We introduce and axiomatize dynamic variational preferences, the dynamic version of the variational preferences we axiomatized in [21], which generalize the multiple priors preferences of Gilboa and Schmeidler [9], and include the Multiplier Preferences inspired by robust control and first used in macroeconomics by Hansen and Sargent (see [11]), as well as the classic Mean Variance Preferences ...

This paper explores some applications of a twomoment inequality for the integral of the r-th power of a function, where 0 < r < 1. The first contribution is an upper bound on the Rényi entropy of a random vector in terms of the two different moments. When one of the moments is the zeroth moment, these bounds recover previous results based on maximum entropy distributions under a single moment c...

We propose a direct and robust method for quantifying the variance risk premium on financial assets. We show that the risk-neutral expected value of return variance, also known as the variance swap rate, is well approximated by the value of a particular portfolio of options.We propose to use the difference between the realized variance and this synthetic variance swap rate to quantify the varia...

A common application of multilevel models is to apportion the variance in the response according to the different levels of the data.Whereas partitioning variances is straightforward in models with a continuous response variable with a normal error distribution at each level, the extension of this partitioning to models with binary responses or to proportions or counts is less obvious. We descr...

Models of the time-varying conditional minimum-variance hedge ratio (MVHR) typically do not provide a significant improvement in terms of hedging performance over the unconditional MVHR model. In view of the widely documented success of conditional volatility models (on which models of the conditional MVHR are usually based), this is somewhat surprising. In this paper, using the recently develo...

The selection of a variance estimator for large complex sample surveys is not straightforward. Most of the methods of variance estimstion for such surveys are b~sed upon some form of repeated subsampling. The random group, jackknife and balanced repeated replication methods differ primarily in the procedures for forming the subsamples. Previous comparative studies have been primarily empirical....

Fractional hot deck imputation, considered in Fuller and Kim (2005), is extended to multivariate missing data. The joint distribution of the study items is nonparametrically estimated using a discrete approximation, where the discrete transformation also serves to define imputation cells. The procedure first estimates the probabilities for the cells and then imputes real observations for missin...

The authors propose a new approach for measuring, analyzing, and predicting a brand’s equity in a product market. Brand equity is defined as the incremental contribution ($) per year obtained by the brand in comparison to the underlying product (or service) with no brand-building efforts. The incremental contribution is driven by the individual customer’s incremental choice probability for the ...

Total variance is a statistical tool developed for improved estimates of frequency stability at averaging times up to half the test duration. As a descriptive statistic, Total variance performs an exact decomposition of the sample variance of the frequency residuals into components associated with descending frequency octaves. As an estimator of Allan variance, Total variance has modest bias an...

List of Symbols 12.1 Concepts, Definitions, and Measures of Stabilitv 12.1 .l Relationship between the Power Spectrum and the Phase Spectrum 12.1.2 The IEEE Recommended Measures of Frequency Stability 12.1.3 The Concepts of the Frequency Domain and the Time Domain 12.1.4 Translation between the Spectral Density of Frequency and the Allan Variance 12.15 The Modified Allan Variance 12.1.6 Determi...