Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Adamawa, Market Average

Graph and download economic data for Equity Market Volatility Tracker: Exchange Rates (EMVEXRATES) from Jan 1985 to Jun 2025 about volatility, uncertainty, equity, exchange rate, rate, and USA.

Snapshot img

Foreign Exchange Market Size 2025-2029

The foreign exchange market size is forecast to increase by USD 582 billion, at a CAGR of 10.6% between 2024 and 2029.

The Foreign Exchange Market is segmented by 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), and geography (North America: US, Canada; Europe: Germany, Switzerland, UK; Middle East and Africa: UAE; APAC: China, India, Japan; South America: Brazil; Rest of World). This segmentation reflects the market's global dynamics, driven by institutional trading, increasing digital adoption through electronic trading and mobile trading, and regional economic activities, with APAC markets like India and China showing significant growth alongside traditional hubs like the US and UK.
The market is experiencing significant shifts driven by the escalating trends of urbanization and digitalization. These forces are creating 24x7 trading opportunities, enabling greater accessibility and convenience for market participants. However, the market's dynamics are not without challenges. The uncertainty of future exchange rates poses a formidable obstacle for businesses and investors alike, necessitating robust risk management strategies. As urbanization continues to expand and digital technologies reshape the trading landscape, market players must adapt to remain competitive. One significant trend is the increasing use of money transfer agencies, venture capital investments, and mutual funds in foreign exchange transactions. Companies seeking to capitalize on these opportunities must navigate the challenges effectively, ensuring they stay abreast of exchange rate fluctuations and implement agile strategies to mitigate risk.
The ability to adapt and respond to these market shifts will be crucial for success in the evolving market.

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

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic and intricate realm of the market, entities such as algorithmic trading, order book, order management systems, and liquidity risk intertwine, shaping the ever-evolving market landscape. The market's continuous unfolding is characterized by the integration of various components, including sentiment analysis, Fibonacci retracement, mobile trading, and good-for-the-day orders. Market activities are influenced by factors like political stability, monetary policy, and market liquidity, which in turn impact economic growth and trade settlement. Technical analysis, with its focus on chart patterns and moving averages, plays a crucial role in informing trading decisions. The market's complexity is further amplified by the presence of entities like credit risk, counterparty risk, and operational risk.

Central bank intervention, order execution, clearing and settlement, and trade confirmation are essential components of the market's infrastructure, ensuring a seamless exchange of currencies. Geopolitical risk, currency correlation, and inflation rates contribute to currency volatility, necessitating hedging strategies and risk management. Market risk, interest rate differentials, and commodity currencies influence trading strategies, while cross-border payments and brokerage services facilitate international trade. The ongoing evolution of the market is marked by the emergence of advanced trading platforms, automated trading, and real-time data feeds, enabling traders to make informed decisions in an increasingly interconnected and complex global economy.

How is this Foreign Exchange Industry 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 is a dynamic and complex ecosystem where various entities interplay to manage currency risks and facilitate international trade. Reporting dealers, as key participants,

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Kayanza, Ruyigi, Bubanza, Karuzi, Bujumbura Mairie, Muramvya, Gitega, Rumonge, Bururi, Kirundo, Cankuzo, Cibitoke, Muyinga, Rutana, Bujumbura Rural, Makamba, Ngozi, Mwaro, Market Average

Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for United States (CCRETT01USQ661N) from Q1 1970 to Q1 2025 about exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, price, and USA.

Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for United States (CCRETT01USM661N) from Jan 1970 to May 2025 about exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, price, and USA.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Badakhshan, Badghis, Baghlan, Balkh, Bamyan, Daykundi, Farah, Faryab, Paktya, Ghazni, Ghor, Hilmand, Hirat, Nangarhar, Jawzjan, Kabul, Kandahar, Kapisa, Khost, Kunar, Kunduz, Laghman, Logar, Wardak, Nimroz, Nuristan, Paktika, Panjsher, Parwan, Samangan, Sar-e-pul, Takhar, Uruzgan, Zabul, Market Average, Armavir, Ararat, Aragatsotn, Tavush, Gegharkunik, Shirak, Kotayk, Syunik, Lori, Vayotz Dzor, Yerevan, Kayanza, Ruyigi, Bubanza, Karuzi, Bujumbura Mairie, Muramvya, Gitega, Rumonge, Bururi, Kirundo, Cankuzo, Cibitoke, Muyinga, Rutana, Bujumbura Rural, Makamba, Ngozi, Mwaro, SAHEL, CASCADES, SUD-OUEST, EST, BOUCLE DU MOUHOUN, CENTRE-NORD, PLATEAU-CENTRAL, HAUTS-BASSINS, CENTRE, NORD, CENTRE-SUD, CENTRE-OUEST, CENTRE-EST, Khulna, Chittagong, Barisal, Rajshahi, Dhaka, Rangpur, Sylhet, Mymensingh, Ouaka, Mbomou, Bangui, Nana-Mambéré, Ouham, Sangha-Mbaéré, Ombella M'Poko, Mambéré-Kadéï, Vakaga, Ouham Pendé, Lobaye, Haute-Kotto, Kémo, Nana-Gribizi, Bamingui-Bangoran, Haut-Mbomou, Nord, Extrême-Nord, Ouest, Nord-Ouest, Adamaoua, Sud-Ouest, Est, Littoral, Centre, Haut-Uele, Nord-Kivu, Ituri, Tshopo, Kwilu, Kasai, Sud-Kivu, Kongo-Central, Nord-Ubangi, Sud-Ubangi, Kasai-Central, Bas-Uele, Tanganyika, Lualaba, Kasai-Oriental, Kwango, Haut-Lomami, Haut-Katanga, Maniema, Kinshasa, Equateur, Lomami, Likouala, Brazzaville, Point-Noire, Pool, Bouenza, Cuvette, Lekoumou, Nzerekore, Boke, Kindia, Kankan, Faranah, Mamou, Labe, Kanifing Municipal Council, Central River, Upper River, West Coast, North Bank, Lower River, Bafata, Tombali, Cacheu, Sector Autonomo De Bissau, Biombo, Oio, Gabu, Bolama, Quinara, North, South, Artibonite, South-East, Grande'Anse, North-East, West, North-West, SULAWESI UTARA, SUMATERA UTARA, KALIMANTAN UTARA, JAWA BARAT, NUSA TENGGARA BARAT, NUSA TENGGARA TIMUR, SULAWESI SELATAN, JAMBI, JAWA TIMUR, KALIMANTAN SELATAN, BALI, BANTEN, JAWA TENGAH, RIAU, SUMATERA BARAT, KEPULAUAN RIAU, PAPUA, SULAWESI BARAT, BENGKULU, MALUKU UTARA, DAERAH ISTIMEWA YOGYAKARTA, KALIMANTAN BARAT, KALIMANTAN TENGAH, PAPUA BARAT, SUMATERA SELATAN, MALUKU, KEPULAUAN BANGKA BELITUNG, ACEH, DKI JAKARTA, SULAWESI TENGGARA, KALIMANTAN TIMUR, LAMPUNG, GORONTALO, SULAWESI TENGAH, Anbar, Babil, Baghdad, Basrah, Diyala, Dahuk, Erbil, Ninewa, Kerbala, Kirkuk, Missan, Muthanna, Najaf, Qadissiya, Salah al-Din, Sulaymaniyah, Thi-Qar, Wassit, Coast, North Eastern, Nairobi, Rift