The main stock market index of Philippines, the PSEi, rose to 6406 points on June 9, 2025, gaining 0.46% from the previous session. Over the past month, the index has declined 2.45% and is down 0.81% 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.

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 9 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: 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.

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.

Pakistan's main stock market index, the KSE 100, fell to 121641 points on June 5, 2025, losing 0.13% from the previous session. Over the past month, the index has climbed 7.11% and is up 64.68% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Pakistan. Pakistan Stock Market (KSE100) - values, historical data, forecasts and news - updated on June of 2025.

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.

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.

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

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: 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.

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.

Czech Republic Index: PSE: Annual: PX 50 data was reported at 1,760.170 05Apr1994=1000 in 2024. This records an increase from the previous number of 1,414.020 05Apr1994=1000 for 2023. Czech Republic Index: PSE: Annual: PX 50 data is updated yearly, averaging 986.560 05Apr1994=1000 from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 1,815.100 05Apr1994=1000 in 2007 and a record low of 394.200 05Apr1994=1000 in 1998. Czech Republic Index: PSE: Annual: PX 50 data remains active status in CEIC and is reported by Prague Stock Exchange. The data is categorized under Global Database’s Czech Republic – Table CZ.Z001: Prague Stock Exchange: Index.

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.

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.

Abstract

The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

Geographic coverage

Palestine West Bank Gaza Strip Jerusalem

Analysis unit

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Universe

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Kind of data

Sample survey data [ssd]

Sampling procedure

A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

Sampling deviation

Not apply

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

Cleaning operations

The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

Response rate

Not apply

Sampling error estimates

The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

Data appraisal

Other technical procedures to improve data quality: Seasonal adjustment processes and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

Abstract

The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

Geographic coverage

Palestine West Bank Gaza Strip Jerusalem

Analysis unit

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Universe

The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

Kind of data

Sample survey data [ssd]

Sampling procedure

A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

Sampling deviation

Not apply

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

Cleaning operations

The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

Response rate

Not apply

Sampling error estimates

The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

Data appraisal

Other technical procedures to improve data quality: Seasonal adjustment processes and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

Czech Republic Index: PSE: Annual: PX-GLOB data was reported at 2,332.800 30Sep1994=1000 in 2024. This records an increase from the previous number of 1,875.490 30Sep1994=1000 for 2023. Czech Republic Index: PSE: Annual: PX-GLOB data is updated yearly, averaging 1,239.490 30Sep1994=1000 from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 2,332.800 30Sep1994=1000 in 2024 and a record low of 478.300 30Sep1994=1000 in 1998. Czech Republic Index: PSE: Annual: PX-GLOB data remains active status in CEIC and is reported by Prague Stock Exchange. The data is categorized under Global Database’s Czech Republic – Table CZ.Z001: Prague Stock Exchange: Index.

For continuous variables, the mean and range or standard error of the mean are given.

Philippines PE Ratio: Index Level: PSE Property data was reported at 19.123 Unit in Oct 2018. This records a decrease from the previous number of 19.932 Unit for Sep 2018. Philippines PE Ratio: Index Level: PSE Property data is updated monthly, averaging 22.319 Unit from Jul 2006 (Median) to Oct 2018, with 148 observations. The data reached an all-time high of 39.348 Unit in May 2014 and a record low of 10.232 Unit in Feb 2009. Philippines PE Ratio: Index Level: 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.Z005: Philippines Stock Exchange: PE Ratio, PB Ratio and Yield: By Index Level Values.