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An Empirical Comparison of Forward-Rate and Spot-Rate Models for Valuing Interest-Rate Options

Wolfgang Bühler, Marliese Uhrig-Homburg, Ulrich Walter, Thomas Weber
1999 Journal of Finance  
The second model has a linear proportional volatility-that is, the proportional volatility depends solely on time-to-maturity of forward rates. We also test two forward-rate models with two factors.  ...  This implies that this study is not a test of an option market's efficiency. Second, we estimate all parameters, including the volatility, from time series.  ...  Therefore, "local tests" consider only small deviations from observed prices of derivatives.  ... 
doi:10.1111/0022-1082.00104 fatcat:u2vrhqwlvnf2bi5e43goy6voxi

Local parametric analysis of hedging in discrete time

Peter Bossaerts, Pierre Hillion
1997 Journal of Econometrics  
Plots of the locally estimated volatility parameter against moneyness and maturity reveal the biases of the Black-Scholes model when hedging in discrete time.  ...  It does so by comparing the performance of Black-Scholes hedge ratios against those obtained from a novel estimation procedure, namely local parametric estimation.  ...  investigated. 19 ( Table 3 about here) 4 Patterns In The Locally Estimated Volatility Parameter Local parametric estimation is based on locally tting a parametric model using nonlinear least squares  ... 
doi:10.1016/s0304-4076(97)00046-8 fatcat:bljbxzz3iveu7ohyymaqiqcmmi

Scaling the volatility of GDP growth rates

D Canning, L.A.N Amaral, Y Lee, M Meyer, H.E Stanley
1998 Economics Letters  
The distribution of shocks to GDP growth rates is found to be exponential rather than normal. Their standard deviation b scales with GDP where b 5 2 0.1560.03.  ...  These macroeconomic results place restrictions on the microeconomic structure of interactions between agents.  ...  Instead, it appears linear in the absolute value of the residual.  ... 
doi:10.1016/s0165-1765(98)00121-9 fatcat:js75dvn3jfdehafu6pv5ywq4g4

The temporal dimension of risk

Javier Estrada
2000 Quarterly Review of Economics and Finance  
If returns are stationary, then the risk of an asset in any time frequency can be estimated from the risk of the asset in any other time frequency through a simple linear rescaling.  ...  The underestimation of total risk ranges between .25% and 2.18% a month, and averages almost 1% a month.  ...  ; that is, the risk of a security in any time frequency can be estimated from the risk of the security in any other time frequency through a simple linear rescaling.  ... 
doi:10.1016/s1062-9769(99)00056-3 fatcat:xwmxqxqimvawvkvv4tlfze5ete

Modeling and estimation on long memory stochastic volatility for index prices of FTSE Bursa Malaysia KLCI

Kho Chia Chen, Arifah Bahar, Chee-Ming Ting, Haliza Abd Rahman
2017 Malaysian Journal of Fundamental and Applied Sciences  
The least square estimator (LSE) and quadratic generalised variations (QGV) methods were used to estimate the drift and diffusion coefficient of the volatility process respectively.  ...  Procedures for constructing the LMSV model and the estimation methods were applied to the real daily index prices of FTSE Bursa Malaysia KLCI over a period of 20 years.  ...  ACKNOWLEDGEMENT I would like to express my gratitude to the Ministry of High Education (MOHE), STEM Grant with vote no. A.  ... 
doi:10.11113/mjfas.v13n4-1.875 fatcat:avfk4uhoxbb6lcam6toj63yyn4

Nonlinear time-series analysis of stock volatilities

C. Q. Cao, R. S. Tsay
1992 Journal of applied econometrics  
Based on mean squared error and average absolute deviation, the comparisons show that (a) the TAR models consistently outperform the linear ARMA models in multi-step ahead forecasts for large stocks, (  ...  The absolute value of the mean-corrected excess return is used in this paper to measure the volatility of stock returns.  ...  The estimated volatility (or standard deviation) of a security return IS widely used as a simple risk measure in many asset pricing models.  ... 
doi:10.1002/jae.3950070512 fatcat:hjzlfseakbao3iotnpedj24akq

Modelling the absolute returns of different stock indices: exploring the forecastability of an alternative measure of risk

Clive W. J. Granger, Chor-Yiu Sin
2000 Journal of Forecasting  
Conventional measures of the risk of a financial asset make use of the unobserved (conditional) variance or standard deviation of its return.  ...  ) variance or standard deviation of its return.  ...  The expectiles are modelled as a linear function of the lags of the absolute return.  ... 
doi:10.1002/1099-131x(200007)19:4<277::aid-for774>3.0.co;2-5 fatcat:mmuubzpfzbfjpalq5pnsxvycdy

