Gann Method Forex Trading

William Delbert Gann (1878–1955) was a successful stocks and commodities trader who wrote seven books and many short courses on how to trade. Gann’s success as a trader rested on the forecasting method he developed from his research between 1902 and 1908. It helps to understand William Gann Trading Rules.

This article examines whether Gann’s approach can be applied to the currency markets. The evidence suggests that Gann did not trade currencies; I look at why that was, whether his method can be used in today’s forex market, and the practical problems that come with it.

Gann’s Method in the Forex Market

Why didn’t Gann trade currencies?

Gann does not mention currency trading in his books and courses, nor in his various advisory services or his personal trading records, so it is reasonable to assume he did not trade them. To work out why, we first need to look at how his method works.

Time cycles form the basis of Gann’s approach, and he referred to cycles throughout his writings, including:

“Time is the most important factor in determining market movements, because the future is a repetition of the past, and every market movement works out a time relation to some previous time cycle” (Gann, 1946).

“Experience has taught me that nothing can stop the trend as long as the time cycle shows an uptrend, and nothing can stop its decline as long as the time cycle points down. Securities can rise on bad news and fall on good news” (Gann, 1949).

Gann summed up his approach in the following statement:

“In making my calculations on the stock market, or any future event, I get the past history and find out what cycle we are in, then project the curve for the future, which is a repetition of past market movements” (Gann, 1927).

Gann’s approach therefore consists of three stages:

1. Obtain a detailed price history of the financial instrument.
2. Analyse that price history to identify the underlying cycles driving the instrument.
3. Use the future progression of those cycles to estimate where prices may move next.

A necessary condition for applying Gann’s method is that the instrument’s price should fluctuate freely according to its underlying cycles — both historically (over the period covered by the price history) and in the future.

The evidence suggests, however, that between 1908 (when Gann completed the development of his method) and 1955 (when he died), this condition generally did not exist in the currency markets. Specifically, the major currencies were usually not free to fluctuate.

A detailed history of currencies from 1908 to 1955 is beyond the scope of this article, but here is a summary of the exchange-rate regimes in the leading industrial countries during that period, which points to the restrictions and controls on currency prices:

• 1908–1914: the gold standard, with fixed exchange rates
• 1914–1918: World War I — restrictions on gold and capital controls
• 1919–1927: a period of floating, later managed, exchange rates
• 1928–1931: the major currencies had returned to the gold standard by 1928; from 1931 they began leaving it in response to the Great Depression
• 1931–1939: the interwar period of managed floating exchange rates
• 1939–1945: World War II
• 1945–1955: the Bretton Woods system of fixed exchange rates

In short, Gann appears not to have traded the currency market because, from 1908 to 1955, the major currencies were usually prevented from fluctuating freely — which invalidated his method.

Applying Gann’s method to today’s forex market

More than 60 years have passed since Gann’s death. The Bretton Woods system of fixed exchange rates, in force during the last decade of his life, collapsed in 1971–1973. Today the major currencies (the Australian dollar, British pound, Canadian dollar, euro, Japanese yen, Swiss franc and US dollar) appear to float freely, monitored by their central banks — all of which are mandated to maintain economic stability and can therefore intervene in the currency market when they consider it necessary. For example, the Swiss National Bank pegged the Swiss franc to the euro from September 2011 to January 2015.

The key question I will now examine is: can Gann’s method be applied to the currency market today?

As noted above, the first stage is to obtain a detailed price history of the instrument. I decided to start with the US dollar, so I obtained daily price charts of the US Dollar Index (that is, the dollar measured against a trade-weighted basket of currencies) from 1988 to 2017. I chose a 30-year window because it is long enough to cover a range of market conditions, and a start date of 1 January 1988 because that was 15 years after the end of the Bretton Woods system of fixed exchange rates — by which time, I hoped, the US dollar and the other major currencies were fluctuating freely according to their underlying cycles.

The second stage, as noted above, is to analyse the price history to identify the underlying cycles. I found it fairly straightforward to identify the set of cycles driving the US dollar, and so concluded that Gann’s method could be applied to today’s currency markets.