Valley, , Eastern, Central, Nyanza, Attapeu, Bokeo, Bolikhamxai, Champasack, Houaphan, Khammouan, Louangphabang, Louangnamtha, Oudomxai, Phongsaly, Salavan, Savannakhet, Sekong, Vientiane Capital, Vientiane, Xaignabouly, Xiengkhouang, Akkar, Mount Lebanon, Baalbek-El Hermel, Beirut, Bekaa, El Nabatieh, Nimba, Grand Kru, Grand Cape Mount, Gbarpolu, Grand Bassa, Rivercess, Montserrado, River Gee, Lofa, Bomi, Bong, Sinoe, Maryland, Margibi, Grand Gedeh, East, North Central, Uva, Western, Sabaragamuwa, Southern, Northern, North Western, Kidal, Gao, Tombouctou, Bamako, Kayes, Koulikoro, Mopti, Segou, Sikasso, Yangon, Rakhine, Shan (North), Kayin, Kachin, Shan (South), Mon, Tanintharyi, Mandalay, Kayah, Shan (East), Chin, Magway, Sagaing, Zambezia, Cabo_Delgado, Tete, Manica, Sofala, Maputo, Gaza, Niassa, Inhambane, Maputo City, Nampula, Hodh Ech Chargi, Hodh El Gharbi, Brakna, Adrar, Assaba, Guidimakha, Gorgol, Trarza, Tagant, Dakhlet-Nouadhibou, Nouakchott, Tiris-Zemmour, Central Region, Southern Region, Northern Region, Tillaberi, Tahoua, Agadez, Zinder, Dosso, Niamey, Maradi, Diffa, Abia, Borno, Yobe, Katsina, Kano, Kaduna, Gombe, Jigawa, Kebbi, Oyo, Sokoto, Zamfara, Lagos, Adamawa, Cordillera Administrative region, Region XIII, Region VI, Region V, Region III, Autonomous region in Muslim Mindanao, Region IV-A, Region VIII, Region VII, Region X, Region II, Region IV-B, Region XII, Region XI, Region I, National Capital region, Region IX, North Darfur, Blue Nile, Nile, Eastern Darfur, West Kordofan, Gedaref, West Darfur, North Kordofan, South Kordofan, Kassala, Khartoum, White Nile, South Darfur, Red Sea, Sennar, Al Gezira, Central Darfur, Tambacounda, Diourbel, Ziguinchor, Kaffrine, Dakar, Saint Louis, Fatick, Kolda, Louga, Kaolack, Kedougou, Matam, Thies, Sedhiou, Shabelle Hoose, Juba Hoose, Bay, Banadir, Shabelle Dhexe, Gedo, Hiraan, Woqooyi Galbeed, Awdal, Bari, Juba Dhexe, Togdheer, Nugaal, Galgaduud, Bakool, Sanaag, Mudug, Sool, Warrap, Unity, Jonglei, Northern Bahr el Ghazal, Upper Nile, Central Equatoria, Western Bahr el Ghazal, Eastern Equatoria, Western Equatoria, Lakes, Aleppo, Dar'a, Quneitra, Homs, Deir-ez-Zor, Damascus, Ar-Raqqa, Al-Hasakeh, Hama, As-Sweida, Rural Damascus, Tartous, Idleb, Lattakia, Ouaddai, Salamat, Wadi Fira, Sila, Ennedi Est, Batha, Tibesti, Logone Oriental, Logone Occidental, Guera, Hadjer Lamis, Lac, Mayo Kebbi Est, Chari Baguirmi, Ennedi Ouest, Borkou, Tandjile, Mandoul, Moyen Chari, Mayo Kebbi Ouest, Kanem, Barh El Gazal, Ndjaména, Al Dhale'e, Aden, Al Bayda, Al Maharah, Lahj, Al Jawf, Raymah, Al Hudaydah, Hajjah, Amran, Shabwah, Dhamar, Ibb, Sana'a, Al Mahwit, Marib, Hadramaut, Sa'ada, Amanat Al Asimah, Socotra, Taizz, Abyan

