European Central Bank - eurosystem
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Paġna ewlenija Midja Spjegazzjonijiet Riċerka u Pubblikazzjonijiet Statistika Politika Monetarja L-€uro Ħlasijiet u Swieq Karrieri
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Ernst Glatzer

1 January 2003
In this paper we study risk-neutral densities (RNDs) for the German stock market. The use of option prices allows us to quantify the risk-neutral probabilities of various levels of the DAX index. For the period from December 1995 to November 2001, we implement the mixture of log-normals model and a volatility-smoothing method. We discuss the time series behaviour of the implied PDFs and we examine the relations between the moments and observable factors such as macroeconomic variables, the US stock markets and credit risk. We find that the risk-neutral densities exhibit pronounced negative skewness. Our second main observation is a significant spillover of volatility, as the implied volatility and kurtosis of the DAX RND are mostly driven by the volatility of US stock prices.
JEL Code
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C51 : Mathematical and Quantitative Methods→Econometric Modeling→Model Construction and Estimation
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G15 : Financial Economics→General Financial Markets→International Financial Markets
14 September 2005
Based on individual price records collected for the computation of the Austrian CPI, average frequencies of price changes and durations of price spells are estimated to characterize price setting in Austria. Depending on the estimation method, prices are unchanged for 10 to 14 months on average. We find strong heterogeneity across sectors and products. Price increases occur only slightly more often than price decreases. The typical size of a price increase (decrease) is 11 (15) percent. The aggregate hazard function of prices is decreasing with time. Besides heterogeneity across products and price setters, this is due to oversampling of products with a high frequency of price changes. Accounting for unobserved heterogeneity in estimating the probability of a price change with a fixed-effects logit model, we find a positive effect of the duration of a price spell. During the Euro cash changeover the probability of price changes was higher.
JEL Code
C41 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Duration Analysis, Optimal Timing Strategies
D21 : Microeconomics→Production and Organizations→Firm Behavior: Theory
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
L11 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Production, Pricing, and Market Structure, Size Distribution of Firms
Eurosystem inflation persistence network