Long and Short Trend Systems

Trends in financial instruments are extremely interesting. A certain trend-based model can provide consistent outsized returns in some applications, but when the same model is applied to a different market those outsized returns may vanish quickly. Likewise, similarly constructed trend-based models that vary only in duration of trends can have wildly different results on the same market.

On the one hand this may tempt us to create different trend models for different markets, but on the other we know it's dangerous to data mine results for a backtest. This type of period specific data mining can provide catastrophic results moving forward.

Over the past few weeks I have been looking carefully at complex trend models applied to a range of markets. This includes focusing on shorter-term trend models, longer-term trend models, blended trend models, long/flat applications to trend models, and long/short applications to trend models.

Trend Models on Equity Markets

When I want to do a long backtest on an equity market, I am generally confined to the S&P 500. This is the only market where I can get free daily or weekly data on that extends back to 1950. From there, I can get Nikkei 225 data from 1965, NASDAQ Composite data from 1971, FTSE 100 data from 1984, Russell 2000 data from 1988, and so on.

Unfortunately MSCI and FTSE keep a pretty tight lid on daily data from their more popular international indices: the MSCI EAFE, MSCI Emerging markets, FTSE Developed ex-U.S. and FTSE Emerging markets index.

Aside from being the most popular stock index in the world, this is why we see the S&P 500 being used as the example market in nearly every model published on the internet blogs. This includes my little writing project.

Long/Short Trend Model (Short-term)

Short-term trend following is very profitable in certain time periods. While it can appear highly technical and advanced, or at least difficult for your average self-directed trader to implement, it has become a lot easier with developments like the E-mini futures on major indices.

In this subsection I've simulated a long/short trend model on the S&P 500 (price only) using trends which are shorter in duration. I took more than 80 trend measurements ranging from 2.5 weeks through 3 months. These were derived into a factor ranging from -10 through +10. If the factor was -10 the investor was fully short; if the factor was +10 the investor was fully long.

A trader in the late 1980s who ran a long/short fund on S&P 500 going back to 1950 using a model like the one described above looked like a genius. It generally performed very well from early 1960s, but importantly it got you on the right side of the 1987 crash. Investors with any sense would have poured money into your hands.

Credit: TheRichMoose.com, Standard & Poors

Since 1987 things have not gone that well for this strategy applied to the S&P 500. The nature of the market seems to have changed after 1987 and the exact same model substantially underperformed the S&P 500 as seen below.

Credit: TheRichMoose.com, Standard & Poors

If you look at the poor performing chart more closely, there are moments of apparent brilliance. In September and October 2008, this single system would have returned nearly 40 percent. This is very aligned with the performance seen by some of the short-term trend equity funds at that time (often amplified by leverage).

Long/Short Trend Model (Long-term)

As one might predict, when we move to longer duration trends on the S&P 500 index the backtest becomes more stable. This is mainly because transitions from fully long to fully short occur more slowly.

In this subsection the trend durations used are much longer. Again I took over 80 different measurements of trend that ranged from 3 months through 12 months. I derived these into a factor ranging from -10 through +10. When the factor was -10 the investor was fully short the S&P 500; when the factor was +10 the investor was fully long.

Unlike the short-term trend strategy, this long-term strategy didn't have any long periods of outperformance relative to the index (except the period from 2000 until 2009 using peak-to-trough measurements).

Credit: TheRichMoose.com, Standard & Poors

The brief moments of massively outperforming the index were quite fleeting. This strategy saw a peak 55 percent jump in 1973-1974, a peak 45 percent jump in 2001-2002, and a peak 75 percent jump in 2008. On the surface this looks like amazing downside protection, but these short periods of outperformance were quickly followed by underperformance.

A quick spike up immediately followed by a quick drop is not a desirable or sustainable solution to portfolio construction. It's all but impossible to try ride the climb up only to get out before it drops down.

A rolling return average demonstrates the sharp moves in the long/short model relative to the index quite clearly. It also shows the sustained underperformance compared to the index.

