Problem: Despite the fact that an astounding 106 trillion dollars are invested in the global equity market as of 2023, most people simply don’t know how to trade stocks properly. In fact, popular estimates of the amount of people who end up losing money in the stock market typically fall around 90 percent. As far as examples regarding how disastrous one’s ventures in stocks can be, day trading is perfect. 40 percent trade for only a month before stopping, and only around 1.2 percent of all day traders in any given year manage to come out on top with a profit. Ignoring the heavy time investment (at least 3–4 hours per week), it’s also the type of investing most susceptible to the general aspects of stock trading most likely to make them lose money. These include: cognitive bias, emotional responses to volatility, overconfidence, lack of diversification, and general lack of research.
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Solution: Instead of all that, make stock trading easy and, more importantly, quantitative, with an AI analyzer based upon the principles of the renown Benjamin Graham, who inspired modern day billionaire investors like Warren Buffet, Irving Kahn, and Charles Brandes. The AI would rely upon the principles found in his book, widely known as the investor’s bible, The Intelligent Investor: The Definitive Book on Value Investing, where Graham strongly advocates for an investing strategy that emphasizes buying stocks below the intrinsic value of the company. This style of investing was what allowed Graham to earn around 500,000 dollars per year in the 1920s at the young age of 25.
This brings me to his most instrumental principle: investing with a margin of safety. That means buying below the intrinsic value of a company, which can be calculated using ratios like earnings per share and expected annual growth rate, and relying on economic theories like efficient markets, which believe market actors to be rational, to let the current price catch up to its actual, and higher, price. The corollary to this is to sell the movement the prices meets the intrinsic value of the company, as any higher value would be simply speculative and couldn’t be reliably depended upon for profit. This plays into Grahams belief that the volatility of the market and the investors’ resulting mood swings are overly emotional, perfecting encapsulating the necessity for an analytical AI to serve as a guiding hand for investors.
Source: Vintage Value Investing
Another key area where the business could implement Graham’s strategies are personalized stock recommendations depending on the users investment style, active or passive. The difference between the two is that an active investor is willing to put more research and effort into maintaining their portfolio, while the passive investor will often look into the extremely long term by more typically investing in funds linked to indexes.
This business is made possible be recent advancements in analyzing text, web scraping, and notable accuracy improvements. It improves upon the pre-existing stock analyzer models by putting AI in places where otherwise people would have to manually put in values or rely on the business to put it in for them, thus limiting the amount of stocks you can use the site for. Instead, the business would use AI to pull publicly available financial data from the internet regarding any company you would consider investing in and calculates the relevant values itself, giving the user a percentage based buy or sell recommendation.
Monetization: Advertisements, paid newsletters regarding stokes and investing strategies, and subscriptions for courses.
Contributed by: David Salinas (Billion Dollar Startup Ideas)