June 27, 2019
Also known as automated trading, algorithmic trading has been used in the past decade by a number of trading companies, brokers, and individual investors. Over the past few years, a lot has been said and written about algorithmic trading. While there are many video and text-based guides about it online, there is isn’t just one source that will make you a master in algorithmic trading.
So, your best chance of getting good at algorithmic trading is finding out everything there is to know about it. With this knowledge and stock trading software, you will improve your chances of trading the stock market profitably. To help readers get knowledgeable in algorithmic trading, I am going to provide answers to the following 3 most frequently asked questions about algorithmic trading.
FAQ #1. What Is Algorithmic Trading?
This is probably the most frequently asked question about algorithmic trading. To put it simply, algorithmic trading is the automation of trading activities. Automating here means executing trades via computers instead of humans. The automated stock trading app executing the trades is given instructions via ‘algorithms’ defined with the programming language of the software.
An established definition of an algorithm is that it’s a ‘step-by-step process’ of solving a problem. The problem could be a mathematical problem or a computer process. The computers executing ‘algorithmic trading’ place trades automatically based on defined criteria. Within an electronic marketplace, algorithmic trading implementation depends on the development of a broad trading system.
This is a system that includes a set of parameters with a solid and finite scope. The parameters reflect the trading methodology that has been adopted and are based on mathematical computations varying in complexity. Last but not least, algorithmic trading can only be performed using stock trading software.
FAQ #2. What are the Most Commonly Used Strategies in Algo-Trading?
The most commonly used strategies for algorithmic trading are also the best strategies for it. They are the best strategies because they help investors to improve earnings or lower costs. The best and most commonly used strategies for algo-trading are:
1. Trend-Following Strategies
These are strategies that involve following trends in price level movements, channel breakouts, moving averages, and the associated technical indicators. The trend-following strategies for algo-trading are easy and simple to execute since no predictions or price forecasting are required by traders.
2. Arbitrage Opportunities
When you buy a stock listed in two separate markets at a lower price in one market and sell it at a higher price in another, the price difference you get is arbitrage or risk-free profit. With algorithmic trading and the use of a stock trading app, you can find and make use of the arbitrage opportunities in the market. This, in turn, will allow you to trade profitably.
3. Mathematical Model-Based Strategies
These strategies for algorithmic trading involve the use of proven mathematical models to trade on a combination of options. A technology that is helping to better implement this strategy is Algorithmic Intelligence (A.I) software.
4. Implementation Shortfall
The fourth and final most commonly used algorithmic trading strategy today is implementation shortfall. This strategy involves trading the market in real-time to minimize the cost of executing an order and taking advantage of the postponed execution’s opportunity cost.
FAQ #3. What are the Advantages of Algorithmic Trading?
Of course, people want to know the potential advantages of algorithmic trading before they make use of it. Perhaps, the biggest benefit of algorithmic trading is automation which eliminates human error from the execution of trades. Automation also leads to other benefits in trading including:
One of the biggest challenges for traders is showing consistency in trading despite the volatile nature of the markets. There is no hiding the fact that the stock market is volatile in nature. It will be chaotic at times and orderly on other occasions. In other words, the market can be a difficult place for a human trader to act in a consistent and rational manner.
An automated stock trading software, on the other hand, can ensure consistency in trading no matter how volatile a market gets. There are no emotions involved in algorithmic trading systems and orders are executed automatically by computer based on the trade signals. Additionally, the system automatically manages the trade in accordance with the instructions given to it. Finally, the automated stock trading app takes in the profit or loss based on the money management principles it has been programmed with.
Since intricate parameters define them, algorithmic trading systems require mechanical trade execution. Within the content of the performance of a trading system, this means ensuring precision in the execution of entry and stop orders, and the profit target. The precision increases with an increase in the number of trades to be executed by the system.
Even if the rate of error in execution is a modest 2%, it would still mean that 20 trades are almost certain to not produce the desired results. When trades are executed with errors, they are likely to produce random outcomes and compromise the integrity of the entire trading system. An algorithmic trading strategy can help to overcome this by eliminating errors caused by physical order entries.
As seen above, algorithmic trading has several advantages over manual trades executed by humans. With the advent of an intelligent automated stock trading app such as Algorithmic Intelligence (A.I) trading software, the popularity and use of algorithmic trading is only going to grow!
A self-made entrepreneur, Randy Tate built an athletic apparel company that grew to over $5M in revenue. Over the past decade, he has been training employees and business owners on how to market effectively, grow sales and build sustainable growth in their companies. Tate has an enviable list of accomplishments to his name including starting a software company that reached over 150,000 users; developing and overseeing the expansion of the Elite Business Education curriculum program; and co-founding iFlip, a SAAS Financial Technology Company empowering individuals to preserve, protect and grow their wealth through AI investing.