April 1, 2026
The Beginning
We began by digging through financial data across various websites that publish company fundamentals. What we quickly noticed was that, for the same metric, different platforms were often reporting completely different numbers.
That raised an obvious question: which one is actually correct?
To find out, we turned directly to the companies’ official earnings releases. What we discovered was surprising—many times, none of the figures shown across those websites were accurate.
For example, one site reported Microsoft’s EPS at X, while another showed Y. After reviewing Microsoft’s official reports, we found the actual number was Z. Neither of the widely reported figures was correct.
This led us to a decision: instead of relying on third-party platforms, we would start collecting and recording official financial data ourselves. We began building Excel models for the companies we were most interested in, updating them quarterly with each new earnings release.
Over time, we noticed something important. The numbers we had compiled ourselves provided a much clearer explanation of stock price movements over the years.
By systematically recording financial statement data and supplementing it with historical figures, we developed a much deeper understanding of each company’s profitability. This process helped us build strong foundations—ones we continue to refine today—and allowed our earnings estimates to increasingly align with reality.
At the same time, we observed that analyst price targets often vary widely, creating a broad and sometimes confusing range. In many cases, the time horizon behind these targets is unclear. It raises the question: do prices follow price targets, or do price targets simply adjust to prices?
Often, price targets change based on sentiment-driven news rather than factors that materially impact a company’s fundamentals.
For this reason, we chose to focus on targets derived from fundamental analysis. We also introduced a valuation range to reflect potential deviations from those targets.
The upper and lower bounds of this range reflect extreme market conditions—periods when sentiment reaches either euphoric or pessimistic levels, when companies experience significant tailwinds or headwinds, or when major news and macroeconomic shifts materially impact expectations.
The target price, in contrast, represents our base-case scenario, where sentiment is more neutral and fundamentals are the primary driver of valuation.
In periods like the one we are experiencing today, marked by geopolitical tensions and war, market sentiment can turn negative. However, this does not necessarily mean that company fundamentals are affected. Each case should be evaluated individually, with careful thought given to whether such events truly impact the underlying business.
This is just the starting point of our journey. We will continue refining our models, expanding our coverage, and sharing insights grounded in real data rather than assumptions.
If this approach resonates with you, we invite you to follow along and become part of our growing community as we build a more transparent and disciplined way of looking at markets.
That raised an obvious question: which one is actually correct?
To find out, we turned directly to the companies’ official earnings releases. What we discovered was surprising—many times, none of the figures shown across those websites were accurate.
For example, one site reported Microsoft’s EPS at X, while another showed Y. After reviewing Microsoft’s official reports, we found the actual number was Z. Neither of the widely reported figures was correct.
This led us to a decision: instead of relying on third-party platforms, we would start collecting and recording official financial data ourselves. We began building Excel models for the companies we were most interested in, updating them quarterly with each new earnings release.
Over time, we noticed something important. The numbers we had compiled ourselves provided a much clearer explanation of stock price movements over the years.
By systematically recording financial statement data and supplementing it with historical figures, we developed a much deeper understanding of each company’s profitability. This process helped us build strong foundations—ones we continue to refine today—and allowed our earnings estimates to increasingly align with reality.
At the same time, we observed that analyst price targets often vary widely, creating a broad and sometimes confusing range. In many cases, the time horizon behind these targets is unclear. It raises the question: do prices follow price targets, or do price targets simply adjust to prices?
Often, price targets change based on sentiment-driven news rather than factors that materially impact a company’s fundamentals.
For this reason, we chose to focus on targets derived from fundamental analysis. We also introduced a valuation range to reflect potential deviations from those targets.
The upper and lower bounds of this range reflect extreme market conditions—periods when sentiment reaches either euphoric or pessimistic levels, when companies experience significant tailwinds or headwinds, or when major news and macroeconomic shifts materially impact expectations.
The target price, in contrast, represents our base-case scenario, where sentiment is more neutral and fundamentals are the primary driver of valuation.
In periods like the one we are experiencing today, marked by geopolitical tensions and war, market sentiment can turn negative. However, this does not necessarily mean that company fundamentals are affected. Each case should be evaluated individually, with careful thought given to whether such events truly impact the underlying business.
This is just the starting point of our journey. We will continue refining our models, expanding our coverage, and sharing insights grounded in real data rather than assumptions.
If this approach resonates with you, we invite you to follow along and become part of our growing community as we build a more transparent and disciplined way of looking at markets.