Anyone interested in trading will have to develop a successful trading strategy. When doing so, you will most likely encounter a plethora of strategies and types of analyses. In this article, we’ll introduce you to the most common types of trading strategies, what they consist of, and how you may implement them, so you can find the right strategy for your needs.
What Is a trading strategy?
Although this term accommodates a range of definitions and segmentations, a trading strategy essentially represents a set of rules that create entry and exit signals in a given market. More precisely, these are signals for opening positions (both long and short) and closing positions (both long and short).
Given the complexity of financial markets, this definition suggests that a trading strategy, while essential, isn’t sufficient by itself. It should be part of a broader plan that includes diligent risk management (such as setting stop loss levels), effective money management, and a strong understanding of trading psychology.
Types of trading systems: mechanical vs discretionary trading strategies
Based on how trading decisions are made, there are two general types of trading strategies.
As the name suggests, the signals in these strategies are generated mechanically (or automatically) using a predetermined set of rules (a trading system). Once the rules are established, the orders will be generated without our intervention. This helps to eliminate emotions when trading and remain consistent to ensure trading success.
In these strategies, the trader relies on predefined rules but also applies personal intuition for each operation in the market. The significant advantage lies in the flexibility and adaptability to market changes.
However, the challenges include the need for constant decision-making, which can affect emotional control, and the impracticality of verifying results against a historical series. This strategy also requires significant concentration and time from the trader. Its use is not recommended unless the trader has extensive experience.
3 most popular trading strategies
1. Trend following strategies
Trend trading strategies aim to generate profits by analysing the direction of an asset’s price. Traders enter a long position if the trend is bullish (increasing) or a short position if the trend is bearish (decreasing).
2. Day trading strategies
Day trading strategies involve opening and closing all positions within the same trading day. These strategies aim to avoid overnight market risks and gaps. Traders often obtain small profits from intraday price movements.
3. Swing trading strategies
Swing trading strategies involve taking positions that might last from a single day to several weeks. Although these strategies use intraday data, there’s no obligation to close the positions at the end of the trading session.
The risk-return ratio with these strategies typically falls somewhere between day trading and trend-following strategies.
Types of markets: trending, sideways, volatile
Generally, there are three types of markets: trending, sideways, and volatile. This classification is based on these market phases. A trending market is when the price exhibits sustained increases or decreases over a specific time. A sideways market is when there is little variation in price – and is often referred to as a “trendless” market. Finally, a volatile market is one where the price makes significant movements, but these are short-lived.
Trending markets are typically the most profitable, the challenge being that we can never predict the onset of a substantial trend nor its duration. Some experts, such as John J. Murphy, posit that markets trend only about one-third of the time.
These strategies are effective during extended periods of upward or downward trends.
An example is the breakout strategy, which is based on price, technical indicators, or a data point. This is often used in the early stage of a trend.
Most breakout traders use technical analysis to decide when to enter a trade (typically when the price moves outside of a trendline).
Broadly speaking, trend traders look for market trends – in either direction, such as up or down. When the trend is bullish (up), the trader places long positions. If the trend is bearish (down), short positions are opened instead.
Some traders may also opt for countertrend trading strategies – these assume that the current trading will reverse.
Some of the main trend indicators are the moving average and relative strength index (RSI).
Sideways trading strategies
Sideways or trendless markets are more challenging to trade. Traders usually look for breakouts or breakdowns using technical indicators or chart analysis. In general, sideways trading strategies are based on attempting to make profits as the price moves between the support and resistance levels.
Options trading is also quite popular in sideways trading.
Volatility trading strategies
Volatile markets are marked by sudden price leaps, which we can exploit primarily through conditional buy or sell orders or options trading (such as long puts, short calls). These are generally quick and short-term movements.
An important principle to use and consider is the Pareto Principle.
The Pareto Principle, also known as the 80/20 rule, is a concept developed by Italian economist Vilfredo Pareto in the late 19th century. Pareto noticed that 80% of the land in Italy was owned by 20% of the population. He also observed that 20% of the pea pods in his garden contained 80% of the peas.
This observation led to the formulation of the Pareto Principle, which states that, for many events, roughly 80% of the effects come from 20% of the causes. It’s a common rule of thumb in business, for example, “80% of your sales come from 20% of your clients.”
In the context of trading, it may imply that 80% of profits could come from 20% of trades, although the exact ratios can of course vary.
Market facilitation – theory in favour of trend systems
Peter Steidlmayer is widely known in the Trading industry for his Market Profile theory, however, few know his theory on Market Facilitation, which is crucial to give us the serenity we need in sideways periods (Choppy Markets), since operating with a Trend System, in moments of sideways our system will lose money and we must have enough confidence in our rules, to endure these losses and wait for the trend to arrive.
According to this Theory, the only reason for the existence of Markets is to facilitate Trading. Markets exist to attract traders. The Market needs traders to buy or sell constantly, otherwise it will die. They must move to survive. According to Steidlmayer, markets are like living organisms, which base their survival on attracting buyers and sellers.
