Argentina's main stock market index, the Merval, rose to 2031093 points on July 1, 2025, gaining 1.82% from the previous session. Over the past month, the index has declined 7.94%, though it remains 24.12% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Argentina. Argentina Stock Market (MERVAL) - values, historical data, forecasts and news - updated on July of 2025.

The Buenos Aires' stock exchange index, known as MERVAL, saw a sharp decrease since the outbreak of the coronavirus pandemic. On March 18, 2020 the MERVAL stock market index reached its lowest value in the year, at around 22,087 Argentine pesos. Argentina was the first country to report a confirmed death due to COVID-19 in Latin America. 2023 onwards, the index surged significantly, reaching nearly 1.2 million Argentine pesos on April 15, 2024.

Argentina Index: BCBA: Merval: US Dollars data was reported at 1,795.593 30Jun1986=0.01 in Apr 2025. This records a decrease from the previous number of 2,177.617 30Jun1986=0.01 for Mar 2025. Argentina Index: BCBA: Merval: US Dollars data is updated monthly, averaging 604.550 30Jun1986=0.01 from Dec 1990 (Median) to Apr 2025, with 413 observations. The data reached an all-time high of 2,453.251 30Jun1986=0.01 in Dec 2024 and a record low of 88.208 30Jun1986=0.01 in May 2002. Argentina Index: BCBA: Merval: US Dollars data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

Key information about Argentina S&P MERVAL

• Argentina S&P MERVAL closed at 2,205,800.5 points in Feb 2025, compared with 2,564,659.0 points at the previous month end
• Argentina Equity Market Index: Month End: BCBA: S&P MERVAL data is updated monthly, available from Jun 1986 to Feb 2025, with an average number of 1,375.4 points
• The data reached an all-time high of 2,564,659.0 points in Jan 2025 and a record low of 0.0 points in Nov 1986

Stock market return (%, year-on-year) in Argentina was reported at 54.64 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Argentina - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Argentina Index: BCBA: Merval25 data was reported at 37,849.990 31Dec2002=524.95 in Feb 2019. This records a decrease from the previous number of 39,930.350 31Dec2002=524.95 for Jan 2019. Argentina Index: BCBA: Merval25 data is updated monthly, averaging 2,864.790 31Dec2002=524.95 from Oct 2004 (Median) to Feb 2019, with 173 observations. The data reached an all-time high of 39,930.350 31Dec2002=524.95 in Jan 2019 and a record low of 993.000 31Dec2002=524.95 in Nov 2008. Argentina Index: BCBA: Merval25 data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

Argentina Index: BCBA: M.AR data was reported at 29,979.320 30Dec1999=550.47 in Nov 2019. This records a decrease from the previous number of 30,562.740 30Dec1999=550.47 for Oct 2019. Argentina Index: BCBA: M.AR data is updated monthly, averaging 1,640.480 30Dec1999=550.47 from Nov 2000 (Median) to Nov 2019, with 229 observations. The data reached an all-time high of 37,370.350 30Dec1999=550.47 in Jul 2019 and a record low of 182.490 30Dec1999=550.47 in Nov 2001. Argentina Index: BCBA: M.AR data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

The statistic shows the annual development of the Merval Buenos Aires stock index from 1996 to 2024. The Merval (Mercado de Valores) index reflects the performance of leading stocks traded on the Buenos Aires stock exchange in Argentina. The year end value of the Merval index amounted to 2,533,635 points in 2024.

Argentina Index: BCBA: Burcap: US Dollars data was reported at 2,560.308 30Dec1992=426.33 in Feb 2019. This records a decrease from the previous number of 2,845.445 30Dec1992=426.33 for Jan 2019. Argentina Index: BCBA: Burcap: US Dollars data is updated monthly, averaging 1,325.241 30Dec1992=426.33 from Jan 1993 (Median) to Feb 2019, with 314 observations. The data reached an all-time high of 4,982.950 30Dec1992=426.33 in Jan 2018 and a record low of 398.736 30Dec1992=426.33 in May 2002. Argentina Index: BCBA: Burcap: US Dollars data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

Argentina Index: BCBA: Burcap data was reported at 100,236.070 30Dec1992=426.33 in Feb 2019. This records a decrease from the previous number of 106,277.370 30Dec1992=426.33 for Jan 2019. Argentina Index: BCBA: Burcap data is updated monthly, averaging 4,239.535 30Dec1992=426.33 from Jan 1993 (Median) to Feb 2019, with 314 observations. The data reached an all-time high of 106,277.370 30Dec1992=426.33 in Jan 2019 and a record low of 412.730 30Dec1992=426.33 in Feb 1993. Argentina Index: BCBA: Burcap data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

Argentina Trading Value: BCBA: ARS: Index Futures data was reported at 0.000 ARS mn in Feb 2021. This stayed constant from the previous number of 0.000 ARS mn for Jan 2021. Argentina Trading Value: BCBA: ARS: Index Futures data is updated monthly, averaging 0.000 ARS mn from Jan 2000 (Median) to Feb 2021, with 254 observations. The data reached an all-time high of 101.342 ARS mn in May 2003 and a record low of 0.000 ARS mn in Feb 2021. Argentina Trading Value: BCBA: ARS: Index Futures data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z003: Buenos Aires Stock Exchange: Trading Value (Discontinued).

