Relevant bibliographies by topics / And Skewness

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'And Skewness'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "And Skewness"

1

Eling, Martin, Simone Farinelli, Damiano Rossello, and Luisa Tibiletti. "Skewness in hedge funds returns: classical skewness coefficients vs Azzalini's skewness parameter." International Journal of Managerial Finance 6, no. 4 (2010): 290–304. http://dx.doi.org/10.1108/17439131011074459.

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Zaremba, Adam, and Andrzej Nowak. "Skewness preference across countries." Business and Economic Horizons 11, no. 2 (2015): 115–30. http://dx.doi.org/10.15208/beh.2015.09.

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Roll, Richard, and Avanidhar Subrahmanyam. "Liquidity skewness." Journal of Banking & Finance 34, no. 10 (2010): 2562–71. http://dx.doi.org/10.1016/j.jbankfin.2010.04.012.

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Neuberger, Anthony. "Realized Skewness." Review of Financial Studies 25, no. 11 (2012): 3423–55. http://dx.doi.org/10.1093/rfs/hhs101.

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Oh, Sangmin S., and Jessica A. Wachter. "Cross-Sectional Skewness." Review of Asset Pricing Studies 12, no. 1 (2021): 155–98. http://dx.doi.org/10.1093/rapstu/raab023.

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Abstract What distribution best characterizes the time series and cross-section of individual stock returns? To answer this question, we estimate the degree of cross-sectional return skewness relative to a benchmark that nests many models considered in the literature. We find that cross-sectional skewness in monthly returns far exceeds what this benchmark model predicts. However, cross-sectional skewness in long-run returns in the data is substantially below what the model predicts. We show that fat-tailed idiosyncratic events appear to be necessary to explain skewness in the data. (JEL, G10,
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Harvey, Campbell R., and Akhtar Siddique. "Autoregressive Conditional Skewness." Journal of Financial and Quantitative Analysis 34, no. 4 (1999): 465. http://dx.doi.org/10.2307/2676230.

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Gunasingham, Brindha. "Expected Idiosyncratic Skewness." CFA Digest 40, no. 2 (2010): 8–9. http://dx.doi.org/10.2469/dig.v40.n2.28.

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Jeong, Giho, Jangkoo Kang, and Kyung Yoon Kwon. "Liquidity skewness premium." North American Journal of Economics and Finance 46 (November 2018): 130–50. http://dx.doi.org/10.1016/j.najef.2018.04.015.

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Kallersjo, Mari, James S. Farris, Arnold G. Kluge, and Carol Bult. "SKEWNESS AND PERMUTATION." Cladistics 8, no. 3 (1992): 275–87. http://dx.doi.org/10.1111/j.1096-0031.1992.tb00071.x.

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Jondeau, Eric, Qunzi Zhang, and Xiaoneng Zhu. "Average skewness matters." Journal of Financial Economics 134, no. 1 (2019): 29–47. http://dx.doi.org/10.1016/j.jfineco.2019.03.003.

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Dissertations / Theses on the topic "And Skewness"

1

Shum, Wai Yan. "Modelling skewness in financial data." Thesis, University of East Anglia, 2014. https://ueaeprints.uea.ac.uk/48762/.

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The first systematic analysis of the skew-normal distribution in a scalar case is done by Azzalini (1985). Unlike most of the skewed distributions, the skew-normal distribution allows continuity of the passage from the normal distribution to the skew-normal distribution and is mathematically tractable. The skew-normal distribution and its extensions have been applied in lots of financial applications. This thesis contributes to the recent development of the skew-normal distribution by, firstly, analyzing the the properties of annualization and time-scaling of the skew-normal distribution under
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Eriksson, Måns. "A simulation method for skewness correction." Thesis, Uppsala University, Department of Mathematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-120037.

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Kapadia, Nishad Ghysels Eric. "Skewness, idiosyncratic volatility and expected returns." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,1128.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2007.<br>Title from electronic title page (viewed Mar. 27, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Kenan-Flagler Business School Finance." Discipline: Business Administration; Department/School: Business School, Kenan-Flagler.
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Martinsson, Engshagen Jan. "Nothing is normal in nance! : On Tail Correlations and Robust Higher Order Moments in Normal Portfolio Frameworks." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102699.

