We characterize when physical probabilities, marginal utilities, and the discount rate can be recovered from observed state prices for several future time periods. We make no assumptions of the probability distribution, thus generalizing the time-homogeneous stationary model of Ross (2015). Recovery is feasible when the number of maturities with observable prices is higher than the number of states of the economy (or the number of parameters characterizing the pricing kernel). When recovery is feasible, our model is easy to implement, allowing a closed-form linearized solution. We implement our model empirically, testing the predictive power of the recovered expected return and other recovered statistics
In this paper we analyse recovery rates on defaulted bonds using the Standard and Poor's / PMD datab...
We show that a simple and intuitive three-parameter equation fits remarkably well the evolution of t...
We derive a parsimonious returns-based stochastic discount factor that is robust to model misspecifi...
Includes bibliographical references.This dissertation is concerned with Ross' (2011) Recovery Theore...
It is generally held that derivative prices do not contain useful predictive information, that is, i...
Recently, Ross [30] suggested that it is possible to recover an objective measure from a risk-neutra...
The forward-looking nature of option prices provides an appealing way to extract risk measures. In t...
Asset prices contain information about the probability distribution of future states and the stochas...
Recently, Ross derived a theorem, namely the “Recovery Theorem”, that allows for the recovery of the...
Thesis (Ph.D.)--University of Washington, 2018This thesis has three separate goals: to provide a met...
We can only estimate the distribution of stock returns but we observe the distribution of risk neutr...
In the first essay, we examine two related questions. First, can the recover theory recover the whol...
Ross (2015) developed a recovery theorem with the aim to recover the physical probability distributi...
In this paper we analyse recovery rates on defaulted bonds using the Standard & Poor's/ PMD database...
I propose a regression approach to recovering the return distribution of an individual asset conditi...
In this paper we analyse recovery rates on defaulted bonds using the Standard and Poor's / PMD datab...
We show that a simple and intuitive three-parameter equation fits remarkably well the evolution of t...
We derive a parsimonious returns-based stochastic discount factor that is robust to model misspecifi...
Includes bibliographical references.This dissertation is concerned with Ross' (2011) Recovery Theore...
It is generally held that derivative prices do not contain useful predictive information, that is, i...
Recently, Ross [30] suggested that it is possible to recover an objective measure from a risk-neutra...
The forward-looking nature of option prices provides an appealing way to extract risk measures. In t...
Asset prices contain information about the probability distribution of future states and the stochas...
Recently, Ross derived a theorem, namely the “Recovery Theorem”, that allows for the recovery of the...
Thesis (Ph.D.)--University of Washington, 2018This thesis has three separate goals: to provide a met...
We can only estimate the distribution of stock returns but we observe the distribution of risk neutr...
In the first essay, we examine two related questions. First, can the recover theory recover the whol...
Ross (2015) developed a recovery theorem with the aim to recover the physical probability distributi...
In this paper we analyse recovery rates on defaulted bonds using the Standard & Poor's/ PMD database...
I propose a regression approach to recovering the return distribution of an individual asset conditi...
In this paper we analyse recovery rates on defaulted bonds using the Standard and Poor's / PMD datab...
We show that a simple and intuitive three-parameter equation fits remarkably well the evolution of t...
We derive a parsimonious returns-based stochastic discount factor that is robust to model misspecifi...