Value investing identifies assets trading below their intrinsic or fundamental value and holds until the market recognises the discount. In traditional markets this means studying P/E ratios, discounted cash flows, and book value; in crypto it extends to token economics, revenue-generating protocols, and fully diluted valuation analysis.
Intrinsic value and margin of safety. Discounted cash flow (DCF) analysis. Price-to-Earnings (P/E) and Price-to-Book (P/B) ratios. Crypto: Fully Diluted Valuation (FDV) vs market cap. Protocol revenue (fees, burns) relative to token price. Token velocity and demand sinks. Network value to on-chain metrics (NVT).
Asset trading at >30% discount to estimated intrinsic value. Protocol revenue growing while token price declining. On-chain metrics (active addresses, TVL) diverging bullishly from price. Sector-wide sell-off creating indiscriminate discounts.
Price reaches or exceeds estimated fair value. Fundamental thesis broken (revenue declining, active users dropping). Better risk-adjusted opportunity elsewhere. Time stop — thesis hasn't played out within expected window.
Weekly, Monthly — value investing is inherently a medium to long-term strategy. Often measured in quarters or years.
Cheap can always get cheaper — always use a margin of safety. In crypto, pay close attention to token unlock schedules and inflation rates which can erode value. Diversify across multiple undervalued assets rather than concentrating in one.
Earnings and valuation analysis evaluates a company's financial performance and market pricing to determine whether its stock is undervalued, fairly valued, or overvalued. By examining revenue growth, profit margins, earnings per share, and valuation multiples such as price-to-earnings and price-to-sales ratios, traders and investors can assess whether the current market price is justified by fundamentals.
Intermarket analysis studies the correlations and divergences between asset classes — equities, bonds, commodities, currencies, and crypto — to gain a macro edge. When relationships that normally hold start breaking down, it often foreshadows major market regime shifts. Traders use these cross-market signals to confirm or contradict setups in their primary market.
Qualitative factor analysis evaluates the non-numerical attributes of an asset or company that influence long-term value — management quality, competitive moats, brand strength, regulatory positioning, and industry trends. While quantitative metrics measure what has happened, qualitative analysis assesses the strategic factors that will drive future performance, providing context that numbers alone cannot capture.
Event-driven trading capitalises on price dislocations caused by scheduled and unscheduled catalysts — earnings announcements, FOMC meetings, governance votes, protocol upgrades, token unlocks, mergers, and geopolitical shocks. The edge comes from correctly anticipating the event's impact or exploiting the volatility expansion around it.