Today’s article is the eighth installment of the Trend Composite strategy. Last week we looked at ATR Trailing Stops and time-based exits, but these did not add much value. Today we will add various profit targets based on percentage gains. The strategy will still sell when/if the Trend Composite turns negative, but will also exit should prices reach the profit target. This added dimension will increase trade frequency, which in turn can increase total return.
Trend Composite Strategy Series
- Introduction to the Trend Composite and its Indicators (1-Feb)
- Trend Composite Signal and StochClose Ranking Table (2-Feb)
- All Signals Tests and Indicator Comparison (8-Feb)
- Trend Portfolio: TrendComp Crosses, StochClose Rank, Mkt Regime (15-Feb)
- Momentum Portfolio: Trend Status, StochClose Rank, Bear Mkt ETFs (22-Feb)
- The All Weather Portfolio, Bull-Bear Market ETFs, Market Regime (17-Mar)
- Adding an ATR Trailing Stop and Testing Time Exits (24-Mar)
- Live Example as Composite Breadth Model turned Bullish (28-Mar)
- Adding a Profit Target (31-Mar)
Note that the Trend Composite is part of the TIP Indicator Edge Plugin for StockCharts ACP. I use Amibroker because this is where I can build the indicators, test the indicators and fully customize the chart views.
Basic Trend-Momentum Strategy and Parameters
Using the All Weather ETF list as the universe, the basic strategy is to buy ETFs that are in uptrends (positive Trend Composite). Any ETF can be bought when the Market Regime is bullish. Only bear market ETFs can be bought when the Market Regime is bearish. Instead of waiting for the Trend Composite to cross from negative to positive territory, the strategy simply buys the top ranked ETFs with existing uptrends. ETFs are ranked by their StochClose values and there are 14 positions maximum. When there are more buy candidates than available positions, the strategy picks the ETF(s) with the highest StochClose rank. ETFs are sold when the Trend Composite turns negative. See part 5 for more details.
- Test period: 1/1/2007 to 1/31/2022 (15 years)
- All Weather ETF List for Universe
- 14 Equal-weight Positions
- Buy/Sell based on opening prices the next day
- Commission: $5 per trade (buy/sell = two trades)
- Slippage: 1/4 percent or .0025 per trade
- No dividends (article explaining why)
The performance tables shows the Compound Annual Return (CAR), Maximum Drawdown (MDD), Win Rate and some other metrics. The Gain/Loss Ratio is the Average Gain divided by the Average Loss. This one is pretty straight forward. Trend-followers would like to see this ratio above 3. Profit Factor equals the number of winners multiplied by Average Gain divided by the number of losers multiplied by the Average Loss. A Profit Factor of 2 means total profits are outpacing total losses by a two to one margin.
Adding Percentage Profit Targets
A profit target is an exit based on a percentage gain or a gain based on an ATR multiple. This article will focus on percentage based price targets. I plan on an ATR based profit target test in the future, but need to work through some coding issues first. A percentage profit target means selling after a certain percentage gain (6%, 8%, 10% etc…).
For example, if the buy price is 20 and the profit target is 10%, then 22 will be the target price (20 + (20 x .10)). A HIGH above 22 would trigger the profit target and the exit would be on the open the next day. Note that I am using the HIGH. Thus, the strategy checks the high of the day and plans for a next open exit if the high exceeds the profit target.
The chart below shows a real world example using XLY, slippage and the percent profit target. Using the strategy from part 5, the Consumer Discretionary SPDR (XLY) triggered a buy signal on 28-Sept-2021 and there was an entry the next day (29-Sep-2021). The open was 182.93, but the buy price is slightly higher because I am including slippage of 1/4 percent. Thus, the actual buy price is 45 cents higher or the open plus slippage (182.93 x 1.0025 = 183.39).
The profit target is calculated from the buy price. Thus, a 16% gain from the buy price would put XLY at 212.73 (Buy Price plus a 16% gain or 183.39 x 1.16). The blue oval shows XLY hitting this profit target with the high on November 22nd and exiting on the open the next day (red arrow).
Trading Considerations
Slippage of a 1/4 percent (.0025) is a little on the high side, but I prefer to err in this direction and be overly realistic. Also note that volatility is quite high right now, especially on the open.
I also have a relatively high slippage number because the strategy sells one ETF on the open and buys another that same day on the open when a profit target is hit. This same day trade also occurs when on a Trend Composite sell signal.
