Understanding Benefits Of Algorithmic Trading: With the advancement in technology, humans have become more reliant on computers and modern machinery for the completion of their tasks.
Technology has become so advanced that humans can trade/invest automatically in the stock market with the help of a few commands. Yes, we are talking about Algorithmic Trading which is gaining popularity in the modern era.
In this article, we will be discussing what is algorithmic trading and the Benefits of algorithmic trading.
What Is Algorithmic Trading?
Also referred to as algo-trading, black box trading, or automated trading, Algorithmic trading is a strategy that involves using computer programs to execute trades under a specific set of instructions.
Price, timing, quantity, or any supporting mathematical model are the basis for its operation. This sort of trading has gained popularity because it may provide income and profits at a rate that is difficult for a single human to achieve.
Due to its high profits, a large number of traders now rely on high-frequency trading in the market. The ability to place a large number of orders across multiple markets is one of the high-frequency trade’s distinctive qualities.
Additionally, it operates at rapid speed thanks to preprogrammed instructions. In this trading system, a computer program is designed in such a way that it monitors the prices and places the orders upon the completion of set conditions.
This manual intervention is reduced significantly as the trades are executed by the system and not the trader. Now that we have understood the meaning of Algorithmic Trading, let us look at the benefits of algorithmic trading
Benefits Of Algorithmic Trading
1. Increased Speed
Since trades use the swings in the prices of the securities to capture trades, speed becomes one the most important factors while trading. Algorithmic trading enables quick execution of trades by instantly examining various parameters and technical indicators.
2. Increased Accuracy
As algo trading is computerized, it will lead to less human intervention resulting in reducing of human errors. Although an individual can misinterpret the technical indications and analyze them improperly, algo trading can avoid such discrepancies as it is automated on a computer,
3. Capacity To Quickly Execute Several Trades
Algorithmic transactions enable traders to carry out several trades while maintaining accuracy and speed. This in turn increases the chances of an individual making more money by executing multiple trades simultaneously.
4. Back Test Capability
In order to prevent excessive losses, traders must find out about their flawed trading system and make changes to them. Algo trading enables traders to back-test their trades using historical data and contrast them with recent data. This method is recommended to ascertain whether transaction outcomes would have remained the same,
5. Lower Transaction Costs
As traders don’t need to stay stuck to their devices to constantly monitor their transactions, algo-trading greatly reduces transaction costs.
The programmed set of instructions monitors the trading activities which enables the trades to be conducted without constant supervision, saving costs and time that would have been used to constantly monitor trading activities.
6. Trading At A High Rate
High-Frequency Trading (HFT) is a unique approach to algorithmic trading that uses highly effective and powerful computers to carry out trades in accordance with a specific set of instructions.
These complex algorithms enable extremely fast processing of these transactions. Trading turnover is typically higher for users of high-frequency trading systems than for users of other systems. Algorithmic trading has high trade ratios in addition to large turnovers.
Drawbacks Of Algorithmic Trading
- As Algorithmic trading is an online trading strategy executed through the use of computers, it is highly reliant on the internet and computers. Any failures in the system or issues related to network connectivity can lead to failure to properly execute trades, which in turn can result in losses.
- As algorithmic trading involves costly and complex technology, it may be found challenging to many individuals as they lack the cash and expertise to pay for such services.
- Malfunctioning of Algos can sometimes lead to manipulation of the market as the malfunctioned Algo can push the market in a certain direction creating an artificial Demand or Supply.
Popular Strategies Of Algorithmic Trading
Now that we have looked at the drawbacks and benefits of Algorithmic Trading, let us take a look at some of the popular strategies of Algorithmic trading:
1. Momentum Strategy
Momentum trading is a strategy used by companies and traders to invest and buy shares when their value is increasing and sell them when they are showing signs of falling down.
This strategy utilizes market volatility to make huge returns. In short, this strategy works by buying short-term uptrends and selling them as soon as the price starts falling.
2. Mean Reversion Strategy
The mean reversion strategy postulates that the extreme move in the prices is hard to sustain for an extended period and it tends to return to their average price levels. Many methods have been used by traders who partake in mean reversion to capitalize on the theory.
In every instance, they are placing a bet that an extreme level, such as volatility, price, growth, or a technical signal, would eventually revert to normal. The mean reversion technique attempts to capture profits as an asset price reverts to average or normal levels.
3. Sentiment-Based Strategy
Sentiment strategies work by filling positions in the market driven by bulls and bears. When there is optimism in the market, there is a strong likelihood that the price of an asset will increase.
On the other hand, when there is a pessimistic outlook and prices are anticipated to decline.
In this article, we covered the meaning and benefits of Algorithmic Trading and also strategies used in algorithmic trading.
Algo trading will increasingly incorporate artificial intelligence as it continues to advance. As the algorithms utilized advance in complexity, more automation will be made possible in the future.
Systems might be able to develop themselves, adapting and improving their techniques to account for additional market volatility.
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