A researcher allocates a budget of informative tests across multiple unknown attributes to influence a decision-maker. We derive the researcher's equilibrium learning strategy by solving an auxiliary single-player problem. The attribute weights in this problem depend on how much the researcher...

A researcher allocates a budget of informative tests across multiple unknown attributes to influence a decision-maker. We derive the researcher's equilibrium learning strategy by solving an auxiliary single-player problem. The attribute weights in this problem depend on how much the researcher...

Investing in stocks and shares is a common strategy to pursue potential gains while considering future financial needs, such as retirement and children's education. Effectively managing investment risk requires thoroughly analyzing stock market returns and making informed predictions....

This paper describes three methods for carrying out non-asymptotic inference on partially identified parameters that are solutions to a class of optimization problems. Applications in which the optimization problems arise include estimation under shape restrictions, estimation of models of...

We document that even though the normal distribution provides a good approximation to GDP fluctuations, it severely underpredicts “macroeconomic tail risks,” that is, the frequency of large economic downturns. Using a multi-sector general equilibrium model, we show that the interplay of...

We document that even though the normal distribution provides a good approximation to GDP fluctuations, it severely underpredicts "macroeconomic tail risks," that is, the frequency of large economic downturns. Using a multi-sector general equilibrium model, we show that the interplay of...

We document that even though the normal distribution is a good approximation to the nature of aggregate fluctuations, it severely underpredicts the frequency of large economic downturns. We then provide a model that can explain these facts simultaneously. Our model shows that the propagation of...

ARMA-GARCH-Modellierung; nicht-Normalität; normal-inverse Gauss-Verteilung (NIG-Verteilung); realisierte Momente; Staatsanleihen; Strom Forwards; stylized facts von Finanzzeitreihen; Value at Risk; Verteilung von Anleiherenditen

The paper investigates the effects of deviations from normality on the estimates of risk premiums and the real equilibrium, short-term interest rate in the conventional rational expectations equilibrium model of Lucas (1978). We consider a time-continuous approach, where both the aggregate...

We document that even though the normal distribution provides a good approximation to GDP fluctuations, it severely underpredicts "macroeconomic tail risks," that is, the frequency of large economic downturns. Using a multi-sector general equilibrium model, we show that the interplay of...

We derive a Gaussian approximation result for the maximum of a sum of high dimensional random vectors. Specifically, we establish conditions under which the distribution of the maximum is approximated by that of the maximum of a sum of the Gaussian random vectors with the same covariance...

We derive a central limit theorem for the maximum of a sum of high dimensional random vectors. More precisely, we establish condi- tions under which the distribution of the maximum is approximated by the maximum of a sum of the Gaussian random vectors with the same covariance matrices as the...

We develop a new direct approach to approximating suprema of general empirical processes by a sequence of suprema of Gaussian processes, without taking the route of approximating empirical processes themselves in the sup-norm. We prove an abstract approximation theorem that is applicable to a...

Purpose To improve the trajectory tracking accuracy of 6R decoupled manipulator in singularity region, this paper aims to propose a singularity avoidance algorithm named “singularity separation plus improved Gaussian distribution damped reciprocal”. Design/methodology/approach The...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited Information Bayesian Model Averaging (LIBMA) methodology and then test it using simulated data. Simulation...

We derive forecast confidence bands using a Global Projection Model covering the United States, the euro area, and Japan. In the model, the price of oil is a stochastic process, interest rates have a zero floor, and bank lending tightening affects the United States. To calculate confidence...

We obtain two characterizations of the Gaussian distribution on a Hilbert space from samples of random size.

In this paper we derive the asymptotic behaviour of the survival function of both random sum and random maximum of log-normal risks. As for the case of finite sum and maximum investigated in Asmussen and Rojas-Nandayapa (2008) also for the more general setup of random sums and random maximum the...

There is strong evidence that interest rates and bond yield movements exhibit both stochastic volatility and unanticipated jumps. The presence of frequent jumps makes it natural to ask whether there is a premium for jump risk embedded in observed bond yields. This paper identifies a class of...

This paper presents the design aspects and probabilistic approach for the generation reliability evaluation of an alternative resource: municipal waste water (MWW) based micro-hydro power plant (MHPP). Annual and daily flow duration curves have been obtained for design, installation,...

One approach to oil markets is to treat oil as an asset, besides its role as a commodity. Speculative and nonspeculative activity by investors in the derivatives markets could be responsible for a sizable increase in oil prices. This paper recognizes both the consumption and investment aspects...

In this paper, we construct an intermediate distribution linking the Gaussian and the Cauchy distribution. We provide the probability density function and the corresponding characteristic function of the intermediate distribution. Because many kinds of distributions have no moment, we introduce...

Previous early-warning systems (EWSs) for currency crises have relied on models that require a priori dating of crises. This paper proposes an alternative EWS, based on a Markov-switching model, which identifies and characterizes crisis periods endogenously; this also allows the model to utilize...

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was...

Within a unified theory for stocks and corporate bonds, based on dynamic optimization by investors, this paper derives analytical expressions for the momentary distributions of expected price, respectively known to approximate lognormal with systematic deviations (high peak, fat tail) and double...

We propose new measures of both risk and anticipated return that incorporate the effects of skewness and heavy tails from a financial return’s probability distribution. Our cosine-based analysis, which involves maximizing the marginal Shannon information associated with the Fourier transform...

It has been found that the structure of complex network has significant influence on the condensation of particles and the equilibrium state of particles is dynamical. We study here the fluctuation of particles on each individual node at equilibrium status and find that the particle...

A Gaussian version of the iterative proportional fitting procedure (IFP-P) was applied by Speed and Kiiveri to solve the likelihood equations in graphical Gaussian models. The calculation of the maximum likelihood estimates can be seen as the problem to find a Gaussian distribution with...

The statistical properties of daily closing futures prices for nine commodities are studied. Two hypotheses are examined: Price changes are normally distributed, and prices follow a random walk process. Normality is tested by estimating kurtosis, the R/S statistic, and characteristic exponents....