Search results for: Ivo Jánský

Authors: Jana Chvalkovska, Petr Jansky, Petr Teply

Abstract:

The impact assessment in its various forms has recently become a very important part of policy-making and legislation in many different countries. Regulatory impact assessment (RIA) is yet another set of analytical methods deployed in the legislation of the European Union, of many developed countries as well as in many developing ones such as Mexico, Malaysia and Philippines. The aim of this paper is to provide a theoretical background for economic models in regulatory impact assessment and an overview of their application especially on the financial market in the Czech Republic. We found out an inadequate application of these models, what makes room for further research in this field.

Keywords: regulatory impact assessment, RIA, impact evaluation, building societies, Czech Republic

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Authors: Chvalkovska, J., Jansky, P., Mejstrik, M.

Abstract:

The objective of this article is to discuss the potential of economic analysis as a tool for identification and evaluation of corruption in legislative acts. We propose that corruption be perceived as a risk variable within the legislative process. Therefore we find it appropriate to employ risk analysis methods, used in various fields of economics, for the evaluation of corruption in legislation. Furthermore we propose the incorporation of these methods into the so called corruption impact assessment (CIA), the general framework for detection of corruption in legislative acts. The applications of the risk analysis methods are demonstrated on examples of implementation of proposed CIA in the Czech Republic.

Keywords: corruption; corruption impact assessment (CIA); legislative; legislative process; risk analysis; Czech Republic

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Authors: Ivo Jánský, Milan Rippel

Abstract:

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.

Keywords: VaR, risk analysis, conditional volatility, garch, egarch, tarch, moving average process, autoregressive process

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