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Abstract This thesis project is divided in two parts. The first part examines the possibility that correlation matrix estimates based on an outlier sample would contain information about extreme events. According to my findings, such methods do not perform better than simple shrinkage methods where robust shrinkage targets are used. The method tested is especially outperformed when it comes to the extreme events, where a shrinkage of the correlation matrix towards the identity matrix seems to give the best result. The second part is about valuation of skewness in marginal distributions and the
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Luo, Lin. "Modelling FX smile : from stochastic volatility to skewness." Thesis, Imperial College London, 2007. http://hdl.handle.net/10044/1/11313.

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This thesis is concerned with the design and analysis of a tractable model, which can capture the key features ofthe observed implied volatility smile surface in the foreign exchange (FX) market, and is flexible enough to be extended to price path-dependent exotic options. In the first part, we examine the dynamics ofthe exchange rate via the conditional distribution implied from option prices, in which the theory and various techniques for implied distribution are analyzed. We identify three sources of uncertainty that need to be modelled: the stochastic exchange rate process, the stochastic
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Gumbo, Victor. "Mean absolute deviation skewness model with transactions costs." Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-09052005-115438.

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Ovacikli, Kubilay. "Blind Enhancement of Harmonically Related Signals by Maximizing Skewness." Licentiate thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26461.

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Rolling element bearings are used in rotating machinery in various industry branches. Their health status must be monitored continuously in order to establish proper operational conditions in a production process. Numerous approaches, which can be investigated under the subject of ``Condition Based Maintenance", have been studied within mechanical engineering and signal processing to be able to detect and classify possible faults on rolling bearings.Periodic impulsive signals can emerge from defected bearings within rotating machinery. As the signal is distorted by an unknown transfer function
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Rubio, Francisco J. "Modelling of kurtosis and skewness : Bayesian inference and distribution theory." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/56471/.

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This thesis is concerned with the study of distributional and inferential aspects of some classes of flexible distributions used for modelling asymmetric data. In the last couple of decades, a great effort has been devoted to proposing new dis- tributions that can capture departures from normality. A popular method to obtain such distributions consists of adding parameters to a known, typically symmetric, distribution. In order to do so, several classes of parametric transformations have been employed. In Chapter 2, we analyse two families of such transformations that have recently been recom-
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Karehnke, Paul. "Portfolio choice and asset pricing with endogenous beliefs and skewness preference." Thesis, Paris 9, 2014. http://www.theses.fr/2014PA090050.

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Cette thèse étudie le choix de portefeuille et l'évaluation d'actifs avec des préférences qui vont au-Delà des préférences d'espérance d'utilité et de moyenne-Variance standard. La première partie de cette thèse porte sur un modèle de décision dans lequel le décideur forme des croyances endogènes compte tenu de son utilité d'anticipation et de sa déception à posteriori. Les implications du modèle en termes de choix de portefeuille et d'évaluation d'actifs sont dérivées et comparées aux implications du modèle d'espérance d'utilité standard. La deuxième partie de cette thèse porte sur des invest
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Crawford, Anna M. "Field observations of linear transition ripple migration and wave orbital velocity skewness." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/NQ54833.pdf.

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Books on the topic "And Skewness"

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Javaheri, Alireza. Inside volatility filtering: The secrets of skewness. John Wiley & Sons, Inc., 2015.

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Das, Shubhabrata. On a new measure of skewness for unimodal distributions. Indian Institute of Management, 2003.

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Chen, Joseph. Forecasting crashes: Trading volume, past returns and conditional skewness in stock prices. National Bureau of Economic Research, 2000.

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Mills, T. C. Modelling skewness and kurtosis in the London Stock Exchange FT-SE return distributions. University of Hull, Department of Economics, 1993.

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Deissler, Robert G. Numerical solution for the velocity-derivative skewness of a low-Reynolds-number decaying Navier-Stokes flow. National Aeronautics and Space Administration, 1990.

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Ben, Munk, and Lewis Research Center, eds. The reflection and transmission properties of a triple band dichroic surface: Final technical report. The Ohio State University, ElectroScience Laboratory, 1990.

