The ongoing banking disruption across America, coupled with the emergency takeover of Credit Suisse, highlights the challenges of managing investment portfolios in volatile markets.
Asset managers regularly look for ways to improve their investment strategies to make better decisions and weather times of volatility. The rise of AI technology has meant that asset managers now have access to powerful tools that can be used for effective portfolio decisions that align with complex market dynamics.
AI technology has become immensely popular with fund managers in recent years given its ability to generate alpha through challenging market conditions by providing predictive insights, portfolio optimisation and risk management tools, the effectiveness of these AI models. Today, as asset managers face difficult decisions in an increasingly volatile market, AI is clearly something that they should have on their radar.
Advanced analytics and data systems
One of the most effective benefits of AI technology is its ability to analyse huge datasets quickly and accurately. AI has a superior ability to identify non-linear patterns in data (such as fundamentals, technical indicators and macroeconomics), see how those patterns have developed over time and how they interact, and use them to predict future returns.
The majority of AI models use machine learning algorithms that can analyse historical data and identify patterns to indicate to portfolio managers where there are potential market shifts, meaning appropriate action can be taken accordingly. Using this historical market data, these models generate predictive signals that can be used to inform decision-making. Axyon AI’s system, for example, has been actively providing interesting alerts on the banking sector throughout the first two months of this year, including alerts of potential risks, using macroeconomic data and price action to elaborate its view.
This suggests that disruption in long-standing patterns and dissonance between market prices and fundamental/macro data can be detected earlier by AI, providing asset managers with valuable insights into how to minimise risk while making more effective decisions with their quantitative and discretionary strategies.
Automation of tasks and market insights
Alongside advanced analytics capabilities, AI technology can be used by asset managers to automate specific tasks, granting managers more time to spend on more significant aspects of their portfolio management.
Risk assessments and portfolio rebalancing can be time-consuming and require high levels of expertise – with AI-powered models, however, portfolio managers can save a considerable amount of time and reduce errors for these tasks that remain critical, particularly during volatile periods which demand increased scrutiny and attention from managers.
In addition, AI is capable of providing insight into market conditions by scoping a broad range of data sources to provide asset managers with further insights into market trends and investor sentiment. In order to react quickly to changing market conditions, it is essential for asset managers to be well equipped with AI-powered signals that can detect shifts in market data and respond in real time to changing trends, such as the ongoing banking issues across Europe and the US.
There is no doubt that with AI, investment managers can examine data more efficiently, receive timely insights and use AI-based suggested model allocations to generate alpha and maximise the potential of their portfolios during periods of economic uncertainty. Particularly in these volatile periods, this is an area that professionals in asset management should certainly be taking note of.
Written by Daniele Grassi, CEO at Axyon AI
Originally published on IFA Magazine and reproduced with kind permission.