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Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? : a quantile machine-learning approach

Gupta, Rangan; Pierdzioch, Christian - In: Financial innovation : FIN 9 (2023), pp. 1-22

Persistent link: https://www.econbiz.de/10014288917

Intra-Day Realized Volatility for European and USA Stock Indices

Degiannakis, Stavros Antonios - 2019

The paper constructs measures of intra-day realized volatility for 17 European and USA stock indices. We utilize a … model-free de-noising method by assembling the realized volatility in sampling frequency selected according to the … volatility signature plot which minimizes the micro-structure effects. Having verified the stylized facts of realized volatility …

Persistent link: https://www.econbiz.de/10012897936

The factor-spline-GARCH model for high and low frequency correlations

Rangel, Jose Gonzalo; Engle, Robert F. - 2009

frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …

Persistent link: https://www.econbiz.de/10003821063

Predictability of bull and bear markets : a new look at forecasting stock market regimes (and returns) in the US

Haase, Felix; Neuenkirch, Matthias - 2021 - This Version: January 8, 2021

The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...

Persistent link: https://www.econbiz.de/10012180543

Do high-frequency financial data help forecast oil prices? : the MIDAS touch at work

Baumeister, Christiane; Guérin, Pierre; Kilian, Lutz - 2013

The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market...

Persistent link: https://www.econbiz.de/10010203447

Evaluating density forecasts with an application to stock market returns

Raaij, Gabriela de; Raunig, Burkhard - 2002

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

Persistent link: https://www.econbiz.de/10011431370

Forecasting value-at-risk using block structure multivariate stochastic volatility models

Asai, Manabu; Caporin, Massimiliano; McAleer, Michael - 2013

Persistent link: https://www.econbiz.de/10009767006

Measuring and modeling risk using high-frequency data

Härdle, Wolfgang (contributor); … - 2008

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management … the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns.In turn, this so …-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure …

Persistent link: https://www.econbiz.de/10003727640

Nonparametric prediction of stock returns guided by prior knowledge

Scholz, Michael; Nielsen, Jens Perch; Sperlich, Stefan - 2012

Persistent link: https://www.econbiz.de/10009666508

The US stock market leads the federal funds rate and treasury bond yields

Guo, Kun; Zhou, Wei-Xing; Cheng, Si-Wei; Sornette, Didier - 2011

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be...

Persistent link: https://www.econbiz.de/10009009600

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