Credit: TheRichMoose.com, Standard & Poors

Short-term vs. Long-term Trend Model

When we compare our short-term trend model to our long-term trend model, we can see a massive divergence and shift in overall market conditions post-1987. The long-term trend model began to outperform and just 10 years later had pulled ahead of the short-term model.

Credit: TheRichMoose.com, Standard & Poors


Applying complex trend models to an equity index like the S&P 500 can show some clear differences in how markets behave in short trends and longer trends.

We can see a pretty clear shift in how the S&P 500 behaved (and could be traded profitably) prior to 1988 and following this period. Before 1988, a short-term trend system that traded the S&P 500 both long and short was extremely profitable.

Since October 1987, short-term trends applied to the S&P 500 in the same manner would have performed very poorly. I don't have the necessary data to determine if the profitable period between 1960 and 1987 was an anomaly, or if the market shifted in nature after 1987. Either way, a short-term strategy that went long and short the S&P 500 after 1987 never again saw those great returns in any sustainable way.

Long-term long/short trend systems on equity markets can show impressive profits in downtrending markets. But it would be difficult to realize and hold onto those gains when the market reverses course. We saw this play out in 1973-1974, 2002, and 2008.

In future posts I will apply my trend model to long/flat strategies in the S&P 500 and other equity indices. I also hope to do the same with several of the major currency pairs.

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Improving Portfolio Re-balancing

Several weeks ago I shared a post on the clear risk superiority of Leveraged Barbell Portfolios when compared to a standard 60/40 index portfolio. In my example, with a tiny 12.5 percent allocation to a 3x leveraged ETF and the rest of your portfolio in bonds, you could have matched the returns of a 60/40 portfolio over the past seven decades.

Your drawdowns would have been much smaller and your returns much smoother than a traditional 60/40 portfolio. Effectively, a Leveraged Barbell Portfolio can provide outstanding risk-adjusted and gross returns.

You can read the details in this post: Risk Mitigation with a Barbell Portfolio.

My example used simple annual re-balancing without any added strategies to further control risk. As my post shows, regular periodic re-balancing works pretty good. If you want to have a low maintenance portfolio that shows great historical returns, you can do well re-balancing your positions to target once per year, or even once every six months or quarter.

One of the downsides of periodic re-balancing is the effect of compounding losses in multi-period market drawdowns. Regularly pulling capital away from bonds and placing it into declining stocks can become very costly. If we avoid re-balancing in downtrending markets, we can reduce overall portfolio drawdowns and increase performance.

There are some relatively simple strategies we can use to improve results. Basic indicators identifying trends can help avoid pulling money away from bonds in a downtrending market.  At the same time, these indicators can help us stay in uptrending markets for as long as possible in attempt to capture the compounded gains on our equity positions.

In all of the following examples in this post we will target the following portfolio allocation on re-balancing: 15 percent 3x daily leveraged S&P 500 and 85 percent U.S. T-bill returns (no fees or taxes).

Avoid Re-balancing Into a Downtrend

There are many ways to measure trends; the pros and cons of various tools are extensively debated. One of the most popular, tried and true methods is the simple moving average (SMA).

In this first demonstration, we will use the 12-month SMA to identify long-term trends. Our goal is to focus on long-term trends to avoid re-balancing in extended drawdowns or lose on potential gains by re-balancing in small market corrections.

Here are the re-balancing rules for this first test:

  • If the monthly close of the S&P 500 is above the 12-month SMA, we will re-balance the portfolio every twelve months.
  • If the monthly close of the S&P 500 is below the 12-month SMA, we will re-balance to take risk off (if needed) and then not re-balance again until the monthly close is back above the 12-month SMA.
  • We will only re-balance if the allocation is reset in the favour of the trend. For example, we will not re-balance if the trend turns up by adding to the bond position. Likewise, we will not re-balance if the trend turns down by adding to the leveraged equity position.

