Deep Learning Tools Could Compound Returns on Technical Analysis Trading
Traders can use complicated deep learning tools to understand market behavior and forecast trends with surprising accuracy
Artificial intelligence is upending the financial management industry in spectacular ways. The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. However, deep learning and other artificial intelligence technologies will also change the future of technical analysis as well.
A number of experts have started analyzing the role of AI in technical analysis. One white paper published on Science Direct shows that it could be one of the biggest breakthroughs in modern financial trading.
Will deep learning and AI finally make technical analysis a mainstream financial management strategy?
Technical analysis is a controversial financial management topic. It relies on the premise that human beings make decisions based on deeply ingrained behavioral patterns. Technical analysts try to monitor market trends and make accurate predictions.
There is strong evidence that technical analysis can be effective at forecasting asset prices. However, many notable investors, including Warren Buffett, dubbed the greatest investor in the world, scoff at it. Buffett reportedly joked that he gave up on technical analysis after turning the chart upside down and getting the same results. However, other investors have had much more success with technical analysis.
The skepticism of many fundamental analysts is not proof that technical analysis is invalid. The Journal of Internet Banking and Commerce shows that AI has a lot of potential in this area and will be used in more trading accounts. However, it is a very different skill from fundamental investment analysis. Many investors struggle to master it, which is why it does not have as large of a following as more widely accepted investing strategies.
Artificial intelligence and deep learning are likely to rewrite the script on technical analysis. Complex AI algorithms are capable of analyzing highly complicated trends defined behavioral patterns that human analysts often miss.
Will artificial intelligence make technical analysis much more popular in the future? Could machine learning algorithms outperform seasoned fundamental analysts and legendary investors like Warren Buffett? In order to answer this question, we need to assess the current landscape of AI in technical analysis.
New developments in deep learning with technical analysis
Towards Data Science recently published an article on the intersection of technical analysis and AI. Author Luke Posey wrote that a number of important technical indicators can easily be integrated into these algorithms. One of the most important is called Moving Average Convergence Divergence (more commonly referenced as MACD).
Posey developed an indicator with the Python programming language. He used a number of markers to help track crossovers with this indicator. After Posey tested one of his algorithms with this indicator, he created another set of algorithms with over 50 other commonly used indicators. He claimed that this AI system was able to forecast stock patterns very accurately.
This AI algorithm required several years of asset price data. He originally decided to use a deep learning algorithm that would track a single stock: AMD.
Posey said that his deep learning algorithm was incredibly accurate. He could predict price movements two days out with 91.58% accuracy. He could predict prices up to 10 days out with 83.62% accuracy.
Deep learning is driving tremendous changes in the field of technical analysis
Technical analysis is a complex financial trading strategy. It requires extensive market data, a strong appreciation for immutable human behavioral tendencies and a small leap of faith. Many people were hesitant to attempt to use technical analysis in the past.
However, big data is helping prove the viability of technical analysis in trading financial assets. Traders can use complicated deep learning tools to understand market behavior and forecast trends with surprising accuracy.
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