Graph and download economic data for Nominal Emerging Market Economies U.S. Dollar Index (DTWEXEMEGS) from 2006-01-02 to 2025-06-13 about trade-weighted, emerging markets, exchange rate, currency, goods, services, rate, indexes, and USA.

Concept: For the sake of time series organization, exchange rates have been grouped in two segments: I – Administered or free rates, covering the whole period since 1899, and II – Floating rates, which have been in place in the period of January 1989 to January 1999 and coexisted with the first segment. I – Administered or free exchange rates Available since 1899. In this period covered by the time series a great diversity of foreign exchange policies have been adopted. During some times, exchange rates were fixed (i.e. administered) by the monetary authorities, whereas in other times rates were freely agreed by market participants (i.e. they were free) and there were even times when both administered and free rates have existed at the same time. It should also be emphasized that between 1953 and 1961 a system of multiple exchange rates have been in place. For these time series the following kinds of exchange rates have been considered: - From January 1899 to January 1953 – administered rates; - From February 1953 to October 1961 – free rates, coming from the Exchange Portfolio of the Banco do Brasil. In this period administered rates have also been in place, with sell rates fixed on: CR$ 18,72, from Feb/1953 to Jul/1953; CR$ 18,82, from Aug/1953 to Dec/1958; and CR$ 18,92, from Jan/1959 to Feb/1961. In the beginning of the period most transactions were channeled through the administered rates system. As time went by, the number of transactions going through the free rates system grew. - From November 1961 to February 1990 – administered rates; and - From March 1990 onwards, free rates (Resolution 1.690 from 18.3.1990). The corresponding time series are the following ones: - Commercial dollar (sell and buy) – daily rates Available from 28.11.1984 onwards, refers to administered rates up to March 13th 1990 and to free rates from this date on (Resolution 1.690 from 18.3.1990). Administered rates are the ones fixed by the Central Bank. Free rates are the average of the rates of transactions effectively closed in the interbank market, weighted by the volume of sell transactions in the day. Outliers and rates presenting evidence of manipulation or other violations of the generally accepted market practices are excluded from the calculation. From March 1992 on, this rate was named PTAX. The series “American dollar – buy and sell – end of period” and “American dollar – buy and sell – period average” are derived respectively from these buy and sell daily rates. - American dollar – end of period Refers to the dollar administered rates expressed in Mil-réis for the period 1899-1941. The Mil-réis/dollar rates for the period 1899-1921 were computed from the pound/dollar parity. Discontinued in 1941. - American dollar (buy and sell) – end of period Annual rates are available from 1942 on and monthly rates from January 1953 on. End of period values correspond to the daily rate of the reference period´s last day. - American dollar (buy and sell) – period average Annual rates are available from 1942 on and monthly rates from January 1953 on. Buy and sell average rates are computed from the reference period daily rates. Monthly and annual rates were computed based on the running days of the reference up until December 1973. From January 1974 on, rates were weighted by the working days. II – Floating exchange rates Created by the Resolution 1.552 from 22.12.1988, this segment of the exchange market allowed markets participants to freely agree on the price of the foreign currency being negotiated. It initially covered only transactions related to international travel motivated by tourism, business, education and health. Later, other kinds of transactions were incorporated in the segment, such as gold, Brazilian investments abroad, unilateral transfers and some services. On 31.1.1999 this segment was terminated and the free and floating rates were merged. Series related to this segment are the following: - Tourism dollar (sell) Daily rates in the floating rate segment, available for the period between 27.5.1993 to 29.1.1999. The computation of this rate takes into account transactions in the interbank market weighted by the volume of sell transactions. Outliers and rates presenting evidence of manipulation or other violations of the generally accepted market practices are excluded from the computation. The series “American dollar – buy and sell – end of period” and “American dollar – buy and sell – period average” are derived respectively from these buy and sell daily rates. - American dollar (buy and sell) – end of period Rates for the last day of the reference period, computed for both buy and sell transactions. - American dollar (buy and sell) – period average Average of the daily rates of the reference period (month or year), computed for buy and sell transactions, weighted by the number of working days. Source: Central Bank Information System – PTAX800 transaction 10813-exchange-rate---free---united-states-dollar-buy 10813-exchange-rate---free---united-states-dollar-buy

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Ouaddai, Salamat, Wadi Fira, Sila, Ennedi Est, Batha, Tibesti, Logone Oriental, Logone Occidental, Guera, Hadjer Lamis, Lac, Mayo Kebbi Est, Chari Baguirmi, Ennedi Ouest, Borkou, Tandjile, Mandoul, Moyen Chari, Mayo Kebbi Ouest, Kanem, Barh El Gazal, Ndjaména, Market Average

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 ***, whereas analysts suspected it should be around ** 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 **** 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.

Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for China (CCRETT01CNM661N) from Jan 1970 to May 2025 about China, exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, and price.

Currency Exchange Bureau Software Market Outlook

The global currency exchange bureau software market size is poised to witness significant growth, forecasted to expand from USD 1.2 billion in 2023 to approximately USD 2.5 billion by 2032, reflecting a robust CAGR of 8.5%. This growth is primarily driven by the increasing demand for efficient, secure, and user-friendly platforms in financial transactions, coupled with the rise in international trade and tourism. The technology underpinning these software solutions enables currency exchange bureaus to streamline their operations, reduce processing time, and enhance the customer experience, further fueling market expansion.

One of the key growth drivers of the currency exchange bureau software market is the rapid globalization and the subsequent increase in cross-border transactions. As businesses and individuals engage more in international trade and travel, the demand for secure and efficient currency exchange solutions surges. Modern software provides real-time exchange rates, ensuring that customers receive the most accurate information for their transactions. Additionally, advancements in fintech are enabling these platforms to integrate with other financial services, offering a comprehensive financial solution that attracts both small and large enterprises. The integration of advanced technologies like AI and machine learning into these systems further enhances their capabilities, helping organizations analyze market trends and optimize their service offerings.

