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Modeling persistent interest rates with volatility-induced stationarity
Hansen, Anne Lundgaard - 2019
volatilityinduced stationarity. Our model employs a leveldependent conditional volatility that maintains stationarity despite the …
Persistent link: https://www.econbiz.de/10012111254
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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
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Jump factor models in large cross‐sections
Li, Jia; Todorov, Viktor; Tauchen, George Eugene - In: Quantitative economics : QE ; journal of the … 10 (2019) 2, pp. 419-456
We develop tests for deciding whether a large cross‐section of asset prices obey an exact factor structure at the times of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of asset returns with asymptotically increasing...
Persistent link: https://www.econbiz.de/10012042424
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Value-at-risk and expected shortfall when there is long range dependence
Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2008
characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …
Persistent link: https://www.econbiz.de/10003636008
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Fractional integration and fat tails for realized covariance kernels and returns
Lucas, André; Opschoor, Anne - 2016 - This version: September 1, 2016
We introduce a new fractionally integrated model for covariance matrix dynamics based on the long-memory behavior of daily realized covariance matrix kernels and daily return observations. We account for fat tails in both types of data by appropriate distributional assumptions. The covariance...
Persistent link: https://www.econbiz.de/10011531139
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Data-driven jump detection thresholds for application in jump regressions
Davies, Robert; Tauchen, George Eugene - 2015
This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...
Persistent link: https://www.econbiz.de/10011524214
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Data-driven jump detection thresholds for application in jump regressions
Davies, Robert; Tauchen, George Eugene - In: Econometrics : open access journal 6 (2018) 2, pp. 1-25
This paper develops a method to select the threshold in threshold-based jump detection methods. The method is motivated by an analysis of threshold-based jump detection methods in the context of jump-diffusion models. We show that over the range of sampling frequencies a researcher is most...
Persistent link: https://www.econbiz.de/10011823308
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Do we need stochastic volatility and generalised autoregressive conditional heteroscedasticity? : Comparing squared end-of-day returns on ftse
Allen, David E.; McAleer, Michael - In: Risks : open access journal 8 (2020) 1/12, pp. 1-20
The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional … Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV … two standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV …
Persistent link: https://www.econbiz.de/10012203997
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Intraday stochastic volatility in discrete price changes : the dynamic Skellam model
Koopman, Siem Jan; Lit, Rutger; Lucas, André - 2015
We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete … series per day varies from 1000 to 10,000. Complexities in the intraday dynamics of volatility and in the frequency of trades … intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling …
Persistent link: https://www.econbiz.de/10011295740
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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