This is the second article in a three part mini-series on the topic of systematic trend investing. In part one we looked closer at what systematic trend investing is and why we do it. In the last part we will give an example of how you can design a systematic trend strategy, followed by a practical example.
Traders in the stock and commodity markets have tried to find ways to capture trend profits for at least 200 years using different strategies, and for many years these strategies delivered strong returns.
However, market conditions, post the credit crisis in 2008, have not been favorable to trend investing.
Read more about the history of trend investing in my last blogpost.
Trend investing is reactive in nature
Government rhetoric and intervention has made it difficult for trend detection signals to capture consistency in performance during the last decade. But there are no indications of macroeconomic conditions or market structures having changed, or that markets have become more efficient due to a change in investor behavior.
The report of my death was an exaggeration
We argue that continuant recovery of the global economy and a normalization of policy actions will give rise to more apparent trends again.
What is a trend and how do we recognize it?
While there is no stringent analytical definition of what constitutes a trend, the basic idea is to capture consistency in performance over a given time horizon. We do not want to focus on the individual fluctuations, but on the main movements.
There is no common definition of a trend
A trend can be both upwards- and downwards moving. A short-term strategy would expect to hold the positions for hours and days, while for a medium- to long-term strategy, the positions could be held over weeks and months.
To identify a trend we use various trend indicators such as moving averages (MA) cross-over, single look-back window, breakout from historical high/low, and/or channel breakout.
Examples of trend indicators are illustrated in the graphs below. A cross-over strategy will typically look for when the short-term moving average (e.g. 50 days) crosses the long-term moving average (e.g. 200 days), and then enter a long (short) position if above (below).
Trend investing is reactive in nature
Investors are normally skeptical to a “black box” investment process that lacks economic rationale and intuition. While trend investing can offer complex statistical techniques within filter theory, systematic trend investing is normally fairly simple and unsophisticated, and provides a transparent and consistent investment approach.
A single look-back strategy will compare the price today with the price at some point in the past, e.g. three months ago. If the price today is above, then take a long position. Otherwise take a short. A breakout from historical high/low strategy will typically compare the price today with the last N-days high/low (e.g. last 50 days), and enter a long (short) position if above (below). It will then exit the long (short) position if the price goes below (above) the last N/2-days low (high). A breakout from channel strategy will compare the price today with the historical (e.g. last 52 weeks) average. If the price is above (below) e.g. one standard deviation from the average, then take a long (short) position.
Trend investing does not try to predict the future, but waits until a trend is well established, and then stays with the trend until it clearly reverses.
Systematic trend investing provides a transparent and consistent approach
Why do trends exist?
According to modern financial theory all known information is already reflected in the price. Thus, past price movements cannot be used for predicting future performance. Still, academic literature shows that “reactive” strategies, like trend investing, works.
The common economical rational can be attributed to exposure to systematic risk premium, inefficiencies caused by investor behavior, like herding and under-reaction to news, macroeconomic conditions, like supply/demand frictions and feedback loops, and market structures. Summarized:
1. Biases in behavioral finance and investor psychology. Market inefficiency due to investor irrationality.
- Disposition effect: Tendency of investors to realize winners while hanging on to losers.
- Confirmation bias: Investors favor information that confirms their previously existing beliefs. Strengthens a trend.
- Under-reaction to news: Investors receive, interpret and process information over different horizons.
- Bandwagon effect: Investors preference to favor past winners (amplification effect).
2. Market structures
- Non-profit seeking market participant (like central banks operating with broader macroeconomic goals)
- Investors with different objectives and mandates (hedging demands, etc.)
3. Macroeconomic conditions
- Supply and demand frictions (prevent instantaneous adjustment of the level of economic activity)
- Feedback loops (strong equity markets create wealth that boost consumer spending and in turn corporate earnings)
4. Systematic risk premium. Required by investors in order to compensate for the additional risk incurred.
Due to these conditions and effects we believe in systematic trend investing in the years to come.
 The Efficient Market Hypothesis (EMH)
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