If you know the enemy and know yourself, you need not fear the result of a hundred battles.
We’ll talk about knowing the ‘enemy’ in a subsequent section on Market Research. For now, let’s focus on understanding yourself as a trader.
There are three general areas that you should address:
- Trading Style
- Trading Timeframe
- Trading Goals
Trading Strategy Style
Trading can be emotionally challenging for many people. Select an appropriate strategy style will give you better peace of mind.
There are two main types of strategies among retail traders: trend following and countertrend.
Strong trends occasionally appear in the markets. These are usually triggered by economic or geopolitical factors, and are subsequently reinforced by market participants’ herd mentality.
A classic example is the GBP’s slump in the aftermath of Brexit, where it hit a 31-year low against the USD.
Trend following (or momentum) strategies are reactive in nature, entering the market in the direction of an emerging trend. Capturing a strong trend can give you a huge boost in profits.
Unfortunately, markets trend only about 30% of the time, and most of your trades will be losers. The chart below shows a 16-year backtest of a basic trend following strategy on the GBPJPY.
Notice how the curve consists of many flat periods, punctuated by a few large increases.
Countertrend strategies bet on the reversal of a temporary price extension. This means buying when the market is oversold, and selling when it is overbought.
Countertrend trading is the basis of ‘night scalper’ or ‘Asian scalper’ strategies. The hour after the New York close is particular quiet, and there is a good chance that price extensions will reverse to their mean.
The chart below shows a 12-year backtest on GBPCAD. The strategy had an 82% win rate, but losing trades were 3X as large as winning trades on average.
Notice how the occasional large loss puts quite a dent on the equity curve, although it is rising most of the time.
Pros & Cons of Each Style
In general, trend following and countertrend strategies are on opposite ends of the spectrum. The following table sums up the pros and cons of each trading style.
Since markets do not trend often, trend following strategies typically have a win rate of between 35-50%. On the other hand, countertrend strategies have win rates of 70% or more.
To compensate for this, the average winning trade for a trend following strategy is much larger than the average losing trade. The opposite is true for countertrend strategies.
In the long-term, both types of strategies can be equally profitable. However, if you’re trading a trend following strategy in real time, you may be annoyed that you’re wrong most of the time.
I firmly believe that being right is good, but being rich is better. If you prefer a high win rate, countertrend trading may be your thing.
Impact of Transaction Costs
Since trend following aims to capture long trends that are often hundreds of pips, your strategy’s average trade (mathematical expectancy) will be higher. Transaction costs will have less impact on your bottom line.
On the other hand, short-term countertrend strategies exploit small market moves; profit targets of 10 pips or less are not uncommon. Your average trade may only be a few pips.
If you underestimate your transaction costs during development, such strategies will deteriorate significantly during live trading. It can be challenging to accurately account for transaction costs due to variable factors such as slippage; your best bet is to be conservative.
Importance of Signal Accuracy
Similarly, your entry and exit accuracy is less critical when you’re capturing the long trends. Different trend following strategies will simply capture different parts of the trend.
In fact, it is practically impossible to consistently pick out market tops and bottoms. Attempting to do so will likely lead to curve fitting and hair pulling.
On the flip side, a countertrend strategy’s edge is transient. Missing the entry or exit by 1-2 bars could drastically affect your trade outcome.
Average Size of Losses
Successful trend following strategies cut losses quickly. As shown in the equity curve above, prolonged flat periods are not uncommon.
Countertrend strategies are banking on the probable reversal of prices, and thus contain stop losses that are much larger than their profit targets. Suffering a few consecutive losses can lead to a deep drawdown.
I don’t think either strategy style is superior to the other. It is crucial, however, to select an appropriate market for each strategy you trade. We’ll talk about that in the Market Research section.
Can You Combine Both Styles?
Of course you can, and you probably should.
One way is to trade a mean reversion strategy. These strategies trade in the direction of the long-term trend, but take advantage of a temporary countertrend move.
