For too long, the Efficient Market Hypothesis treated stock pickers like gamblers, claiming no one could truly beat the system and that success was just luck. It was a frustrating, dismissive era. But we always knew better. We knew that investing is a skill that can be studied and sharpened. Now, the evidence finally backs us up, replacing that old frustration with a clear sense of purpose.
Stock pickers have always known the truth: investing is a refined skill that can be mastered and perfected. Yet, for decades, the proponents of the Efficient Market Hypothesis insisted we were no better than monkeys tossing coins—that our success was nothing but a statistical fluke. It was a disheartening narrative to fight against. But now, with the proof in hand, that weight has lifted. We have reclaimed the fact that diligence pays off and skill is the true driver of performance.
“I’ve always been a stock picker at heart, but the ‘presumption of efficiency’ always sat uneasily with me. I needed to know for certain: is outperformance skill, or merely luck? After putting the market to a rigorous logical and statistical test, the results are in. Markets are not efficient. The data shows a clear positive correlation in year-over-year performance—proof that a disciplined investor can find an advantage. The overhang of EMH is gone; I’m ready to play the game on my own terms.”
The ‘random walk’ myth is officially busted. This paper proves that market outperformance is a skill, not a roll of the dice. Knowing that diligence leads to results brings a huge sense of relief—I can finally stop second-guessing the process.
Seeing the proof that stock prices aren’t just random movements has changed everything for me. It confirms that investing is a true skill and that hard work actually pays off in the market. I finally feel a sense of peace and validation in the path I’ve chosen.
I am very happy to share my paper published in the International Journal of Research in Finance and Management.
PP- Geometry of Wealth.pdf (351.5 KB)
Happy Reading.