Common Types of Algorithmic Trading Strategies

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To understand algorithmic trading strategies, you must first understand how large orders impact the market. When an investment firm or brokerage makes a huge order for shares in a stock or another security, everyone else takes note, which means that the order can artificially influence the market.

It’s just like a consumer market. If you saw everyone clustered around a specific product at a store, wouldn’t you want to know what was so special about it? You might even buy one without doing any other research just because you know it’s popular.

The stock market can succumb to that type of trade influence, too, and market makers avoid the problem by using child orders and algorithmic trading strategies.

It’s a great idea to learn as many day trading strategies as possible. Adding an algorithmic factor to your investment approach can strengthen it.

What Are Algorithmic Trading Strategies?

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Algorithmic trading strategies use technology to execute trades long after you place the order. Each system works differently, but the object is to improve your odds of profiting by spreading out orders or waiting for the right conditions to arise.

Other forms of algorithmic trading strategies involve using complex mathematical algorithms to execute trades automatically. In other words, the computer does the heavy lifting by sorting massive amounts of data and searching for the right environment in which to invest.

Some algorithmic trading strategies involve day trades or swing trading, while others involve long-term investments.

What Are the Most Common Types of Algorithmic Trading Strategies?

Many types of algorithmic trading strategies exist. The more you know about them, the easier it becomes to make smart, profitable decisions.

Some rely almost exclusively on mechanical intervention, while others require human involvement in at least parts of the process. Regardless, the major investment firms and market makers have far greater technology than we do, so every advantage helps.

Now that we’re comfortable with the terminology, let’s take a look at some of the most common forms of algorithmic trading strategies. You can get a feel for each one and decide if any of them sound like good fits for your goals and risk level.

Momentum

Market trend and market sentiment are extremely important to momentum trading. The goal is to find patterns that indicate a continuing trend in one direction or another, and then to capitalize on it. You might buy a small position of a particular stock, for instance, then add to it as the price movement works for you.

By executing these trades through algorithmic trading strategies, you don’t have to watch them carefully. Instead, you can use a trading platform to tell the system when you want specific orders to be executed.

Trend-Following

Similarly to momentum trading, trend trading is one of the most popular algorithmic trading strategies. It uses algorithms to find specific patterns upon which to execute trades. Specifically, when a stock breaks resistance, you might have executed an order to buy. If it cracks resistance, you might short-sell that security.

Statistical Arbitrage

Arbitrage is not nearly as common today as it was before the internet became available to traders. Generally speaking, arbitrage occurs when the value of a security, such as shares in a stock, are different in disparate markets.

For instance, if Stock XYZ is valued at $10 per share on the New York Stock Exchange and $9.85 per share on the London Stock Exchange, you could buy the stock from the London exchange and sell it on the NYSE for a profit.

Algorithmic trading strategies that incorporate arbitrage use highly sophisticated systems that must buy and sell trades extremely quickly. Arbitrage situations don’t last long, so you need the algorithmic component to take advantage of arbitrage when it occurs.

Factor-Based

If something has happened at the same time of year every year for 10 years, would you expect it to happen during the 11th year as well? Probably.

That’s how factor-based trading works. Like other algorithmic trading strategies, the computer system looks for circumstances that arise around a given price movement for a security, then searches for those same conditions to recur. By buying or shorting stocked based on specific factors, such as market capitalization or free cash flow, you set yourself up for a profit.

Mean Reversion

There’s an assumption among stock traders that stock prices often return to a mean price after they undergo drastic price movements. It’s kind of like an object coming to rest after it’s been flung about by the wind.

Algorithmic trading strategies look for these situations to capitalize on the reversion. For instance, if a stock has been significantly overbought, the algorithm will initiate a short sell to take advantage of the inevitable fall in price.

This often works best after a pump-and-dump, which occurs when a well-known authority promotes a stock heavily. Suddenly, everyone’s buying the stock, but eventually there will be a panic. People who bought will be looking for buyers like crazy, and you can capitalize on the swing in price.

Scalping

Scalping might sound like a bad thing, but it can actually result in profit. Unlike other algorithmic trading strategies, scalping relies on the differences between the bid and ask price of a given security. The goal is to create such an impact on the market that the trader creates the bid-ask spread.

It’s not easy to do, and you need serious capital for this to work out. If you’re an amateur in investing, stick to less complex day trading strategies until you’re more comfortable.

Sentiment Analysis

Market sentiment simply describes the way in which a crowd views a particular stock. If you buy 100 shares of Stock XYZ and many other traders follow suit, you would call that positive market sentiment. If traders are dumping shares as fast as they can, there’s a source of negative sentiment.

One of the most common algorithmic trading strategies uses computer processing power to aggregate all types of information, from news stories and social media to earnings reports. It then predicts market sentiment and executes trades accordingly.

Conclusion

If you’re new to trading, you might not have tried any algorithmic trading strategies. That’s okay. Work your way up to this more advanced way of making trade decisions.

For a sneak peek, try paper trading. It’s a great way to get your feet wet and learn how trading platforms work without putting your own money at risk.

In the meantime, you want to know what day trading strategies work and which ones don’t. I’m here to help. Sign up for Stealth Profits Trader to get access to some of my best advice and tips on day trading strategies today.

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