SKEW AND IMPLIED LEVERAGE EFFECT: SMILE DYNAMICS REVISITED

We revisit the "Smile Dynamics" problem, which consists in relating the implied leverage (i.e. the correlation of the at-the-money volatility with the returns of the underlying) and the skew of the option smile. The ratio between these two quantities, called "Skew-Stickiness Ratio" (SSR) by Bergomi (2009), saturates to the value 2 for linear models in the limit of small maturities, and converges to 1 for long maturities. We show that for more general, non-linear models (such as the asymmetric GARCH model), Bergomi's result must be modified, and can be larger than 2 for small maturities. The discrepancy comes from the fact that the volatility skew is, in general, different from the skewness of the underlying. We compare our theory with empirical results, using data both from option markets and from the underlying price series, for the S&P 500 and the DAX. We find, among other things, that although both the implied leverage and the skew appear to be too strong on option markets, their ratio is well explained by the theory. We observe that the SSR indeed becomes larger than 2 for small maturities, signalling the presence of non-linear effects.

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Modeling S&P Bombay Stock Exchange BANKEX Index Volatility Patterns Using GARCH Model

Emerging Research on Monetary Policy, Banking, and Financial Markets - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-5225-9269-3.ch013 ◽

2019 ◽

pp. 259-268

Keyword(s):

Time Series ◽

Banking Sector ◽

Stock Exchange ◽

Time Lag ◽

Garch Model ◽

Recent Past ◽

Volatility Clustering ◽

Asymmetric Volatility ◽

Empirical Results ◽

Asymmetric Garch

The main objective of this chapter is to estimate volatility patterns in the case of S&P Bombay Stock Exchange (BSE) BANKEX index in India. In recent past, the Indian banking sector was one of the fastest-growing industries and all major banks have been included in S&P BANKEX index as index benchmark constituent companies. The financial econometric framework is based on asymmetric GARCH (1, 1) model which is performed in order to capture asymmetric volatility clustering and leptokurtosis. Data time lag is considered from the first transaction day of January 2002 to last transaction day of June 2014. The empirical results revealed the existence of volatility shocks in the selected time series and also volatility clustering. The volatility impact has generated highly positive clockwise and impacted actual stocks. Moreover, the empirical findings reveal that the BANKEX index grown over 17 times in 12 years and volatility returns have been found present in listed stocks.

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NeAT: a Nonlinear Analysis Toolbox for Neuroimaging

Neuroinformatics ◽

10.1007/s12021-020-09456-w ◽

2020 ◽

Vol 18 (4) ◽

pp. 517-530

Author(s):

Adrià Casamitjana ◽

◽

Verónica Vilaplana ◽

Santi Puch ◽

Asier Aduriz ◽

...

Keyword(s):

Linear Models ◽

Brain Aging ◽

Nonlinear Effects ◽

Brain Morphology ◽

Model Estimation ◽

Wide Range ◽

Non Linear ◽

Linear Effects ◽

Interaction With Age ◽

User Friendly

Abstract NeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. NeAT provides a wide range of statistical and machine learning non-linear methods for model estimation, several metrics based on curve fitting and complexity for model inference and a graphical user interface (GUI) for visualization of results. We illustrate its usefulness on two study cases where non-linear effects have been previously established. Firstly, we study the nonlinear effects of Alzheimer’s disease on brain morphology (volume and cortical thickness). Secondly, we analyze the effect of the apolipoprotein APOE-ε4 genotype on brain aging and its interaction with age. NeAT is fully documented and publicly distributed at https://imatge-upc.github.io/neat-tool/.

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Design Equations for Bod Removal in Facultative Ponds

Water Science & Technology ◽

10.2166/wst.1987.0145 ◽

1987 ◽

Vol 19 (12) ◽

pp. 187-193 ◽

Cited By ~ 6

Author(s):

E. Joe Middlebrooks

Keyword(s):

Environmental Protection Agency ◽

Linear Models ◽

Plug Flow ◽

Empirical Models ◽

The Us ◽

Non Linear ◽

The Usa ◽

Using Data ◽

Removal Model ◽

Best Fit

Facultative pond performance data collected for the US Environmental Protection Agency (USEPA) at four locations throughout the USA and data collected by others were used to evaluate the most frequently used design equations and to develop non-linear design equations. Empirical models were evaluated as well as the classical plug flow and complete mix models. The first order plug flow model gave the best fit of all the rational models. The empirical non-linear models did not fit the data, nor did the other empirical models with the exception being the areal loading and removal model. Attempts to verify the models developed with the USEPA data using data collected by others were not successful with the exception of the areal loading and removal model.

