Exploring Artificial Intelligence in Fixed-Income Trading: Is it a New Era and Who are the Actors?

The use of Artificial Intelligence (AI) in fixed-income trading raises the question of whether there is a paradigm shift occurring, and who the prominent participants in this new approach are. On December 27, 2023, AI has only scratched the surface of its potential to create more informed, efficient, and profitable trading. It can compile data from past trading patterns and provide forecasts for markets that are not easily accessible. This predictive intelligence enables traders to time their trades and optimize returns while reducing risk levels. I have seen experienced traders do this on their own, but AI can do it quicker and more accurately. The best approach may be for man and machine to work together as AI matures. We can anticipate further developments and entirely new business models, though the latter remain to be seen. According to the McKinsey Global Institute, there could be a potential annual value addition of up to $4.4 trillion globally in specific industries due to general AI, based on 63 use cases they evaluated. They have also determined that the banking sector could potentially gain the most from this. It's indisputable that the most recent AI model strategies are apt for assisting individuals in apprehending liquidity status and the way it rapidly varies, and to put that knowledge to use while trading in fluctuating markets. Market changes in interest rates, valuation, credit quality, prepayments, liquidity, early redemption, corporate events, and tax implications give rise to challenges. Consequently, asset managers look to develop technology-based solutions. External forces such as geopolitical tension and the price of energy and commodities can have a great influence on nations; thus, the challenges caused by the economic cycle become more complex. Fixed income trading need not be challenging anymore, as the use of ISINs, AI, trades, and axes (like IOI) in a portfolio give more visible (observable) prices to traders. Going forward, a combination of both manual and automated processes will be the best approach as AI continues to develop. As data in the capital markets sector multiplies, it can become tough to manage event-driven volatility and trading issues. Companies today strive to maintain an advantage by utilizing data which is more accurate and of higher quality. To obtain such data, they rely on multiple vendors and legacy system engines connected to brokerage platforms and end-of-day performance accounting engines, creating a complex process. The quality of any AI model depends on the data it is based upon, and so all these issues with the data will affect its output. It is undeniable that Artificial Intelligence has enabled traders to access more informed insights and predictions based on the quality of the data. AI has become a necessity for financial institutions, enabling them to make better decisions as markets change quickly. Moreover, it can help detect potential opportunities or risks that may have gone unnoticed before. Ultimately, to ensure risk is mitigated and promote technological growth, it is necessary to keep advancing with AI. This competitive landscape for Fixed Income platforms using AI includes major actors such as Bloomberg, Euronext MTS Markets, MarketAxess, Tradeweb, and Investor Perform. Do you know of any other important stakeholders in the highly competitive market and things that could enable AI to be used more in Fixed Income portfolios? Twitter handle: @FintechSinghE | Email: hardayals2ngh@gmail.com

Source: https://medium.com/@hardayals2ngh/dec-27th-2023-ai-sets-the-stage-for-a-more-informed-efficient-and-profitable-trading-future-48e3b8a0e450?source=rss------fintech-5