Nairobi Securities Exchange All Stocks Prices 2007-2012

Published: 21 March 2020| Version 1 | DOI: 10.17632/5hk4zw32f5.1
Barack Wanjawa


Nairobi Securities Exchange All Stocks Prices 2007-2012 This historical data is valuable for machine learning algorithms that need data for training and testing. It was initially compiled as part of a project to apply Artificial Neural Networks (ANN) for next day stock price prediction, based on the prices of the previous five days. Use of ANN was to contrast to prevalent methods of stock market prediction such as technical, fundamental or time series analysis. This data was used for an initial research [1],[2] that tested an ANN for stock market prediction. This ANN model was of configuration - feedforward multi-layer perceptron (MLP) with error backpropagation, using sigmoid activation function, with network configuration 5:21:21:1. The data used in the research was for the 5-year period (2008 to 2012), with 80% of the data (4-year data) used for training and the balance 20% used for testing (last 1-year data). However, the full data that had been compiled, as presented here is the 6-year data for period 2007 to 2012. This 2007 to 2012 data for the Nairobi Securities Exchange (NSE) was scrapped from a public website that publishes daily stock prices and archives historical data [3]. The raw data was first exported to a spreadsheet then headers, footers and other unnecessary elements were removed. This data consists of daily stock prices for over 60 different stocks and market indices over a 12-month period in each year, for a total of 6-years. Each data row has the following 13 data columns (1) Date of trade (2) Code of the stock (3) Name of the stock (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 by value (11) Change in price by % (12) Volume traded (13) Adjusted price, if any. The original data also had a column on the price direction, being an arrow graphic, showing Up, Down or Unchanged. This column was discarded from this final compilation. While the initial research only tested prediction based on adjusted final price for six stocks, the publishing of the full data now gives other researchers the opportunity to test any other of the more than 60 stocks and test any other hypothesis on this full data set. This data can also be used to reproduce and validate the initial research findings as already published. List of data files on this dataset: NSE_data_all_stocks_2007.csv NSE_data_all_stocks_2008.csv NSE_data_all_stocks_2009.csv NSE_data_all_stocks_2010.csv NSE_data_all_stocks_2011.csv NSE_data_all_stocks_2012.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] Synergy Systems Ltd. (2020). MyStocks. Retrieved March 9, 2020, from



Artificial Neural Networks, Machine Learning, Stock Exchange, Stock Assessment, Stock Price