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.

The USD/CAD exchange rate fell to 1.3598 on July 23, 2025, down 0.05% from the previous session. Over the past month, the Canadian Dollar has strengthened 0.93%, and is up by 1.55% over the last 12 months. Canadian Dollar - values, historical data, forecasts and news - updated on July of 2025.

The USD/SGD exchange rate fell to 1.2784 on July 23, 2025, down 0.03% from the previous session. Over the past month, the Singapore Dollar has strengthened 0.12%, and is up by 4.87% over the last 12 months. Singapore Dollar - values, historical data, forecasts and news - updated on July of 2025.

Canada CA: Purchasing Power Parity: National Currency per USD data was reported at 1.178 USD/CAD in Dec 2026. This records a decrease from the previous number of 1.178 USD/CAD for Sep 2026. Canada CA: Purchasing Power Parity: National Currency per USD data is updated quarterly, averaging 1.193 USD/CAD from Mar 1961 (Median) to Dec 2026, with 264 observations. The data reached an all-time high of 1.254 USD/CAD in Sep 2015 and a record low of 0.878 USD/CAD in Mar 1962. Canada CA: Purchasing Power Parity: National Currency per USD data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.EO: Exchange Rate: Forecast: OECD Member: Quarterly. PPP - Purchasing power parity, national currency per USD

DNB Forecast: Foreign Exchange Rate: US Dollar data was reported at 6.500 DKK/USD in 2021. This stayed constant from the previous number of 6.500 DKK/USD for 2020. DNB Forecast: Foreign Exchange Rate: US Dollar data is updated yearly, averaging 6.500 DKK/USD from Dec 2017 (Median) to 2021, with 5 observations. The data reached an all-time high of 6.600 DKK/USD in 2017 and a record low of 6.300 DKK/USD in 2018. DNB Forecast: Foreign Exchange Rate: US Dollar data remains active status in CEIC and is reported by Danmarks Nationalbank. The data is categorized under Global Database’s Denmark – Table DK.M011: Foreign Exchange Rate: Forecast: Denmark National Bank.

Prices for USDNGN US Dollar Nigerian Naira including live quotes, historical charts and news. USDNGN US Dollar Nigerian Naira was last updated by Trading Economics this July 24 of 2025.

The USD/VND exchange rate fell to 26,143.0000 on July 24, 2025, down 0.03% from the previous session. Over the past month, the Vietnamese Dong has strengthened 0.05%, but it's down by 3.39% over the last 12 months. Vietnamese Dong - values, historical data, forecasts and news - updated on July of 2025.

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.

It is estimated that in 2021, the US-based discount retailing chain Dollar General generated about *** billion U.S. dollars through the sales of household and pet care items, making this category the leading source of company's net sales. Health and beauty products came in second in the ranking with net sales of around *** billion U.S. dollars, followed by edible grocery which produced approximately **************** billion U.S. dollars worth of net sales for the company.

Mexico BDM Forecast: Exchange Rate against US$: Average: Plus 12 Months data was reported at 19.940 MXN/USD in Mar 2019. This records a decrease from the previous number of 20.020 MXN/USD for Feb 2019. Mexico BDM Forecast: Exchange Rate against US$: Average: Plus 12 Months data is updated monthly, averaging 12.920 MXN/USD from Dec 1999 (Median) to Mar 2019, with 155 observations. The data reached an all-time high of 21.470 MXN/USD in Jan 2017 and a record low of 9.940 MXN/USD in Dec 2001. Mexico BDM Forecast: Exchange Rate against US$: Average: Plus 12 Months data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.M006: Foreign Exchange Rates: Forecast.

Prices for USDILS US Dollar Israeli New Sheqel including live quotes, historical charts and news. USDILS US Dollar Israeli New Sheqel was last updated by Trading Economics this July 13 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.

DLTR Dollar Tree Inc. Common Stock

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 USD/THB exchange rate rose to 32.2310 on July 24, 2025, up 0.19% from the previous session. Over the past month, the Thai Baht has strengthened 0.86%, and is up by 10.96% over the last 12 months. Thai Baht - values, historical data, forecasts and news - updated on July 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.

Dollar General Stock Forecast: A Discount Retailer in Trouble

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 USD/GYD exchange rate rose to 209.2000 on July 24, 2025, up 0.43% from the previous session. Over the past month, the Guyanese Dollar has remained flat, but it's down by 0.14% over the last 12 months. Guyanese Dollar - values, historical data, forecasts and news - updated on July of 2025.

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.

Changes in inventories (current US$) in Iran was reported at 39184296473 USD in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Iran - Changes in inventories - actual values, historical data, forecasts and projections were sourced from the World Bank on July 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.

Dollar index faces uncertain future amid economic headwinds

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 foreign exchange (Forex) market is a global decentralized market for the trading of currencies. It is the largest financial market in the world, with an average daily trading volume of over $5 trillion. The market size is expected to reach $84 million by 2033, growing at a CAGR of 5.83% during the forecast period 2025-2033. Key drivers of the Forex market growth include increasing international trade, rising foreign direct investment, and growing demand for hedging and speculation. The market is also being driven by the increasing use of online trading platforms and the growing popularity of cryptocurrencies. The major players in the Forex market include Deutsche Bank, UBS, JP Morgan, State Street, XTX Markets, Jump Trading, Citi, Bank of New York Mellon, Bank America, and Goldman Sachs. The market is segmented by type (spot Forex, currency swap, outright forward, Forex swaps, Forex options, other types), counterparty (reporting dealers, other financial institutions, non-financial customers), and region (North America, South America, Europe, Middle East & Africa, Asia Pacific). Recent developments include: In November 2023, JP Morgan revealed the introduction of novel FX Warrants denominated in Hong Kong dollars in the Hong Kong market, marking its status as the inaugural issuer in Asia to present FX Warrants featuring CNH/HKD (Chinese Renminbi traded outside Mainland China/Hong Kong dollar) and JPY/HKD (Japanese Yen/Hong Kong dollar) as underlying currency pairs. These fresh FX Warrants are set to commence trading on the Hong Kong Stock Exchange., In October 2023, Deutsche Bank AG finalized its purchase of Numis Corporation Plc. The integration of both brands under the name 'Deutsche Numis' underscores their collective influence and standing in the UK and global markets. 'Deutsche Numis' emerges as a prominent entity in UK investment banking and the preferred advisor for UK-listed companies. This acquisition aligns with Deutsche Bank's Global Hausbank strategy, aiming to become the primary partner for clients in financial services and fostering stronger relationships with corporations throughout the United Kingdom., In June 2023, UBS successfully finalized the acquisition of Credit Suisse, marking a significant achievement. Credit Suisse Group AG has merged into UBS Group AG, forming a unified banking entity.. Key drivers for this market are: International Transactions Driven by Growing Tourism Driving Market Demand, Market Liquidity Impacting the Foreign Exchange Market. Potential restraints include: International Transactions Driven by Growing Tourism Driving Market Demand, Market Liquidity Impacting the Foreign Exchange Market. Notable trends are: FX Swaps is leading the market.

This graph shows a forecast of the gross domestic product of the United States of America for fiscal years 2024 to 2034. GDP refers to the market value of all final goods and services produced within a country in a given period. According to the CBO, the United States GDP will increase steadily over the next decade from 28.18 trillion U.S. dollars in 2023 to 41.65 trillion U.S. dollars in 2034. The annual GDP of the United States for recent years can be found here. Also, view the monthly inflation rate for the country.