The USD/INR exchange rate rose to 90.0340 on December 2, 2025, up 0.47% from the previous session. Over the past month, the Indian Rupee has weakened 1.48%, and is down by 6.32% over the last 12 months. Indian Rupee - values, historical data, forecasts and news - updated on December of 2025.

India IN: Exchange Rate: National Currency per USD data was reported at 84.404 USD/INR in 2025. This records an increase from the previous number of 83.630 USD/INR for 2024. India IN: Exchange Rate: National Currency per USD data is updated yearly, averaging 48.323 USD/INR from Dec 1995 (Median) to 2025, with 31 observations. The data reached an all-time high of 84.404 USD/INR in 2025 and a record low of 32.432 USD/INR in 1995. India IN: Exchange Rate: 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 India – Table IN.OECD.EO: Exchange Rate: Forecast: Non OECD Member: Annual. EXCHUD - Exchange rate, national currency per USD

India IN: Exchange Rate: National Currency per USD: Single Hit Scenario data was reported at 75.568 USD/INR in 2021. This records an increase from the previous number of 74.843 USD/INR for 2020. India IN: Exchange Rate: National Currency per USD: Single Hit Scenario data is updated yearly, averaging 46.604 USD/INR from Dec 1995 (Median) to 2021, with 27 observations. The data reached an all-time high of 75.568 USD/INR in 2021 and a record low of 32.432 USD/INR in 1995. India IN: Exchange Rate: National Currency per USD: Single Hit Scenario 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 India – Table IN.OECD.EO: Exchange Rate: Forecast: Non OECD Member: Annual. EXCHUD - Exchange rate, national currency per USD

Introduction: A Comprehensive Historical Tracking of PKR, INR, and USD Exchange Rates from 1947 to 2024. Delve into Pakistan and India's economic narratives in reference to the US Dollar, witnessing the fluctuations, trends, and pivotal moments that shaped their currencies over eight decades. Gain insights into geopolitical shifts, economic policies, and global events, understanding the intricate dynamics of these currencies in the ever-changing financial landscape.

Background: I'm teaching my students about the difference between the Pakistani Rupee and the Indian Rupee since 1947. We're using the US Dollar as a standard for comparison. I gathered this dataset from various internet sources.

About the data: The dataset is tabular and contains three columns: 1. Year: Ranging from 1947 to 2024. 2. INR (Rs): Indian Rupee value equivalent to 1 US Dollar. 3. PKR (Rs): Pakistani Rupee value equivalent to 1 US Dollar.

Use Cases: here are some use cases for this dataset.

1. Historical Analysis: Researchers or economists could use the dataset to analyze the historical trends and fluctuations in exchange rates between PKR, INR, and USD over the years. This analysis could provide insights into the economic performance and stability of Pakistan and India in relation to the US.

2. Educational Purposes: As you're using it for teaching, the dataset can serve as a valuable educational resource for students to understand the economic differences between Pakistan and India since their independence, using the USD as a benchmark.

3. Investment Analysis: Investors and financial analysts could use the dataset to analyze the historical performance of the currencies and make informed decisions about investments or currency trading in the Pakistan and India markets.

4. Policy Making: Government policymakers could utilize the dataset to understand the impact of various economic policies on currency exchange rates and formulate effective strategies for maintaining stability and growth.

5. Cross-Border Transactions: Businesses engaged in cross-border trade between Pakistan, India, and the US could use the dataset to forecast currency exchange rates and mitigate risks associated with fluctuations in currency values.

6. Comparative Studies: Scholars or analysts interested in comparative studies between Pakistan and India could use the dataset to explore the differences and similarities in their economic development trajectories over time.

7. Forecasting: Economists or analysts could develop models to forecast future exchange rates based on historical trends and factors affecting the economies of Pakistan, India, and the US.

Prices for GBPINR British Pound Sterling Indian Rupee including live quotes, historical charts and news. GBPINR British Pound Sterling Indian Rupee was last updated by Trading Economics this December 2 of 2025.

