Generalized parameter functions for option pricing.
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Spiros H. Martzoukos | Chris Charalambous | C. Charalambous | P. Andreou | S. Martzoukos | Panayiotis C. Andreou
[1] Kris Jacobs,et al. The Shape and Term Structure of the Index Option Smirk: Why Multifactor Stochastic Volatility Models Work so Well , 2009, Manag. Sci..
[2] E. Ghysels,et al. A study towards a unified approach to the joint estimation of objective and risk neutral measures for the purpose of options valuation , 2000 .
[3] R. C. Merton,et al. Theory of Rational Option Pricing , 2015, World Scientific Reference on Contingent Claims Analysis in Corporate Finance.
[4] Berkowitz Jeremy. On Justifications for the ad hoc Black-Scholes Method of Option Pricing , 2009 .
[5] F. Black,et al. The Pricing of Options and Corporate Liabilities , 1973, Journal of Political Economy.
[6] Peter Christoffersen,et al. Série Scientifique Scientific Series the Importance of the Loss Function in Option Valuation the Importance of the Loss Function in Option Valuation , 2022 .
[7] Min Qi,et al. Pricing and hedging derivative securities with neural networks: Bayesian regularization, early stopping, and bagging , 2001, IEEE Trans. Neural Networks.
[8] J. Jackwerth. Recovering Risk Aversion from Option Prices and Realized Returns , 1998 .
[9] Yoshua Bengio,et al. Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint , 2000 .
[10] M. Rubinstein.. Implied Binomial Trees , 1994 .
[11] Nicolas P. B. Bollen,et al. Does Net Buying Pressure Affect the Shape of Implied Volatility Functions? , 2002 .
[12] Christine Ann Brown,et al. Skewness and Kurtosis Implied by Option Prices: A Correction , 2002 .
[13] Emmanuel Jurczenko,et al. A note on skewness and kurtosis adjusted option pricing models under the Martingale restriction* , 2004 .
[14] J.W. Bandler,et al. Neuromodeling of microwave circuits exploiting space mapping technology , 1999, 1999 IEEE MTT-S International Microwave Symposium Digest (Cat. No.99CH36282).
[15] R. Sundaram,et al. Of Smiles and Smirks: A Term Structure Perspective , 1998, Journal of Financial and Quantitative Analysis.
[16] Stewart D. Hodges,et al. The dynamics of the volatility skew: A Kalman filter approach , 2009 .
[17] David S. Bates. Post-'87 crash fears in the S&P 500 futures option market , 2000 .
[18] M. Rockinger,et al. Gram–Charlier densities , 2001 .
[19] J. Nazuno. Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .
[20] David S. Bates. Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Thephlx Deutschemark Options , 1993 .
[21] The jump component of S&P 500 volatility and the VIX index , 2009 .
[22] R. Whaley. Valuation of American call options on dividend-paying stocks: Empirical tests , 1982 .
[23] David G. Stork,et al. Pattern Classification , 1973 .
[24] Yacine Ait-Sahalia,et al. Nonparametric Option Pricing Under Shape Restrictions , 2002 .
[25] J. Hull,et al. A Methodology for Assessing Model Risk and its Application to the Implied Volatility Function Model , 2002, Journal of Financial and Quantitative Analysis.
[26] David S. Bates. Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options , 1998 .
[27] Georg Dorffner,et al. Risk-neutral density extraction from option prices: improved pricing with mixture density networks , 2001, IEEE Trans. Neural Networks.
[28] Bertrand B. Maillet,et al. The approximate option pricing model: performances and dynamic properties , 2001 .
[29] Enrique Sentana,et al. Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation , 2005 .
[30] Gurdip Bakshi,et al. Empirical Performance of Alternative Option Pricing Models , 1997 .
[31] Tao Wu,et al. Cross-sectional tests of deterministic volatility functions , 2002 .
[32] Jun Pan. The jump-risk premia implicit in options: evidence from an integrated time-series study $ , 2002 .
[33] B. Dumas,et al. Implied volatility functions: empirical tests , 1996, IEEE Conference on Computational Intelligence for Financial Engineering & Economics.
[34] Panayiotis Ch. Andreou,et al. Pricing and trading European options by combining artificial neural networks and parametric models with implied parameters , 2008, Eur. J. Oper. Res..
[35] Bjørn Eraker. Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices , 2004 .
[36] Mohammad Bagher Menhaj,et al. Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.
[37] C. Corrado. The hidden martingale restriction in Gram-Charlier option prices , 2007 .
[38] Rama Cont,et al. Dynamics of implied volatility surfaces , 2002 .
[39] John W. Bandler,et al. Space mapping technique for electromagnetic optimization , 1994 .
[40] Martin T. Hagan,et al. Neural network design , 1995 .
[41] Fang Wang,et al. Knowledge based neural models for microwave design , 1997, 1997 IEEE MTT-S International Microwave Symposium Digest.
[42] Ulrich Anders,et al. Improving the pricing of options: a neural network approach , 1998 .
[43] K. C. Gupta,et al. EM-ANN models for microstrip vias and interconnects in dataset circuits , 1996 .
[44] Tie Su,et al. Implied Volatility Skews and Stock Index Skewness and Kurtosis Implied by S&P 500 Index Option Prices , 1997 .
[45] Bertrand B. Maillet,et al. Multi-Moment Approximate Option Pricing Models: A General Comparison (Part 1) , 2002 .
[46] Martin Scheicher,et al. GARCH vs. stochastic volatility: Option pricing and risk management , 2002 .
[47] Eirini Konstantinidi,et al. Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices , 2008 .
[48] David S. Bates. The Crash of ʼ87: Was It Expected? The Evidence from Options Markets , 1991 .
[49] Jinjuan Ren,et al. Effects of the volatility smile on exchange settlement practices: The Hong Kong case , 2009 .
[50] George Cybenko,et al. Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..
[51] Luca Benzoni,et al. An Empirical Investigation of Continuous-Time Equity Return Models , 2001 .
[52] Yacine Aït-Sahalia,et al. Do option markets correctly price the probabilities of movement of the underlying asset , 2001 .
[53] Paul Lajbcygier,et al. Improving option pricing with the product constrained hybrid neural network , 2004, IEEE Transactions on Neural Networks.
[54] Jun Pan. The jump-risk premia implicit in options: evidence from an integrated time-series study , 2001 .
[55] M. Rockinger,et al. Reading the Smile: The Message Conveyed by Methods Which Infer Risk Neutral Densities , 1997 .
[56] Andrew W. Lo,et al. Nonparametric estimation of state-price densities implicit in financial asset prices , 1995, Proceedings of 1995 Conference on Computational Intelligence for Financial Engineering (CIFEr).
[57] Tie Su,et al. SKEWNESS AND KURTOSIS IN S&P 500 INDEX RETURNS IMPLIED BY OPTION PRICES , 1996 .
[58] QiMin,et al. Pricing and hedging derivative securities with neural networks , 2001 .
[59] S. Crépey. Delta-hedging vega risk? , 2004 .
[60] Liuren Wu,et al. Accounting for Biases in Black-Scholes , 2004 .
[61] Jeff Fleming,et al. Implied volatility functions: empirical tests , 1996, IEEE/IAFE 1996 Conference on Computational Intelligence for Financial Engineering (CIFEr).
[62] David G. Stork,et al. Pattern classification, 2nd Edition , 2000 .
[63] M. Rubinstein.. Nonparametric tests of alternative option pricing models using all reported trades and quotes on the , 1985 .