No such thing as a perfect hammer: comparing different objective function specifications for optimal control

D. Blueschke, I. Savin
2016 Central European Journal of Operations Research  
We test four alternative designs of the objective function: a least median of squares based approach, absolute deviations, cubic and quartic objective functions.  ...  Linear-quadratic (LQ) optimization is a fairly standard technique in the optimal control framework.  ...  The least median of squares (LMS) estimator (Rousseeuw 1984 ) is among the best known robust estimators for linear problems.  ... 
doi:10.1007/s10100-016-0446-7 pmid:32025199 pmcid:PMC6979702 fatcat:ugieotnfubc2jcin5tndvrzzui

Least Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the Environment

Fatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol Messadi
2017 American Journal of Applied Sciences  
Least Absolute Deviation regression diagnostics offers alternative dicapproaches whose main feature is the robustness.  ...  The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied.  ...  Author's Contributions Fatiha Mebarki: Good Developed methods of least absolut deviation and least squares, Developed deference's Softwares (Matlab, Minitab, Tanagra, genetic Algorithm)and participated  ... 
doi:10.3844/ajassp.2017.592.606 fatcat:ewc2rgoexjfojgwckipqepaisy

Volume 23 Title Page

2015 Global Ecology and Biogeography  
Time-adjusted standard deviation as a measure of volatility resembles with the standard deviation without time-adjustment.  ...  Though standard deviation is generally used as a measure of volatility,it fails in circumstances of time-varying scedasticity.  ...  The study collates large changes in volatility and the global and local events during the period of increased volatility.  ... 
doi:10.1111/geb.12283 fatcat:24hp2h6o7nh5jjwkxa62jyha7e

Amending the heston stochastic volatility model to forecast local motor vehicle crash rates: A case study of Washington, D.C

Darren Shannon, Grigorios Fountas
2022 Transportation Research Interdisciplinary Perspectives  
Specifically, we introduce a stochastic volatility model that aims to capture the nuances associated with crash rates in Washington, DC.  ...  Provided that the traffic volume of urban networks is largely defined by typical work and school commute patterns, crash rates can be determined with a reasonable degree of accuracy.  ...  Nevertheless, our results demonstrate the utility of the Heston stochastic volatility model in providing reasonable estimations for the evolution of crash rates, even in localities affected by frequent  ... 
doi:10.1016/j.trip.2022.100576 fatcat:mzdwmhlpizhvvj5lov7is2uyva

Calibration of a path-dependent volatility model: Empirical tests

Paolo Foschi, Andrea Pascucci
2009 Computational Statistics & Data Analysis  
For this reason it seems that the HR model does not need to be frequently recalibrated, which is a known deficiency of local volatility models.  ...  In this approach we estimate the volatility function both in a parametric and a semi-parametric framework.  ... 
doi:10.1016/j.csda.2008.10.042 fatcat:m4tx4xd7nvehpdbtddrzr3ataa

Dynamic Integration of Time- and State-domain Methods for Volatility Estimation [article]

Jianqing Fan, Yingying Fan, Jiancheng Jiang
2005 arXiv   pre-print
The estimators from both domains are optimally combined based on a data driven weighting strategy, which provides a more efficient estimator of volatility.  ...  By comparing the efficiency of the estimators, it is demonstrated that the proposed integrated estimator uniformly dominates the two other estimators.  ...  Acknowledgements The work was partially supported by a grant from the Research Grants Council of the Hong Kong SAR (Project No.  ... 
arXiv:math/0506029v1 fatcat:rh7p3rflszckrhwzq3int4byne

Dynamic Integration of Time- and State-Domain Methods for Volatility Estimation

Jianqing Fan, Yingying Fan, Jiancheng Jiang
2007 Journal of the American Statistical Association  
The estimators from both domains are optimally combined based on a data driven weighting strategy, which provides a more efficient estimator of volatility.  ...  By comparing the efficiency of the estimators, it is demonstrated that the proposed integrated estimator uniformly dominates the two other estimators.  ...  Acknowledgements The work was partially supported by a grant from the Research Grants Council of the Hong Kong SAR (Project No.  ... 
doi:10.1198/016214507000000176 fatcat:dzrdzg7hcbbytlhwttide6ldwe

New frontiers for arch models

Robert Engle
2002 Journal of applied econometrics  
The volatility of volatility is defined, estimated and compared with option implied volatilities.  ...  Two further frontiers are examined in more detail -application of ARCH models to the broad class of non-negative processes, and use of Least Squares Monte Carlo to examine non-linear properties of any  ...  If in addition where s is a known function, then weighted least squares will be the best linear unbiased estimator of this model.  ... 
doi:10.1002/jae.683 fatcat:gcyee7nsxndcnmzsz6lehz6x7y
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