In our community sessions, we noticed that some of our members were very eager to start building their trading products with us, but didn't know where to start. That's why, in this article, we're compiling three beginner-friendly trading strategies that we hope will give you some inspiration. We'll cover signal detection, sentiment analysis, and pair trading. Better still, you can mix and match them to create your own trading philosophy. Let's start learning now...

 

Let's say you want to trade just like quantitative funds do. What do you need to know? In the United States in 2018, between 70 and 80% of total trade volume was generated through algorithmic trading. It's a pretty safe bet to say that most major institutions use algorithms to power their operations. And often their algorithms are based on one or more well-known trading strategies. Getting familiar with some popular strategies is an excellent way to start your automated strategy journey. Of course, keep in mind that there are many additional components that can make or break a trading strategy, such as trade location, execution speed, market timing, and knowledge about the market.

 

A trading strategy will be either based on the core or back to momentum or average. Others say this distinction can only be applied to technical trading strategies, but for simplicity's sake, we'll assume this classification is valid. The first is the theory that an entity, like a particle, has momentum. If it is rising, it will continue to rise due to momentum. If momentum slows down, it's probably time to get out of your position. Second, it refers to the theory that if they deviate from the mean, prices will revert to the mean. You may find that these schools of thought directly contradict each other. This observation would be correct. So, which should you base your trading strategy on? It totally depends on your trading goals and trade horizon. Momentum-based strategies often perform better in the long run.

 

Signal Detection

 

In trading, signal detection looks for certain predetermined criteria that indicate whether a security should be bought or sold. Signal trading or signal detection is really an umbrella term with many different types of approaches falling under it. The main goal is to develop a methodology with input and output thresholds that can be defined by various signals. For example, you can monitor the volume of a particular stock. If volume seems to be increasing with price, this may indicate that investors believe in that stock. 

 

This will likely be a momentum trading situation, as the response will be to jump in trend (as harmonious price and volume gains often indicate higher prices as well as more purchases in the future). However, at some point, volume can dry up, for example, because investors are not willing to pay more than a certain price for a stock.

 

What Types of Trading Signals Can You Use?

 

The 'signal' need not be volume related. In fact, it can be anything you consider important as a trader. They usually rely on some form of technical analysis, such as setting triggers based on:

 

• Relative Strength Index (RSI),
• Moving Average (MA),
• Moving Average Convergence Divergence (MACD), or
• On-Balance-Volume (OBV).

 

These are often called technical indicators, which are mathematical calculations based on an instrument's properties to predict future performance. Maybe you've heard the terms 'up' and 'down' before. It is usually related to trading sentiment based on technical indicators.

 

The relative strength index is a momentum indicator that measures whether an instrument is overbought or oversold based on recent relative price changes. The moving average (MA) is the average price for a given number of days in the past. It cannot be classified purely based on momentum or averaging because it depends on what you do with it. A return-to-average strategy can execute a buy order if a stock's price exceeds its 200-day MA.

 

How to Analyse Sentiment?

 

There are several ways to analyze emotions. Maybe you believe that frequency is a good indicator of a stock's popularity - if more people are talking about a stock, that should be a good sign, right? Not necessarily. The language used to describe the stock can be negative. Therefore, it is often not enough to simply sum up how many times a stock is tweeted per day, for example.

 

Sentiment Analysis is based on Natural Language Processing (NLP), which scores texts according to the emotion they convey. At least NLP can distinguish between positive, neutral and negative posts. However, more complex applications can go beyond these three simple categories and also describe emotions such as anger, disgust, fear, hope.

 

Why Does Pairs Trading Work?

 

In pairs trading, the assumption is that two financial instruments that were highly correlated in the past will remain correlated in the future. In the scenario where the correlation is temporarily broken, one stock moves up while the other moves down, trading pairs is to short the 'winner' stock and hold the 'loser' long, betting that prices will move.

 

Pair trading provides room for profits in any market, up, down, sideways. The market is neutral, which means you are betting on the spread of the pair, not the direction of the market. However, because spreads (especially those of historically correlated pairs) move less than the market, traders often need to be leveraged for pairs to be efficient for trading.

 

Conclusion

 

Learning about the different pre-existing trading strategies is the first step in designing your own strategy. In fact, you can combine signals trading, sentiment analysis and pair trading to create your own 'super strategy'. It's all about finding a market inefficiency and rolling with it.

 

We hope that this blog post will be beneficial for you. We will continue to create useful works in order to get inspired by everyone. We are sure that we will achieve splendid things altogether. Keep on following Finage for the best and more.  

 

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