How to Develop Simple Swing Trading Strategies lays the foundation for developing short- to intermediate-term overnight trading strategies. We’ll start off discussing what the goals of swing trading are and then move into some of the recommended steps to go about creating a strategy from scratch.
There are no holy grails we’ll be uncovering, but hopefully, the steps and framework outlined in this article will give you a responsible path towards creating a strategy to call your very own.
I’ve recorded the contents of this article in a video, so if you’d rather sit back and listen, and probably hear me go off on some added tangents, click the play button. Otherwise, read on.
Also note, 90% of the ideas and process we discuss throughout this article is applicable to all strategy time-frames (day-trading, position trading, etc), but our focus and examples will be for swing.
What is the goal of swing trading?
First, let’s put a definition to the term swing trading:
Swing trading is an active approach to trading the markets where the planned holding time of the trade extends beyond a day (overnight) and the goal is to capture a single leg (swing) in a stock’s trend.
Like any other active trading strategy, swing trading is intended to mitigate risk and/or produce excess returns (alpha) versus your favorite benchmark.
Due to the short time frame of swing trading, the primary decision-making process to get in and out of the market is nearly always based on market technicals.
The bottom line: as swing traders, our goal is to profit from short-term trends in the marketplace and overnight price movement.
Why develop a trading strategy in the first place?
As fun as it would be to wake up every morning and off the cuff decide what stocks to trade, the direction in which to trade them, the entry signal, and so on, it is just simply not realistic.
I’m sure there are a few people that shoot from the hip that loosely, but my guess is trading would be more of a fun hobby than a serious business in those cases.
In order to achieve and maintain consistency, we must develop a strategy, or set of rules, that we’re going to follow day in and day out. By executing within our rules, we can then document our results, verify performance, and identify what is and is not working.
Make no mistake, profitable trading strategies aren’t something you’re spontaneously going to write up one afternoon in your spare time. Trading strategies are going to take some deliberate thought and creativity to arrive at — the best ones at least.
After all, it’s the trading strategy that defines our edge in the market, and edges are tough to come by.
Step #1 – Build your trading strategy foundation
We know our goal is to capture a multi-day or multi-week move in the market so now it is up to us to find a repeatable pattern and measure its profitability.
The simpler and more straightforward your rules are the more robust and evergreen your strategy will be.
Simple and straightforward may not always equate to most profitable, but it is also ideal when you’re running a strategy live and trying to figure out if it is performing as expected when faced with a drawdown.
There are a million ways to come up with rules for a strategy and for the scope of this article, we’re going to snap our fingers and create them using price action and some moving averages.
If you have niche patterns in mind that you have observed repeatedly, the best way to gather data on possible entry/exit signals is to look back over those occurrences and analyze exactly where they appeared and how they developed.
Price action as our example framework
Over any period, across any market, we can come up with a set of rules to classify price movement as either trending or range-bound.
When a market is trending, the chart will start somewhere in the bottom left of your screen, and stair step to the upper right of the screen.
Trends come with all different rates of change and varying degrees of pullbacks along the way, but overall, a move from the lower left to upper right is “the pattern.”
When a market is range bound, that means there is no trend.
The chart should show a market that is moving sideways with choppy price action and no clear winner (buyers or sellers) in control.
There are lots of ways to come up with a rules-based definition for classifying these price action states, some examples might include using:
- Moving averages.
- Price structure (higher highs and higher lows).
- Lookback return (are we higher than we were X bars ago?).
- Technical patterns and geometrical shapes.
The great news about identifying these types of market environments is that once a market is in a trending state, it tends to want to persist in that state.
The same applies for range-bound markets. Most breakouts will fail, and the market tends to revert to the mean, until of course, it doesn’t.
For more tips on understanding and classifying price action, my favorite books are the Al Brooks series on trading price action:
Step #2 – Create trading strategy rules
When the market is trending, we have a consistent direction to work with.
As tempting as short signals look in an uptrend, we want to avoid the distraction and only focus on trading in the direction of the trend.
The following chart is Priceline (PCLN) in a long-term uptrend, and we’ve gone ahead and identified the price swings within this trend.
So the question is, how could we go about capturing some of that movement in a positive expected value (risk-adjusted) way?
The hindsight answer for this chart is to buy and hold it, duh!
