Forex Market Research

A trading idea that is congruent with your market’s characteristics is likely to perform better. Market behaviour can be quantified in countless ways, but I typically focus on historical volatility and ability to trend well.

This article will illustrate some methods to quantify these characteristics, giving you a head start in finding a trading solution.

Since I predominantly trade forex, the following market research will focus on six liquid forex markets on the hourly timeframe: EURUSD, GBPUSD, USDJPY, GBPJPY, EURJPY, EURGBP.

You can, of course, apply the following methods to any market of your choice.

Trending Tendency

Most strategies can be broadly categorized as being either trend following or countertrend. It makes sense to develop trend strategies for traditionally trending markets, and countertrend strategies for traditionally ranging markets.

For example, you may want to trade a trend strategy on the short-term interest rates, or a countertrend strategy on the intraday S&P500.

Even without quantifying the market’s behaviour, having an understanding of the market’s fundamentals will help you get a feel of it. Most stocks are not known to trend well because investors’ valuations of the company are highly subjective and tend to vary. The S&P500, being a market index measuring the performance of 500 companies, is even less likely to trend well (on the short-term). On the other hand, interest rates track monetary policy and tend to have sustained trends.

I always quantify the market’s tendency to trend before developing a trading idea for it. I will highlight two methods of doing so:

  1. Using Kaufman’s Efficiency Ratio
  2. Backtesting basic trend strategies on the markets

Kaufman’s Efficiency Ratio

In his extremely comprehensive book ‘Trading Systems and Methods’, Perry Kaufman used the ER to quantify market noise. Noise is random price movement that surrounds any underlying direction.

The ER is defined as the net change in price divided by the sum of the individual price changes over the same period. It is a essentially a measure of how smoothly the prices move from point to point over the calculation period. Noisy markets have a low ER, while trending markets have a higher ER.

The lookback period used is discretionary, but should not exceed the length of the longest price run. If the market in question rarely closes higher/lower for 10 consecutive bars, a 10-bar lookback period will be appropriate.

The image below demonstrates the calculation of the ER. Closing prices and a 5-bar calculation period are used.

Repeating this computation for our 6 forex markets above, from 2003 to 2018, yields the following results:

The average ER values for these six markets are surprisingly similar. In fact, I redid the analysis for 28 forex markets, and EURUSD had the largest ER at 0.27, while NZDCAD had the lowest at 0.23.

This small ER range may not be ideal if you are trying to rank forex markets in terms of noise. However, if you are comparing markets from completely different categories, such as interest rates vs. stock indices, you will likely see more differentiation.

Markets with high ER are more likely to exhibit smooth trends, and are good choices for trend following strategies. Conversely, those with low ER are better for countertrend strategies.

You can replicate the above ER analysis by downloading price history from your provider and doing the computations in Excel.

Trend Strategy Backtesting

This is my preferred method of quantifying a market’s ability to trend. The concept is to test the market with a variety of simple trend following strategies. Better performance implies that the market is more conducive for trend strategies.

Although more involved than the Efficiency Ratio method above, it tends to give a wider range of results and is perhaps more representative of actual trading because it reflects the interaction of your algorithm with the market.

Reversal trend strategies will be used due to their simplicity. To make the tests on our six forex pairs more comprehensive, the tests will include:

  1. Three conceptually different reversal trend strategies, each using a distinct technical indicator to gauge trend direction:
    • Strategy 1: Simple moving average
    • Strategy 2: Linear regression line
    • Strategy 3: Donchian channels
  2. Lookback periods in the 10-100 range, in steps of 10

For strategies 1 and 2, long trades are opened when the moving average/linear regression line slopes upwards, and are reversed when the slope turns down. The moving average strategy is shown in action below.

The Donchian channels used in strategy 3 are simply the zone between the highest high and lowest low over the lookback period, similar to those famously used by the Turtles almost four decades ago. The strategy goes long when price closes above the upper channel boundary, and short when when price closes below the lower boundary.

Net profit will be used for the performance metric because it is readily available in the MT4 backtest reports. For each market, these are the average profits obtained across the three strategies, and across all 10 lookback periods.

Ideally a prudent metric would contain some measure of risk, but at this preliminary stage, net profit should suffice. Alternative metrics include the percentage of profitable optimizations, profit factor etc.

All six markets show a loss, which should be expected due to the simplicity of the strategies (trading is not that easy!).

GBPJPY seems well-suited for a trend strategy. JPY is commonly perceived as a safe haven currency, while the opposite is true for the GBP. This often causes tremendous volatility in GBPJPY when risk sentiment changes, giving it nicknames such as the ‘Dragon’ and ‘Widow Maker’.

At the other end of the spectrum lies EURGBP, which often ranges due to the high correlations between EUR and GBP, although this may have changed since Brexit.

Historical Volatility

Trending markets tend to be volatile as well. Volatility measurements can help corroborate the trend analysis conducted above, or help you determine whether a certain market suits your risk appetite.

Wilder’s average true range (ATR) is probably the most common volatility indicator among retail traders. A bar’s true range is the greatest of the following:

  • Current high – current low
  • Current high – previous close
  • Current low – previous close

True range will be equal to the bar range (high – low) unless large price gaps are present. A simple moving average is then applied to the true range to produce the ATR.

Similar to the Efficiency Ratio analysis above, historical ATR for each market can be computed if you have its price history. Using the default 14-period lookback, this was done for the six markets from 2003-2018.

Results are similar to those obtained using the reversal strategies, except that USDJPY is less volatile than expected. These similarities lend confidence to the previous trend analysis.

Volatility can also be quantified using standard deviation, which measures the dispersion of prices from the average value. For the purposes of comparison across markets, either measure should suffice.

How Can You Use These Results?

Suppose you are a trend follower. The results above indicate that GBPJPY is often volatile and trends well. However, its lower Efficiency Ratio implies that trends may not be as ‘clean’ as expected; expect some whipsaws and frequent reversals.

Or if countertrend trading is your cup of tea, EURGBP seems like a solid choice. It performed worst across the trend strategies and the ATR results show that it is a traditionally quiet market.

It may be tempting to cherry-pick 1-2 of the most promising markets and solely develop strategies for them. However, markets are constantly evolving, and there is no guarantee that traditionally trending/ranging markets will remain as such.

Unless you can develop a range of diversified strategies for each market, it is best to trade on a larger basket of markets. If you perform the above analysis on 20 markets, perhaps pick the best 8-10 for future development. A multi-strategy, multi-market portfolio provides the best diversification and is your best shot at obtaining a smooth overall equity curve.

Wrapping Up

This article has illustrated several methods to quantify the volatility and trending tendency of your market. Once these are quantified, a basket of markets can be shortlisted for further strategy development. Since every method has limitations, it is advisable to use several conceptually different methods and look for areas of confluence among them.

Since the hourly GBPJPY has emerged as a solid market for trend following, we’ll focus on this market for the remainder of the strategy development roadmap.

The next few articles will address strategy development using Metatrader 4.

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Hey there, Wayne here! I’m on a mission to develop robust algorithmic trading strategies for the forex markets. Trading Tact is where I share my trading methods and insights.

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