Trading characteristics

Trading characteristics
Most traded currencies by value
Currency distribution of global foreign exchange market turnover[3]Rank Currency ISO 4217 code
(Symbol) % daily share

 1  United States dollar USD ($) 84.9%
2  Euro EUR (€) 39.1%
3  Japanese yen JPY (¥) 19.0%
4  Pound sterling GBP (£) 12.9%
5  Australian dollar AUD ($) 7.6%
6  Swiss franc CHF (Fr) 6.4%
7  Canadian dollar CAD ($) 5.3%
8  Hong Kong dollar HKD ($) 2.4%
9  Swedish krona SEK (kr) 2.2%
10  New Zealand dollar NZD ($) 1.6%
11  South Korean won KRW (₩) 1.5%
12  Singapore dollar SGD ($) 1.4%
13  Norwegian krone NOK (kr) 1.3%
14  Mexican peso MXN ($) 1.3%
15  Indian rupee INR () 0.9%
Other 12.2%
Total[15] 200%


There is no unified or centrally cleared market for the majority of trades, and there is very little cross-border regulation. Due to the over-the-counter (OTC) nature of currency markets, there are rather a number of interconnected marketplaces, where different currencies instruments are traded. This implies that there is not a single exchange rate but rather a number of different rates (prices), depending on what bank or market maker is trading, and where it is. In practice the rates are often very close, otherwise they could be exploited by arbitrageurs instantaneously. Due to London's dominance in the market, a particular currency's quoted price is usually the London market price. Major trading exchanges include EBS and Reuters, while major banks also offer trading systems. A joint venture of the Chicago Mercantile Exchange and Reuters, called Fxmarketspace opened in 2007 and aspired but failed to the role of a central market clearing mechanism.[citation needed]

The main trading center is London, but New York, Tokyo, Hong Kong and Singapore are all important centers as well. Banks throughout the world participate. Currency trading happens continuously throughout the day; as the Asian trading session ends, the European session begins, followed by the North American session and then back to the Asian session, excluding weekends.

Fluctuations in exchange rates are usually caused by actual monetary flows as well as by expectations of changes in monetary flows caused by changes in gross domestic product (GDP) growth, inflation (purchasing power parity theory), interest rates (interest rate parity, Domestic Fisher effect, International Fisher effect), budget and trade deficits or surpluses, large cross-border M&A deals and other macroeconomic conditions. Major news is released publicly, often on scheduled dates, so many people have access to the same news at the same time. However, the large banks have an important advantage; they can see their customers' order flow.

Currencies are traded against one another. Each currency pair thus constitutes an individual trading product and is traditionally noted XXXYYY or XXX/YYY, where XXX and YYY are the ISO 4217 international three-letter code of the currencies involved. The first currency (XXX) is the base currency that is quoted relative to the second currency (YYY), called the counter currency (or quote currency). For instance, the quotation EURUSD (EUR/USD) 1.5465 is the price of the euro expressed in US dollars, meaning 1 euro = 1.5465 dollars. The market convention is to quote most exchange rates against the USD with the US dollar as the base currency (e.g. USDJPY, USDCAD, USDCHF). The exceptions are the British pound (GBP), Australian dollar (AUD), the New Zealand dollar (NZD) and the euro (EUR) where the USD is the counter currency (e.g. GBPUSD, AUDUSD, NZDUSD, EURUSD).

The factors affecting XXX will affect both XXXYYY and XXXZZZ. This causes positive currency correlation between XXXYYY and XXXZZZ.

On the spot market, according to the 2010 Triennial Survey, the most heavily traded bilateral currency pairs were:
EURUSD: 28%
USDJPY: 14%
GBPUSD (also called cable): 9%

and the US currency was involved in 84.9% of transactions, followed by the euro (39.1%), the yen (19.0%), and sterling (12.9%) (see table). Volume percentages for all individual currencies should add up to 200%, as each transaction involves two currencies.

Trading in the euro has grown considerably since the currency's creation in January 1999, and how long the foreign exchange market will remain dollar-centered is open to debate. Until recently, trading the euro versus a non-European currency ZZZ would have usually involved two trades: EURUSD and USDZZZ. The exception to this is EURJPY, which is an established traded currency pair in the interbank spot market. As the dollar's value has eroded during 2008, interest in using the euro as reference currency for prices in commodities (such as oil), as well as a larger component of foreign reserves by banks, has increased dramatically. Transactions in the currencies of commodity-producing countries, such as AUD, NZD, CAD, have also increased.