Unfortunately, markets aren’t always this generous, we had no idea this trend would persist for so long in real-time.
Looking closer, notice how price tends to make a one- to two-week run higher and then goes into a period of equal length consolidation before starting its next move.
Using these observations, and leveraging what we know about trends, we can put together some rules to a trading strategy (in the real world you’ll probably want to start with more than just one observance):
- Wait for a close under the 20 period EMA (yellow line).
- Buy the first bar that closes back above the 20EMA AND the prior day highs.
- Place a stop at 1ATR below entry price (or below prior swing low, whichever is further).
- Take half of the trade off at a 1.5X ATR multiple.
- Exit the remaining on a close below the prior three day lows.
We could label this a price action pullback strategy for stocks in an uptrend.
For you Worden TC2000 users, we’ve built a premium pullback price action scan available for download with similar to rules this. Download it here.
Note we have defined an entry, profit-taking, and exit condition. We also have included some risk management using an initial stop loss.
Further, the rationale and rules are simple and robust:
- Only target stocks in uptrends and trade exclusively in that direction.
- Use a predefined stop loss to limit losses.
- Take partial profits at a 1.5X multiple of risk to reduce whipsaws and smooth equity curve.
- Let the remaining half of the trade run as far as the trend is willing to take it in order to maximize profit.
Step #3 – Backtest trading strategy
So are we done with our trend strategy? Did we just discover the holy grail?
Unfortunately not. While this strategy would have performed magnificently for the Priceline example above, it needs to be tested on more than just this single occurrence.
The next step in our strategy development process would involve running this same rule set across more stocks and time periods. This is commonly referred to as backtesting, which Investopedia defines as:
Backtesting is the process of testing a trading strategy on relevant historical data to ensure its viability before the trader risks any actual capital. A trader can simulate the trading of a strategy over an appropriate period of time and analyze the results for the levels of profitability and risk.
The process of backtesting is something that deserves an entire blog post of its own due to the numerous traps a trader can fall into when going through this process.
We just launched a new series, Beyond The Charts, where we take trading strategies and market observations and backtest them on historical market data. Dive into the lessons here.
We won’t be jumping into those details for the scope of this article, but at a high level, the goal is to validate your strategy across as much in-sample and out-of-sample data that you can get your hands on.
A few quick tips:
- Don’t forget to account for slippage and commission costs.
- Test multiple market regimes. Only backtesting from 2009 to 2017, for example, puts you in a major bull market.
- If a 20-day moving average works great, but 18, 19, 21, day moving averages all perform drastically different, be very cautious.
As a result, you may find that the original parameters you started off with don’t hold up over time and perhaps it is a 10 period EMA with a 2X ATR stop loss which actually models out better on a risk-adjusted return basis.
Ultimately, you’re looking to validate the robustness of your rules, making adjustments where necessary, but very importantly, you do not want to excessively adjust rules and parameters as you will run the risk of curve fitting your strategy to your data set.
Step #3B – Backtesting equivalents for discretionary traders
Discretionary trading systems that rely on varying inputs and dynamic weightings of those inputs won’t be able to fully quantify their rules and therefore participate in the traditional backtesting steps above.
The closest equivalent is to establish a track record and document your live results.
This may mean you paper trade for a few weeks, months, maybe even a year until you have enough confidence and sample size to determine that you do in fact have a profitable trading methodology.
One could argue that paper trading doesn’t carry with it the live financial and emotional consequences of trading real money, so a more realistic track record would use real money, but small size. In fact, this was my approach when I first created my swing trading system.
I started off risking anywhere from 0.25 to 0.30% per trade for an entire year. My second year, I increased my risk per trade to 0.5%, and on the third year, and present level, I risk up to 1% per trade.
By starting small, I was able to identify holes in the system, make necessary tweaks along the way, and slowly increase the risk I was taking on. It took me nearly 3 years to get to “full size”, but throughout that time, I got plenty of experience to build confidence in my system and understand its risk profile across various environments.
Step #4 – Start over or go live
By the time your backtesting is complete, you should have a pretty good idea if the strategy you set out to trade is worth pursuing. Keep in mind, a profitable backtest does not guarantee your system will perform that way into the future.
