Operational analysis is the root, financial analysis is the surface - the strength of the encrypted digital currency exchange platform for withdrawals without interruption

Financial analysis should not be dogmatic. I have hosted a series of programs discussing financial analysis, and many people regard it as the most critical tool for investing. I have said many times that financial analysis is only used to filter companies—filter out bad companies—or, when conducting operational analysis, to confirm qualitative assessments with financial data.

So, in essence, financial analysis is just the language of business. After doing business and achieving operational results, financial analysis reflects those results, showing the company’s operations through a few financial statements. Do not treat financial analysis as some secret weapon; it is simply a condensed result of operational analysis, presented in a numerical, quantitative form—an abstract financial report. The fundamental thing remains operational analysis, i.e., qualitative analysis. Industry analysis, company operational characteristics, demand analysis, competitive landscape, and moats are the true sources.

Operational analysis is the origin and the foundation. Financial analysis is just the result of operational analysis; finance reflects operational outcomes. Therefore, I want to reiterate here: avoid the mistake I’ve mentioned many times—like the story of the “Zheng man buying shoes”—where you mistake the financial data for the core. Your operations are the foot, the core of the business; finance is just the outcome, and financial statements are merely numerical descriptions of those outcomes.

This way, we avoid dogmatic errors, such as the “Zheng man buying shoes” mistake. In many of my programs, I often say: in financial analysis, you can derive some regular, empirical indicators. Through these indicators, you can see the company’s situation. But financial statements are only for confirmation—to verify qualitative assessments, operational conditions, and business characteristics.

If the operational analysis conclusion is invalid or contradicts common sense, even if some financial data looks good, you must ask why. When the conclusion of financial analysis diverges from that of operational analysis, you must analyze and qualitatively assess the underlying issues.

For example, to clarify, when analyzing a company’s strength in the supply chain, if it has a lot of prepayments—like Moutai, which has significant prepayments—this indicates it holds a strong position downstream, with pricing power. Downstream customers want to receive goods early and pay in advance. Conversely, if accounts payable are high—that is, the company owes a lot to suppliers—it often indicates upstream strength, like Gree Electric.

On the other hand, do not be dogmatic. Just because prepayments are high does not necessarily mean the company has higher pricing power over downstream. Similarly, high accounts payable does not necessarily mean strong control over upstream suppliers. A company might have both high prepayments and high payables, but that does not mean it is like Moutai or Gree.

For example, some companies, unlike Moutai, may have high prepayments, such as certain steel or cement companies, especially in the glass industry. These companies often lack pricing power and may even be experiencing sluggish sales. If such a company is unprofitable long-term, operates poorly, and borrows heavily from banks, yet still needs to keep operating, it might be forced to negotiate with distributors: “Send the money to my account first; I need prepayments, and I’ll give you a big discount or lower prices.”

Such companies are often on the brink of bankruptcy or have significant debt problems. When debt burdens are heavy and facing substantial financial pressure, they might negotiate prepayments with suppliers and distributors.

Suppliers need goods but lack funds, so they might accept higher prices and allow the company to owe them money temporarily. Sometimes, suppliers agree to deliver goods first if the company offers a higher price.

These companies tend to be poorly managed, with high debt ratios, and face cash flow issues. They often owe money to both upstream and downstream—upstream to suppliers and downstream to prepayment customers. On the surface, prepayments and payables are both high, but do not mistake them for companies like Moutai or Gree.

This example illustrates that such companies are often in or near bankruptcy, showing these symptoms. At this point, it’s essential to examine whether their products are competitive. Industries like steel, glass, or certain other manufacturing sectors often have no pricing power, which can be inferred from qualitative operational analysis.

They lack pricing power, so ask: why are prepayments and payables so high, especially when the products lack pricing advantages? This divergence indicates issues. Ask why, rather than blindly applying rules or dogma.

Another approach is cross-analysis. For example, look at gross profit margin: if it’s very high, like Moutai, it indicates genuine pricing power, or at least stable gross margins. Check debt ratios in conjunction with other indicators to get a clearer picture.

If a company’s debt ratio is very high, it likely has problems. If prepayments and payables are both high, it probably indicates operational issues rather than good pricing power or upstream/downstream advantages.

Another indicator is whether the company is lowering prices. If it keeps reducing prices while prepayments are high, it might be trying to attract downstream financing through price cuts—that’s the situation.

My main point today is that financial analysis should not be overly dogmatic; it must be combined with operational analysis. Financial analysis is the result, the outcome; operational analysis is the cause, the reason. Also, do not rely on a single indicator or rigid rules; instead, perform cross-analysis—look at gross profit margin, debt ratio, whether the company is lowering prices, etc.—using these operational indicators to verify and see if they align with industry knowledge and logic.

If there are contradictions or logical inconsistencies, you must dig into the real reasons behind them. If you don’t investigate and find the actual causes, you risk choosing the wrong company or stock. Don’t blame others or companies for false accounting or market manipulation.

Everyone should avoid dogmatic thinking. Understand what is cause and what is effect. Use multiple indicators and cross-analysis, combined with qualitative assessments of the business, demand and supply, competition, inventory, and other factors. If your conclusions are consistent and mutually confirm, it’s likely a good company. Otherwise, you might have misjudged or overlooked the company.