily stock market price data relates to the Kenyan Nairobi Securities Exchange (NSE) for full year 2023 and 2024 (Jan-Oct). This data is valuable for any machine learning algorithm that needs data (training, validation, testing). This compilation develops on an earlier dataset (2008-2012) that was initially compiled as part of a research project to predict next day stock price, based on the previous five days, using Artificial Neural Networks (ANN). This initial research [1],[2] tested 6 stocks [3] using ANN of configuration 5:21:21:1. The data was then enhanced as a new compilation of all stocks for the period 2007-2012 [4]. This new dataset augments the NSE dataset for 2007-2012 [4], 2013 to 2020 [5], 2021 [6] and 2022 [7]. The data was scrapping from a publicly accessible website [8] licensed by NSE by exporting raw web data to spreadsheets, then cleaning it up to final CSV. Just like the previous compilations, each stock data row has 13 data columns (1)Date (2)Stock Code (3)Stock Name (4)12-month Low price (5)12-month High price (6)Day's Low price (7)Day's High price (8)Day's Final Price (9)Previous traded price (10)Change in price value (11)Change in price % (12)Volume traded (13)Adjusted price. One additional CSV file is also provided to show the stocks market sector, with 3 columns as: (1)Market sector (2)Stock Code (3)Stock Name. This additional dataset provides researchers with an even larger dataset (2007-2024) of stocks market data including market sector information for bigger opportunities of data analysis and usage in machine learning research. List of data files on this dataset: NSE_data_all_stocks_2023.csv NSE_data_all_stocks_2024_jan_to_oct.csv NSE_data_stock_market_sectors_2023_2024.csv References: [1] Wanjawa, B. W. (2014). A Neural Network Model for Predicting Stock Market Prices at the Nairobi Securities Exchange (Dissertation, University of Nairobi). [2] Wanjawa, B. W., & Muchemi, L. (2014). ANN model to predict stock prices at stock exchange markets. arXiv preprint arXiv:1502.06434. [3] Wanjawa, Barack (2020), “Nairobi Securities Exchange Prices 2008-2012 for 6 selected stocks”, Mendeley Data, v3, http://dx.doi.org/10.17632/95fb84nzcd.3 [4] Wanjawa, Barack (2020), “Nairobi Securities Exchange All Stocks Prices 2007-2012”, Mendeley Data, v1, http://dx.doi.org/10.17632/5hk4zw32f5.1 [5] Wanjawa, Barack (2021), “Nairobi Securities Exchange (NSE) All Stocks Prices 2013-2020”, Mendeley Data, V2, doi: 10.17632/73rb78pmzw.2 [6] Wanjawa, Barack (2022), “Nairobi Securities Exchange (NSE) Kenya - All Stocks Prices 2021”, Mendeley Data, V5, doi: 10.17632/97hkwn5y3x.5 [7] Wanjawa, Barack (2024), “Kenya Nairobi Securities Exchange (NSE) All Stocks Prices 2022”, Mendeley Data, V2, doi: 10.17632/jmcdmnyh2s.2 [8] Synergy Systems Ltd. (2023). MyStocks. Retrieved Jan 31, 2023, from http://live.mystocks.co.ke/

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Artificial Neural Network, Financial Market, Machine Learning, Stock Exchange, Deep Learning

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