Our example will compare returns of this rule-based method with the baseline annual re-balancing method. For the baseline portfolio, the re-balancing is done at the end of each calendar year.

Sources: TheRichMoose.com, S&P, FRED-Federal Reserve St. Louis

The returns of each method overall are nearly the same. Both show a compounded annual return in the range of 9.75 percent.

The following chart shows the drawdowns for each method over the same time period.

Sources: TheRichMoose.com, S&P, FRED-Federal Reserve St. Louis

As the chart shows, the largest drawdown periods since 1950 are much lower when the 12-month SMA trend filter is added. Remember, in uptrends both portfolios are still re-balanced every year.

The 12-month SMA filter doesn't have a significant affect on the small drawdowns that occur over this backtest period. The timing, frequency, intensity, and duration of small drawdowns are nearly identical across both strategies. The small variations that do occur are primarily due to the differences in the re-balancing at the end of the calendar year (annual re-balancing) vs. 12-month intervals (12-month SMA filter).

Responsive Trend Re-balancing

In this next example, we will re-balance following trend signals only. This test will be a demonstration of the sensitivity of shorter signals in downtrends as well as the importance of staying in uptrending markets for as long as possible.

To manage risk in this scenario, we will follow a shorter term trend measurement—the 13-week SMA (one-quarter of the full year).

Here are the re-balancing rules for this test:

  • If the weekly close moves above the 13-week SMA, we will re-balance in the favour of equities.
  • If the weekly close moves below the 13-week SMA, we will re-balance in the favour of bonds.
  • Re-balancing will only be done when a new signal change is shown. We will not re-balance in the middle of a uptrend or downtrend.

The following charts will compare this 13-week SMA method with the 12-month SMA where we re-balanced annually in uptrends (the method used above).

Sources: TheRichMoose.com, S&P, FRED-Federal Reserve St. Louis

Staying in trends for as long as possible is very important and can lead to outsized returns thanks to the effects of compounding returns with leverage. The 13-week SMA method achieved a 10.6 percent compound annual growth rate over the past seven decades.

We can see a consistent pattern on meaningful performance gains across time periods using the 13-week SMA method as shown when looking at the 3-year rolling returns. Most of the excess gains come during uptrending market periods.

Sources: TheRichMoose.com, S&P, FRED-Federal Reserve St. Louis

However, as the rolling return chart above shows, the drawdowns of shorter trend signals compared with longer trend signals demonstrates a noticeably different pattern. The following drawdown chart clarifies this.

Sources: TheRichMoose.com, S&P, FRED-Federal Reserve St. Louis

While the largest drawdowns in the 12-month system capped out at approximately 14 percent, the shorter 13-week signal put us back into the market several times during a long-term downtrend leading to larger compounding losses. We see this with the larger drawdown periods in 1973-1974, 2000-2003, and 2007-2009 periods.

That said, the losses are still very tolerable at just under 18 percent in the worst case. Notably, the shorter signal had us in fewer drawdown periods otherwise. Since the shorter signal re-balanced into leveraged equities faster as new uptrends started, the drawdowns were also typically shorter in duration for the 13-week SMA method.


There are many ways to improve on a basic re-balancing technique and this article just scratches the surface of the various methods available. Our chosen preference also depends on which particular forms of risk we are trying to reduce. For example, we can focus our re-balancing on trying to reduce capital at risk, we can try reduce the severity of drawdowns, we can try reduce overall time in drawdown, or we can try stay in uptrends as long as possible.

Portfolio management and risk management is complex with many variables. We can use tools to shift risks where it best suits our needs, but we can never eliminate risk without sacrificing total returns.

I used a Leveraged Barbell Portfolio to demonstrate various re-balancing methods; these basic principles for thoughtful re-balancing could be applied to traditional 60/40 portfolios as well.

Comments & Questions

All comments are moderated before being posted for public viewing. Please don't send in multiple comments if yours doesn't appear right away. It can take up to 24 hours before comments are posted.

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