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Detecting money market bubbles

Baldeaux, Jan; Ignatieva, Ekaterina; Platen, Eckhard - 2016

Persistent link: https://www.econbiz.de/10011778131

A jumping index of jumping stocks? : an MCMC analysis of continuous-time models for individual stocks

Pollastri, Alessandro; Rodrigues, Paulo Jorge Maurício; … - In: Journal of empirical finance 70 (2023), pp. 322-341

Persistent link: https://www.econbiz.de/10014423714

A jumping index of jumping stocks? : an MCMC analysis of continuous-time models for individual stocks

Pollastri, Alessandro; Rodrigues, Paulo Jorge Maurício; … - 2023

Persistent link: https://www.econbiz.de/10014448099

A jumping index of jumping stocks? : an MCMC analysis of continuous-time models for individual stocks

Pollastri, Alessandro; Rodrigues, Paulo Jorge Maurício; … - 2022 - This version: December 6, 2022

This paper examines continuous-time models for the S&P 100 index and its constituents. We find that the jump process of the typical stock looks significantly different than that of the index. Most importantly, the average size of a jumps in the returns of the typical stock is positive, while it...

Persistent link: https://www.econbiz.de/10013465942

Nonparametric test for a constant beta over a fixed time interval

Reiß, Markus; Todorov, Viktor; Tauchen, George Eugene - 2014

We derive a nonparametric test for constant (continuous) beta over a fixed interval of time. Continuous beta is defined as the ratio of the continuous covariation between an asset and observable risk factor (e.g., the market return) and the continuous variation of the latter. Our test is based...

Persistent link: https://www.econbiz.de/10010253467

Markov regime-switching autoregressive model of stock market returns in Nigeria

Adejumo, Oluwasegun A.; Albert, Seno; Asemota, Omorogbe J. - In: CBN journal of applied statistics 11 (2020) 2, pp. 65-83

studyanalyzes the stock market volatility in three distinct regimes (accumulation or distri-bution - regime 1; big-move - regime 2 …

Persistent link: https://www.econbiz.de/10012513279

Volatility regimes of selected central European stock returns : a Markov switching GARCH approach

Chocholatá, Michaela - In: Journal of business economics and management 23 (2022) 4, pp. 876-894

the behaviour of returns and their volatility during both the calm as well as various crises/turmoil periods. Besides the …-GJR-GARCH) were estimated in order to examine the volatility switches of the Central European transition stock markets. The t …-distribution of error terms was used to capture the dynamics of analysed returns more precisely. The results proved high volatility …

Persistent link: https://www.econbiz.de/10013499116

Partially censored posterior for robust and efficient risk evaluation

Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - 2019

A novel approach to inference for a speciﬁc region of the predictive distribution is introduced. An important domain of application is accurate prediction of ﬁnancial risk measures, where the area of interest is the left tail of the predictive density of logreturns. Our proposed approach...

Persistent link: https://www.econbiz.de/10012057160

The effect of the great moderation on the US business cycle in a time-varying multivariate trend-cycle model

Creal, Drew; Koopman, Siem Jan; Zivot, Eric - 2008

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

Persistent link: https://www.econbiz.de/10011376640

Inference for adaptive time series models : stochastic volatility and conditionally Gaussian state space form

Bos, Charles S.; Shephard, Neil G. - 2004

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

Persistent link: https://www.econbiz.de/10011334849