Money Supply M2 in India increased to 70702.28 INR Billion in August from 70460.97 INR Billion in July of 2025. This dataset provides - India Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Snapshot img

Foreign Exchange Market Size 2025-2029

The foreign exchange market size is valued to increase by USD 582 billion, at a CAGR of 10.6% from 2024 to 2029. Growing urbanization and digitalization will drive the foreign exchange market.

Major Market Trends & Insights

Europe dominated the market and accounted for a 47% growth during the forecast period.
By Type - Reporting dealers segment was valued at USD 278.60 billion in 2023
By Trade Finance Instruments - Currency swaps segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 118.14 billion
Market Future Opportunities: USD 582.00 billion
CAGR from 2024 to 2029 : 10.6%

Market Summary

The market, a dynamic and intricate web of financial transactions, plays a pivotal role in facilitating global trade and economic interactions. Its primary function is to enable the conversion of one currency into another, thereby mitigating the risk of currency fluctuations for businesses and investors. Key drivers of this market include growing urbanization and digitalization, which have expanded trading opportunities to a 24x7 global economy. However, the uncertainty of future exchange rates poses a significant challenge, necessitating effective risk management strategies. The market's evolution reflects the increasing interconnectedness of the global economy. Transactions occur in a decentralized, over-the-counter system, with major trading centers in London, New York, and Tokyo.
Participants include commercial banks, investment banks, hedge funds, and individual investors, all seeking to capitalize on price differences between currencies. Trends shaping the market include the increasing use of automation and artificial intelligence to analyze market data and execute trades. Regulatory changes, such as the introduction of stricter capital requirements, also impact the market's functioning. Looking ahead, the market is expected to remain a vital component of the global financial landscape, with continued growth driven by increased trade and economic interdependence. However, challenges, such as regulatory changes and geopolitical risks, will necessitate adaptability and innovation from market participants.

What will be the Size of the Foreign Exchange Market during the forecast period?

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How is the Foreign Exchange Market Segmented ?

The foreign exchange industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Reporting dealers
  Financial institutions
  Non-financial customers


Trade Finance Instruments

  Currency swaps
  Outright forward and FX swaps
  FX options


Trading Platforms

  Electronic Trading
  Over-the-Counter (OTC)
  Mobile Trading


Geography

  North America

    US
    Canada


  Europe

    Germany
    Switzerland
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The reporting dealers segment is estimated to witness significant growth during the forecast period.

The market, a dynamic and ever-evolving financial landscape, is characterized by constant activity and intricate patterns. Participants engage in various trading strategies, employing advanced tools such as stop-loss and take-profit orders on forex trading platforms. Real-time data feeds and order book dynamics facilitate trade execution speed, while market microstructure and slippage minimization techniques ensure efficient transactions. Currency correlation analysis and transaction cost analysis are integral to informed decision-making, with backtesting methodologies providing valuable insights. Currency forwards contracts, position sizing techniques, and forex derivatives pricing are essential components of risk management systems. Carry trade strategies, hedging strategies, and interest rate parity are popular tactics employed by market participants.

Algorithmic trading strategies, driven by options pricing models and trading algorithms' efficiency, significantly influence price discovery mechanisms. High-frequency trading and volatility modeling contribute to the market's liquidity risk management, while foreign exchange swaps and currency option valuation help manage risk. The market's complexities necessitate sophisticated risk management systems and intricate order routing optimization. Global payments systems facilitate the smooth transfer of funds, and liquidity risk management remains a critical concern for market participants. According to recent studies, The market is estimated to account for approximately USD6 trillion in daily trading volume, und

India IN: Purchasing Power Parity: National Currency per USD: Double Hit Scenario data was reported at 21.619 USD/INR in 2021. This stayed constant from the previous number of 21.619 USD/INR for 2020. India IN: Purchasing Power Parity: National Currency per USD: Double Hit Scenario data is updated yearly, averaging 12.579 USD/INR from Dec 1995 (Median) to 2021, with 27 observations. The data reached an all-time high of 21.619 USD/INR in 2021 and a record low of 7.946 USD/INR in 1995. India IN: Purchasing Power Parity: National Currency per USD: Double Hit Scenario 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 India – Table IN.OECD.EO: Exchange Rate: Forecast: Non OECD Member: Annual. PPP - Purchasing power parity, national currency per USD

Forecast: Value of E-money Payments in India 2022 - 2026 Discover more data with ReportLinker!