Unfortunately, my conclusion was premature. More specifically, when I then applied the same methodology to the other major currencies (as listed above: the Australian dollar, British pound, Canadian dollar, euro, Japanese yen and Swiss franc), I could not clearly identify any underlying cycles — whether I analysed a currency index or various currency pairs.

My first thought was that I had perhaps made a mistake in my analysis of the US dollar; that the proponents of the efficient-market hypothesis were right after all; that market prices are essentially random, making the search for underlying cycles in a price history naive and futile. I soon came to my senses, however, remembering that I had already applied Gann’s approach successfully to a range of stocks and commodities.

I therefore assumed that currencies present a specific problem: individual stocks and commodities are, in essence, single financial instruments measured in a currency that is relatively stable compared with the stock or commodity itself. A currency pair, by contrast, is essentially two financial instruments fluctuating simultaneously according to their own underlying cycles, which makes those cycles difficult to identify.

I then supposed that I had managed to identify the US dollar’s underlying cycles from its index price history because its cycles dominate the basket of currencies it is measured against. The underlying cycles of the other major currencies, by contrast, are relatively evenly balanced. The cycles driving a given currency are therefore obscured, whether one studies a currency index or a currency pair.

I concluded that in order to identify the underlying cycles driving a particular currency, it is necessary to measure that currency in terms of a second, relatively inert currency. So I set out to find a currency issued by a country that is both economically and politically stable, with few natural resources (such as minerals or energy assets, whose own cycles might affect its currency). The New Zealand dollar proved a suitable choice.

I then examined the major currencies using the New Zealand dollar as the reference currency, and in each case the underlying cycles driving the currency could eventually be identified. I then re-examined the US dollar, this time measured in New Zealand dollars, and the results confirmed my earlier findings about its underlying cycles.

Next I examined a set of minor currencies: the Brazilian real, Indian rupee, Mexican peso, Norwegian krone, Russian ruble, South African rand, South Korean won, Swedish krona and Turkish lira. Again I used the New Zealand dollar as the reference currency, and in each case the underlying cycles driving the currency were identified.

I excluded some currencies from this analysis because they are pegged to others, which again invalidates Gann’s method. These were the Chinese yuan (partially pegged to a basket of currencies), the Danish krone (pegged to the euro), the Hong Kong dollar (allowed to trade in a band tied to the US dollar) and the Singapore dollar (stabilised against an undisclosed basket of currencies).

In short, my research covered the 21 most-traded currencies by value, which together account for around 97% of foreign-exchange turnover. More specifically, underlying cycles were identified for 16 currencies; four were excluded because they are pegged to other currencies; and the underlying cycles of the New Zealand dollar itself could not be identified, given the apparent absence of a more stable reference currency.

I then concluded that Gann’s method can be applied in the currency market today — provided that, in order to identify the underlying cycles driving a particular currency, you analyse the price history of that currency measured in New Zealand dollars. As with any form of cycle analysis, what it produces are indications, not certainties: signals can fail.

Potential problems in the practical application of Gann’s method to forex

1. Identifying the underlying cycles that drive a currency.

As discussed above, currencies pose a particular problem because a currency pair is essentially two financial instruments fluctuating simultaneously according to their underlying cycles, making it difficult to identify the cycles driving each one.

The solution, when analysing a given currency, is to use the New Zealand dollar as the reference currency. This works because the currency is relatively inert, apparently reflecting the stability of the country and its small economy (the IMF ranked New Zealand’s GDP 53rd in the world in 2016).

2. A currency stops behaving according to its underlying cycles.

Gann’s method breaks down when a financial instrument stops behaving according to its underlying cycles. In currencies, the main cause of this problem is central-bank intervention. The solution is to avoid such currencies, in the same way that Gann recommended avoiding stocks that behave similarly:

“The kind of stocks to trade in are those that are active and those that follow the rules and a definite trend. There are always cheap stocks and some stocks that do not follow the rules, and these stocks should be left alone” (Gann, 1936).