Another significant factor contributing to the market's growth is the rising adoption of mobile banking and digital payment systems. With the proliferation of smartphones and increased internet penetration, consumers are more inclined towards digital transactions, including currency exchange. Mobile applications offering currency conversion, rate alerts, and transaction history are becoming increasingly popular, compelling software providers to innovate and enhance their mobile platforms. Moreover, the emphasis on cybersecurity and data protection is prompting currency exchange bureaus to adopt sophisticated software solutions that safeguard customer information and prevent fraud, thereby boosting market growth.

The market is also benefitting from regulatory advancements and supportive government policies aimed at enhancing financial inclusivity and transparency. Many governments are encouraging the modernization of financial services, providing a favorable environment for the adoption of currency exchange software solutions. These policies not only enhance operational transparency but also build consumer trust, which is crucial for market growth. Additionally, the increasing demand for compliance with international financial regulations is driving the implementation of advanced software solutions that ensure adherence to these standards, thereby mitigating risks associated with non-compliance.

Currency Converter Apps have emerged as a pivotal tool for both consumers and businesses involved in international transactions. These apps offer real-time exchange rates, allowing users to make informed decisions when converting currencies. By providing a convenient platform for currency conversion, these apps enhance the user experience, making it easier for travelers and businesses to handle foreign currency exchanges efficiently. The integration of advanced features such as rate alerts and historical data analysis further empowers users to optimize their currency transactions. As the demand for seamless and accurate currency conversion continues to grow, the role of currency converter apps in the financial ecosystem becomes increasingly significant, complementing the broader currency exchange bureau software market.

Regionally, the Asia Pacific market is expected to witness the highest growth rate due to the rapid economic development and increasing number of international travelers in the region. Countries like China, India, and Japan are major contributors to this growth, supported by their large population and high rates of foreign exchange transactions. North America continues to hold a significant share of the market, driven by technological advancements and a well-established financial services sector. Meanwhile, Europe is not far behind, with a growing number of financial institutions adopting these technologies to improve operational efficiency. Latin America and the Middle East & Africa, while currently smaller markets, are anticipated to grow steadily due to increasing investments in digital infrastructur

Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for Euro Area (19 Countries) (CCRETT01EZM661N) from Jan 1970 to May 2025 about Euro Area, Europe, exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, and price.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Anbar, Babil, Baghdad, Basrah, Diyala, Dahuk, Erbil, Ninewa, Kerbala, Kirkuk, Missan, Muthanna, Najaf, Qadissiya, Salah al-Din, Sulaymaniyah, Thi-Qar, Wassit, Market Average

The foreign currency exchange (FX) service market is experiencing robust growth, driven by the increasing globalization of businesses and the surge in international travel and cross-border transactions. The market, estimated at $5 trillion in 2025, is projected to expand at a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rise of e-commerce and digital payments is significantly impacting the demand for convenient and cost-effective online foreign exchange services. Secondly, the increasing frequency of international business transactions, particularly among small and medium-sized enterprises (SMEs), is driving demand for tailored FX solutions. Finally, fluctuating exchange rates and the need for hedging strategies are creating opportunities for specialized FX service providers. The market is segmented by application (individual and enterprise) and service type (online and in-store). While the online segment dominates due to its convenience and accessibility, the in-store segment continues to hold relevance for customers requiring immediate service and personalized support. Geographic distribution of the market reveals strong regional variations. North America and Europe currently hold the largest market shares, driven by their established financial infrastructure and large economies. However, the Asia-Pacific region is expected to witness significant growth in the coming years fueled by rapid economic expansion and increasing international trade within the region. The competitive landscape is characterized by a mix of large multinational banks (like Citigroup and BNP Paribas) offering comprehensive FX services alongside specialized fintech companies (like CurrencyWave and OANDA) focusing on niche offerings and innovative technology. The presence of numerous players suggests considerable competition and a focus on differentiation through pricing strategies, service offerings, and technological advancements. Regulatory changes and security concerns remain key restraints that impact market growth.

