Investors over the decades have been trying to figure out one strategy that helps them make money from stock investing. Let me be honest – there is none. It is impossible to have a tool or a strategy that gives you returns with 100% accuracy in the stock market. The stock market is set up in a way that it is impossible to know the direction.
Of the many reasons why we can’t understand the direction is because millions of brains are trying to achieve the same thing – profits. Emotions are humans’ biggest enemy, and they reduce their success rate.
The game is different if you plan for AI stock management. Emotions are removed, and the success rate increases. Please note that it is still not 100% accurate – it can never be. In this answer, we answer if AI tools can outperform the benchmark.
Can an AI tool beat the benchmark?
In the investing world, the success of a fund manager or a tool is determined by comparing it with a benchmark index. The reason is simple – why would someone pay a share market advisor if he is unable to beat the benchmark – that is the least one expects when they are paying for the services that promise them to deliver higher returns.
If you would have asked this question a 5 to 7 years back, it would have been tough to give a clear answer. However, today, AI-based stock trading platforms are advanced and may beat the benchmark. The word to note here is ‘may’ – not all AI tools can beat the benchmark. So, how do you know if a tool can beat the benchmark?
AI tool: Must have
The success of AI tools in surpassing benchmarks depends on how it is created. Here are a few things that the tool must have:
- Data Quality and Quantity: The performance of AI tools heavily relies on the quality and quantity of data available. If the data used for training the AI models is incomplete, biased, or not representative of real-world market conditions, the tool may not perform as expected. Just to let you know, Jarvis Invest used 1.2 crore data pointers to find the right stocks for you.
- Algorithm Complexity: The sophistication of the AI algorithms employed plays a crucial role. Complex algorithms may capture intricate patterns in the data, but they also run the risk of overfitting historical data and performing poorly in real-world scenarios.
- Market Conditions: Financial markets are dynamic and influenced by various factors, including economic events, geopolitical issues, and market sentiment. AI tools need to adapt to changing market conditions, and their success may vary depending on the specific environment.
- Risk Management: Investing always involves risks, and AI tools need robust risk management strategies. Overly aggressive strategies may lead to significant losses, even if the tool performs well under certain conditions. The tool should be able to evaluate your risk profile and give recommendations accordingly.
Are there numbers to confirm?
Yes, Jarvis Invest has been able to deliver benchmark returns for a while now. At Jarvis, the recommendation happens based on different risk profiles. For illustration, we will take the example of a Moderately Aggressive risk profile. The benchmark index that we have taken is Nifty50. We compare the benchmark with two category portfolios – one without a risk management system (RMS) and one with RMS. Here are numbers that should interest you:
- Sharpe Ratio: It is a measure of risk-adjusted return. It quantifies the excess return of an investment per unit of risk, comparing the return of an investment to its volatility. A higher Sharpe Ratio indicates a better risk-adjusted performance and helps you assess the efficiency of a portfolio in generating returns relative to the level of risk taken. Our portfolio had a Sharpe Ratio of 2.02.
- Beta: It is a measure of a stock’s or a portfolio’s sensitivity to market movements. A beta of 1 indicates the asset tends to move in tandem with the market, while a beta greater than 1 suggests higher volatility and a beta less than 1 indicates lower volatility compared to the market. Our portfolio has a beta of 0.04 – much lower volatility.
- Positive Returns: The monthly returns were positive for 47 out of 60 months.
Before you go
The numbers speak for themselves. As an investor, all you need to do is trust the technology. You already trust technology for many other things in life – why not for investing? To start your AI-based stock investing, you can visit our website.