{"product_id":"principles-of-portfolio-choice","title":"Principles of Portfolio Choice","description":"\u003cp\u003e\u003ci\u003ePrinciples of Portfolio Choice: An Information-Theoretic, Likelihood-Based Perspective\u003c\/i\u003e develops a scenario-level theory of portfolio selection. Its starting point is simple but powerful: market prices assign values to future scenarios, and once normalized these state prices define a market-implied probability measure. An investor who disagrees with the market is therefore not merely choosing portfolio weights; she is choosing a different likelihood model over the same scenarios.\u003c\/p\u003e\u003cp\u003eThe book’s central translation is that a budget-normalized nonnegative payoff is a likelihood ratio. It compares the probability measure implied by a portfolio with the probability measure implied by market prices. Thus a portfolio is not only a financial object but also a statistical object: it expresses a scenario distribution. Conversely, a desired scenario distribution determines the payoff that would implement it, whenever that payoff can be replicated.\u003c\/p\u003e\u003cp\u003eFrom this perspective, portfolio choice becomes a form of likelihood-model selection under market constraints. The investor first specifies the scenario probabilities she wishes to express; the financial problem is then to find the attainable payoff whose implied distribution best matches that view.\u003c\/p\u003e\u003cp\u003eThis scenario-by-scenario viewpoint connects portfolio theory to statistics and information theory. At the Kelly optimum, expected log return becomes relative entropy. Realized wealth becomes a likelihood score. Long-run performance becomes accumulated statistical evidence. Constrained portfolio selection becomes the problem of choosing a desired scenario distribution and finding the closest attainable market payoff.\u003c\/p\u003e\u003cp\u003eThe book translates Kelly growth, utility maximization, mean–variance analysis, martingale pricing, option payoffs, hedging, Bayesian averaging, and model selection into this likelihood-based language. It shows that many classical methods can be understood as approximations, transformations, or constrained versions of a single payoff-measure dictionary.\u003c\/p\u003e\u003cp\u003eWritten for quantitative analysts, portfolio managers, researchers, and graduate students, the book offers a new foundation for thinking about prices, beliefs, payoffs, and evidence in financial markets.\u003c\/p\u003e\u003cp\u003eFeatures\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003ePresents portfolio choice at the level of individual market scenarios.\u003c\/li\u003e\n\u003cli\u003eShows that normalized payoffs are likelihood ratios between portfolio-implied and market-implied probability measures.\u003c\/li\u003e\n\u003cli\u003eInterprets portfolio choice as the selection of likelihood models over future scenarios.\u003c\/li\u003e\n\u003cli\u003eInterprets returns as likelihood scores and Kelly growth as relative entropy.\u003c\/li\u003e\n\u003cli\u003eTranslates classical portfolio methods into the language of statistics and information theory.\u003c\/li\u003e\n\u003cli\u003eDevelops applications to option-induced densities, Gaussian mixtures, hedging, Bayesian averaging, and adaptive portfolios.\u003c\/li\u003e\n\u003cli\u003eIncludes exercises designed to test and enhance understanding of the topics.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Product","offer_id":57428047561048,"sku":"9781032951980","price":112.99,"currency_code":"EUR","in_stock":false}],"url":"https:\/\/agendabookshop.com\/products\/principles-of-portfolio-choice","provider":"Agenda Bookshop","version":"1.0","type":"link"}