The price to earnings ratio is a measurement often used to determine stock valuation. In short P/E is used to measure what the market is willing to pay for a company based on its earnings. The trailing P/E for consumer goods & FMCG companies operating in the food processing industries were higher than in other industries as of January 2025. Another formula that is used by investors to measure the value of an industry or potential target company for acquisition is the enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA).

The price to earnings ratio is a measurement often used to determine stock valuation. In short, P/E is used to measure what the market is willing to pay for a company based on its earnings. The forward P/E for retail & trade companies operating in the general retail market was approximately *****. This meant that, according to projections, an investor will be willing to pay ***** dollars (or currency used) for every one dollar made through the companies earnings. Another formula that is used by investors to measure the value of an industry or potential target company for acquisition is the enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA).

Bursa Malaysia: PE Ratio: Industrial Index data was reported at 16.460 Unit in Sep 2018. This records an increase from the previous number of 16.410 Unit for Aug 2018. Bursa Malaysia: PE Ratio: Industrial Index data is updated monthly, averaging 20.610 Unit from Feb 1989 (Median) to Sep 2018, with 349 observations. The data reached an all-time high of 58.290 Unit in Jan 2000 and a record low of -320.570 Unit in Jan 1999. Bursa Malaysia: PE Ratio: Industrial Index data remains active status in CEIC and is reported by Bursa Malaysia. The data is categorized under Global Database’s Malaysia – Table MY.Z008: Bursa Malaysia: Price Earnings Ratio.

The statistic depicts the average p/e (price-to-earnings) ratios in U.S. big pharma and big biotech in 2005 and 2010. In 2005, the average p/e ratio in the U.S. biotech sector was **.

China PE Ratio: Shanghai SE: Information and Technology data was reported at 35.390 NA in Mar 2025. This stayed constant from the previous number of 35.390 NA for Feb 2025. China PE Ratio: Shanghai SE: Information and Technology data is updated monthly, averaging 42.200 NA from Apr 2001 (Median) to Mar 2025, with 287 observations. The data reached an all-time high of 110.338 NA in May 2015 and a record low of 13.270 NA in Aug 2009. China PE Ratio: Shanghai SE: Information and Technology data remains active status in CEIC and is reported by Shanghai Stock Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZA: Shanghai Stock Exchange: PE Ratio.

Key information about Nigeria P/E ratio

• Nigeria Weighted Equities recorded a yearly P/E ratio of 107.985 on 2024, compared with 20.073 from the previous year.
• Nigeria Weighted Equities P/E ratio is updated yearly, with historical data available from Dec 2014 to Dec 2021.
• The P/E ratio reached an all-time high of 107.985 in Dec 2021 and a record low of 17.140 in Dec 2015.
• CEIC calculates annual P/E Ratio from quarterly P/E Ratio based on the average of the quarter. Nigerian Exchange Group provides P/E Ratio. Nigerian Exchange Group does not provide quarter end data; thus quarter average is used instead.

Amazon PE ratio as of June 17, 2025 is 30.55. Current and historical p/e ratio for Amazon (AMZN) from 2010 to 2025. The price to earnings ratio is calculated by taking the latest closing price and dividing it by the most recent earnings per share (EPS) number. The PE ratio is a simple way to assess whether a stock is over or under valued and is the most widely used valuation measure. Please refer to the Stock Price Adjustment Guide for more information on our historical prices.

The price to earnings ratio is a measurement often used to determine stock valuation. In short, P/E is used to measure what the market is willing to pay for a company based on its earnings. The trailing P/E for healthcare product companies operating in the health and pharmaceuticals market was approximately *****. This meant that an investor would be willing to pay ***** dollars for every one dollar made through earnings. Another formula that is used by investors to measure the value of an industry or potential target company for acquisition is the enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA).

NIKE PE ratio as of June 14, 2025 is 18.40. Current and historical p/e ratio for NIKE (NKE) from 2010 to 2025. The price to earnings ratio is calculated by taking the latest closing price and dividing it by the most recent earnings per share (EPS) number. The PE ratio is a simple way to assess whether a stock is over or under valued and is the most widely used valuation measure. Please refer to the Stock Price Adjustment Guide for more information on our historical prices.

