With the advancement of technology, Artificial Intelligence (AI) emerges as a potential force to transform various industries, including the world of financial trading. This development raises questions about the impact of artificial intelligence on the trading profession, presenting both challenges and several benefits.
- Pros and Cons of Artificial Intelligence
Pros:
Improved Efficiency: AI can enhance the efficiency of trading operations by swiftly analyzing data and making decisions based on accurate results.
Reduced Human Error: Increased use of AI decreases the chances of human error. Traditional trading heavily relies on human decisions, which can be influenced by emotional factors and psychological pressures.
Increased Response Speed: AI-powered trading can respond instantly to market changes, providing better opportunities to capitalize on fluctuations.
Cons:
Job Loss: The adoption of AI may lead to a reduction in demand for professionals in traditional trading, resulting in the loss of some traditional jobs.
Market Impact: Excessive reliance on AI in trading can cause significant and unexpected changes in the financial market.
Security Issues: The growing use of technology may increase security problems and cybersecurity threats, especially with the storage of large amounts of sensitive information.
- Role of Artificial Intelligence in the Future of Management, Accounting, and Forex Trading
- Transformation in Management: AI technologies analyze vast amounts of data rapidly, providing accurate reports to assist corporate leaders in making informed decisions and improving risk management. Technology also automates routine tasks in management, allowing employees to focus on creative tasks and strategy development. AI’s ability to understand customer behavior and predict their needs contributes to enhancing companies’ interaction with their customers and delivering better experiences.
- Revolution in Accounting: Artificial intelligence enhances the accuracy of accounting processes and reduces human errors, ensuring precise and reliable financial reports. AI can predict financial data, allowing accountants to understand future financial trends and make strategic decisions. Additionally, AI aids in improving compliance with accounting laws and better financial risk management by analyzing big data related to cash flows.
- Advancements in Forex Trading: With technological advancements and increased information speed, AI capabilities can analyze big data in the forex market. This empowers traders to make informed decisions based on accurate forecasts. Advanced technology can continuously improve trading strategies through intelligent market analysis.
AI techniques contribute to enhancing traders’ interaction with trading platforms, providing efficient and sustainable trading experiences.
- Artificial Intelligence Threatens Programmers
Many programmers and software engineers feel threatened about their jobs, prompting many to seek new skills and learn the fundamentals of generative artificial intelligence engineering.
Samir Panakalabhati, CEO of Ceipal, a talent acquisition platform using AI, says, “It is not fair to say that GPT will completely eliminate job opportunities for programmers and developers.” He explains that while these jobs will remain, their tasks and responsibilities may diminish.
Panakalabhati points out the difference between ChatGPT and general generative AI when it comes to the job market. GPT is a mathematical or statistical model designed to learn patterns and provide results. In contrast, other forms of generative AI can offer more by reconstructing different results based on patterns and learning, resembling the human brain.
For example, GPT can generate code in a matter of seconds, meeting the demands of users without the need for direct interaction with programmers and engineers, a process that typically takes days or even weeks.
On the other hand, generative AI can affect developers and programmers more broadly, as this technology can intervene in all stages of work, from creating code to maintenance operations and launching updates. Generative AI mimics the programmer’s work throughout the development process.
These results indicate that, despite the ability of artificial intelligence to predict stock price trends and general sentiments about financial market movements, its accuracy is insufficient. The “linear regression” model can predict closing prices with a reasonable error rate, but it struggles to accurately predict the value of a stock for the following days, limiting its predictive capabilities to just one day.
Therefore, it appears that this artificial intelligence-based model is not suitable for long-term investments. Additionally, the accuracy of algorithms in predicting buying, selling, or holding decisions may not be satisfactory and could lead to capital loss.
In general, caution should be exercised in using this model in the context of financial investment, with a clear understanding of its accuracy limits and not relying entirely on it for critical investment decisions.
Conclusion:
In the fields of management, accounting, and forex trading, artificial intelligence emerges as a pivotal force for development and improvement. Despite adoption challenges, these technologies are expected to positively and sustainably shape the future of these industries. However, a balance between technology and human involvement is crucial to ensure the ethical and effective realization of the anticipated benefits.