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Center, Langley Research, ed. Static performance investigation of a skewed-throat multiaxis thrust-vectoring nozzle concept. National Aeronautics and Space Administration, Langley Research Center, 1994.

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Javaheri, Alireza. Inside Volatility Arbitrage: The Secrets of Skewness. Wiley & Sons, Incorporated, John, 2011.

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Javaheri, Alireza. Inside Volatility Arbitrage: The Secrets of Skewness. Wiley & Sons, Incorporated, John, 2007.

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Inside Volatility Arbitrage : The Secrets of Skewness. Wiley, 2005.

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Book chapters on the topic "And Skewness"

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Gooch, Jan W. "Skewness." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15378.

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Nahler, Gerhard. "skewness." In Dictionary of Pharmaceutical Medicine. Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_1298.

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Gooch, Jan W. "Skewness." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_10714.

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Chattamvelli, Rajan, and Ramalingam Shanmugam. "Skewness." In Descriptive Statistics for Scientists and Engineers. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-32330-0_4.

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Hippel, Paul von. "Skewness." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_525.

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Hippel, Paul von. "Skewness." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-69359-9_577.

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Gooch, Jan W. "Filling Skewness." In Encyclopedic Dictionary of Polymers. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_4916.

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Panneerselvam, R. "Measures of Skewness." In Business Statistics Using Excel. Routledge India, 2023. http://dx.doi.org/10.4324/9781032671703-7.

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Boyle, Conall. "Skewness and Re-Expression." In Mastering Statistics with your Microcomputer. Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-18211-4_10.

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Blaskowitz, Oliver J., Wolfgang K. Härdle, and Peter Schmidt. "Skewness and Kurtosis Trades." In Handbook of Computational and Numerical Methods in Finance. Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-0-8176-8180-7_1.

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Conference papers on the topic "And Skewness"

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Nishimura, Takeshi, and Yoshikuni Shindo. "Application for Ship Detection Using Skewness and Kurtosis." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641310.

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Zhang, Qiansheng, and Jinyun Li. "Intuitionistic Fuzzy Portfolio Decision Model Based on Possibilistic Skewness." In 2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2024. http://dx.doi.org/10.1109/icnc-fskd64080.2024.10702258.

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Lam, Weng Hoe, Saiful Hafizah Hj Jaaman, and Zaidi Isa. "Portfolio optimization with skewness and kurtosis." In PROCEEDINGS OF THE 20TH NATIONAL SYMPOSIUM ON MATHEMATICAL SCIENCES: Research in Mathematical Sciences: A Catalyst for Creativity and Innovation. AIP, 2013. http://dx.doi.org/10.1063/1.4801249.

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Di Pierro, M., and J. Mosevich. "Portfolio rankings with skewness and kurtosis." In COMPUTATIONAL FINANCE 2008. WIT Press, 2008. http://dx.doi.org/10.2495/cf080111.

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Chen, Guohua, and Xiaolian Liao. "Credibility Mean-Variance-skewness Portfolio Selection Model." In 2010 2nd International Workshop on Database Technology and Applications (DBTA). IEEE, 2010. http://dx.doi.org/10.1109/dbta.2010.5659059.

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Lai, Kin Keung, Lean Yu, and Shouyang Wang. "Mean-Variance-Skewness-Kurtosis-based Portfolio Optimization." In 2006 International Multi-Symposiums on Computer and Computational Sciences (IMSCCS). IEEE, 2006. http://dx.doi.org/10.1109/imsccs.2006.239.

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Sintunata, Vicky, and Terumasa Aoki. "3D object retrieval system using skewness database." In 2016 International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2016. http://dx.doi.org/10.1109/codit.2016.7593547.

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Huttunen, Heikki J. "Skewness correction in automatic license plate recognition." In Electronic Imaging 2005, edited by Edward R. Dougherty, Jaakko T. Astola, and Karen O. Egiazarian. SPIE, 2005. http://dx.doi.org/10.1117/12.586170.

