Artificial Intelligence (AI) has played a pivotal role in pushing digitisation in several realms of financial management, more specifically, portfolio management. From big data to GPUs, AI has skyrocketed its advancements in the fintech domain.
Artificial intelligence-based technologies have finally been optimised in the finance space with the introduction of Robo-advisors and algorithmic trading. Quite a few fintech organisations have focused on uplifting the usage of AI for various purposes like automatic savings and risk management. This has transformed how investors manage their portfolios. Let us see how the upcoming technologies have paved their way into the investing decisions of experienced as well as novice investors. But for that, let us start with understanding what exactly AI is.
What is AI?
AI or Artificial Intelligence is any software that a computer uses to imitate the characteristics of human intellect. Currently, some of the AIs that you come across in everyday life include Amazon’s Alexa, Apple’s Siri, AlphaGo and many more. Alexa and Siri use NLP algorithms to decipher a language, whereas AlphaGo has beaten the champion Go player. So yes, it would not be a challenge for you to understand the capabilities of artificial intelligence in today’s world!
A few of the most used AI techniques are:
- Genetic algorithms: This is a heuristic algorithm that is search-based and derives its inspiration from Charles Darwin’s theory of evolution. This algorithm is mainly used to deal with optimisation and search-based issues.
- Cluster analysis: This is an unsupervised method of machine learning. With this AI technique, you can identify and group similar data points in terms of properties and features.
- Support vector machines: This is a supervised machine learning method that categorises data for regression and classification analysis. However, it is used more for the purpose of classification.
- Decision trees: Like SVMs, decision trees are also a supervised way of machine learning. Yet, this is non-parametric and used for regression and classification.
With this basic understanding of AI, let us now decode AI in portfolio management. But first, a quick look at what is portfolio management?
What is portfolio management?
By portfolio management, we refer to the process of making decisions viz-a-viz the contents of an investor’s investment portfolio. Portfolio management stresses on policies required for managing the investments for an investor. This is based on their financial goals, asset allocation strategies, objectives, and risk appetite. Portfolio management is a financial service rendered by professional financial advisors and investment planners. They are experts with experience in managing investment portfolios, with the ultimate aim of generating high returns and minimising the scope for losses.
Portfolio management helps minimise your risks by a proper set of investment-related plans and strategies that aim at diversification. Suppose you are willing to invest in bonds, stocks, or other assets. In that case, portfolio management will ease your burden by identifying the strengths and weaknesses of your investment choice so that you do not face any unexpected risks.
The objectives of portfolio management include:
- Increase of investment returns
- Appreciation of capital
- Optimal allocation of resources
- Improvement of your overall portfolio by analysis and diversification
- Increased flexibility and dynamism of your portfolio
- Optimisation of your risks
- Protection of your returns against market hazards
Let us understand how the two are related and how AI impacts portfolio management.
Impact of AI on portfolio management
Artificial Intelligence is increasingly impacting portfolio management. From asset allocation to risk management, it is transforming the conventional ways of managing portfolios.
AI assists in the following tasks:
Portfolio optimisation
Artificial intelligence techniques can be implemented to maintain the accuracy and precision of your expected return on investments. This is done by checking variances and choosing the optimal weights of your assets. Despite the accuracy that comes with AI, it is rather difficult to optimise the technical assistant to suit all situations. The dynamic state of the market creates hundreds of possible scenarios, making it difficult to programme AI in a way that it incorporates all of those. However, AI aids financial experts in quickly carrying out an analysis of your returns based on their inputs.
Fundamental analysis
Artificial intelligence techniques can also be applied for organising textual research of economic reports, annual reports, and any other helpful document and statements. This frees the portfolio management experts to focus more on the implementation of data rather than research.
Moreover, other AI methods can also determine the confidential correlations and then pick the stocks that can either surpass or underperform according to those correlations. However, not every trade is based on data. AI lacks the gift of intuition that humans possess. Due to this, human experts still have an edge over AI in terms of emotional intelligence while trading.
Risk management
Risk management is an essential element of portfolio management. In fact, the overall goal of diversification is to reduce the overall risk you undertake. For this, detailed research is paramount. Artificial intelligence techniques can integrate data from social media and news reports and deliver risk variables.
That being said, just sourcing the data is not enough. Portfolio management experts analyse this collected information to understand the impact of a situation. With the right AI tools employed by the best experts, validation of current risk probabilities can help prevent long-term losses.
The takeaway
AI is the new kid on the block, disrupting the archaic and traditional financial management system. As is expected with any new technology, investors and institutions alike are still wary of the things AI can help achieve when it comes to portfolio management.
However, combining AI with the expertise of portfolio managers, a lot more can be achieved. The routine tasks of crunching numbers and sourcing data has become faster with the help of AI tools. It gives experts more room for analysis and experimentation to deliver the highest possible returns.
In a nutshell, artificial intelligence has a broad scope, and all its uses are still being explored. However, it is a given that AI would not be replacing humans anytime soon. It is a welcome aid that requires steering from human experts to deliver the best results.
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