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Editor'S Choice - 2019

Medium Return Strategies or How to Design a System for Flat

It is believed that trends in markets are present less than 30% of the time. The rest of the time, prices randomly and randomly move in ranges. But what should traders do in such cases - to sit and wait for the weather by the sea? Of course not. It was for such situations that systems of returning to the mean were invented, about which our conversation will be today.

Medium-return strategies have become very popular since 2009. They have performed very well over the past 10 years, even during the 2008-2009 bear market. In this class of strategies, a simple and understandable idea is very captivating - if the price moves up today, it will tend to return down tomorrow. We’ll talk about this today.

Mean reversion is a mathematical method that was often used before when investing in securities. It is based on the assumption that both high and low prices are temporary, and that prices usually have an average value over time. When using strategies of this class, the average price is calculated using analytical methods, for example, moving averages. When the current market price is less than average, the asset is considered attractive for purchase because it is expected that the price will increase in the future.

When the current market price is above average, it is expected that the price will decline in the future. In other words, this strategy is based on the expectation that, despite deviations from the average, the market price will return to it anyway. As an indicator of the appropriateness of buying or selling, various oscillators are often used.

An example of such a strategy is the recently reviewed Rubber Band system.

What is an oscillator?

An oscillator is a price-based indicator that tends to fluctuate or oscillate in some fixed or rather tightly limited limits. Oscillators are characterized by some normalization of the range and the removal of long-term price trends. Information is extracted by oscillators from indicators such as impulse and overvoltage. Impulse is a state when prices are powerfully moving in this direction. Overvoltage is a state of excessively high or low prices (overbought and oversold), when prices are ready to sharply return to a more reasonable level.

Sometimes the oscillator is figuratively represented in the form of a pendulum: the more it deviates from the equilibrium value, the greater the force acts on it, returning it to the point of equilibrium. This is a very crude model, but it explains the principle of the idea on which the use of oscillators is based. In a more accurate model, there are much more degrees of freedom. The oscillator is a pendulum, but this pendulum is fixed at the end of another larger pendulum, and the pendulum, in turn, is fixed at the end of an even larger pendulum, and so on - to infinity. Even in this regard, markets are fractal in nature.

There are two main types of oscillators. One of them is linear operators (filters), which carry out certain linear transformations over the time series and, basically, analyze vibration frequencies, representing a kind of band-pass filters. Another class leads to a normalized scale of some aspect of price behavior. Unlike the first category, these oscillators are not linear filters, i.e. the operations they perform on the price chart are irreversible. Both types of oscillators respond to price momentum and cyclical movements, while reducing the role of trends and ignoring long-term shifts. The graphs constructed for such oscillators have a broken, oscillating appearance.

The easiest way to get signals from oscillators is to use them as an overbought / oversold indicator. Buying occurs if the value of the oscillator falls below a certain threshold in the oversold zone and then returns. Selling occurs if the oscillator rises above the overbought threshold and then falls back. There are traditional overbought / oversold thresholds used with various oscillators.

You can also use the relative position of the oscillator and its moving average, which acts as a signal line. If the oscillator crosses its average up, a buy signal is generated, if down - accordingly, to sell. The intersection of the oscillator and the signal line can be used in combination with overbought / oversold zones and corresponding threshold levels. The generated signals can be used simultaneously for input and output, as well as only for input with an output determined by other rules. In addition to moving averages, a wide class of trend of tracking and channel indicators applicable to the oscillator chart, such as, for example, price envelopes, Bollinger Bands, MACD and many others, can be used as signal lines for oscillators.

Another well-known method is the search for differences in the behavior of the oscillator chart and the price chart - divergence. The discrepancy is obtained when prices form a new low (below the previous lows), and the oscillator has a higher low (above the previous lows). This discrepancy gives a buy signal. In the opposite situation, when prices form a new maximum, and the oscillator fails to reach the previous maximum, which is a sign of a loss in price momentum, a sell signal is generated. The discrepancy is easy to see with your eyes, but for a program with simple rules, finding it is almost always difficult. The mechanical generation of signals based on the discrepancy requires pattern recognition, which complicates the system and, therefore, complicates its testing.

Medium Return Strategies

As a rule, it is not difficult to develop a trading system that trades on a return to average values. By and large, almost all strategies for returning to the average consist of three main elements - a trend indicator symbolizing a “fair” price, an indicator of deviation from this price, and various entry filters.

As a trend indicator, a moving average can be used, and of any kind, as well as various channel indicators, for example, Bollinger Bands or Moving Average Envelopes.

