This article presents a new approach for building robust portfolios based on stochastic efficiency analysis and periods of market downturn. The empirical analysis is done on assets traded on the Brazil Stock Exchange, B3 (Brasil, Bolsa, Balcão). We start with information on the assets from...

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which can lead to a mix of point‐ and set‐identified models. We propose...

We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatment-effect...

We use data on the following climate variables for the period of the last 798 thousand years: global ice volume (Icet), atmospheric carbon dioxide level (CO2,t), and Antarctic land surface temperature (Tempt). Those variables are cyclical and are driven by the following strongly exogenous...

Considering a temporal dimension allows for the delivery of rolling solutions to complex real-world problems. Moving forward in time brings uncertainty, and large margins for potential error in solutions. For the multi-year crop planning problem, the largest uncertainty is how the climate will...

We state a sufficient condition under which choice data alone suffices to identify consumer preferences when choices are not fully informed. Suppose that: (i) the data generating process is a search model in which the attribute hidden to consumers is observed by the econometrician; (ii) if a...

Purpose: The banking sector in the MENA region is exposed to financial risks that originate from both the internal and external environment. Related studies in the literature have reached inconclusive determinants of the overall risks to banks. This paper examines the robustness of the...

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ε-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the...

We study an optimal robust monetary policy for a small open economy. The robust control approach assumes that economic agents cannot assign probabilities to a set of plausible models and rather focuses on the worst possible misspecification from a benchmark model. Our findings suggest that,...

We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the instrumental variable (IV) suitably exogenous or to improve precision. Unlike previous...

We revisit the problem of estimating the local average treatment effect (LATE) and the local average treatment effect on the treated (LATT) when control variables are available, either to render the instrumental variable (IV) suitably exogenous or to improve precision. Unlike previous...

Classical Bayesian mechanism design relies on the common prior assumption, but the common prior is often not available in practice. We study the design of prior-independent mechanisms that relax this assumption: the seller is selling an indivisible item to n buyers such that the buyers’...

This paper introduces a unified parametric modeling approach for time-varying market betas that can accommodate continuous-time diffusion and discrete-time series models based on a continuous-time series regression model to better capture the dynamic evolution of market betas.We call this the...

When constructing parametric models to predict the cost of future claims, several important details have to be taken into account: (i) models should be designed to accommodate deductibles, policy limits, and coinsurance factors, (ii) parameters should be estimated robustly to control the...

This paper develops estimation and inference methods for conditional quantile factor models. We first introduce a simple sieve estimation, and establish asymptotic properties of the estimators under large $N$. We then provide a bootstrap procedure for estimating the distributions of the...

Robust Estimation of Loss Models for Lognormal Insurance Payment Severity Data Chudamani Poudyal1Department of Statistics and Data Science University of Central Florida. The primary objective of this scholarly work is to develop two estimation procedures –maximum likelihood estimator(MLE) and...

With some regularity conditions maximum likelihood estimators (MLEs) al-ways produce asymptotically optimal (in the sense of consistency, efficiency, sufficiency,and unbiasedness) estimators. But in general, the MLEs lead to non-robust statisticalinference, for example, pricing models and risk...

Bilateral Gamma processes generalize the Variance Gamma process and allow to capture more precisely the differences between upward and downward moves of financial returns, notably in terms of jump speed, frequency, and size. Like in most other pure jump models, option pricing under Bilateral...

We consider games where an analyst is not confident about players' true information structure for payoff-relevant parameters. We define a robust prediction by a set of action profiles such that, given any information structure among the players, there is a Bayesian Nash equilibrium given that...

We consider a game between several principals and a common agent, where principals know only a subset of the agent's available actions. Principals demand robustness and evaluate contracts on a worst-case basis. This robust approach allows for a crisp characterization of the equilibrium contracts...

Surplus-lag testing has been proposed as a means of undertaking persistence-robust causality analysis irrespective of the integrated nature of economic and/or financial series under examination. The present paper examines whether this suggested robustness holds when considering series...

In this paper, we consider robust estimation of claim severity models in insurance, when data are affected by truncation (due to deductibles), censoring (due to policy limits), and scaling (due to coinsurance). In particular, robust estimators based on the methods of trimmed moments...

The solutions to robust optimization problems are sometimes too conservative because of the focus on worst-case performance. For the least-squares (LS) problem, we describe a way to overcome this by combining the classical formulation with its robust counterpart. We focus on the issue of...

This paper develops a theory of dynamic pessimism and its impact on asset prices. Notions of time-varying pessimism arise endogenously in our setting as a consequence of agents’ concern for model misspecification. We generalize the robust control approach of Hansen and Sargent (2001) by...

We propose and analyze a sequential design of price experimentation that balances the learning and earning trade-off in revenue management. Assuming the demand function belongs to a parametric family with an unknown parameter value, we derive a closed-form stopping rule based on the realized...

Transition metal sulfide is a promising electrocatalyst for the hydrogen evolution reaction (HER), yet it is still uncompetitive with platinum-based electrodes for clean and renewable energy applications. To resolve this issue, grid-matched palladium-nickel sulfides (Pd4S/Ni3S2) are successfully...

We propose a new dimension reduction procedure for portfolio optimization. The vanilla principal component analysis (PCA) restricts the portfolio on the linear subspace spanned by the PCs, which often requires many PCs to performance well. In our framework, the linear subspace is based on a most...

Situations where simple and affordable testing tools are available but not accurate enough to be operationally relevant are ubiquitous. For COVID-19 detection, rapid point-of-care tests are cheap and provide results in minutes, but largely fail policymakers' accuracy requirements. We propose an...

Interest rates have fallen worldwide in recent decades, a phenomenon that has been linked at least in part to a decline in the natural rate of interest, r* (a.k.a. “r-star”). To investigate this decline, we consider a multivariate trend-cycle decomposition of real interest rates using a...

Necessarily, new technical change is facilitated by the development of new technical proficiencies. Whenever the claim to `new technical change' is robust, the accompanying `new technical proficiencies' facilitate an `outcome', in respect of which `old technical proficiencies' are intractable....