Uruguay BCU Forecast: Exchange Rate against US$: Median: Next 18 Month data was reported at 34.500 UYU/USD in Jul 2018. This records a decrease from the previous number of 34.600 UYU/USD for Jun 2018. Uruguay BCU Forecast: Exchange Rate against US$: Median: Next 18 Month data is updated monthly, averaging 24.350 UYU/USD from Jul 2006 (Median) to Jul 2018, with 145 observations. The data reached an all-time high of 38.500 UYU/USD in May 2016 and a record low of 19.010 UYU/USD in Jun 2011. Uruguay BCU Forecast: Exchange Rate against US$: Median: Next 18 Month data remains active status in CEIC and is reported by Central Bank of Uruguay. The data is categorized under Global Database’s Uruguay – Table UY.M006: Foreign Exchange Rate: Forecast: Central Bank of Uruguay.

A graphic that displays the dollar performance against other currencies reveals that economic developments had mixed results on currency exchanges. The third quarter of 2023 marked a period of disinflation in the euro area, while China's projected growth was projected to go up. The United States economy was said to have a relatively strong performance in Q3 2023, although growing capital market interest rate and the resumption of student loan repayments might dampen this growth at the end of 2023. A relatively weak Japanese yen Q3 2023 saw pressure from investors towards Japanese authorities on how they would respond to the situation surrounding the Japanese yen. The USD/JPY rate was close to 150, whereas analysts suspected it should be around 90 given the country's purchase power parity. The main reason for this disparity is said to be the differences in central bank interest rates between the United States, the euro area, and Japan. Any future aggressive changes from, especially the U.S. Fed might lower those differences. Financial markets responded somewhat disappoint when Japan did not announce major plans to tackle the situation. Potential rent decreases in 2024 Central bank rates peak in 2023, although it is expected that some of these will decline in early 2024. That said, analysts expect overall policies will remain restrictive. For example, the Bank of England's interest rate remained unchanged at 5.25 percent in Q3 2023. It is believed the United Kingdom's central bank will ease its interest rate in 2024 but less than either the U.S. Fed or the European Central Bank. This should be a positive development for the pound compared to either the euro or the dollar.

Argentina MES: Nominal Exchange Rate: 12 Months: Average Forecast data was reported at 1,302.788 USD/ARS in Feb 2025. This records an increase from the previous number of 1,236.852 USD/ARS for Jan 2025. Argentina MES: Nominal Exchange Rate: 12 Months: Average Forecast data is updated monthly, averaging 118.591 USD/ARS from Jun 2016 (Median) to Feb 2025, with 105 observations. The data reached an all-time high of 1,886.045 USD/ARS in Jan 2024 and a record low of 17.520 USD/ARS in Jun 2016. Argentina MES: Nominal Exchange Rate: 12 Months: Average Forecast data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.M013: Foreign Exchange Rates: Forecast: Central Bank of Argentina.

Uruguay BCU Forecast: Exchange Rate against US$: Average: End of Month data was reported at 32.700 UYU/USD in Nov 2018. This records a decrease from the previous number of 33.070 UYU/USD for Oct 2018. Uruguay BCU Forecast: Exchange Rate against US$: Average: End of Month data is updated monthly, averaging 23.645 UYU/USD from Jun 2005 (Median) to Nov 2018, with 162 observations. The data reached an all-time high of 33.200 UYU/USD in Sep 2018 and a record low of -2.350 UYU/USD in Apr 2013. Uruguay BCU Forecast: Exchange Rate against US$: Average: End of Month data remains active status in CEIC and is reported by Central Bank of Uruguay. The data is categorized under Global Database’s Uruguay – Table UY.M006: Foreign Exchange Rate: Forecast: Central Bank of Uruguay.

Although speculative activity is central to black markets for currency, the out-of-sample performance of structural models in those settings is unknown. We substantially update the literature on empirical determinants of black market rates and evaluate the out-of-sample performance of linear models and non-parametric Bayesian treed Gaussian process (BTGP) models against the random walk benchmark. Fundamentals-based models outperform the benchmark in out-of-sample prediction accuracy and trading rule profitability measures given future values of fundamentals. In simulated real-time trading exercises, however, the BTGP achieves superior realized profitability, accuracy and market timing, while linear models do no better than a random walk.

