An Introduction to Foreign Exchange Trading
Reference: The Art of Currency Trading (2019) by Brent Donnelly and published by Wiley.
The “FX market is the largest globally. It has over US$6.6 trillion of trading volume or trade value daily” - Mr. Loh Boon Chye, CEO of SGX (September 2020).
Reference URL: https://www.channelnewsasia.com/news/business/money-mind-interview-loh-boon-chye-sgx-foreign-exchange-13062772
Foreign exchange trading or most other financial trading in any asset class encompass a number of different disciplines such as:
technical analysis
macro fundamentals
behavioural finance
risk management
market sentiment
cross market correlation
To succeed in Forex trading, you need to master the approach of using multiple types of analysis to reach stronger and more sophisticated conclusions, then understand your own psychology and risk management, to trade with higher confidence. You need to develop your own thought process on how to trade.
You don’t want to rely on a one-dimensional over-emphasis of simple, short-term technical patterns, while ignoring fundamentals, psychology, positioning and proper risk management. Currency trading is like playing the piano. The mechanics are very simple, just press a few keys. But mastery takes a long while.
Trading is a seriously intellectual pursuit that is also incredibly fun. The joy of attempting to solve an unsolvable puzzle. The nearly impossible daily test of discipline and self control. The emotional roller coaster of instant feedback, frequent disappointments, sudden euphoria and nearly unbearable periods of crushing self-doubt.
But don’t worry about all that. Just enjoy the ride!
How it started
The mechanics and structure of foreign exchange markets and how currency trading works:
In 1944, the Bretton Woods system of monetary management established a fixed gold exchange standard for the major currencies. The IMF and World Bank also formed at this time. Under the Bretton Woods system, countries kept their currencies fixed to the dollar. International balances were settled in dollars, using a fixed conversion rate of US$35/ounce for gold. This system worked as long as money was flowing into the US. However, it broke down when the opposite happened when global trade increased and the Vietnam War and the OPEC oil embargoes hit.
On August 15, 1971, Richard Nixon addressed the nation, announcing the end of the gold standard and the implementation of new wage and price controls. By 1973, exchange rates were flexible and currency trading as we know it began. One by one, most countries moved to a floating exchange rate, although some remained on fixed or managed exchange rates, even up to this day.
The system of floating currencies backed only by faith of the issuing country (and not gold), is known as a fiat currency system. The value of currencies float based on market perceptions of relative value.
FX Trading from the 1970s
The Telex Era (1971 to 1981): In the 1970s and 80s, currency trading was conducted primarily over telex machines and telephone. A small group of bank traders (primarily in London and New York) executed transactions for multinational corporations and high net worth individuals. Currency futures were launched on May 16, 1972, allowing non-bank players a way to get involved in currency markets, but still restricted to high-net-worth individuals and sophisticated speculators.
Direct Dealing Era (1981 to 1992): In 1981, Reuters launched a computerized dealing monitor service where traders used human brokers for most of the transactions.
The Electonic Era (1992 to 2001): In 1992, Reuters launched Dealing 2000, an online trading and matching platform that allowed banks to show buying and selling interest (bids and offers) to other banks electronically. Around the same time, EBS (Electronic Brokerage Services) launched a similar product to start the electronic era of FX trading. As electronic platforms increased liquidity and transparency, the direct market between banks closed as there were no longer a need for banks to trade directly.
The Algo Era (2001 to Present): In the early 2000s, hedge funds developed algorithms to trade electronically on EBS and Reuters. Algorithms became more and more involved that now, algorithms do more trading than humans on the FX market, estimated at around a 60/40 split. By the late 1990s and early 2000s, the birth of retail forex came about as the internet allowed individuals with limited capital to trade FX using leverage. This type of trading has now ballooned and now makes up a small but important part of foreign exchange trading, especially in Japan.
The importance of FX Liquidity
FX liquidity refers to a currency pair’s ability to be bought and sold without creating a major impact on its exchange rate.
A currency pair is regarded to have a high level of liquidity when it can be bought or sold easily and it has significant trading activity.
Having greater FX liquidity enables an easier transaction flow and makes pricing more competitive.
FX Trading Algorithm Strategies
Correlation: Algorithms watch other markets and trade FX based on those moves. For example, if oil rallies, an algorithm might buy Canadian dollars if Canada is a large crude oil exporter.
Arbitrage: Algorithms try to profit from disparities in price between trading venues. If Citibank is willing to buy at 50 and EBS is willing to sell at 49, the algorithm will buy and sell for a nearly risk-free profit.
Trends: These algorithms look for intra-day trends and buy pull-backs to a moving average or sell breakouts.
Mean reversions: As opposed to trend algorithms, this is based on the simple assumption that while the price of a currency will fluctuate between highs and lows, it will return to its mean or “true value”. Algorithms rely on selling rallies and buying dips, in an effort to capture profits when returning to its mean. There are risks associated with this approach, especially when markets are trending in a particular direction. The mean can be calculated by using something like a 50 day smooth moving average or a 100 day moving average.
Data trading: Algorithms read released economic data and trade instantaneously based on pre-programmed estimates of how much the market will move.
Market trading: Algorithms show a bid and an offer in the market and attempts to earn a spread and profit from intra-day fluctuations.
Gamma trading: This algorithm buys options and then trades the gamma electronically to generate income in excess of the cost of the option.