Key information about Sri Lanka P/E ratio

• Sri Lanka All Shares recorded a daily P/E ratio of 8.300 on 24 Mar 2025, compared with 8.210 from the previous day.
• Sri Lanka All Shares P/E ratio is updated daily, with historical data available from Aug 1998 to Mar 2025.
• The P/E ratio reached an all-time high of 29.530 in Feb 2011 and a record low of 4.520 in Nov 2022.
• Colombo Stock Exchange provides daily P/E Ratio.

The price to earnings ratio is a measurement often used to determine stock valuation. In short, P/E is used to measure what the market is willing to pay for a company based on its earnings. The trailing P/E for green & renewable energy companies operating in the environmental and waste services market was approximately ****. This meant in theory that investors would be willing to pay just over **** (dollars or currency used) for every one (dollar) the company made through earnings.Another formula that is used by investors to measure the value of an industry or potential target company for acquisition is the enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA).

North American public software companies have higher price-to-earnings (PE) ratios in comparison to their European and APAC counterparts, signifying investors' willingness to pay more for their stocks for future earnings. In 2020, the PE ratio of North American listed software companies stood at 51.

The PE ratios are based on aggregated annual reports and recent data from listed companies. A more detailed methodic description can be found in the report Global software industry: financial insight.

Hong Kong PE Ratio: Hang Seng Index: Properties Sector data was reported at 5.800 Unit in Nov 2018. This records an increase from the previous number of 5.330 Unit for Oct 2018. Hong Kong PE Ratio: Hang Seng Index: Properties Sector data is updated monthly, averaging 11.275 Unit from Jan 1986 (Median) to Nov 2018, with 395 observations. The data reached an all-time high of 24.871 Unit in Feb 2004 and a record low of 4.080 Unit in Aug 1998. Hong Kong PE Ratio: Hang Seng Index: Properties Sector data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited. The data is categorized under Global Database’s Hong Kong SAR – Table HK.Z003: Main Board: PE Ratio.

Bursa Malaysia: PE Ratio: Industrial Products Index data was reported at 28.440 Unit in Nov 2018. This records a decrease from the previous number of 28.690 Unit for Oct 2018. Bursa Malaysia: PE Ratio: Industrial Products Index data is updated monthly, averaging 23.640 Unit from Sep 1993 (Median) to Nov 2018, with 275 observations. The data reached an all-time high of 272.750 Unit in Sep 2001 and a record low of 5.520 Unit in Jan 2009. Bursa Malaysia: PE Ratio: Industrial Products Index data remains active status in CEIC and is reported by Bursa Malaysia. The data is categorized under Global Database’s Malaysia – Table MY.Z008: Bursa Malaysia: 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.

The Dow Jones Industrial Average

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

The price to earnings ratio is a measurement often used to determine stock valuation. In short, P/E is used to measure what the market is willing to pay for a company based on its earnings. The trailing P/E for building supply companies in the construction sector was approximately ****. This meant in theory that investors would be willing to pay **** (dollars or currency used) for every one (dollar or currency used) the company made through earnings.Another formula that is used by investors to measure the value of an industry or potential target company for acquisition is the enterprise value to earnings before interest, taxes, depreciation and amortization (EV/EBITDA).

PPG Industries current p/s ratio as of June 27, 2025 is 1.69. PPG Industries average p/s ratio for 2024 was 1.93, a 3.5% decline from 2023. PPG Industries average p/s ratio for 2023 was 2, a 25% decline from 2022. PPG Industries average p/s ratio for 2022 was 1.6, a 28.25% increase from 2021. P/s ratio can be defined as the price to sales or PS ratio is calculated by taking the latest closing price and dividing it by the most recent sales per share number. The PS ratio is an additional way to assess whether a stock is over or under valued and is used primarily in cases where earnings are negative and the PE ratio cannot be utilized.

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.

Will the Dow Jones Industrial Average Index Maintain Its Momentum?

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

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.

Dow Jones Industrial Average Index Target Price Prediction

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

CF Industries Holdings current p/s ratio as of June 27, 2025 is 2.62. CF Industries Holdings average p/s ratio for 2024 was 2.52, a 39.23% increase from 2023. CF Industries Holdings average p/s ratio for 2023 was 1.81, a 1.09% increase from 2022. CF Industries Holdings average p/s ratio for 2022 was 1.83, a 15.67% decline from 2021. P/s ratio can be defined as the price to sales or PS ratio is calculated by taking the latest closing price and dividing it by the most recent sales per share number. The PS ratio is an additional way to assess whether a stock is over or under valued and is used primarily in cases where earnings are negative and the PE ratio cannot be utilized.