Maximum likelihood estimation of the equity
نویسندگان
چکیده
The equity premium, namely the expected return on the aggregate stock market less the government bill rate, is of central importance to the portfolio allocation of individuals, to the investment decisions of firms, and to model calibration and testing. This quantity is usually estimated from the sample average excess return. We propose an alternative estimator, based on maximum likelihood, that takes into account information contained in dividends and prices. Applied to the postwar sample, our method leads to an economically significant reduction from 6.4% to 5.1%. Simulation results show that our method produces more reliable estimates under a wide range of specifications.
منابع مشابه
The Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...
متن کاملChange Point Estimation of the Stationary State in Auto Regressive Moving Average Models, Using Maximum Likelihood Estimation and Singular Value Decomposition-based Filtering
In this paper, for the first time, the subject of change point estimation has been utilized in the stationary state of auto regressive moving average (ARMA) (1, 1). In the monitoring phase, in case the features of the question pursue a time series, i.e., ARMA(1,1), on the basis of the maximum likelihood technique, an approach will be developed for the estimation of the stationary state’s change...
متن کاملMaximum Likelihood Estimation of Parameters in Generalized Functional Linear Model
Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...
متن کاملBearing Fault Detection Based on Maximum Likelihood Estimation and Optimized ANN Using the Bees Algorithm
Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...
متن کاملA comparison of algorithms for maximum likelihood estimation of Spatial GLM models
In spatial generalized linear mixed models, spatial correlation is assumed by adding normal latent variables to the model. In these models because of the non-Gaussian spatial response and the presence of latent variables the likelihood function cannot usually be given in a closed form, thus the maximum likelihood approach is very challenging. The main purpose of this paper is to introduce two n...
متن کاملWindowing Effects of Short Time Fourier Transform on Wideband Array Signal Processing Using Maximum Likelihood Estimation
During the last two decades, Maximum Likelihood estimation (ML) has been used to determine Direction Of Arrival (DOA) and signals propagated by the sources, using narrowband array signals. The algorithm fails in the case of wideband signals. As an attempt by the present study to overcome the problem, the array outputs are transformed into narrowband frequency bins, using short time Fourier tran...
متن کامل