We explain the main concepts of Prospect Theory and Cumulative Prospect Theory within the framework of rational dynamic asset pricing theory. We derive option pricing formulas when asset returns are altered with a generalized Prospect Theory value function or a modified Prelec weighting probability function and introdu…
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The paper refutes standard asset pricing models and introduces new theories.
Develops a theory linking managers' disclosures to market pricing.
Combines option pricing and portfolio theory for optimal hedging.
Revisits behavioral finance option pricing model to align with rational asset pricing theory.
Quantum computing speeds up asset pricing models exponentially.
We derive behavioral finance option pricing formulas consistent with the rational dynamic asset pricing theory. In the existing behavioral finance option pricing formulas, the price process of the representative agent is not a semimartingale, which leads to arbitrage opportunities for the option seller. In the literatu…
The paper revisits and applies FTAP to life insurance and annuities pricing.
Subordination is an often used stochastic process in modeling asset prices. Subordinated Levy price processes and local volatility price processes are now the main tools in modern dynamic asset pricing theory. In this paper, we introduce the theory of multiple internally embedded financial time-clocks motivated by beha…
The paper extends option pricing theory for markets with informed traders.
We explore a decomposition in which returns on a large class of portfolios relative to the market depend on a smooth non-negative drift and changes in the asset price distribution. This decomposition is obtained using general continuous semimartingale price representations, and is thus consistent with virtually any ass…
This paper develops a pricing model for data assets from the buyer's perspective.
The paper models asset pricing in a partially observed market using mean field game theory and exponential quadratic Gaussian framework.
Is the elasticity of intertemporal substitution (EIS) more or less than one? This question can be answered by confronting theoretical results of asset pricing models with investor behaviour during episodes of stock market panic. If we consider these episodes as periods of high risk aversion, then lower asset prices are…
Quantum assets are priced using a new theorem, extending classical asset pricing.
The study identifies features making cross-impact relevant in explaining price variance of US assets.
Model asset pricing with habit formation in a large market.
We decompose returns for portfolios of bottom-ranked, lower-priced assets relative to the market into rank crossovers and changes in the relative price of those bottom-ranked assets. This decomposition is general and consistent with virtually any asset pricing model. Crossovers measure changes in rank and are smoothly …
The paper reviews historical and modern approaches to asset pricing probability measures.
We consider a class of generalized capital asset pricing models in continuous time with a finite number of agents and tradable securities. The securities may not be sufficient to span all sources of uncertainty. If the agents have exponential utility functions and the individual endowments are spanned by the securities…
This paper optimizes liquidity provision in automated market makers using auction theory.
EB improves asset pricing by mining large strategies without lookahead bias.
The paper extends asset pricing theory by considering conditional markets.
How to price and hedge claims on nontraded assets are becoming increasingly important matters in option pricing theory today. The most common practice to deal with these issues is to use another similar or "closely related" asset or index which is traded, for hedging purposes. Implicitly, traders assume here that the h…
We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components o…
Price and return predictions are limited by economic complexity, not just volatility.
De Finetti's 1931 work laid the groundwork for modern arbitrage theory.
Cryptocurrencies are examined through the asset flow equations and experimental asset markets. Since tangible value of a typical cryptocurrency is non-existent, the theory suggests that price will gravitate toward liquidity value, i.e., the total amount of cash available for purchase of the asset divided by the number …
We propose a reduced form set of two coupled continuous time equations linking the price of a representative asset and the price of a bond, the later quantifying the cost of borrowing. The feedbacks between asset prices and bonds are mediated by the dependence of their "fundamental values" on past asset prices and bond…
Paper establishes robust asset pricing theorems under uncertainty.
The study models market price movement based on investors' expectations.
This paper formulates a model of utility for a continuous time framework that captures the decision-maker's concern with ambiguity about both volatility and drift. Corresponding extensions of some basic results in asset pricing theory are presented. First, we derive arbitrage-free pricing rules based on hedging argumen…
Develops a dynamic latent-factor model for high-dimensional asset characteristics.
Paper explores asset pricing dynamics in Bachelier model.
Game theory model shows optimal investment strategy for wealth growth.
Researchers calculate the price of a perpetual put option in Lévy models.
The paper revisits classical competition theory to explain speculative asset price dynamics.
Develops asset pricing models with mean field game theory for heterogeneous agents.
The paper proposes a new algorithm for the high-dimensional financial data -- the Groupwise Interpretable Basis Selection (GIBS) algorithm, to estimate a new Adaptive Multi-Factor (AMF) asset pricing model, implied by the recently developed Generalized Arbitrage Pricing Theory, which relaxes the convention that the num…
Generalizes insider trading model to multiple assets.
We add size factor to CAPM and normalize residuals by Volatility Index.
Deep learning improves asset pricing and risk premium measurement.
In this paper we propose a general derivative pricing framework which employs decoupled time-changed (DTC) Lévy processes to model the underlying asset of contingent claims. A DTC Lévy process is a generalized time-changed Lévy process whose continuous and pure jump parts are allowed to follow separate random time scal…
A new framework for asset pricing based on modelling the information available to market participants is presented. Each asset is characterised by the cash flows it generates. Each cash flow is expressed as a function of one or more independent random variables called market factors or "X-factors". Each X-factor is ass…
We propose a class of discrete-time stochastic models for the pricing of inflation-linked assets. The paper begins with an axiomatic scheme for asset pricing and interest rate theory in a discrete-time setting. The first axiom introduces a "risk-free" asset, and the second axiom determines the intertemporal pricing rel…
It is essential to incorporate the impact of investor behavior when modeling the dynamics of asset returns. In this paper, we reconcile behavioral finance and rational finance by incorporating investor behavior within the framework of dynamic asset pricing theory. To include the views of investors, we employ the method…
This work presents an asset pricing model that under rational expectation equilibrium perspective shows how, depending on risk aversion and noise volatility, a risky-asset has one equilibrium price that differs in term of efficiency: an informational efficient one (similar to Campbell and Kyle (1993)), and another one …
In this paper we extend the theory of option pricing to take into account and explain the empirical evidence for asset prices such as non-Gaussian returns, long-range dependence, volatility clustering, non-Gaussian copula dependence, as well as theoretical issues such as asymmetric information and the presence of limit…