JSE reported ZAR5.11 in EPS Earnings Per Share for its fiscal semester ending in December of 2024. Data for JSE - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last August in 2025.

JSE reported 12.05 in PE Price to Earnings for its fiscal semester ending in June of 2024. Data for JSE - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last August in 2025.

South Africa PE Ratio: FTSE/JSE: Financials data was reported at 14.392 NA in Jun 2018. This records a decrease from the previous number of 15.888 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Financials data is updated monthly, averaging 12.715 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 16.144 NA in Dec 2017 and a record low of 9.325 NA in Feb 2016. South Africa PE Ratio: FTSE/JSE: Financials data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Shareholder Weighted Top 40 data was reported at 12.484 NA in Jun 2018. This records a decrease from the previous number of 16.687 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Shareholder Weighted Top 40 data is updated monthly, averaging 19.678 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 23.724 NA in May 2017 and a record low of 12.484 NA in Jun 2018. South Africa PE Ratio: FTSE/JSE: Shareholder Weighted Top 40 data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

PE Ratio: FTSE/JSE: Mid Cap data was reported at 20.608 NA in Jun 2018. This records a decrease from the previous number of 22.774 NA for May 2018. PE Ratio: FTSE/JSE: Mid Cap data is updated monthly, averaging 17.816 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 36.529 NA in Jul 2016 and a record low of 7.027 NA in Nov 2016. PE Ratio: FTSE/JSE: Mid Cap data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Telecommunication data was reported at 16.690 NA in Jun 2018. This records a decrease from the previous number of 18.961 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Telecommunication data is updated monthly, averaging 14.639 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 36.254 NA in May 2017 and a record low of 7.780 NA in Feb 2016. South Africa PE Ratio: FTSE/JSE: Telecommunication data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Electronic and Electrical Equipment data was reported at 11.684 NA in Nov 2018. This records a decrease from the previous number of 12.903 NA for Oct 2018. South Africa PE Ratio: FTSE/JSE: Electronic and Electrical Equipment data is updated monthly, averaging 12.299 NA from Apr 2013 (Median) to Nov 2018, with 68 observations. The data reached an all-time high of 23.079 NA in May 2014 and a record low of -99.000 NA in Nov 2013. South Africa PE Ratio: FTSE/JSE: Electronic and Electrical Equipment data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Software and Computer Services data was reported at 26.590 NA in Jun 2018. This records a decrease from the previous number of 32.043 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Software and Computer Services data is updated monthly, averaging 16.690 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 32.043 NA in May 2018 and a record low of 8.307 NA in Apr 2018. South Africa PE Ratio: FTSE/JSE: Software and Computer Services data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Small Cap data was reported at 99.000 NA in Jun 2018. This stayed constant from the previous number of 99.000 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Small Cap data is updated monthly, averaging 15.785 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 99.000 NA in Jun 2018 and a record low of -30.975 NA in Apr 2016. South Africa PE Ratio: FTSE/JSE: Small Cap data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

JSE reported ZAR425.06M in Net Income for its fiscal semester ending in December of 2024. Data for JSE - Net Income including historical, tables and charts were last updated by Trading Economics this last August in 2025.

South Africa PE Ratio: FTSE/JSE: Industrial Transportation data was reported at 17.486 NA in Jun 2018. This records a decrease from the previous number of 18.812 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Industrial Transportation data is updated monthly, averaging 13.473 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 72.535 NA in Jan 2018 and a record low of 8.408 NA in Jan 2016. South Africa PE Ratio: FTSE/JSE: Industrial Transportation data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Food Producers data was reported at 21.341 NA in Jun 2018. This records an increase from the previous number of 20.323 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Food Producers data is updated monthly, averaging 22.001 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 27.977 NA in Nov 2014 and a record low of 17.012 NA in Feb 2014. South Africa PE Ratio: FTSE/JSE: Food Producers data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

JSE stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

South Africa PE Ratio: FTSE/JSE: Industrials data was reported at 13.002 NA in Nov 2018. This records a decrease from the previous number of 13.975 NA for Oct 2018. South Africa PE Ratio: FTSE/JSE: Industrials data is updated monthly, averaging 15.267 NA from Apr 2013 (Median) to Nov 2018, with 68 observations. The data reached an all-time high of 19.820 NA in Jan 2018 and a record low of 3.131 NA in Aug 2016. South Africa PE Ratio: FTSE/JSE: Industrials data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

South Africa PE Ratio: FTSE/JSE: Technology data was reported at 26.590 NA in Jun 2018. This records a decrease from the previous number of 32.043 NA for May 2018. South Africa PE Ratio: FTSE/JSE: Technology data is updated monthly, averaging 16.121 NA from Apr 2013 (Median) to Jun 2018, with 63 observations. The data reached an all-time high of 32.043 NA in May 2018 and a record low of 8.307 NA in Apr 2018. South Africa PE Ratio: FTSE/JSE: Technology data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

JSE reported ZAR533.35M in EBITDA for its fiscal semester ending in December of 2024. Data for JSE - Ebitda including historical, tables and charts were last updated by Trading Economics this last August in 2025.

South Africa PE Ratio: FTSE/JSE: Pharmaceuticals and Biotech data was reported at 10.824 NA in Oct 2018. This records a decrease from the previous number of 11.936 NA for Sep 2018. South Africa PE Ratio: FTSE/JSE: Pharmaceuticals and Biotech data is updated monthly, averaging 28.532 NA from Apr 2013 (Median) to Oct 2018, with 67 observations. The data reached an all-time high of 51.100 NA in Oct 2014 and a record low of 10.824 NA in Oct 2018. South Africa PE Ratio: FTSE/JSE: Pharmaceuticals and Biotech data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

JSE reported 6.49 in Dividend Yield for its fiscal semester ending in December of 2024. Data for JSE - Dividend Yield including historical, tables and charts were last updated by Trading Economics this last August in 2025.

South Africa PE Ratio: FTSE/JSE: Africa Real Estate Investment and Services data was reported at -89.733 NA in Oct 2018. This records an increase from the previous number of -90.829 NA for Sep 2018. South Africa PE Ratio: FTSE/JSE: Africa Real Estate Investment and Services data is updated monthly, averaging 14.003 NA from Apr 2013 (Median) to Oct 2018, with 67 observations. The data reached an all-time high of 29.507 NA in Jul 2017 and a record low of -99.000 NA in Feb 2018. South Africa PE Ratio: FTSE/JSE: Africa Real Estate Investment and Services data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z006: Johannesburg Stock Exchange: Price Earnings Ratio.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Jadestone Energy (JSE) : Navigating the choppy waters of oil and gas

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data