USD 204.71 Million in 2024; projected USD 331.58 Million by 2033; CAGR 5.5%.

Forecast: Number of E-money Payments in India 2022 - 2026 Discover more data with ReportLinker!

Daily GBP to INR open, high, low, close and mid rates for the calendar year 2025.

Money Supply M1 in India increased to 68578.97 INR Billion in August from 68337.66 INR Billion in July of 2025. This dataset provides - India Money Supply M1 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In April 2025, the value of the Indian rupee per unit of U.S. dollar amounted to ***** Indian rupees. The exchange rate of one U.S. dollar to Indian rupee reached ** Indian rupees at the beginning of the fourth quarter of 2022 from ***** INR at the beginning of the year 2022 and has stayed above ** rupees since the beginning of 2025.

The benchmark interest rate in India was last recorded at 5.50 percent. This dataset provides - India Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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Gold Price Prediction in INR (2004-2024)🇮🇳 - Can You Forecast the Future? ✨

Data Description:

1. Time Period: October 2004 - December 2024 (20 years) - Long-term Trend Analysis!
2. Frequency: Monthly Average Gold Price (INR) - Uncover Seasonality!
3. Source: Financial Service Website (verified) ✅ - Reliable Data for Accurate Predictions!

Potential Applications:

• Time Series Analysis: Analyze trends and seasonality in gold prices. - Unravel the Gold Market Mystery! ️‍♀️
• Gold Price Prediction: Forecast future gold prices using ARIMA, SARIMA, fbProphet, etc. - Predict the Next Big Move!

Key Points:

• Long-Term Trend: Explore the evolution of gold prices over two decades. - See How Gold Has Changed Over Time! ⏳
• Prediction Models: Evaluate the effectiveness of different time series forecasting models. - Find the Best Tool for the Job!
• INR Focus: Gain insights specific to the Indian gold market. 🇮🇳 - Understand the Indian Gold Market Landscape! ️

⚠️ Note:

• Past performance does not guarantee future results.

Bonus:

This dataset allows you to explore the fascinating world of gold price prediction in the Indian market. Challenge yourself! Can you develop a model that outperforms the rest?

It has been estimated that by 2030, the export value of drones from India will reach around *** billion Indian rupees. During the same period, the domestic market size of drone in India will reach around *** trillion rupees.

Money Supply M3 in India increased to 289951 INR Billion in the week ending October 31 from 287145.32 INR Billion two weeks before. This dataset provides - India Money Supply M3 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The size of the India Trade Finance Industry market was valued at USD 2 Million in 2023 and is projected to reach USD 3.46 Million by 2032, with an expected CAGR of 8.15% during the forecast period. Recent developments include: July 2022: A new foreign exchange mechanism has been introduced by the Reserve Bank of India (RBI) to stabilize the Indian economy and promote increased international trade. According to a public statement made on July 11th, the system will make it easier for international trade transactions to be made in Indian rupees (INR). Indian importers and exporters can now use their own currency instead of US dollars to pay for transactions. This arrangement needs to be approved by banks first., December 2022: Japan's MUFG Bank announced the execution of a INR 450 crore (USD 54.3 million) sustainable trade finance facility for Tata Power. MUFG has extended this financing for the procurement of two solar power projects of TP Kirnali Limited (TPKL).. Notable trends are: Digitalization is Driving the Market.

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.

INR IONEER LTD

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