Every investor has surely heard bold predictions like these, whether on YouTube or social media: “This stock will double in a year” or “The market will crash next quarter.” These confident forecasts are seductive because they promise certainty in a world full of uncertainty. But this prediction-based thinking is precisely what leads many investors astray. If anyone could make predictions that are 100% accurate, they could simply go all-in on those specific stocks, so why would they share such insights openly with others?
The alternative is not to stop analysing or forming views, but to fundamentally change how we think about the future. Instead of making predictions, thinking in probabilities offers a more grounded perspective. This mental shift transforms not just how you invest, but how you handle being wrong, size your positions, and ultimately build wealth over time.
The prediction illusion
Predictions feel powerful because they’re definitive. When you say something like “Company X will succeed”, you are drawing a clear line. The problem is that this certainty is false. Markets are complex systems influenced by countless variables, including management decisions, regulatory changes, macroeconomic shifts, and even random events and black-swan events. No amount of analysis or thinking can compress this complexity into a single guaranteed outcome.
More dangerously, predictions encourage binary thinking. You’re either right or wrong; things are black or white; the stock either goes up or down. This framework ignores the vast grey area where most of reality exists.
Consider a company launching a new product; it could achieve blockbuster success, moderate adoption, niche appeal, or complete failure. Each outcome carries different probabilities, weightings, and implications for the stock price. When you make a prediction, you’re essentially betting everything on a single scenario while ignoring the others. Even when your analysis is sound and you’re “right” about the business fundamentals, you may still lose money if you fail to account for other possible outcomes. For example, if the valuation is already priced in or a competitor releases a disruptive product.
Understanding probabilistic thinking
Probabilistic thinking starts with a simple recognition: stocks don’t have only one future, they have multiple possible futures. Your job is not to predict which one will happen; it’s to map out the landscape of possibilities and assign rough probabilities to each.
Instead of asking “Will this company succeed?”, probabilistic thinkers ask: “What are the possible outcomes this could play out, and how likely is each scenario?” For example, 50% chance of strong growth, 30% modest performance, 15% stagnation, and 5% severe problems. These numbers don’t need to be precise; investing is not physics. But explicitly acknowledging multiple outcomes changes everything.
This framework embraces uncertainty rather than fighting it. You are no longer pretending to know the unknowable. Instead, you’re honestly assessing what you do know, what you don’t know and how various scenarios might unfold when you’re assigning the probability. The grey area between success and failure becomes your terrain for analysis rather than something to be ignored.
Expected value and position sizing
How do you actually arrive at these probabilities? It depends on many factors, both quantitative and qualitative. Start with the business, for instance, the growth trajectory, margins, competitive position, and management quality. If a company with widening moats and strong pricing power gets higher probability weights for positive outcomes than one facing severe competition and risks. Given the industry dynamics, is the market growing or declining? Is the competition intense? Factor in the balance sheet health, as it shows a business’s resilience during downturns. Valuation is also important as it directly reflects the potential gain.
Other external factors, such as the regulatory environment, macroeconomic sensitivity, and market disruptors, also affect your probabilities. The key is to consider each factor’s impact on the range of outcomes, then synthesise them into an overall probability distribution.
If you want an exact figure to quantify or compare, with a probability assigned, you can calculate the expected value. Just multiply the probability and the potential scenarios (gains and losses). For instance, the stock is trading at $50, and a 40% chance of reaching $100, a 40% chance of staying at $50 and a 20% chance of falling to $25; the expected value is $65 (0.4 x $100 + 0.4 x $50 + 0.2 x $25). This is a simplified example, but it illustrates the core concept: you’re weighing outcomes by their likelihood.
Not just evaluating individual stocks, this framework is also valuable when comparing multiple stocks in your watchlist. An idea with a higher probability of success deserves a larger portion than a speculative bet with a lower probability in your portfolio. When comparing opportunities across different companies, you’re not just asking which one you like more; you’re comparing their probability-weighted return profile.
Building your probability calibration
But I really need to say this: the probability assignment is really an art. But I believe it comes from the deep analytical work that you’ve done. Every company you analyse, every industry that you study, every business model you dissect adds to your mental encyclopaedia of stocks. Over time, you will develop pattern recognition. You’ve seen how companies with certain characteristics tend to perform or turn around, you recognise warning signs and promising indicators. This accumulated knowledge is what allows you to estimate probabilities and different outcomes with increasing accuracy.
The beautiful part is that, like any skill, it gets easier with each analysis. Your hundredth company evaluation will be faster and more insightful than your first because you’re building on a foundation of experience. But still, nothing is certain; don’t fall into the trap of other biases, like overconfidence and confirmation biases. The only thing certain is uncertainty.
Embracing being wrong
Perhaps the most liberating aspect of probabilistic thinking is how it reframes being wrong. If you assign a 70% probability to a positive outcome, you’re simultaneously acknowledging a 30% chance of being a negative outcome. When the 30% scenario happens, you haven’t failed; you’ve experienced an expected result of thinking probabilistically. Lower probability doesn’t mean it won’t happen.
This distinction between bad decisions and bad outcomes is crucial. A good decision can still lead to a bad outcome and vice versa. What matters is whether your process was sound, whether you assessed the probabilities properly, and whether your position sizing reflected the uncertainty involved. When you think probabilistically, a losing investment doesn’t trigger an emotional crisis or self-doubt; it’s just simply part of the statistical distribution you anticipated.
It helps to remove emotional burden. We’re not trying to be right every time, which is impossible. We’re just trying to make decisions where the probabilities favour us more. Being wrong becomes data that helps refine our probability estimates for future decisions rather than a personal failure.
The fifth perspective
Personally, I apply this mindset in all other aspects of my life as well. Before making any significant decision, I map out the possible outcomes and their probabilities to see if the path is worth taking. This makes the picture clearer, and when low-probability events actually occur, I‘m already prepared rather than panicked as I’ve thought through the scenarios and planned my next steps.
One important caveat: don’t let probabilistic thinking become analysis paralysis because sometimes overthinking keeps you frozen in place. Once you’ve done the work and the probabilities favour action, take the bet. Perfect certainty will never arrive.
Try this in your next analysis of an investment and resist the urge to make a prediction. Instead, map the possibilities, assign probabilities based on your analytical work, and let that framework guide your decisions. You’ll gain not just better returns, but genuine peace of mind.