New Zealand ANZ Forecast: Foreign Exchange Rate: United States Dollar: Annual data was reported at 0.640 NZD/USD in 2025. This records an increase from the previous number of 0.630 NZD/USD for 2024. New Zealand ANZ Forecast: Foreign Exchange Rate: United States Dollar: Annual data is updated yearly, averaging 0.645 NZD/USD from Dec 2018 (Median) to 2025, with 8 observations. The data reached an all-time high of 0.680 NZD/USD in 2021 and a record low of 0.590 NZD/USD in 2023. New Zealand ANZ Forecast: Foreign Exchange Rate: United States Dollar: Annual data remains active status in CEIC and is reported by ANZ Bank New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.M017: Foreign Exchange Rate: Forecast: ANZ Bank Ltd.

One euro in 2022 was worth less Indian rupees than in 2021, with exchange rates reaching values close to 2018 or 2019. This according to a comparison between average monthly and daily exchange rates. As of March 21, 2025 one euro was worth 93.65 Indian rupees. The average, or standardized, measure is based on many observations throughout the period in question. This is different than an annual measure that denotes concrete values as of the end of the year.EstablishmentThe euro, which was established in 1992, introduced in non-physical form in 1999 and finally rolled out in 2002, is used by 19 of the 27 member states of the European Union. This group of 19 countries is otherwise known as the eurozone or euro area. By 2018, the total value of euro currency in circulation was almost 1.2 trillion euros, or over 3.4 thousand euros per capita.Euro to Indian rupeeBetween the years of 2001 and 2014, the average annual exchange rate of the euro to the Indian rupee noted an overall increase. In 2014, the euro to Indian rupee annual average exchange rate was equal to 81.04, which meant that one euro could buy 81.04 Indian rupees. By 2019, this value had fluctuated, to a value of 78.84, which meant that one euro could buy 78.84 Indian rupees. A similar pattern of fluctuation can be seen with the euro against the U.S. dollar.

This dataset provides values for REAL EFFECTIVE EXCHANGE RATE WB DATA.HTML. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Long term historical dataset of the daily U.S. Dollar - Japanese Yen (USDJPY) exchange rate back to 1971.

Long term dataset showing the daily Euro - British Pound (EURGBP) exchange rate back to 1999.

The official currency of Netherlands is the Euro. Euro Exchange Rate - EUR/USD - Netherlands - values, historical data, forecasts and news - updated on March of 2025.

This dataset provides values for EXCHANGE RATE. reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for REAL EFFECTIVE EXCHANGE RATE INDEX 2000 100 WB DATA.HTML reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Real Effective Exchange Rate in Dominican Republic was reported at 0 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Dominican Republic - Real Effective Exchange Rate - actual values, historical data, forecasts and projections were sourced from the World Bank on March of 2025.

The USDTHB decreased 0.0550 or 0.16% to 33.9050 on Thursday March 27 from 33.9600 in the previous trading session. Thai Baht - values, historical data, forecasts and news - updated on March of 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.

How accurate is machine learning in stock market? (TD Stock Forecast)

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

Singapore MAS Forecast: Exchange Rate: Maximum data was reported at 1.900 SGD/USD in Dec 2018. This records an increase from the previous number of 1.390 SGD/USD for Sep 2018. Singapore MAS Forecast: Exchange Rate: Maximum data is updated quarterly, averaging 1.500 SGD/USD from Dec 1999 (Median) to Dec 2018, with 77 observations. The data reached an all-time high of 2.000 SGD/USD in Mar 2001 and a record low of 1.200 SGD/USD in Mar 2013. Singapore MAS Forecast: Exchange Rate: Maximum data remains active status in CEIC and is reported by Monetary Authority of Singapore. The data is categorized under Global Database’s Singapore – Table SG.M007: Foreign Exchange Rate: Forecast: Monetary Authority of Singapore: Survey of Professional Forecasters.

The USDTZS increased 40.0000 or 1.53% to 2,660.0000 on Wednesday March 26 from 2,620.0000 in the previous trading session. Tanzania Shilling - values, historical data, forecasts and news - updated on March of 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.

Can we predict stock market using machine learning? (LON:PNL Stock Forecast)

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

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Costa Rica Exchange Rate.