Market Overview

The Advantages Of Using Algorithms In Your Trading Toolkit


High frequency trading is often known as algorithmic trading due to the high speed buying and selling of stocks and other securities aided by sophisticated computer algorithms. In previous years, high frequency or algorithmic trading was reserved for the extremely wealthy and hedge funds. But these days, the technology has improved both in accessibility to the intelligent investor as well as in terms of transaction costs. In fact, transactions costs have been trending towards becoming much more inexpensive, including at price points that experienced investors can often afford. Therefore, algorithmic trading may be another tool to add to your trading toolkit. Let’s examine how in this article.

Bring The Power of Hedge Fund Trading To Your Portfolio

One of the biggest obstacles financial traders face is the problem of making emotional investment decisions. A person can develop a successful, high-returning portfolio based on years of sound strategy, but can cause a serious drop in that portfolio with one unintelligent and emotional investment decision. One benefit of algorithmic trading is that you can build an algorithm to execute your investment strategy, without worrying about the system making an emotional investment that may be unsound.

Another important reason for harnessing algorithmic trading is that this technology has previously only been available for the wealthiest and best-connected investors. As a result, retail investors have been kept out of the loop, creating unfair advantages for wealthier investors who had access to more sophisticated trading technology. But due to the consistently declining costs of algorithmic and high frequency trading, you can now have access to the same technology. This evens the playing field, so that you can benefit from a technology that was previously out of your reach.

And there are now several platforms that offer sophisticated, algorithmic trading to ordinary investors. Services such as QuantShare, AlgoTrades and OptionsCity all provide unique opportunities for retail traders to gain access to this niche.

For example, at OptionsCity it’s possible to buy (and sell) different algorithms in the Algo Store. These algos can then be implemented without the need for expensive setup and development costs. They can then be fine-tuned and run over market data which can be recorded and replayed at various speeds.

Further benefits of Algorithmic trading

Services such as OptionsCity’s Freeway Analytics and the others mentioned above are useful as they provide an all-in-one type solution and remove the barriers for true system trading. And one of the most important benefits of algorithmic trading is the ability to implement the process of back-testing. 

With back-testing, (or back-trading), you can apply your algorithmic model to historical market data in order to test the viability of your strategy in different markets. When you land on an algorithm that is consistently outperforming your other strategies, whether in an up or a down market, then you may have found a strategy that could outperform the market now and into the future, and therefore deliver higher and smoother returns.

Finally, algorithmic and high frequency trading brings with it the ability to place high-speed trades with improved order entry speed and functionality. When you are placing trades that rely on real-time market data, the movement of even a few seconds could be the difference between a decent trade and a huge gain, or a gain and a loss. With algorithmic trading, you can place that trade faster so that you can better and more accurately execute your trading strategy in the market.

As algorithmic trading becomes even less expensive and more mainstream, individual investors are going to leverage this high-performing resource in order to maximize their returns. As such, the sooner you evaluate algorithmic trading for your portfolio, the sooner you can take advantage of the technology before the rest of the market does.

The preceding article is from one of our external contributors. It does not represent the opinion of Benzinga and has not been edited.


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