3. A currency’s low sensitivity to its underlying cycles.

According to Gann’s approach, the price of a financial instrument is driven by cycles. One consequence is that the larger the amount of the instrument in issue, the stronger the cycles needed to move it:

“Do not expect General Motors to make a big advance because Studebaker has already advanced. You must consider that it has a capital stock of fifty million shares, while Studebaker has only 750,000 shares. It requires far greater buying power to move a stock with many millions of shares than one with only 750,000” (Gann, 1923).

The currency market is one of the largest financial markets in the world. It therefore shows particularly low sensitivity to its underlying cycles, and only the strongest cycles produce major moves.

One suggested workaround is to trade so-called digital currencies (for example, Bitcoin or Ethereum), since these usually have a price history from which underlying cycles can be identified and used to estimate future price movement, and the amount of currency issued appears to be tightly controlled. Unfortunately, there also appears to be a significant risk that these currencies will not behave according to their underlying cycles in the future, owing to factors such as fraud, hacking, infrastructure failure and regulatory intervention.

4. A breakdown in the geometry of the currency market.

Although cycles are the basis of Gann’s approach, he also found that market prices usually unfold in a coherent way in response to those cycles — hence there is a geometry to stock and commodity markets.

As a result, in his analysis of stock and commodity markets, Gann analysed both the underlying cycles and the resulting market geometry. In the currency market, however, that geometry usually breaks down because of the simultaneous price fluctuations of each component of a currency pair.

Although the New Zealand dollar is stable enough as a reference currency to allow the cycles driving a given currency to be identified, it is usually not stable enough to allow market geometry to be used as a complementary analytical method. Unlike in the stock and commodity markets, then, analysis of the currency market can rely only on the underlying cycles.

To recap: a necessary condition for applying Gann’s method is that a financial instrument should fluctuate freely according to its underlying cycles, both historically (over the period covered by the price history) and in the future.

That condition generally did not exist in the currency market during Gann’s lifetime, which is why he did not trade currencies. It does generally exist in today’s currency markets, so his method can now be applied there. The exception is pegged currencies, which do not fluctuate freely.

One key problem in applying it is identifying the cycles that drive a particular currency; the solution is to use the New Zealand dollar as the reference currency. Another problem arises when a currency stops behaving according to its underlying cycles for a period of time, usually because of central-bank intervention. The third problem is a currency’s low sensitivity to its underlying cycles, usually caused by the large amount of currency in issue. The final problem is the breakdown of market geometry, usually caused by the simultaneous price fluctuations of each component of a currency pair.

Since Gann’s approach can be applied to any financial instrument that fluctuates freely according to its underlying cycles — and where a detailed price history is available so those cycles can be identified — today’s investment universe essentially includes all stocks, all commodities, and all currencies that are not pegged to other currencies.

Frequently Asked Questions

What are Gann angles?

A Gann angle is a diagonal line that moves at a uniform rate of speed. A trend line is created by connecting bottoms to bottoms in an uptrend and tops to tops in a downtrend. The benefit of drawing a Gann angle compared with a trend line is that it moves at a uniform rate of speed.

What is Gann analysis?

Gann believed that the market follows a natural time cycle. His theory was based on natural geometric shapes and ancient mathematics. Gann theory states that the patterns and angles of an asset in the market can be used as an indicator of possible future price movement.

How do I learn digital analysis?

To work as a digital analyst, you need at least a university degree in finance, logistics, mathematics or statistics, and you should have experience with multiple analysis tools and software.

What is digital analysis in trading?

Digital analysis refers to trade enabled by electronic means — via telecommunications and/or information and communication technology services — and covers trade in both goods and services. It affects all sectors of the economy and is highly important for trading in the markets.

How do you become a successful trader?

1. Always use a trading plan.
2. Treat trading like a business.
3. Use technology.
4. Protect your trading capital.
5. Study the markets.
6. Only risk what you can afford to lose.
7. Develop a trading methodology.
8. Always use a stop-loss order.

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