Modelling the Implied Probability of Stock Market Declines

Glatzer, Ernst; Scheicher, Martin

doi:10.2139/ssrn.300199

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…Glatzer and Scheicher (2002) derived risk-neutral moments of the German DAX through a smile-fitting method and a mixture of lognormals. The higher moments differed somewhat in magnitude while being highly correlated in the two 13 The ERM was a commitment on the part of members of the European Monetary Systemmost members of the European Economic Community-to maintain relatively fixed currency exchange rates.…”

Section: Option-implied Risk-neutral Distributions and Risk Aversionmentioning

confidence: 99%

Option-Implied Risk-Neutral Distributions and Risk Aversion

Jackwerth

2004

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Section: Option-implied Risk-neutral Distributions and Risk Aversionmentioning

confidence: 99%

Option-Implied Risk-Neutral Distributions and Risk Aversion

Jackwerth

2004

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“…The studies with the greatest affinity with our approach relate the volatility of share price indices, or currencies, to a number of their presumed fundamental economic influences. The studies include the investigations by Schwert (1989), Morelli (2002), Glatzer and Scheicher (2003) and Kim and Kim (2003). Schwert explains the expected stock price in terms of the dividend discount model.…”

Section: Introductionmentioning

confidence: 99%

Towards Decoding Currency Volatilities

Jüttner¹,

Leung²

2009

MFJ

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This study contributes, on the basis of economic theory, to an explanation of exchange rate volatilities for a large number of currencies. We relate daily changes in GARCH(1,1) volatilities of exchange rates to the volatility changes of several of their presumed fundamental economic determinants. The use of highfrequency data limits the choice of the explanatory economic variables that can be included. The first differences of GARCH(1,1) volatilities of share and bond price indices proxy for wealth uncertainty and the latter, in addition, for interest rate variability. Likewise, first differences of the gold price volatility, as an additional determinant, are related to exchange rate volatilities of two commodity currencies in the sample. The estimates produce coefficients with the expected signs and statistical significance. JEL classification: F31: G154: C22

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Determining and benchmarking risk neutral distributions implied from option prices

Celis

Liang

Lemmens

et al. 2015

Applied Mathematics and Computation

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a b s t r a c tRisk neutral probability density functions (RNDs) play a central role in assessing models for stock market behavior. However, it remains challenging to distill a realistic estimate for the RND from empirical data. In this work we introduce a novel method to infer a RND estimate from observed option prices. Our method efficiently yields a realistic rational function approximation to the RND, it is flexible w.r.t. the shape of the underlying distribution and robust in the presence of noise. To show this, we first investigate how well a method can actually retrieve a known distribution from noisy option prices. Then we consider real market data and show how our method can be used to derive a single continuously differentiable RND estimate from empirical call and put option price data.

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Modelling the Implied Probability of Stock Market Declines

Cited by 3 publications

References 27 publications

Option-Implied Risk-Neutral Distributions and Risk Aversion

Option-Implied Risk-Neutral Distributions and Risk Aversion

Towards Decoding Currency Volatilities

Determining and benchmarking risk neutral distributions implied from option prices

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