A case study of the residual-based cointegration procedure.
A dynamic factor model for economic time series
A multimodal beta distribution with application to economic data
Beta distributions are popular models for economic data. In this paper, a new multimodal beta distribution with bathtub shaped failure rate function is introduced. Various structural properties of this distribution are derived, including its cdf, moments, mean deviation about the mean, mean deviation about the median, entropy, asymptotic distribution of the extreme order statistics, maximum likelihood estimates and the Fisher information matrix. Finally, an application to consumer price indices...
A time-series approach to non-self-financing hedging in a discrete-time incomplete market.
Adaptive prediction of stock exchange indices by state space wavelet networks
The paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session ahead and five sessions ahead adaptive predictors of the WIG20 index...
Analysis of Simulation Model Aplication to Forecast the Railway Workers Failures
Beiträge zur Theorie der Vermehrungsformeln
Computational aspects of robust Holt-Winters smoothing based on -estimation
To obtain a robust version of exponential and Holt-Winters smoothing the idea of -estimation can be used. The difficulty is the formulation of an easy-to-use recursive formula for its computation. A first attempt was made by Cipra (Robust exponential smoothing, J. Forecast. 11 (1992), 57–69). The recursive formulation presented there, however, is unstable. In this paper, a new recursive computing scheme is proposed. A simulation study illustrates that the new recursions result in smaller forecast...
Discrete stochastic dynamics of income inequality in education: An applied stochastic model and a case study.
Dynamics of loans in the Polish banking system
Econometric modeling at mixed frequencies.
Ergodic cobweb chaos.
Estimation and testing of cointegration relationships with strongly seasonal monthly data
Evidence for nonlinear asymmetric causality in US inflation, metal, and stock returns.
Evolutionary training for Dynamical Recurrent Neural Networks: an application in finantial time series prediction.
Theoretical and experimental studies have shown that traditional training algorithms for Dynamical Recurrent Neural Networks may suffer of local optima solutions, due to the error propagation across the recurrence. In the last years, many researchers have put forward different approaches to solve this problem, most of them being based on heuristic procedures. In this paper, the training capabilities of evolutionary techniques are studied, for Dynamical Recurrent Neural Networks. The performance...
EWMA historical volatility estimators
Exponential smoothing for irregular time series
The paper deals with extensions of exponential smoothing type methods for univariate time series with irregular observations. An alternative method to Wright’s modification of simple exponential smoothing based on the corresponding ARIMA process is suggested. Exponential smoothing of order m for irregular data is derived. A similar method using a DLS **discounted least squares** estimation of polynomial trend of order m is derived as well. Maximum likelihood parameters estimation for forecasting...
Forecasting Telecommunication New Service Demand by Analogy Method and Combined Forecast
General Laws of Adaptation to Environmental Factors: from Ecological Stress to Financial Crisis
We study ensembles of similar systems under load of environmental factors. The phenomenon of adaptation has similar properties for systems of different nature. Typically, when the load increases above some threshold, then the adapting systems become more different (variance increases), but the correlation increases too. If the stress continues to increase then the second threshold appears: the correlation achieves maximal value, and start to decrease, but the variance continue to increase. In many...
Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence
Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions are complex-valued...