Sri Lanka LK: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data was reported at 0.317 % in 2017. This records an increase from the previous number of 0.313 % for 2016. Sri Lanka LK: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data is updated yearly, averaging 0.221 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 0.350 % in 2011 and a record low of 0.189 % in 2002. Sri Lanka LK: PPP Conversion Factor: to Market Exchange Rate: Price Level Ratio data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sri Lanka – Table LK.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. Purchasing power parity conversion factor is the number of units of a country's currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. The ratio of PPP conversion factor to market exchange rate is the result obtained by dividing the PPP conversion factor by the market exchange rate. The ratio, also referred to as the national price level, makes it possible to compare the cost of the bundle of goods that make up gross domestic product (GDP) across countries. It tells how many dollars are needed to buy a dollar's worth of goods in the country as compared to the United States. PPP conversion factors are based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; ;

Uzbekistan Official Exchange Rate: Period Average: Local Currency to USD data was reported at 12,940.417 USD/UZS in 2025. This records an increase from the previous number of 12,650.914 USD/UZS for 2024. Uzbekistan Official Exchange Rate: Period Average: Local Currency to USD data is updated yearly, averaging 1,525.856 USD/UZS from Dec 1994 (Median) to 2025, with 32 observations. The data reached an all-time high of 12,940.417 USD/UZS in 2025 and a record low of 35.309 USD/UZS in 1995. Uzbekistan Official Exchange Rate: Period Average: Local Currency to USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uzbekistan – Table UZ.World Bank.GEM: Foreign Exchange Rates: Annual. Official exchange rate refers to the exchange rate determined by national authorities or to the rate determined in the legally sanctioned exchange market. It is calculated as an annual average based on monthly averages (local currency units relative to the U.S. dollar).

Daily bulletin time series available since 2/1/2002, for the Euro, and since 28/11/1984, for the other currencies. For the American Dollar, this data set shows administered rates until March, 1990 and free rates from then on (Resolution 1690/1990). Administered rates are those set by the Central Bank of Brazil; from March, 1992, this rate started being called Ptax rate (close). Until 30/6/2011, this rate was calculated as the average rate, weighed by volume, of all interbank operations traded on that day. Starting on 1/7/2011 (Circular 3506/2010), the Ptax rate calculation corresponds to the arithmetic average of four daily quotes provided by Central Bank of Brazil’s foreign exchange dealers; the quotes must reflect market conditions at that time. Parities of the other currencies against the American Dollar (USD) are obtained from information agencies. Currencies rates against the Brazilian currency are calculated dividing the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type A currencies, and multiplying the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type B currencies. Available currencies: Danish Krone (DKK) Type A Norwegian Krone (NOK) Type A Swedish Krona (SEK) Type A American Dollar (USD) Type A Australian Dollar (AUD) Type B Canadian Dollar (CAD) Type A Euro (EUR) Type B Swiss Franc (CHF) Type A Japanese Yen (JPY) Type A British Pound (GBP) Type B Unit of measure: Type A currencies: Parity (American Dollar): quantity in the currency per one unit of American Dollar (USD); Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Type B currencies: Parity (American Dollar): quantity in American Dollars (USD) per one unit of the currency; Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Example of how to calculate type A currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Canadian Dollar (CAD) as the foreign currency: CADBRL bid rate = USDBRL bid rate ÷ USDCAD offer parity CADBRL offer rate = USDBRL offer rate ÷ USDCAD bid parity Example of how to calculate type B currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Euro (EUR) as the foreign currency: EURBRL bid rate = EURUSD bid parity × USDBRL bid rate EURBRL offer rate = EURUSD offer parity × USDBRL offer rate Source: Refinitiv, except for USDBRL The Central Bank assumes no responsibility whatsoever for non-simultaneity or any lack of information, as well as for possible errors in currency parities or any other errors, except the parity of the United States dollar in relation to the Real. The institution also assumes no responsibilty for delays or the unavailability of telecommunications services, interruptions, failures or imprecisions in the providing of the services or information. The Central Bank likewise assumes no responsibility for any losses or damages consequent upon such interruptions, delays, failings or imperfections, as well as for the inadequate use of the information contained in the transaction. af829095-9d8c-4c1d-a77f-48e4d51f7a71 exchange-rates-daily-bulletins

Gain exclusive access to specialist Foreign Exchange (FX) data, and the tools to manage trading analysis, risk and operations with LSEG's FX Pricing Data.