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Should firms spend more on research and development and advertising during recessions?

Srinivasan, Raji; Lilien, Gary L.; Sridhar, Shrihari - In: Journal of marketing 75 (2011) 3, pp. 49-65

Persistent link: https://www.econbiz.de/10009160719

Brokers and business cycles: Does financial market volatility cause real fluctuations?

Döpke, Jörg; Pierdzioch, Christian - 1998

This paper elaborates on the link between financial market volatility and real economic activity. Using monthly data for Germany from 1968 to 1998, we specify GARCH models to capture the variability of stock market prices, of the real exchange rate, and of a long-term and of a short-term rate of...

Persistent link: https://www.econbiz.de/10010275423

The Warsaw Stock Exchange index WIG : modelling and forecasting

Wdowiński, Piotr; Zglinska-Pietrzak, Aneta - 2005

In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock indexes (DAX and FTSE) on the Warsaw Stock Exchange index WIG within a framework of a GARCH model. By applying a procedure of checking predictive quality of econometric models as...

Persistent link: https://www.econbiz.de/10010277059

Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching

Lux, Thomas; Kaizoji, Taisei - 2006

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

Persistent link: https://www.econbiz.de/10010294979

The multi-fractal model of asset returns: Its estimation via GMM and its use for volatility forecasting

Lux, Thomas - 2003

forecasting financial volatility. We use the auto-covariances of log increments of the multi-fractal process in order to estimate … ?scaling? approach. Our empirical estimates are used in out-of-sample forecasting of volatility for a number of important …

Persistent link: https://www.econbiz.de/10010295056

The Markov-switching multi-fractal model of asset returns: GMM estimation and linear forecasting of volatility

Lux, Thomas - 2004

Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … leads to gains in forecasting accuracy for some time series. …

Persistent link: https://www.econbiz.de/10010295106

Forecasting volatility and volume in the Tokyo stock market: The advantage of long memory models

Lux, Thomas; Kaizoji, Taisei - 2004

-memory counterparts. Since long memory models should have a particular advantage over long forecasting horizons, we consider predictions …

Persistent link: https://www.econbiz.de/10010295136

The Markov-Switching Multifractal Model of asset returns: GMM estimation and linear forecasting of volatility

Lux, Thomas - 2006

forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … leads to gains in forecasting accuracy for some time series. …

Persistent link: https://www.econbiz.de/10010295151

Local adaptive multiplicative error models for high-frequency forecasts

Härdle, Wolfgang Karl; Hautsch, Nikolaus; Mihoci, Andrija - 2012

modelling bias and estimation (in)efficiency. In forecasting, the proposed adaptive approach significantly outperforms a MEM …

Persistent link: https://www.econbiz.de/10010330969

One-factor-Garch models for German stocks: Estimation and forecasting

Kaiser, Thomas - 1996

This paper presents theoretical models and their empirical results for the return and variance dynamics of German stocks. A factor structure is used in order to allow for a parsimonious modeling of the first two moments of returns. Dynamic factor models with GARCH dynamics (GARCH(1,1)-M,...

Persistent link: https://www.econbiz.de/10010435583