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Revisiting the role of dissimilarity of host communities in driving dissimilarity of ectoparasite assemblages: non-linear vs linear approach

Parasitology ◽

10.1017/s003118201700066x ◽

2017 ◽

Vol 144 (10) ◽

pp. 1365-1374 ◽

Cited By ~ 3

Author(s):

LUTHER VAN DER MESCHT ◽

IRINA S. KHOKHLOVA ◽

ELIZABETH M. WARBURTON ◽

BORIS R. KRASNOV

Keyword(s):

Linear Models ◽

Species Turnover ◽

Geographic Distance ◽

Parasite Community ◽

Model Fit ◽

Linear Approach ◽

Non Linear ◽

Using Data ◽

Better Than

SUMMARYWe revisited the role of dissimilarity of host assemblages in shaping dissimilarity of flea assemblages using a non-linear approach. Generalized dissimilarity models (GDMs) were applied using data from regional surveys of fleas parasitic on small mammals in four biogeographical realms. We compared (1) model fit, (2) the relative effects of host compositional and phylogenetic turnover and geographic distance on flea compositional and phylogenetic turnover, and (3) the rate of flea turnover along gradients of host turnover and geographic distance with those from earlier application of a linear approach. GDMs outperformed linear models in explaining variation in flea species turnover and host dissimilarity was the best predictor of flea dissimilarity, irrespective of scale. The shape of the relationships between flea compositional turnovers along host compositional turnover was similar in all realms, whereas turnover along geographic distance differed among realms. In contrast, the rate of flea phylogenetic turnover along gradients of host phylogenetic turnover differed among realms, whereas flea phylogenetic turnover did not depend on geographic distance in any realm. We demonstrated that a non-linear approach (a) explained spatial variation in parasite community composition better than and (b) revealed patterns that were obscured by earlier linear analyses.

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Modelling Volatility Persistence and Asymmetry with Structural Break: Evidence from the Nigerian Stock Market

Journal of Economics and Behavioral Studies ◽

10.22610/jebs.v8i6(j).1489 ◽

2017 ◽

Vol 8 (6(J)) ◽

pp. 153-160

Author(s):

Aluko Olufemi Adewale ◽

Adeyeye Patrick Olufemi ◽

Migiro Stephen Oseko

Keyword(s):

Stock Market ◽

Structural Break ◽

Garch Model ◽

Market Volatility ◽

Leverage Effect ◽

Stock Market Volatility ◽

Sample Period ◽

Asymmetric Garch ◽

High Degree ◽

Break Period

Abstract: This study contributes to existing literature on the Nigerian stock market by modelling the persistence and asymmetry of stock market volatility taking into account structural break. It utilises returns generated from data on monthly all-share index from January 1985 to December 2014. After identifying structural break in the return series, the study splits the sample period into pre-break period (January 1985 â€“ November 2008) and post-break period (January 2009 â€“ December 2014). Using the symmetric GARCH model, the study shows that the sum of ARCH and GARCH coefficients is higher in the pre-break period compared to the post-break period, thus indicating that persistence of shock to volatility is higher before structural break in the market. The asymmetric GARCH model provides no evidence of asymmetry as well as leverage effect with or without accounting for structural break in the Nigerian stock market. This study concludes that the Nigerian stock market is characterised by inefficiency, high degree of uncertainty and non-asymmetric volatility.Keywords: Persistence, asymmetry, stock market volatility, structural break

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G Optimal Design in Non linear Models to Increase Silicon Oxide Purity Levels and Electrical Conductivity

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset21841110 ◽

2018 ◽

pp. 150-155

Author(s):

Muklas Rivai

Keyword(s):

Electrical Conductivity ◽

Optimal Design ◽

Linear Models ◽

Silicon Oxide ◽

Information Matrix ◽

Relevant Information ◽

Non Linear

Optimal design is a design which required in determining the points of variable factors that would be attempted to optimize the relevant information so that fulfilled the desired criteria. The optimal fulfillment criteria based on the information matrix of the selected model.

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