Portfolio trading is another great way to exploit the benefits of both strategy styles. If I took both the trend following and countertrend strategies above and traded them equally from 2011-2020, I’d get the following curves:
The portfolio equity curve exhibits better risk-adjusted returns and a shorter stagnation period.
Portfolio composition is a non-trivial topic, however. Towards the end of the strategy development roadmap, I will explain portfolio composition in detail.
Closely related to strategy style is your choice of trading timeframe.
With automated trading, you no longer have to be confined to the higher timeframes. You can keep your day job while maintaining a complete trading portfolio across multiple timeframes.
The following are some factors to consider when picking your trading timeframe:
If you’re a trend follower, you will probably be more successful on the higher timeframes.
Higher timeframes contain less noise, which is random price movement unrelated to any underlying trend. This means you are less likely to capture a false breakout.
Market noise can be measured using the Kaufman Efficiency Ratio. I find the 30-minute timeframe and above to be good for trend following.
On the other hand, countertrend strategies work better on the lower timeframes. You want to exploit the temporary price extensions that are often caused by noise.
Time Spent in the Market
Trading a higher timeframe likely means you will holding positions for longer periods, exposing you to more risk.
Markets can abruptly reverse for a multitude of reasons, ranging from poor economic reports to political upheavals.
In addition, if you trade an illiquid market and hold a position over the weekend, be prepared for price gaps on Monday if something unexpected occurs. An example would be how the EURUSD gapped down on Monday after the 2015 Greek referendum.
The more trades you have in your backtest, the more reliable the results.
Trading frequency will be lower on the higher timeframes, making it difficult to get a sufficient sample size for your backtest. The effect of a small sample size on your backtest metrics can be quantified using standard error.
If you have only a few years of historical data, an hourly timeframe or lower is recommended.
Setting goals encourages you to evaluate your trading preferences and helps track your progress.
Goals usually address the following aspects of trading: returns, risks, and time commitment. Examples for each are given below.
- % profit per month/year
- % winning rate, or % of profitable months
- Number of pips/month
Measuring returns using pips may seem weird; after all you can’t pay for your mortgage in pips.
But I like using pips because it removes the effects of position sizing, and provides a more objective measure of trading performance.
For example, a $100 profit can be the result of a 0.1 lot trade that captures 100 pips. It can also be the result of an oversized 10 lot trade that captures 1 pip. The latter can hardly be described as good trading.
Of course, returns should never be considered in isolation, which brings us to risk.
- Maximum % drawdown
- Longest stagnation period
- % of time in market
Your preferred risk metric will depend on your trading situation. If you have limited capital, drawdown will likely be your main concern.
Drawdown is defined as the decline in account equity from a prior equity peak. Maximum drawdown is most commonly used; practically every trading/backtest platform provides this metric. Other drawdown metrics include average drawdown and the Ulcer Index.
If you use maximum drawdown, I think an annualized 20% return, with a 10% maximum drawdown, is a good benchmark.
Alternatively, if you trade for daily income, you may be more concerned about stagnation.
- Time spent on strategy development & backtesting
- Time spent on literature reviews
Time may seem like a trivial consideration, but successful trading is like running a business.
Contrary to what you see on advertisements, trading is not easy. Skill, experience and discipline will separate the boys from the men.
I’ll say it again. Becoming a consistently profitable trader is often a long and hard process.
Establishing your preferences and (realistic) goals early on will improve your chances of success.
Regardless of your preferences, automated trading will likely mitigate some of the emotional challenges you will face.
For example, premature profit taking is a common problem faced by trend followers. The saying ‘Nobody ever got hurt taking a profit’ does not hold true in trend following. You need the occasional outsized win to compensate for the large number of losing trades.
The catch is that you’ll need to spend time and/or money on strategy development and its required software.
We’ll talk about software requirements next.