Investment Portfolio Diversification Using AI: Risks and Benefits

Investment Portfolio Diversification Using AI: Risks and Benefits

Editorial Note: The following content does not reflect the views or opinions of BeInCrypto. It is provided for informational purposes only and should not be interpreted as financial advice. Please conduct your own research before making any investment decisions.

Broadening an investment portfolio by trading across multiple asset classes is a tried and true method for managing risk and opening the door to additional market opportunities. 

While portfolio diversification can be performed manually, with the massive growth in mainstream access to artificial intelligence (AI)-based bots, investment portfolio diversification using AI has surged in popularity. This AI revolution has brought a variety of benefits and drawbacks for traders.

The Advantages of AI for Portfolio Expansion 

AI diversification of investment portfolios can be incredibly beneficial. Machines don’t get diverted from a trading plan, changing risk parameters based on emotion. They also don’t tire, and can work 24/7 to track and analyze enormous amounts of data, relating to multiple markets.


The latest generation of machine learning (ML) algorithms has immense processing power and is able to assess millions of datapoints simultaneously to build the ideal diversified portfolio that is perfectly suited to the trader’s risk appetite and trading goals. 

When building an investment diversification strategy using AI, traders can benefit from accuracy, scalability and speed that a human could never match. Strategies can be backtested to model various outcomes and quantify returns with unparalleled precision.

An AI bot can manage a huge volume of portfolios at once, automating manual processes to reduce the time and costs of trading, providing professional-grade analysis at a fraction of the price that would be charged by a human investment advisor, making the financial markets accessible to a wider audience. 

The Downsides of Using AI to Diversify

On the flip side, diversification using AI exposes the trader to certain risks. The most significant of these is that a trading bot is only as good as the data it receives. If the data on which it is basing its decision-making is low quality then this will negatively impact trading outcomes. Flawed information will inevitably lead to faulty market decisions and biased data and algorithms can lead to discriminatory, unethical allocations of funds within a diversified portfolio.

An AI is also only as secure as the platform on which it is run. An untrustworthy company, or one that does not implement strict security measures can expose the user to the dangers of hacks and fraud. Moreover, outdated algorithms can mean inefficiencies and a significant loss of funds, as can an overreliance on the backtesting of historical data as a predictor of future performance.

A diversified investment portfolio using AI can also carry risks associated with a lack of audit trails, transparency and explainability, relating to AI decision-making processes. Moreover, reliance on a machine entails a loss of real-world insight and the benefits of human judgment, gained through on-the-ground experience. So, an unexpected market event causing massive upheaval may throw an AI off its game as a black swan event is unlikely to be accounted for by the algorithm.

How to Mitigate the Risks of Using an AI to Broaden a Portfolio

A newly launched AI trading bot that hit the scene in late 2023, potentially offers a solution to the risks presented by artificial intelligence in the financial services sector. is a next-generation AI-powered trading platform that uses advanced machine learning (ML) capabilities to manage diverse multi-market portfolios, including stocks, commodities, crypto, indices, forex, and bonds.  

The company has developed its own cutting-edge deep neural networks, which it uses in combination with the latest natural language processing (NLP) models to provide an impressive trade success rate. However, it does not rely solely on the power of its technology.

A Hybrid Strategy

One of the main ways in which AlgosOne is managing risk for traders is by implementing a hybrid approach to diversified investment. 

The sophisticated AI allows for end-to-end automation. It offers a solution for those without the time to invest to research a diverse range of assets, track and analyze market movements across multiple markets and execute trades around the clock. 

AlgosOne does it all, with no coding experience or market knowledge required. There are no building and programming strategies, setting stop losses and take profit orders to be triggered when certain prices are hit, managing a portfolio or executing trades. The user just signs up, makes a deposit of as little as $300, and leaves the rest up to the bot.

However, while AlgosOne is all about the technology, the company understands that a completely hands-free approach carries inherent risks. The benefit of human discernment and lived experience of the markets cannot be replaced. As a result AlgosOne has veteran risk management teams that monitor the markets and the activity of the algorithm 24/7, with the ability to intervene in the case of an extreme market upheaval. 

Integration into a Wider Risk Management Strategy

Even the best diversified portfolios will not be fully shielded against risk. AlgosOne has integrated investment portfolio diversification into a wider risk mitigation approach. The ML algorithm utilizes smart hedging tools, places caps of between 5% and 10% on the amount of a balance that can be used for a single trade and implements stop loss, trailing stop and take profit orders. These risk parameters are constantly being tweaked as market conditions shift.

Diverse Data Sources

The best way to diversify investments effectively is by using an extensive array of data sources. In this way, there is less chance of a single flawed data source distorting trade outcomes. AlgosOne has been trained on vast volumes of quality data. It also tracks, processes and analyses data from a wealth of alternative and traditional sources, including global news, on-chain activity, corporate filings, legislative announcements, social media posts, economic reports and more. 

Solid Security Guardrails

Another way in which AlgosOne mitigates the risk of using an AI to diversify a portfolio is by complying with strict regulation. The licensed platform adheres to requirements such as ID verification procedures, tough technological security measures, segregation of company and user funds as well as the maintenance of a reserve fund, with a sufficient balance to cover all user accounts in the case of a technical malfunction, company failure, hack, or major market collapse.

Minimizing Capital Losses

In addition to diversifying, AlgosOne optimizes trader profitability, while minimizing potential losses by ensuring that all of a trader’s money is used to grow capital and doesn’t get eroded with subscription, deposit and transaction fees.

However, there is a commission fee. It is only charged on winning trades and the money goes back into the platform, being used to pay for live support, technical and risk management teams, to maintain the balance in the reserve fund, and to pay out compensation on losing trades.

The commission percentage that traders have to pay on profitable trades is lower at higher trading tiers. Also, the higher the tier, the higher the compensation on failed trades, and the more trades are made for the account, for larger amounts.  

Constantly Learning and Refining 

AlgosOne further mitigates the risk from portfolio diversification using complex machine learning tools.

Able to learn and improve over time, AlgosOne is enhancing its predictive accuracy on an ongoing basis. Not only basing decisions on historic data, the algorithm is constantly honing risk parameters, as it gains knowledge and experience from each new user, and every fresh dataset, and trades to minimize losses with greater precision. As a result, over time, trade win ratios keep getting better.

It is worth noting that rigorous risk management protocols ensure that a starting trade success rate of just 50:50 will still result in a positive balance.

Without a doubt, artificial intelligence is the future of trading and anyone who wants to diversify across multiple markets simultaneously will be best served by using an AI-based bot to research, track and manage all the assets in their portfolio.

However, in light of the potential risks, an AI, like AlgosOne, that leverages the power of deep learning, while also harnessing the real world experience and insight of  human risk management specialists is the path forward. To try out the platform risk-free, you can register with AlgosOne, and take advantage of the 2-week trial period, during which you can test-drive the AI and see if it’s right for you.


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