Prices for Philippines Stock Exchange PSEi Index including live quotes, historical charts and news. Philippines Stock Exchange PSEi Index was last updated by Trading Economics this June 28 of 2025.

The main stock market index of Philippines, the PSEi, rose to 6408 points on June 27, 2025, gaining 1.23% from the previous session. Over the past month, the index has declined 0.27% and is down 0.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Philippines. Philippines Stock Market (PSEi) - values, historical data, forecasts and news - updated on June of 2025.

Philippines Index: PSE: All Shares data was reported at 4,441.330 14Nov1996=1000 in Nov 2018. This records an increase from the previous number of 4,370.460 14Nov1996=1000 for Oct 2018. Philippines Index: PSE: All Shares data is updated monthly, averaging 1,668.750 14Nov1996=1000 from Nov 1996 (Median) to Nov 2018, with 265 observations. The data reached an all-time high of 5,124.830 14Nov1996=1000 in Jan 2018 and a record low of 400.470 14Nov1996=1000 in Aug 1998. Philippines Index: PSE: All Shares data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.

The PSEi Composite index is expected to continue its upward trend in the coming months, supported by strong corporate earnings and economic growth. The index is expected to reach a new high in the next six months, although there are some risks to consider. These include geopolitical uncertainty and rising inflation. Overall, the upside potential for the PSEi Composite index outweighs the risks, and investors are advised to stay invested for the long term.

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.

When Will PSEi Composite Recover?

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 Philippines: Stock market return, percent: The latest value from 2021 is 7.82 percent, an increase from -19.62 percent in 2020. In comparison, the world average is 32.21 percent, based on data from 87 countries. Historically, the average for the Philippines from 1988 to 2021 is 9.06 percent. The minimum value, -30.47 percent, was reached in 1998 while the maximum of 60.82 percent was recorded in 1994.

Philippines Index: PSE: Services data was reported at 1,462.550 29Dec2005=1000 in Oct 2018. This records a decrease from the previous number of 1,494.970 29Dec2005=1000 for Sep 2018. Philippines Index: PSE: Services data is updated monthly, averaging 1,571.185 29Dec2005=1000 from Jan 2006 (Median) to Oct 2018, with 154 observations. The data reached an all-time high of 2,237.160 29Dec2005=1000 in Aug 2014 and a record low of 1,027.130 29Dec2005=1000 in Jan 2006. Philippines Index: PSE: Services data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.

Stock market return (%, year-on-year) in Philippines was reported at 7.8165 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Key information about Philippines PSEi

• Philippines PSEi closed at 5,998.0 points in Feb 2025, compared with 5,862.6 points at the previous month end
• Philippines Equity Market Index: Month End: PSEi data is updated monthly, available from Jan 1987 to Feb 2025, with an average number of 2,806.2 points
• The data reached an all-time high of 8,764.0 points in Jan 2018 and a record low of 511.2 points in Mar 1987

• In the latest reports, PSEi recorded a monthly P/E ratio of 12.0 in Dec 2024

Philippines Index: PSE: Property data was reported at 3,601.140 30Sep1994=1000 in Nov 2018. This records an increase from the previous number of 3,495.490 30Sep1994=1000 for Oct 2018. Philippines Index: PSE: Property data is updated monthly, averaging 1,152.325 30Sep1994=1000 from Oct 1994 (Median) to Nov 2018, with 290 observations. The data reached an all-time high of 3,978.190 30Sep1994=1000 in Dec 2017 and a record low of 370.050 30Sep1994=1000 in Oct 2000. Philippines Index: PSE: Property data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.

Comprehensive list of blue chip stocks listed on the Philippine Stock Exchange for 2025

Philippines Index: PSE: Holding Firms data was reported at 7,230.900 29Dec2005=1000 in Nov 2018. This records an increase from the previous number of 7,003.530 29Dec2005=1000 for Oct 2018. Philippines Index: PSE: Holding Firms data is updated monthly, averaging 4,471.060 29Dec2005=1000 from Jan 2006 (Median) to Nov 2018, with 155 observations. The data reached an all-time high of 8,957.810 29Dec2005=1000 in Jan 2018 and a record low of 860.940 29Dec2005=1000 in Nov 2008. Philippines Index: PSE: Holding Firms data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.

List of highest-yielding dividend stocks in the Philippine Stock Exchange for 2025

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 PSEi Index Soar Higher?

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

Philippines Index: PSE: Banking and Financial Services data was reported at 1,758.250 14Nov1996=1000 in Nov 2018. This records an increase from the previous number of 1,607.900 14Nov1996=1000 for Oct 2018. Philippines Index: PSE: Banking and Financial Services data is updated monthly, averaging 787.650 14Nov1996=1000 from Nov 1996 (Median) to Nov 2018, with 265 observations. The data reached an all-time high of 2,230.170 14Nov1996=1000 in Dec 2017 and a record low of 340.630 14Nov1996=1000 in Feb 2003. Philippines Index: PSE: Banking and Financial Services data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.

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.

PSEi Composite: Is it a Rocky Road Ahead?

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

Philippines PE Ratio: Index Level: PSEi data was reported at 11.064 Unit in Feb 2025. This records an increase from the previous number of 10.737 Unit for Jan 2025. Philippines PE Ratio: Index Level: PSEi data is updated monthly, averaging 17.168 Unit from Jul 2006 (Median) to Feb 2025, with 224 observations. The data reached an all-time high of 26.282 Unit in May 2021 and a record low of 9.230 Unit in Oct 2008. Philippines PE Ratio: Index Level: PSEi data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z004: Philippine Stock Exchange: PE Ratio, PB Ratio and Yield. [COVID-19-IMPACT]

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.

Is the PSEi Index Poised for Growth?

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

Philippines Dividend Yield Ratio: Index Level: PSEi data was reported at 3.445 % in Feb 2025. This records a decrease from the previous number of 3.535 % for Jan 2025. Philippines Dividend Yield Ratio: Index Level: PSEi data is updated monthly, averaging 2.225 % from Jul 2006 (Median) to Feb 2025, with 224 observations. The data reached an all-time high of 6.080 % in Oct 2008 and a record low of 1.529 % in Jan 2018. Philippines Dividend Yield Ratio: Index Level: PSEi data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z004: Philippine Stock Exchange: PE Ratio, PB Ratio and Yield. [COVID-19-IMPACT]

Philippines Index: PSE: Industrial data was reported at 10,655.140 28Feb1990=1422 in Nov 2018. This records an increase from the previous number of 10,648.790 28Feb1990=1422 for Oct 2018. Philippines Index: PSE: Industrial data is updated monthly, averaging 3,188.340 28Feb1990=1422 from Jan 1987 (Median) to Nov 2018, with 383 observations. The data reached an all-time high of 12,872.310 28Feb1990=1422 in Feb 2015 and a record low of 605.300 28Feb1990=1422 in Jan 1987. Philippines Index: PSE: Industrial data remains active status in CEIC and is reported by Philippine Stock Exchange. The data is categorized under Global Database’s Philippines – Table PH.Z003: Philippines Stock Exchange: Index.