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Podgornik, B., and M. Sedlacˇek. "Surface Texturing Effect, Characterization and Optimization for Boundary and Mixed Lubrication." In ASME/STLE 2011 International Joint Tribology Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ijtc2011-61184.

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Under boundary and mixed lubrication surface roughness and topography have significant influence on the tribological behaviour of contact surfaces, where even a small change in surface topography can lead to a considerable change in tribological behaviour. In recent years an effort for better controlling friction and wear has been focused also on the surface topography modification, especially on surface texturing. The aim of the present research work was to investigate the possibility of using roughness parameters kurtosis and skewness as design parameters for optimizing texturing pattern in
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Andrews, Larry, and Melissa Beason. "Collimated Gaussian Beam Size: Near-Field and Far-Field Approximations." In Propagation Through and Characterization of Atmospheric and Oceanic Phenomena. Optica Publishing Group, 2022. http://dx.doi.org/10.1364/pcaop.2022.ptu4d.4.

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Spot radius is dependent upon whether the receiver is in the near or far field which becomes significant when considering beam skewness. We compare methods to calculate beam radii, impact on skewness, and suggest an empirical method to transition between regimes.
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Reports on the topic "And Skewness"

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Oh, Simon, and Jessica Wachter. Cross-sectional Skewness. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w25113.

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Bauer, Michael, and Mikhail Chernov. Interest Rate Skewness and Biased Beliefs. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28954.

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Dew-Becker, Ian. Real-Time Forward-Looking Skewness over the Business Cycle. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30478.

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Bekaert, Geert, and Alexander Popov. On the Link Between the Volatility and Skewness of Growth. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w18556.

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Kott, Phillip S. Better Coverage Intervals for Estimators from a Complex Sample Survey. RTI Press, 2020. http://dx.doi.org/10.3768/rtipress.2020.mr.0041.2002.

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Coverage intervals for a parameter estimate computed using complex survey data are often constructed by assuming the parameter estimate has an asymptotically normal distribution and the measure of the estimator’s variance is roughly chi-squared. The size of the sample and the nature of the parameter being estimated render this conventional “Wald” methodology dubious in many applications. I developed a revised method of coverage-interval construction that “speeds up the asymptotics” by incorporating an estimated measure of skewness. I discuss how skewness-adjusted intervals can be computed for
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Wilson, D., Matthew Kamrath, Caitlin Haedrich, Daniel Breton, and Carl Hart. Urban noise distributions and the influence of geometric spreading on skewness. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42483.

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Statistical distributions of urban noise levels are influenced by many complex phenomena, including spatial and temporal variations in the source level, multisource mixtures, propagation losses, and random fading from multipath reflections. This article provides a broad perspective on the varying impacts of these phenomena. Distributions incorporating random fading and averaging (e.g., gamma and noncentral Erlang) tend to be negatively skewed on logarithmic (decibel) axes but can be positively skewed if the fading process is strongly modulated by source power variations (e.g., compound gamma).
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Chen, Joseph, Harrison Hong, and Jeremy Stein. Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices. National Bureau of Economic Research, 2000. http://dx.doi.org/10.3386/w7687.

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Smith, Donald L., Denise Neudecker, and Roberto Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, 2018. http://dx.doi.org/10.61092/iaea.yxma-3y50.

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In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Concept
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Smith, Donald L., Denise Neudecker, and Roberto Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, 2020. http://dx.doi.org/10.61092/iaea.nqsh-f02d.

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In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Concept
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Smith, D. L., D. Neudecker, and R. Capote Noy. Investigation of the Effects of Probability Density Function Kurtosis on Evaluated Data Results. IAEA Nuclear Data Section, 2020. http://dx.doi.org/10.61092/iaea.3ar5-xmp8.

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In two previous investigations that are documented in this IAEA report series, we examined the effects of non-Gaussian, non-symmetric probability density functions (PDFs) on the outcomes of data evaluations. Most of this earlier work involved considering just two independent input data values and their respective uncertainties. They were used to generate one evaluated data point. The input data are referred to, respectively, as the mean value and standard deviation pair (y0,s0) for a prior PDF p0(y) and a second mean value and standard deviation pair (ye,se) for a likelihood PDF pe(y). Concept
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