If you didn’t find something that is producing favorable returns you’ll once again need to resist the temptation to repetitively make tweaks and adjustments to the parameters of a strategy just to make it fit your data set.
The same risks we discussed earlier of overfitting can be very dangerous. so starting with a fresh strategy foundation, rules, etc. is generally recommended.
Step #5 – Maintenance & strategy improvement
If you’ve made it to step #5 with a trading strategy that is running live, generating profits, and following your backtest profile closely, congratulations!
That’s the good news. The bad news is, this doesn’t mean you can sit back and expect the profits to roll in forever.
Market conditions are constantly shifting, new participants are entering the market, others are leaving, which means your trading system can lose its edge over time.
To combat this, you’ll need to constantly monitor your system and verify everything is operating as your backtest and live trading experience suggest.
Sooner or later you’re bound to run into a longer drawdown than you are used to, or some unexpected set of events will hit the market which will cause you to question whether or not your system is still working as originally designed.
When you’re starting to doubt your system, the best question to ask yourself is:
Is my system performing as expected given the current market conditions (inputs)?
If for example, your system performs lousy during low volatility environments, and we’ve suddenly hit a stretch in the market of extended periods of low volatility, then poor results should actually be expected.
There’s nothing wrong with your system, it’s just not the ideal environment.
On the other hand, if your system does great historically in uptrending markets, and you find yourself in an unusually large drawdown during a major market uptrend, it’s time to look carefully at what’s going on.
Trading is not always smooth
It would be nice if our trading accounts paid steady weekly dividends for all of our hard work but unfortunately, that’s not the case.
The truth is, most trading strategies offer lumpy returns, are probably not correlated with the S&P500, and will leave us disappointed more often than not.
Trend following strategies have well-documented return profiles of exactly this.
It’s easy to accept this when reading it in a blog post, but try executing on a strategy and being on day #137 of drawdown while the S&P500 makes new all-time highs and your neighborhood social media trading guru is posting how profits don’t stop rolling in.
I guarantee the only thought you’ll have is:
What a piece of shit system! I need to find something new.
Resisting this temptation to jump ship to a new trading strategy is strongly advised.
Looking at my personal trading results for the calendar year 2016, just 2 months of that year accounted for 80% of my profits. That means 10 months were spent grinding it out not really moving the needle one way or the other.
As long as your system is performing as expected given the market conditions, don’t be so quick to bail on it.
Trade management & position sizing is king
Risk management and position sizing is probably the closest thing we can get to a holy grail in trading.
The most profitable strategies in the world can turn disastrous in the hands of an irresponsible or overly aggressive trader. Further, being too risk-averse can be equally as damaging from an opportunity cost perspective.
There are a lot of common sense principles and rules to apply when thinking about risk management, however, the specific thresholds are going to vary wildly depending on the individual trader.
For example, a 20-year-old trader fresh out of college with a $10,000 trading account can probably justify risking 2% of their account per trade idea.
On the other hand, a 55-year-old with a $1,000,000 trading account probably shouldn’t even have all of that capital in one single strategy let alone risk 1 to 2% of their entire account per trade.
Here are some quick risk management tips and general guidelines to consider.
- Always have a pre-determined price selected where you will exit the trade for when it doesn’t move in your favor.
- Never risk more than 1% per trade.
- Never enter more than 20% of your total capital in a single stock.
- Always note the stocks historic volatility (average true range) to get an idea of the volatility you’ll be dealing with.
At the end of the day, risk management and position sizing will vary largely from trader to trader based on their individual risk tolerance and time horizon.
For more information on position sizing, you’ll want to read this post.
How to develop simple swing trading strategies – wrap up
By now it’s probably clear that a lot of work goes into creating profitable trading strategies.
It requires an investment in time, experience with markets, and creativity to put together a unique strategy.
Even more challenging is that throughout the development process, nothing is guaranteed to work when you come out the other side.
We couldn’t possibly cover every aspect of strategy development in a single article but hopefully, we hit on most of the high-level steps to steer you in the right direction.
If you’re still interested in learning more about swing trading strategy, I’d recommend heading over to our learning center where you can choose from over 30 other lessons and guides on the topic. You may also want to read up on our flagship trading strategy, Merlin, that we use and trade on a daily basis.
Thank you for reading, and good luck strategizing.
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