In this blog post, we’re going to take a deep dive into the world of generative AI. Now, you might be wondering, what’s generative AI? Well, it’s a type of technology that can create things like art, music, and even text all on its own, without any human help. Sounds pretty cool, right?
But here’s the thing: while generative AI has the potential to magically change a lot of things including the world of investing, it also comes with some risks, especially for retail investors. So, we’re going to explore those risks and talk about whether or not generative AI will shake up the way we do things, or if it might not be as important as some people think. Stick around to find out!
The Context
Generative AI has become a hot topic, stirring both excitement and fear worldwide.
But, amidst the dominance of innovative disruption across many sectors and industries, a significant dilemma arises: Are common investors losing their footing after centuries of a successful run? The public debut of GPT-3 on November 30, 2022, merely five months ago, has already brought significant transformations across sectors.
GPT-4, the latest iteration, boasts a staggering 100 trillion parameters, dwarfing GPT-3’s 175 billion. Responding to GPT’s success, Google’s Bard was revealed last year.
This language model, which Google employs to enhance Bard, now comprises an impressive 540 billion parameters, dictating how neural networks process data. The medical field, too, is undergoing a major revolution. Google recently unveiled Med-PaLM2, an AI product specifically designed for medicine.
Remarkably, Google’s AI has accurately predicted the shapes of all 200 million known proteins, including those found in plants, animals, and microorganisms. In the world of financial markets, where maneuvering through variables is paramount, a similar AI model capable of identifying 1 in 200 million factors would make navigating market variables and possibilities a breeze.
However, it is crucial to question whether these advancements truly hold the power to reshape the very core of financial markets as we understand them. Delving further into this captivating topic will unveil additional insights as we steer you toward the future of investing and personal finance so, read on to the end.
Some Risks Are Evident
With the evolution of generative AI, common investors should be mindful of certain risks. Firstly, the increased market volatility caused by AI models making rapid predictions based on vast amounts of data can lead to unpredictable market movements, making decision-making challenging.
Overreliance on AI-generated insights is another risk, potentially excluding human judgment and qualitative factors that impact investment outcomes. Additionally, AI biases and errors may arise from models trained on biased historical data or failing to capture emerging trends and valuations accurately.
The ethical implications of AI-driven trading strategies, affecting market fairness and stability, are also a concern. Therefore, investors must be aware of these risks and exercise caution when integrating generative AI into their investment strategies.
Venturing into a Primitive AI Experiment
Our experiments aimed at gauging the accuracy of these models have yielded intriguing results. Surprisingly, we found that the technical prediction of stock movements was accurate only 33% of the time.
From a trading perspective, this presents a highly precarious risk-reward ratio.
To conduct these experiments, we employed Microsoft Bings Generative AI capability, a web-connected tool that scours the internet for the latest data. This allowed us to gather valuable insights into stock market dynamics. Furthermore, we explored Chat GPT’s perspective on the best stocks to invest in India. Interestingly, the much-discussed generative AI recommended five prominent large-cap giants:
≡ Reliance Industries Ltd. (RELIANCE)
≡ Tata Consultancy Services Ltd. (TCS)
≡ Housing Development Finance Corporation Ltd. (HDFC)
≡ Infosys Ltd. (INFY), and
≡ HDFC Bank Ltd. (HDFCBANK).
However, it responsibly cautioned that investing in the stock market carries risks, emphasizing the need for thorough research and consultation with a financial advisor before making any investment decisions.
During our experiment, we made noteworthy observations. First, the model exhibited a bias towards selecting companies with the highest market capitalization, neglecting current valuations. Additionally, we found it striking that a massive 40% of the guidance was concentrated in the financial sector, with two out of the five stocks belonging to this industry.
In our assertion, it’s an over-exposure from a diversification viewpoint.
Is Your Relevance Still Intact?
Upon further investigation into the ramifications of generative AI, our reasoning has unveiled compelling evidence that underscores the enduring significance of ordinary investors, who are poised to persist as these models advance. Here’s the intriguing rationale behind it.
Generative AI Lacks A Core Essence
Contrary to common investor perceptions, the market is not simply a static entity. Our investing experience and countless hours of in-depth study have revealed a fascinating truth: the market functions as a dynamic collective consciousness. It seamlessly integrates trillions of ever-changing split-second decisions, largely driven by the powerful forces of fear and greed. In this intricate web of market dynamics, generative AI stands apart. Unlike humans, AI systems—powered by machine learning and deep learning algorithms—are devoid of emotions like fear and greed.
Instead, they rely on mathematical and statistical principles to meticulously analyze vast amounts of data, enabling them to make informed predictions and decisions. It is precisely this absence of subjective experiences and emotional states that distinguishes financial markets as a unique realm. While human investors are influenced by complex psychological factors, AI operates on a rational and logical framework, allowing it to perceive and navigate market trends with a distinct perspective.
A Level Playing Field
It’s important to bear in mind that all generative AI tools are ultimately consumer products. In a future where generative AI becomes universally accessible, be it through free or paid means, a fascinating paradigm emerges—a level playing field for all.
Picture a scenario where everyone has access to the same type of insights, leading to a collective pursuit of identical stocks. This creates a synthetic surge in demand, distorting the rationality of fair valuation.
It’s a classic case of the age-old herd mentality, where the actions of the masses influence the market in unforeseen ways.
So, what has changed?
You Are Dealing With Chaos
Financial markets exhibit “level 2 chaos” characterized by complexity and unpredictability. This concept, rooted in Edward Norton Lorenz’s theory, acknowledges chaotic behavior in natural systems.
For starters, level 1 chaos involves information having no impact on outcomes (like a weather forecast), while level 2 chaos sees additional information influencing decisions and altering outcomes. In financial markets, the interplay of factors and the influence of knowledge shape market dynamics.
A prime illustration of this phenomenon can be observed in the stock market, where knowledge of a company’s profitability heavily influences investors, prompting them to purchase specific stocks and consequently driving up their prices. Generative AI acts as an advanced tool within this chaotic environment, contributing to market complexity and influencing outcomes. This merely renders it to become an accessory to the ever-evolving landscape of financial markets, predictably impacting their observed results.
Conclusion
As we guide you toward the future of financial markets, it becomes evident that opinions among investors regarding generative AI are widely varied, representing a broad range of perspectives. While some investors express apprehension about the impact of generative AI on the investment landscape, others perceive it as an opportunity to enhance decision-making and gain deeper market insights.
It is worth considering that individual stances on this issue can be influenced by factors such as risk tolerance, familiarity with AI technologies, and personal investment strategies. Furthermore, there are nuanced elements like fear, greed, and intuition that continue to distinguish human intelligence from synthetic intelligence. Ultimately, the level of concern among investors regarding generative AI hinges on their understanding of its potential benefits and risks to their specific investment objectives.
We value your perspective on these viewpoints. Feel free to share your thoughts in the comments below.
Invest wisely!
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