Economic factors

Economic factors

These include: (a)economic policy, disseminated by government agencies and central banks, (b)economic conditions, generally revealed through economic reports, and other economic indicators.
Economic policy comprises government fiscal policy (budget/spending practices) and monetary policy (the means by which a government's central bank influences the supply and "cost" of money, which is reflected by the level of interest rates).
Government budget deficits or surpluses: The market usually reacts negatively to widening government budget deficits, and positively to narrowing budget deficits. The impact is reflected in the value of a country's
currency.

Balance of trade levels and trends: The trade flow between countries illustrates the demand for goods and services, which in turn indicates demand for a country's currency to conduct trade. Surpluses and deficits in trade of goods and services reflect the competitiveness of a nation's economy. For example, trade deficits may have a negative impact on a nation's currency.

Inflation levels and trends: Typically a currency will lose value if there is a high level of inflation in the country or if inflation levels are perceived to be rising. This is because inflation erodes purchasing power, thus demand, for that particular currency. However, a currency may sometimes strengthen when inflation rises because of expectations that the central bank will raise short-term interest rates to combat rising inflation.
Economic growth and health: Reports such as GDP, employment levels, retail sales, capacity utilization and others, detail the levels of a country's economic growth and health. Generally, the more healthy and robust a country's economy, the better its currency will perform, and the more demand for it there will be.
Productivity of an economy: Increasing productivity in an economy should positively influence the value of its currency. Its effects are more prominent if the increase is in the traded sector

High-frequency trading

High-frequency trading (HFT) is the use of sophisticated technological tools to trade securities like stocks or options, and is typically characterized by several distinguishing features
HFT is highly quantitative, employing computerized algorithms to analyze incoming market data and implement proprietary trading strategies;

HFT usually implies a firm holds an investment position only for very brief periods of time - even just seconds - and rapidly trades into and out of those positions, sometimes thousands or tens of thousands of times a day;
HFT firms typically end a trading day with no net investment position in the securities they trade;
HFT operations are usually found in proprietary firms or on proprietary trading desks in larger, diversified firms;
HFT strategies are usually very sensitive to the processing speed of markets and of their own access to the market.

In high-frequency trading, programs analyze market data to capture trading opportunities that may open up for only a fraction of a second to several hours.High-frequency trading (HFT) uses computer programs and sometimes specialised hardware  to hold short-term positions in equities, options, futures, ETFs, currencies, and other financial instruments that possess electronic trading capability.[4] High-frequency traders compete on a basis of speed with other high-frequency traders, not long-term investors (who typically look for opportunities over a period of weeks, months, or years), and compete with each other for very small, consistent profits. As a result, high-frequency trading has been shown to have a potential Sharpe ratio (measure of reward per unit of risk) thousands of times higher than the traditional buy-and-hold strategies. By 2010 high-frequency trading accounted for over 70% of equity trades taking place in the US and was rapidly growing in popularity in Europe and Asia. Aiming to capture just a fraction of a penny per share or currency unit on every trade, high-frequency traders move in and out of such short-term positions several times each day. Fractions of a penny accumulate fast to produce significantly positive results at the end of every day. High-frequency trading firms do not employ significant leverage, do not accumulate positions, and typically liquidate their entire portfolios on a daily basis.

One financial industry source claims algorithmic trading, including high-frequency trading, substantially improves market liquidity.An academic study shows additional benefits, including lowering the costs of trading,increasing the informativeness of quotes,improved linkage between markets, and other positive spillover effects, at least in quiescent or stable markets; the authors of this study also note that "it remains an open question whether algorithmic trading and algorithmic liquidity supply are equally beneficial in more turbulent or declining markets...algorithmic liquidity suppliers may simply turn off their machines when markets spike downward."Also noteworthy is that HFT only takes place in markets that are already deemed liquid, hence calling its necessity into question.

Algorithmic and high-frequency trading were both implicated in the May 6, 2010 Flash Crash, when high-frequency liquidity providers were in fact found to have withdrawn from the market. A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010."