We study the asymptotic distribution of Tikhonov Regularized estimation of quantile structural effects implied by a nonseparable model. The nonparametric instrumental variable estimator is based on a minimum distance principle. We show that the minimum distance problem without regularization is...

This paper is concerned with inference about an unidentified linear function, L(g), where the function g satisfies the relation Y=g(X)+U; E(U |W)=0. In this relation, Y is the dependent variable, X is a possibly endogenous explanatory variable, W is an instrument for X and U is an unobserved...

This paper is concerned with inference about an unidentified linear functional, L(g), where the function g satisfies the relation Y=g(x) + U; E(U/W) = 0. In this relation, Y is the dependent variable, X is a possibly endogenous explanatory variable, W is an instrument for X, and U is an...

Rank-ordering of individuals or objects on multiple criteria has many important practical applications. A reasonably representative composite rank ordering of multi-attribute objects/individuals or multi-dimensional points is often obtained by the Principal Component Analysis, although much...

Many optimisation problems in finance and economics have multiple local optima or discontinuities in their objective functions. In such cases it is stressed that ‘good starting points are important’. We look into a particular example: calibrating a yield curve model. We find that while...

In this paper we propose a quasi-shrinkage approach for minimum-variance portfolios which does not use a quadratic loss function to derive the optimal shrinkage intensity. We develop two alternative objective functions for linear shrinkage. The first targets the reduction of portfolio variance....

To create their rankings, university-ranking agencies usually combine multiple performance measures into a composite index. However, both rankings and index scores are sensitive to the weights assigned to performance measures. This paper uses a stochastic dominance efficiency methodology to...

A portfolio of independent, but not identically distributed, returns is optimized under the variance risk measure, in the high-dimensional limit where the number N of the different assets in the portfolio and the sample size T are assumed large with their ratio r=N/T kept finite, with a ban on...

I jointly treat two critical issues in the application of mean-variance portfolios, i.e., estimation risk and portfolio instability. I find that theory-based portfolio strategies known to outperform naive diversification (1/N) in the absence of transaction costs, heavily underperform it under...

The purpose of this paper is to introduce the Gerber statistic, a robust co-movement measure for covariance matrix estimation for the purpose of portfolio construction. The Gerber statistic extends Kendall's Tau by counting the proportion of simultaneous co-movements in series when their...