Position Sizing in Momentum Models

In an ideal investment model, the investor should target a roughly equal amount of portfolio influence with each asset they invest in. In other words, a trade in Bitcoin should have no more or less impact on your portfolio than a trade in Treasury bonds. (Recognizing that some trades will always be much more profitable than others, while many will be a loss.)

The foundation for calculating this impact is based on pre-determined stop losses. Before entering a trade, you need to know where you will exit the trade. That works in two parts.

First, you should have an initial price level at which you will exit the trade. In trading, approximately one-half of all trades will go against you. No signal—or combination of signals—is perfect. Having a pre-determined initial exit price is crucial to limiting losses and sizing your initial trade.

Second, you should have a system in place to determine where to exit trades that move in your favour. This isn't about targeting a profit. A good trend can continue much longer and be much more powerful than you could initially predict. You need to take advantage of these long, powerful trends to push your portfolio forward. Rather, your system should be specific in determining when the trend direction is changing and it is time to take your profits on the trade.

I have published several posts on position sizing using various methods for calculating initial stops:

Position Sizing with Average True Range

Position Sizing with Percent Risk

Position Sizing with Breakouts

Position Sizing with LEAPS Options

Position Sizing with One-Signal Models

Charts can be very helpful in visualizing your trades and finding entry points on a moving average model. Whether you use Price > Moving Average or Moving Average Direction or Moving Average Crossover, the idea is similar and the challenges surrounding position sizing are similar.

This is a simple example of entries and exits with Moving Average Direction with a 50-day simple moving average.

Credit: StockCharts.com, TheRichMoose.com

As the chart shows, entries and exits are easy. Position sizing is not so clear. For the October to April trade, the trend was profitable so a large trade would have been to the trader's advantage. However, the May swing trade was a classic whipsaw and would have seen the investor in at $1,305 and out at $1,275. That's a 30 point or 2.3 percent drop.

With one signal models to calculate momentum, entries, and exits, I would suggest that using methods such as Average True Range or recent price lows (such as the 50-day low if using the 50-day SMA) can be highly effective. These methods incorporate recent market conditions, allow for flexibility in the markets, and can backtest very well.

Percent risk is not as effective across a wide range of markets, but can be very effective for an investor who only invests in small cap stocks, tech stocks, IPOs, or cryptocurrencies. These instruments are less predictable, need small position sizes, and can have unreliable, or even non-existent, historical data.

However, in a model where we measure momentum in many different ways and can measure the strength of that momentum, a different option may be available that is still very robust.

Position Sizing with Multi-Signal Models

Where we use multi-signal models, we can stick with moving average signals and find the points where the momentum direction changes based on the signals we use. If we translate chart data and moving average data to an Excel spreadsheet, we can actually plot the price forward to find these points.

Using this time period example (with LBMA data which is slightly different from the futures data shares above) we can create a simple signal.

Source: TheRichMoose.com, Quandl.com

Above we have the comparable data in Excel format with the 50-day simple moving average in red. (A single model system, but it helps illustrate the idea.) We see the buy and sell signals for the entire trade. In this case we know the Buy signal failed between $1,285 and $1,275. Of course we never know future prices when we enter a position; however, we can easily calculate that fail point by "walking the market forward" to find point where momentum fails and the signal would say sell.

Using a momentum model that tracks many signals (mine tracks momentum in dozens of calculations in several different styles) this type of stop-loss system is quite robust. Price movements have less impact on the trading system across the many signals. Also, by scaling into and out of positions we can reduce the impact of entry and exit signals. There is no "all-in" or "all-out" unless we have a major move.

At the point of entering positions and building positions, we need to think about how much of our portfolio capital we are willing to risk. How much of our money is in stocks, options, futures, ETFs, or volatile currency pairs and how much do we have in the safer stuff—such as short-term bonds. Once again this forces us to think about capital efficiency, use of instruments like options, and futures which trade around the clock.

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Trend Investing in Choppy Markets

Well... since last January being a trend investor has not been especially fun. U.S. markets have been stopped three times. The international equity markets haven't been doing too well at all; they more or less broke down near the end of January 2018, most countries have dropped substantially, and, based on my momentum scoring, they are on the slide again despite the signs of optimism earlier this year.

Only U.S. stocks have made new highs since January 2018, but even there it has been a range-bound and choppy market. New highs haven't carried the momentum we like to see in a strong market. We have also seen a pick up in volatility.

Take a look at the size of the weekly bars in the red areas compared to the black area.

Credit: TheRichMoose.com, StockCharts.com
Right-click to expand image.

These factors spell trouble for any trend investor. Trend investing performs the best in smooth uptrending markets or in longer downtrending markets. We go with the uptrend and capitalize with leverage where we can. In a long downtrend we sit on the sidelines in cash or bonds and watch the markets burn.

These types of market conditions in stocks are not rare. This is, after all, why trend investing works. Great recent examples of clean uptrends are from March 2016 through January 2018. Or before that from January 2012 through September 2014. These are two year holding periods where trend investors capitalized. In my own account I generated a 68 percent return in the latest period.

On the downside, we all remember October 2007 to March 2009. I had no money back then, so it didn't really affect me. But the S&P 500 fell 55 percent. The trend investor using my model would be off by just 13 percent. For those interested, we're more than halfway there already in 2019.

We see a more recent picture of the protection that trend investing offers by looking outside of the United States. Emerging markets fell around 27 percent from January to December 2018. A trend investor would have been down 14 percent.

Stretching back, emerging markets are down more than 25 percent since 2007. Not a profitable investment for a buy-and-hold investor patiently waiting—with their money tied up—for more than a decade. The trend investor would be roughly flat in their emerging markets trading during the same time period, but could have profited over the years by putting their money to better use when the trend model prescribed no allocation to emerging markets (often for many months at a time).

Of course this is all without factoring in leverage—which rewards handsomely but also punishes cruelly.

The Big Picture

Trend investing offers a good long-term outcome considering there is no crystal ball. We only know what happened yesterday, last week, or in the past years. That's the data a trend investor can use to try get a long-term, but certainly not easy, edge in the portfolio.

As a trend investor, it's important to recognize different market conditions. Markets which are expected to be good for your style and markets which are not. In choppy markets—the markets of today—you will lose money. That's what happens when stocks are not trending well.

Too often we hear from the boisterous crowds employing hindsight bias and capitalizing on narrow time frames. Of course with a crystal ball we would have invested (with ample leverage) in emerging markets from 2004 to 2007, went to long-term bonds until March 2009, then put all of our money in U.S. tech stocks until today. But no one did.

As humans using their superior discretion it's more likely that in 2007 they were diving greedily into emerging markets. By 2009 they were exhausted by the losses and switched to cash. And this past year they are finally buying tech stocks on the dips hoping to catch the rise of Netflix, Uber, Lyft, and Amazon (after all, even Mr. Buffett is buying it now).

Stick with the trend. Ignore the noise. With a lot of patience, a little alignment of the stars, a few whipsaw trades, and a bit of leverage I'm pretty confident I'll be much wealthier ten or twenty years from now. You should be too.

Trend investing may be the only quantifiable, repeatable, and diversifiable way to invest in a broad range of markets with a long-term edge.

Comments & Questions

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Comments containing links or "trolling" will not be posted. Comments with profane language or those which reveal personal information will be edited by moderator.