Ideas on Markets, Valuation & Behavior
A growing library of practical frameworks at the intersection of finance, investing and human decision making.
This section brings together Dr. Tiran Rothman’s core ideas on behavioral finance, startup valuation, investing and financial freedom. It is designed as a knowledge hub: concise enough to answer a specific question, but connected to deeper topic guides, research and published work.
Behavioral finance
Good investment decisions require more than financial literacy. They require a process for dealing with attention, uncertainty, social influence and the emotional asymmetry between gains and losses. The behavioral-finance guide develops these mechanisms and translates them into practical decision rules.
Read the behavioral finance guide →
Startup valuation
Valuation becomes most interesting when the future is difficult to forecast. Early-stage companies force founders and investors to confront the assumptions behind growth, margins, capital needs and financing terms. The startup-valuation guide presents a framework based on scenarios, DCF logic, market evidence and capital structure.
Read the startup valuation guide →
Financial freedom
Financial freedom can be framed as the ability to convert accumulated capital into time and optionality. That requires more than maximizing returns: consumption, lifestyle adaptation, risk tolerance and the design of repeatable financial rules all matter. These ideas are being developed further in the forthcoming book How Do You Buy Time?
Research and evidence
Where possible, practical arguments should remain connected to evidence. The research section links the applied themes above to published work on investor behavior, pharmaceutical events, valuation and the broader study of complex financial systems.
Explore research & publications →
What comes next
Future essays will expand this library with focused pieces on investor behavior, valuation under uncertainty, decision architecture and the relationship between money and time. Each article will identify the author, publication date, sources and related topic pages so that both readers and search or answer engines can distinguish first-party analysis from external references.