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Author:Robotti, Cesare 

Working Paper
Pricing model performance and the two-pass cross-sectional regression methodology

Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular approach for estimating and testing asset pricing models. Statistical inference with this method is typically conducted under the assumption that the models are correctly specified, that is, expected returns are exactly linear in asset betas. This assumption can be a problem in practice since all models are, at best, approximations of reality and are likely to be subject to a certain degree of misspecification. We propose a general ...
FRB Atlanta Working Paper , Paper 2009-11

Working Paper
Mimicking portfolios, economic risk premia, and tests of multi-beta models

This paper considers two alternative formulations of the linear factor model (LFM) with nontraded factors. The first formulation is the traditional LFM, where the estimation of risk premia and alphas is performed by means of a cross-sectional regression of average returns on betas. The second formulation (LFM*) replaces the factors with their projections on the span of excess returns. This formulation requires only time-series regressions for the estimation of risk premia and alphas. We compare the theoretical properties of the two approaches and study the small-sample properties of estimates ...
FRB Atlanta Working Paper , Paper 2005-04

Working Paper
Analytical solution for the constrained Hansen-Jagannathan distance under multivariate ellipticity

We provide an in-depth analysis of the theoretical properties of the Hansen-Jagannathan (HJ) distance that incorporates a no-arbitrage constraint. Under a multivariate elliptical distribution assumption, we present explicit expressions for the HJ-distance with a no-arbitrage constraint, the associated Lagrange multipliers, and the SDF parameters in the case of linear SDFs. This approach allows us to analyze the benefits and costs of using the HJ-distance with a no-arbitrage constraint to rank asset pricing models.
FRB Atlanta Working Paper , Paper 2012-18

Working Paper
Model comparison using the Hansen-Jagannathan distance

Although it is of interest to empirical researchers to test whether or not a particular asset-pricing model is true, a more useful task is to determine how wrong a model is and to compare the performance of competing asset-pricing models. In this paper, we propose a new methodology to test whether two competing linear asset-pricing models have the same Hansen-Jagannathan distance. We show that the asymptotic distribution of the test statistic depends on whether the competing models are correctly specified or misspecified and are nested or nonnested. In addition, given the increasing interest ...
FRB Atlanta Working Paper , Paper 2007-04

Working Paper
Robust inference in linear asset pricing models

We derive new results on the asymptotic behavior of the estimated parameters of a linear asset pricing model and their associated t-statistics in the presence of a factor that is independent of the returns. The inclusion of this "useless" factor in the model leads to a violation of the full rank (identification) condition and renders the inference nonstandard. We show that the estimated parameter associated with the useless factor diverges with the sample size but the misspecification-robust t-statistic is still well-behaved and has a standard normal limiting distribution. The asymptotic ...
FRB Atlanta Working Paper , Paper 2012-17

Working Paper
Minimum-variance kernels, economic risk premia, and tests of multi-beta models

This paper uses minimum-variance (MV) admissible kernels to estimate risk premia associated with economic risk variables and to test multi-beta models. Estimating risk premia using MV kernels is appealing because it avoids the need to 1) identify all relevant sources of risk and 2) assume a linear factor model for asset returns. Testing multi-beta models in terms of restricted MV kernels has the advantage that 1) the candidate kernel has the smallest volatility and 2) test statistics are easy to interpret in terms of Sharpe ratios. The authors find that several economic variables command ...
FRB Atlanta Working Paper , Paper 2001-24

Working Paper
The price of inflation and foreign exchange risk in international equity markets

In this paper the author formulates and tests an international intertemporal capital asset pricing model in the presence of deviations from purchasing power parity (II-CAPM [PPP]). He finds evidence in favor of at least mild segmentation of international equity markets in which only global market risk appears to be priced. When using the Hansen & Jagannathan (1991, 1997) variance bounds and distance measures as testing devices, the author finds that, while all international asset pricing models are formally rejected by the data, their pricing implications are substantially different. The ...
FRB Atlanta Working Paper , Paper 2001-26

Working Paper
Dynamic strategies, asset pricing models, and the out-of-sample performance of the tangency portfolio

In this paper, I study the behavior of an investor with unit risk aversion who maximizes a utility function defined over the mean and the variance of a portfolio's return. Conditioning information is accessible without cost and an unconditionally riskless asset is available in the market. ; The proposed approach makes it possible to compare the performance of a benchmark tangency portfolio (formed from the set of unrestricted estimates of portfolio weights) to the performance of a restricted tangency portfolio which uses single-index and multi-index asset pricing models to constrain the first ...
FRB Atlanta Working Paper , Paper 2003-6

Working Paper
The exact distribution of the Hansen-Jagannathan bound

Under the assumption of multivariate normality of asset returns, this paper presents a geometrical interpretation and the finite-sample distributions of the sample Hansen-Jagannathan (1991) bounds on the variance of admissible stochastic discount factors, with and without the nonnegativity constraint on the stochastic discount factors. In addition, since the sample Hansen-Jagannathan bounds can be very volatile, we propose a simple method to construct confidence intervals for the population Hansen-Jagannathan bounds. Finally, we show that the analytical results in the paper are robust to ...
FRB Atlanta Working Paper , Paper 2008-09

Working Paper
On the Hansen-Jagannathan distance with a no-arbitrage constraint

We provide an in-depth analysis of the theoretical and statistical properties of the Hansen-Jagannathan (HJ) distance that incorporates a no-arbitrage constraint. We show that for stochastic discount factors (SDF) that are spanned by the returns on the test assets, testing the equality of HJ distances with no-arbitrage constraints is the same as testing the equality of HJ distances without no-arbitrage constraints. A discrepancy can exist only when at least one SDF is a function of factors that are poorly mimicked by the returns on the test assets. Under a joint normality assumption on the ...
FRB Atlanta Working Paper , Paper 2010-04

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