Past market behaviour and trends, reactions, roadmaps, and statistical data are aspects that constitute a technical analysis for trading. Owing to the analytical nature of trading, artificial intelligence (AI) and machine learning (ML) have significant scope to be inculcated in trading.
Today, we already find ourselves in an automated or algorithmic era of trading: When certain requirements are met, computers are instructed in accordance to trade independently. This has paved the way for complicated trading techniques to be executed with greater accuracy vis-à-vis manual trading. Investors and brokers have also been able to plan and execute strategies in advance. For instance, traders can leverage automatic stop-loss orders to mitigate the impact of downside risk.
Based on insights, let’s delve deeper into the impact that AI and ML are set to have on trading.
With the worldwide pandemic leading to increased volatility, the impetus behind machine learning is gaining traction. Experts believe that models created with machine learning are quicker, more sophisticated, and better able to react to severe occurrences, such as the COVID-19 outbreak-induced spike in volatility. Further, being that we are living in times that are unprecedented, relying extensive on historical market trends is no longer a good strategy.
According to the Aite Group’s study “Hedge Fund Survey, 2020: Algorithmic Trading,” the major reason for the rising use of algorithms in trading is to try to decrease the impact of the human factor on the market, which is a result of its high volatility. The economic impact from COVID-19 has resulted in a record-breaking slump in the financial markets of the United States, Europe, and China.
We have also come to realize that trading with algorithms isn’t always perfect. We can teach a machine to execute A when B happens via algorithmic trading. Humans can pre-program and set criteria, while the computer does the rest. However, when presented with conflicting or unexpected facts pre-programmed techniques might break apart. So, what then is the solution?
Better market insights
Real-time data analytics and automated trading options have the potential to transform the market. It allows traders to examine live pricing in real time, detect problems sooner, and nearly instantaneously correct them. Machine Learning can analyse trading data in real-time using vast quantities of historical data, offering greater insights into the market and assisting traders in developing trading strategies, based on current market volatility.
Nikkei, a Japanese company, is an excellent illustration of how predictive analytics may be advantageous in the currency market. They held a quarterly Dollar-Yen derby, in which they used Artificial Intelligence to forecast exchange rates for the following month. The AI software gathered information from a variety of sources, including the organization’s articles, industry trends, and market swings. They compared the findings of predictive analysis against the forecasts of their top analysts to see how effective it was. The results were astounding: The AI software provided a much more accurate estimate (it was only 0.05 away from the exact value).
The road ahead
Analytics and AI are taking out much of the guesswork in trading. They will play a critical role in wealth creation by protecting traders from sudden market fluctuations and false signals.