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The modeling of earnings per share of Polish companies for the post-financial crisis period using random walk and ARIMA models

Kuryłek, Wojciech - In: Journal of banking and financial economics 19 (2023) 1, pp. 26-43

The proper forecasting of listed companies' earnings is crucial for their appropriate pricing. This paper compares forecast errors of different univariate time-series models applied for the earnings per share (EPS) data for Polish companies from the period between the last financial crisis of...

Persistent link: https://www.econbiz.de/10014285928

Prognose mit nichtparametrischen Verfahren

Härdle, Wolfgang Karl; Schulz, Rainer; Wang, Weining - 2010

Statistische Prognosen basieren auf der Annahme, dass ein funktionaler Zusammenhang zwischen der zu prognostizierenden Variable y und anderen j-dimensional beobachtbaren Variablen x = (x1,...xl) besteht. Kann der funktionale Zusammenhang geschätzt werden, so kann im Prinzip für jedes x der...

Persistent link: https://www.econbiz.de/10010281577

Out-of-Sample Comparison of Copula Specifications in Multivariate Density Forecasts

Diks, Cees G. H.; Panchenko, Valentyn; Dijk, Dick van - 2011

We introduce a statistical test for comparing the predictive accuracy of competing copula specifications in multivariate density forecasts, based on the Kullback-Leibler Information Criterion (KLIC). The test is valid under general conditions: in particular it allows for parameter estimation...

Persistent link: https://www.econbiz.de/10014047091

Splines for Financial Volatility

Audrino, Francesco; Buhlmann, Peter - 2007

We propose a flexible GARCH-type model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B-splines of lagged observations and volatilities. Estimation of such a B-spline basis expansion is constructed within the likelihood framework...

Persistent link: https://www.econbiz.de/10014051065

Jump-Robust Volatility Estimation Using Nearest Neighbor Truncation

Andersen, Torben; Dobrev, Dobrislav; Schaumburg, Ernst - 2010

We propose two new jump-robust estimators of integrated variance based on highfrequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical...

Persistent link: https://www.econbiz.de/10014200896

Strategies for Sequential Prediction of Stationary Time Series

Gyorfi, Laszlo; Lugosi, Gábor - 2001

We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combination of several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost...

Persistent link: https://www.econbiz.de/10014142874

Allowing for Jump Measurements in Volatility : A High-Frequency Financial Data Analysis of Individual Stocks

Papavassiliou, Vassilios G. - 2016

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyze the distributional...

Persistent link: https://www.econbiz.de/10013004411

Forecasting with Dynamic Pane Data Models

Liu, Laura - 2017

This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's formula for the posterior mean of heterogeneous coeffcients under a correlated random effects distribution. This...

Persistent link: https://www.econbiz.de/10012964303

Coupling High-Frequency Data with Nonlinear Models in Multiple-Step-Ahead Forecasting of Energy Markets' Volatility

Baruník, Jozef - 2015

-predict volatility uniformly during all tested periods. Our analysis favors the median realized volatility, as it delivers the best …

Persistent link: https://www.econbiz.de/10013033742

Forecasting Distribution of Inflation Rates : Functional Autoregressive Approach

Chaudhuri, Kausik - 2015

In line with the recent developments on the statistical analysis of functional data, we develop the semiparametric … functional autoregressive (FAR) modeling approach to the density forecasting analysis of national inflation rates using sectoral … their statistical validity. The fan-chart analysis and the probability event forecasting exercise provide a further support …

Persistent link: https://www.econbiz.de/10013039117