If there is no clear trend for a long time, traders will lose interest in trading in them, the volume will decrease, the lack of liquidity will increase the slippage and in the end, inevitably, the market will close. This theory is essential for the Trader who operates with Trend Systems to have confidence that sideways periods cannot last forever, sooner or later the market will have to break somewhere, offering us a trend that will compensate us for the losses caused by the previous period of sideways. Charlie F. Wright in his work “Trading as a Business”, offers us the following table to help us decide our type of System.
|Type of system||Trend||S/R||Volatility|
|Time on market||Always in the market||Not always on the market||Long time out of the market|
|Reliability (% of winning trades)||Low||Average||High|
|Where money is made||In big movements||In sideways periods||In market bursts|
|Where money is lost||In sideways periods||In periods of strong trend||In quiet periods|
|Main Disadvantages||Many false signals and long drawdown periods||Difficulty in maintaining long term profitability||Never catches big moves, exits early|
|Main advantages||Possibility of high long term profits||Higher Reliability||High Reliability|
|Average profit per trade||High on a long test period||Lower than above||Low|
|Philosophy||Buy high and close higher still. Sell low and close lower||Buy low and sell high (popular wisdom)||Very fast, short duration trades|
|Emotional Control||Very difficult to trade due to 80/20 rule and buy high and sell low.||Easier as we buy low and sell high||Very easy to use, very fast and exciting trades|
In this category, we will mention a junk drawer of the rest of systems, whose particularities force us to establish differentiated categories, these are less known systems, some are considered ‘extravagant’, and others have important entry barriers, such as mathematical calculation and the need to develop them with good computer equipment. For these reasons, being more restricted to the general public, they have a high potential for growth.
Systems based on lunar phases
These are systems based on lunar cycles. We know that the gravitational force of the moon affects the tides, the movements of the coral reefs and above all affects human behavior, affecting the number of crimes, or births that occur during periods of full moon. If the moon affects our behavior, and the market is nothing more than a mass of traders who position themselves according to their expectations, we come to the conclusion that a system based on lunar phases can make a lot of sense. Many traders have dedicated time to this type of systems, from Larry Williams to Larry Pesavento.
I had always believed it was something ridiculous and senseless, until I saw a Larry Pesavento chart like the ones I show below in Figures 2 and 3, in which the influence of the lunar phases on the chart of the future of the Ibex-35 is clearly seen. It is not about trading, from tomorrow, using the full moon or the new moon, but about having a new field of activity to investigate and that can undoubtedly give many satisfactions to any system developer, who has concerns to expand their knowledge, it is certainly charts that should make us reflect.
Figure 2. Future of the Ibex-35 in a 30-minute bar chart, in which the change of trend produced on January 2, 2003, full moon day, is appreciated.
Figure 3. Future of the Ibex-35 in a 30-minute bar chart, in which the bullish turn that occurred on April 1, 2003, with the new moon and how the rise stopped on the 16th of the same month coinciding with the full moon is appreciated.
Systems based on solar activity
This is a type of system similar to the previous one, in which the signals will be generated through solar spots, instead of lunar phases. Maybe you think I’m crazy trying to look for a relationship between solar spots and market movements, but this relationship exists and is widely documented, as you can see in the following examples.
In times of high solar activity, long-distance radio transmissions are affected, even the interference we see on television is sometimes caused by solar activity, as well as changes in the climate and of course, alterations in human behavior, and therefore in financial markets. During 1987 there were only 3 days when the number of solar spots (Solar Activity Index) was higher than 100, two of these days were October 15 and 16. The probability of correspondence between Black Monday and high solar activity is less than 1%. Probably, now you are more interested than before in this phenomenon and you no longer see it as something extravagant. From my point of view, any phenomenon that, in some way, affects human behavior and can be quantified is susceptible to research by the Trader in his constant search for tools to face the market.
Systems based on cycles
The two previous models are also based on a certain type of cycles, so in this section we will refer to the cycles in a generic way. Cycles that repeat periodically forming figures that we can take advantage of to generate winning operations. Anyone interested in deepening this topic will find Walter Bressert one of the gurus in the matter. Probably, the most famous software on cyclic processes is MESA (Maximum Entropy Spectral Analysis), developed by John Ehlers.
Systems based on neural networks (AI)
Neural networks are framed within Artificial Intelligence and were developed with the aim of simulating the methodology of processing and the decision-making process of living organisms. We will try to simulate the behavior of the neurons of the human brain, with the help of specialized software. Research began in 1940, however, until 1989 specialized software was not developed in financial models, so we are talking about a very young and little evolved working philosophy. The main difficulty of these models lies in the training of the network, which will affect its future learning, as well as the risk of OverOptimization caused by the use of a large number of parameters.
Systems based on econometric models
Through models based on statistical and econometric techniques, we can establish prediction systems for prices, among these models we find the Autoregression models with Moving Averages (ARIMA), which try to predict future price movements, through regressions of past prices. The model is susceptible to include numerous parameters, although in the words of its creators, Box and Jenkins, the success in prediction lies in the development of a system as simple as possible, within a logical and rational base. This last point is applicable to the development of any Trading System, not only to ARIMA models.
Conclusion and final opinion on the various trading systems
After defining the types of traders that exist, we have advanced in the classification of systems. Because each author classifies them according to their experience and knowledge of the market, it is not easy to establish a universal classification. Four categories have been established and we have enunciated the theory of Market Facilitation to highlight the trend-following systems, which are those used by the great traders and those that I recommend from this article.
The important thing about this exposition is to be able to classify our entry and exit rules, although this does not give us anything about the comparison between systems or the way to build a better system, it is a necessary but not sufficient base in our process of developing a trading system with which to generate money in the markets. In subsequent articles we will continue to define the phases in the development of Systems.