End-of-day prices refer to the closing prices of various financial instruments, such as equities (stocks), bonds, and indices, at the end of a trading session on a particular trading day. These prices are crucial pieces of market data used by investors, traders, and financial institutions to track the performance and value of these assets over time. The Techsalerator closing prices dataset is considered the most up-to-date, standardized valuation of a security trading commences again on the next trading day. This data is used for portfolio valuation, index calculation, technical analysis and benchmarking throughout the financial industry. The End-of-Day Pricing service covers equities, equity derivative bonds, and indices listed on 170 markets worldwide.

Argentina Index: BCBA: Bolsa data was reported at 90,145,801.820 30Jun2000=19570.98 in Apr 2025. This records a decrease from the previous number of 100,410,600.860 30Jun2000=19570.98 for Mar 2025. Argentina Index: BCBA: Bolsa data is updated monthly, averaging 104,619.440 30Jun2000=19570.98 from Jan 1991 (Median) to Apr 2025, with 412 observations. The data reached an all-time high of 110,074,149.150 30Jun2000=19570.98 in Jan 2025 and a record low of 3,472.860 30Jun2000=19570.98 in Jan 1991. Argentina Index: BCBA: Bolsa data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z001: Buenos Aires Stock Exchange: Index.

Argentina Buenos Aires Stock Exchange: Index: S&P MERVAL data was reported at 1,581,107.160 NA in Sep 2024. This stayed constant from the previous number of 1,581,107.160 NA for Aug 2024. Argentina Buenos Aires Stock Exchange: Index: S&P MERVAL data is updated monthly, averaging 32,742.840 NA from Jul 2013 (Median) to Sep 2024, with 135 observations. The data reached an all-time high of 1,581,107.160 NA in Sep 2024 and a record low of 3,357.860 NA in Jul 2013. Argentina Buenos Aires Stock Exchange: Index: S&P MERVAL data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Argentina – Table AR.EDI.SE: Buenos Aires Stock Exchange: S&P/BYMA: Monthly.

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.

Telecom Argentina SA (TEO): A Glimmer of Hope?

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.

Loma Negra: Argentina's Cement Giant (LOMA)

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.

BBAR Banco BBVA Argentina S.A. ADS

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

Argentina Buenos Aires Stock Exchange: Index: S&P BOLSA-G data was reported at 67,450,383.459 NA in Sep 2024. This stayed constant from the previous number of 67,450,383.459 NA for Aug 2024. Argentina Buenos Aires Stock Exchange: Index: S&P BOLSA-G data is updated monthly, averaging 1,389,636.000 NA from Jul 2013 (Median) to Sep 2024, with 135 observations. The data reached an all-time high of 67,450,383.459 NA in Sep 2024 and a record low of 194,992.000 NA in Jul 2013. Argentina Buenos Aires Stock Exchange: Index: S&P BOLSA-G data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Argentina – Table AR.EDI.SE: Buenos Aires Stock Exchange: S&P/BYMA: Monthly.

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.

Grupo Supervielle (SUPV) Stock Forecast: Navigating Argentina's Economic Landscape

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

In January 2025, it was estimated that a Big Mac burger in Argentina would cost an average of 6.95 U.S. dollars. Overall, Argentina ranked with the highest price for a Big Mac in selected Latin American countries. The Big Mac Index in Argentina The Big Mac Index is an indicator that measures an economy's purchasing power. As it is mainly a standardized product, elaborated similarly across many markets, the evolution of its cost can provide insights into variations of real consumption prices in a given country. For instance, the price for a Big Mac in Argentina decreased by almost half from 2018 to 2019. This reflects Argentina's peso devaluation in comparison to the U.S. dollar and other foreign currencies in that period, caused by high inflation rates in the country, among other macroeconomic reasons. McDonald's in Latin America Arcos Dorados Holdings Inc. is McDonald's franchisee in Latin America. The company's name was inspired by McDonald's famous logo, as 'Arcos Dorados' means 'Golden Arches' in Spanish. It manages the brand's operations in Mexico, Central America, the Caribbean, and South America. Arcos Dorados’ revenue averages three billion U.S. dollars per year, making it McDonald's largest franchisee in the world. The company is also publicly listed in the New York Stock Exchange. Based on its market capitalization value, Arcos Dorados' net worth was estimated at around 1.64 billion U.S. dollars in 2023.