Crowd path following may not always be advisable, but when it comes to trading, going with the trend is usually a good idea.
Trend following is probably one of the oldest approaches to investment, still widely and successfully implemented in modern days trading.
The approach is based on making trading decisions solely according to the observed market trend.
A trend is an observable direction of the market – up, down, or sideways and by acting in concert with the market trend, we significantly increase our odds of success.
A trend is determined by comparing current data with previous data, in order to evaluate the price direction.
The accuracy of the evaluation depends on the methods used for comparison.
Patterns change on daily, monthly and yearly basis, providing an enormous amount of data, which often makes it difficult to recognize a trend.
Trend-following is a reactive trading method in response to the real-time market situation.
It does not attempt to forecast the market direction, but activates the trading rules once the trend is identified and adheres rigidly to the rules until the next trend is identified.
The nature of trend-following makes it ideal for implementing in automated trading software where human intervention is not required.
Over the past decades, manifestations of automated trend-following, such as Turtle Trader software, emerged in the financial industry.
Nowadays there are many types of trend-following algorithms, that can be used with different timeframes (intraday to long-term) and different indicators (moving averages, support and resistance, Bollinger bands, parabolic SAR, etc.). Algorithms do not predict the market movement, but merely identify a trend at early stage and trade automatically afterwards by a pre-defined strategy regardless of the changes in market direction over the set timeframe.
Automated trend following has been growing in popularity and for a good reason.
Software is able to analyze a vast amount of data in a short period of time, which greatly increases the chances of correct identification of a trend.
However, algorithmic trend following remains to be dependent upon the human judgement applied in setting the rules (strategy) manually. Artificial intelligence (AI) systems employ various trend following software, including the “trend recalling” models that work by partially matching the current trend with one of the proven successful past patterns – a method that has proved to be highly profitable.
But artificial intelligence takes trend-following much further than any previously known and tried algorithmic trading strategies. Previous systems, limited by market volatility and prone to false signals, are surpassed by behavior -based artificial intelligence. Trends are based on certain human elements and the quintessential of artificial intelligence technology is its ability to identify, with high accuracy, both human patterns and market trends.
Artificial intelligence trading systems employ neural shells that operate similar to the brain’s neural network.
Neural shell consists of sophisticated algorithms that imitate certain aspects in the functioning of the human brain.
This unique self-training quality enables them to make forecasts based on historical data they are provided with.
Each “neuron” in a neural shell performs complex calculations, capturing and organizing historical and statistical data. A neural shell consists of layers of interconnected nodes. Each node is a perceptron and resembles a multiple linear regression. The perceptron feeds the signal generated by a multiple linear regression into an activation function that may be nonlinear. A neural shell analyses a vast amount of data, evaluates trading opportunities and makes trading decisions based on the calculations and thoroughly analyzed data.
The neural shells are able to detect subtle interdependencies, co-relations and patters that are too difficult to find and quantify using other methods, with high level of precision and in extremely short periods of time. Trend-trading strategies used by artificial intelligence systems vary widely, in accordance to many different factors – timeframe, bullish/bearish markets, price fluctuations (volatility) and more, but any AI trend-trading strategy will be based on two main characteristics:
One of the key benefits of artificial intelligence trading is that while being highly adaptive to real market conditions, it never breaks the rules. Anyone who ever tried to trade trends manually is likely to have encountered common problems, such as false starts, early shakeouts, premature or late exits. The reason? Psychological factors.
Diversifying your trend following opportunities is absolutely vital for a long-term success. With artificial intelligence systems, it is possible to diversify investment by adding different time frames, different entries on a per market basis, or different markets and asset classes. You can choose to use one or all three of these approaches.