There are also instances when an ETF is sold because it hits the profit target and is immediately bought back because the Trend Composite is positive and StochClose is high. This happens more often with low profit targets (<10%) and much less often with higher profit targets. This is just the nature of the system.
Profit Target Results
Note that these numbers were revised to account for a start date error. The start date was 1/1/2003 when it should have been 1/1/2007.
The table below shows the results for the Trend-Momo strategy put forth in part 5 on the first line. The next lines show progressively higher profit targets in column one (from 6% to 20%). Overall, the Compound Annual Returns and Maximum Drawdowns are not that different and nothing stands out. The differences appear when we look at total trades, win rates, gain/loss ratios. The number of trades and the win rates decrease as the profit target increases (red shading). Conversely, the average gain increases and the gain/loss ratios increase as the profit target increases (green shading).
A 6% profit target generated 837 trades, while a 20% profit target generated half as many (408). The Trend-Momo strategy with a 6% profit target performs more like a mean-reversion strategy. The results move towards trend-momentum territory as the profit target increases. Eventually, the Trend-Momo strategy with a 20% profit target performs more like a trend-momo strategy, but is still a hybrid.
Win Rate, Gain/Loss Ratio and Expectancy
The win rate is affected by the profit target with the smallest profit target having a much higher win rate than the largest profit target. A 6% profit target has a win rate of 69%, while a 20% profit target has a win rate of 54%.
High win rates come at a cost though. The gain/loss ratio and the average gain are lower when the profit target is small. A 6% profit target had a gain/loss ratio below 1 (.86), which means the average gain was slightly smaller than the average loss. The average gain was just 6.26%, which makes sense because the profit target was 6%. A large portion of the trades hit the 6% profit target because it was relatively small. The 20% profit target generated a gain/loss ratio of 2.60 and an average gain of 14%. This is because fewer ETFs hit their profit targets.
The win rate and gain/loss trade off is typical when it comes to trading strategies. We cannot expect a high win rate and a high gain/loss ratio or high average gain. High win rates usually come with lower average gains and gain/loss ratios nearer to 1. These strategies make money because of the high win rates.
Strategies with low win rates generally have higher gain/loss ratios and higher average gains. These strategies are profitable because the gain/loss ratios are higher than 2 and the average gains are much larger.
The chart above comes from Nick Radge of The Chartist in Australia. His expectancy curve shows that high win rates (percentages) can generate profits with lower win/loss ratios (gain/loss ratios). Low win rates (upper left), in contrast, need higher win/loss ratios to generate profits.
Trend-momentum strategies typically have 40-45% win rates and 2.5/1 gain/loss ratios (blue square). Mean reversion strategies typically have 70% win rates and 1/1 win/loss ratios (red square). The trend-momentum strategy with a 16% profit target falls in between with a 53% win rate and a 2.14/1 gain/loss ratio (green square)
Frequency and Total Return
As noted above, a profit target introduces more trades and more trades means more chances to generate profits. The trend-momo strategy generated just 270 trades over a 15 year period. Meanwhile, adding a profit target between 12 and 20 percent increased the number of trades dramatically (red shading).
The green shading shows that the Profit Factor and Expectancy also increased as the profit target increased. Expectancy is the net profit percent expected per trade. Positive expectancy means the system is profitable. The last column shows the total return. The total return numbers increased as the Profit Target increased. This means letting the trend run further led to higher returns.
The total return for the Trend-Momentum strategy was 307.64% (first line). This is the highest of the group because this strategy caught the biggest trends (no profit target). Even so, I think a strategy with a profit target provides more chances to put money to work because trade frequency increases (more signals).
Conclusions
Trend-momentum strategies are designed to let profits run and catch the big trends. Adding a profit target changes this dynamic and creates more opportunities. Small profit targets (6%) generate performance numbers akin to a mean-reversion strategy. Large profit targets (12-20%) shift performance more towards classic trend-momentum, but is still a hybrid strategy. Nevertheless, the trend-momentum strategy with larger profit targets put out some pretty good numbers. Trade frequency increased and this provided more opportunities to put money to work.
I do not think one profit target stood out. It really depends on your trading style and goals. Active traders leaning towards mean-reversion metrics may choose the smaller profit target (6%), while trend-followers looking to add en extra dimension may choose the larger profit target (20%). I picked 16% in the XLY example at the beginning because it sits between 12 and 20 percent and may represent a sweet spot of sorts.
Note that these backtests are simulations and past performance does not guarantee future performance! Trading and investing always involves risk. Do you own due diligence.