In the first case, the moving average is used more likely to exit the position, and the main signals are input by various oscillators:

As you can see, the signals come out quite inaccurate and premature. Therefore, such strategies are often combined with a topping system, with grid trading. Experiments with the type of moving average, as well as a more thorough selection of the oscillator, will not greatly improve the result. Therefore, a whole group of oscillators is often used, which filter each other's readings:

But this approach also filters out a significant portion of potentially profitable transactions. The main problem with the use of the oscillator is that we do not have information about the optimal deviation of the price from the moving average - we only know that at the moment we are in oversold or overbought conditions.

The simplest way to take the deviation distance into account is to set the minimum distance in points. A similar option is to use the Envelopes indicator. With this approach, it will be necessary to constantly adapt to the current volatility, which is not only different every day, but also decently varies from session to session. Therefore, it is more logical to use indicators such as Keltner channels and Bollinger Bands for these purposes:

Different levels, for example, round, are also good filters.

As for the filters, then everything is quite simple. Most often these are temporary filters or volatility filters. For example, you can set a ban on entering the market if the current volatility is too low or, conversely, high. Quite often, the price is stamped in place only in order to continue moving towards a new trend, thereby dooming the closing position in the stop. Conversely, increased volatility may indicate a dangerous news background when the price behaves unpredictably. In such conditions, the effectiveness of using pending orders is small and often inferior to market entry.

A time filter will also help improve the overall system results. Most often, the hours between sessions are eliminated, when the volatility is very low, as well as the hours of combining several sessions, when the volatility, on the contrary, is large and strong movements against the position are possible.

Closing a position is often done when you return to the moving average area. But, given the volatility of modern markets, the timely closure of profit positions and their competent accompaniment come to the fore. Position tracking in return to average systems is not only various trailing stop options. Oscillator exits also show themselves very well, which allow you to close a position at the very beginning of the upcoming price reversal.

A separate group of strategies of the return to middle class can be distinguished night strategies. In fact, the main differences here are the use of these strategies exclusively in the Asian session, as well as the low time frame, as a rule, M15, or even M5. Do not forget about the disadvantages of night trading: increased spreads, swaps for transferring the position to the next day, as well as low quality of quotes during these hours with relatively low average profits and rather impressive stops. Not infrequently, such systems in one unsuccessful night session can deprive you of a monthly profit. Even despite the rather smooth yield curves, there are quite long periods of increased volatility in the Asian session, leading to prolonged drawdowns. Therefore, do not consider night trading systems return to average as the main source of income.

Restrictions on trading to return to the average

The fact is that some markets are well suited to the strategy of returning to the middle, while working on this strategy in others will lead to nothing but losses. It depends on many factors, the main of which are:

  • what drives the price of a particular instrument (macroeconomics, reports, news, etc.);
  • number of market participants;
  • the ability to open short positions;
  • trade volumes;
  • average volatility of the instrument in question.

There is a general opinion that the time series of commodity assets are better suited for continuation trading systems (trend trading, breakouts, etc.) than for systems based on a return to the average. The same applies to currency pairs in which long-term and short-term trend movements are observed. Therefore, if for trend strategies, periods no lower than daily are best suited, then for reversal strategies, these are usually periods up to H1. At the same time, traders try to choose pairs that have an average level of volatility.

Popularity of return strategies

There are at least two main reasons for such a radical change in the short-term behavior of the Forex market, in which following the trend changed to a return to the average. The first is an extraordinary increase in market transactions over the past 30 years. The buy-and-hold investment strategy, which has been a hallmark of most of the 1900s, has given way to active investment, as well as short-term trading and day trading. This increase in volumes brought to the market an unprecedented level of liquidity of assets, allowing sellers and buyers to more effectively find each other and, thus, restraining “departing trains” associated with illiquid markets. Nowadays, any person can carry out operations in the foreign exchange market almost anywhere.

And finally, you need to consider the entry into the market of automated trading systems and high-frequency traders. We can say that they gave the market significant short-term rationality. Trading systems designed to recognize panic sales come into play in oversold situations, using excessive market reaction to buy. This favors a return to the middle.


A return to the middle is not a universal phenomenon. The prices of some financial instruments have this tendency, while others do not. This makes many analysts and traders look at a return to the middle with some skepticism. Nevertheless, these systems may well bring very good income to traders, especially in the period of the absence of any trends.

Watch the video: Behind the Scenes at Puget Systems Custom Computer Builders - Smarter Every Day 2 (November 2019).

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