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Nonparametric Filtering of the Realised Spot Volatility: A Kernel-Based Approach · Study

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PreprintNonparametric Filtering of the Realised Spot Volatility: A Kernel-Based Approach

Dennis Kristensen2008

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Preprintgreen2008

Nonparametric Filtering of the Realised Spot Volatility: A Kernel-Based Approach

Dennis Kristensen

26 citations·0/0 files stored·SSRN Electronic Journal

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Statistical Methods and Inference

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References

1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options 1999Continuous Martingales and Brownian Motion 2003Modeling and Forecasting Realized Volatility 1987The Pricing of Options on Assets with Stochastic Volatilities 1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts 1980On estimating the expected return on the market 2002Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models 2001The Distribution of Realized Exchange Rate Volatility

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2011Volatility in Discrete and Continuous-Time Models: A Survey with New Evidence on Large and Small Jumps

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2009NONPARAMETRIC FILTERING OF THE REALIZED SPOT VOLATILITY: A KERNEL-BASED APPROACHarticle · 27 shared references 2009Stochastic Volatilityother · 18 shared references 2016Between data cleaning and inference: Pre-averaging and robust estimators of the efficient pricearticle · 17 shared references 2005Variation, Jumps, Market Frictions and High Frequency Data in Financial Econometricspreprint · 15 shared references 2002Parametric and Nonparametric Volatility Measurementpreprint · 15 shared references 2015ESTIMATION OF STOCHASTIC VOLATILITY MODELS BY NONPARAMETRIC FILTERINGarticle · 14 shared references

Details

Year2008

Typepreprint

Published2008-01-01

VenueSSRN Electronic Journal

ISSN-L1556-5068

Languageen

Citations26

Files0 public / 0

ShelfFinancial Risk and Volatility Modeling

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doi10.2139/ssrn.1089289

openalex_workW2124940758

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