Diversifying your investment portfolio using artificial intelligence: Risks and benefits
Expanding your investment portfolio by trading multiple asset classes is a tried and proven method of managing risk and opening the door to additional market opportunities.
While portfolio diversification can be done manually, with the massive increase in widespread access to artificial intelligence (AI) bots, investment portfolio diversification using AI has gained popularity. The AI revolution has brought several benefits to investors but also difficulties.
Advantages of artificial intelligence in expanding your portfolio
Diversifying your investment portfolio using AI can be highly beneficial. The machines do not deviate from the trading plan by changing risk parameters based on emotions. They also don’t get tired and can work 24/7 to track and analyze vast amounts of data across multiple markets.
The latest generation of machine learning (ML) algorithms have enormous computing power and can simultaneously evaluate millions of data points to build an ideal diversified portfolio that perfectly matches a trader’s risk appetite and trading goals.
By building an investment diversification strategy using AI, investors can benefit from accuracy, scalability, and speed that humans could never match. Strategies can be backtested to model different outcomes and accurately quantify returns.
The AI bot can manage a huge volume of portfolios simultaneously, automating manual processes to reduce trading time and costs, providing professional analysis at a fraction of the price a human investment advisor would charge, and making financial markets accessible to a broader audience.
Disadvantages of using AI for diversification
On the other hand, diversifying using AI exposes the trader to some risk. The most important of these is that a trading bot is only as good as the data it receives. If the data on which he bases his decisions is of low quality, this will hurt his trading results. Faulty information inevitably leads to poor market decisions, and biased data and algorithms can lead to discriminatory, unethical allocations of funds within a diversified portfolio.
Artificial intelligence is also only as secure as the platform it runs on. An untrustworthy company or one that does not implement stringent security measures can expose you to the risk of hacking and fraud. Moreover, outdated algorithms can mean inefficiency and a significant waste of funds, as can over-reliance on backtesting historical data as a predictor of future performance.
A diversified AI investment portfolio may also pose risks related to the lack of audit trails, transparency, and explainability of AI decision-making processes. Moreover, relying on a machine entails a loss of insight into reality and the benefits of human judgment gained from experience in the field. So, an unexpected market event causing massive shocks can throw the AI off its game because the algorithm is unlikely to account for a black swan event.
Ability trades are lower at higher levels of trading.
Moreover, the higher the level, the higher the compensation for failed trades and the more trades are made in the account for more significant amounts.