in Estudios de economía
The quantum harmonic oscillator expected shortfall model
Abstract:
This paper presents a new Expected Shortfall (ES) model based on the Quantum Harmonic Oscillator (QHO). It is used to estimate market risk in banks and other financial institutions according to Basel III standard. Predictions of the model agree with the empirical data which displays deviations from normality. Using backtesting, it is shown that the model can be reliably used to assess market risk.
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Abstract:
Reference
Stock market volatility and learning
K. Adam
The Journal of finance, 71: 33-82, 2016
Reference
Backtesting Expected Shortfall
C. Acerbi
Backtesting Expected Shortfall: 2014
Reference
Modeling stock return distributions with a quantum harmonic oscillator
K. Ahn
Europhysics Letters, 120: 2017
Reference
A nonparametric approach to calculating VaR
R. Alemany
Insurance: Mathematics and Economics, 52: 255-262, 2013
Reference
Stock price prediction using geometric Brownian motion
Journal of Physics: Conference Series, 974: 2018
Reference
Genetic algorithms and Darwinian approaches in financial applications: A survey
R. Aguilar-Rivera
Expert Systems with Applications, 42: 7684-7697, 2015
Reference
On the number of bootstrap repetitions for bootstrap standard errors, confidence intervals and tests
D. Andrews
On the number of bootstrap repetitions for bootstrap standard errors, confidence intervals and tests: 1997
Reference
Wave function for stock market returns
A. Ataullah
Physica A, Statistical Mechanics and its Applications, 388: 455-461, 2009
Reference
Surveying stock market forecasting techniques part II: Soft computing methods
G.S. Atsalakis
Expert Systems with Applications, 36: 5932-5941, 2009
Reference
Simulation of nonlinear interest rates in quantum finance: libor market model
P. Baaquie
Physica A, 391: 1287-1308, 2012
Reference
Théorie de la spéculation
L. Bachelier
Théorie de la spéculation: 1900
Reference
A quantum statistical approach to simplified stock markets
F. Bagarello
Physica A, 388: 4397-4406, 2009
Reference
Mean Reversion across National Stock Markets and Parametric Contrarian Investment Strategies
R. Balvers
Journal of Finance, 55: 745-772, 2000
Reference
Non-parametric VaR techniques. Myths and realities
G. Barone-Adesi
Economic Notes, 30: 167-181, 2001
Reference
Consultative Document: Fundamental Review of the Trading Book: A Revised Market Risk Framework
Bank for International Settlements
Consultative Document: Fundamental Review of the Trading Book: A Revised Market Risk Framework: 2013
Reference
Dynamic value-at-risk models and the peaks-over-threshold method for market risk measurement: an empirical investigation during a financial crisis
M. Bee
Journal of Risk Model Validation, 2: 3-45, 2012
Reference
Testing density forecasts, with applications to risk management
J. Berkowitz
Journal of Business & Economic Statistics, 19: 465-474, 2001
Reference
A comparation of Stable and Student Distributions as Statistical Models for Stock Prices: Reply
R. C. Blattnerg
Journal of Business, 36: 420-429, 1977
Reference
Backtesting value-at-risk: a comparison between filtered bootstrap and historical simulation
D. Brandolini
Journal of Risk Model Validation, 6: 3-16, 2012
Reference
Computational intelligence and financial markets: A survey and future directions
R.C. Cavalcante
Expert Systems with Applications, 55: 194-211, 2016
Reference
Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes
B. Chen
Journal of Forecasting, 30: 51-71, 2011
Reference
Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies
E. Chong
Expert Systems with Applications, 83: 187-205, 2017
Reference
Elements of Financial Risk Management
P.F. Christoffersen
Elements of Financial Risk Management: 2011
Reference
Quantum Mechanics
C. Cohen-Tannoudji
Quantum Mechanics: 1992
Reference
A quantum model of option pricing: When Black–Scholes meets Schrödinger and its semi-classical limit
M. Contreras
5447-5459
Reference
A finite-dimensional quantum model for the stock market
L. Cotfas
Physica A, 392: 371-380, 2013
Reference
Heterogeneous agent models in finance
R. Dieci
Handbook of computational economics, 4: 257-328, 2018
Reference
Expected shortfall model based on a neural network
S. Doncic
Journal of Risk Model Validation, 16: 2022
Reference
Probability distribution of returns in the Heston model with stochastic volatility
A.A. Dragulescu
Quantitative. Finance, 2: 443-453, 2002
Reference
Mandelbrot and the stable Peretian hypothesis
E.F. Fama
journal of business, 36: 420-429, 1963
Reference
Sensitivity analysis of VaR and Expected Shortfall for portfolios under netting agreements
J.D. Fermanian
Journal of Banking and Finance, 29: 927-958, 2005
Reference
Deep learning with long short-term memory networks for financial market predictions
T. Fischer
European Journal of Operational Research, 270: 654-669, 2018
Reference
New Distribution of Stock Market Return by Schrodinger Equation
L. Haijun
New Distribution of Stock Market Return by Schrodinger Equation: July 28-30
Reference
NSE stock market prediction using deep-learning models
M. Hiransha
Procedia Computer Science, 132: 1351-1362, 2018
Reference
Inverted anhamonic oscillator model for distribution of financial returns
N. Jaroonchokanan
Journal of Physics: Conference Series, 1144: 2018
Reference
Modeling non-normality using multivariate t: implications for asset pricing
R. Kan
China Finance Review International, 7: 2-32, 2017
Reference
The Variance Gamma Model for Share Market Returns
D.B. Madan
Journal of Business, 64: 511-524, 1990
Reference
The Variation of Certain Speculative Prices
B. Mandelbrot
Journal of Business, 36: 394-419, 1963
Reference
Certain speculative prices (1963)
B. Mandelbrot
Journal of Business, 45: 542-543, 1972
Reference
Modeling stock prices in a portfolio using multidimensional geometric brownian motion
A. Maruddani
Journal of Physics: Conference Series, 1025: 2018
Reference
Quantum Brownian motion model for the stock market
X. Meng
Physica A-statistical Mechanics and Its Applications, 452: 281-288, 2016
Reference
Quantum spatial-periodic harmonic model for daily price-limited stock markets
X. Meng
Physica A, 438: 154-160, 2015
Reference
A systematic review of fundamental and technical analysis of stock market predictions
I.K. Nti
Artificial Intelligence Review: 1-51, 2019
Reference
Bootstrap prediction for returns and volatilities in GARCH models
L. Pascual
Computational Statistics & Data Analysis, 50: 2293-2312, 2006
Reference
Risk budgeting: Portfolio Problem Solving with Value at Risk
N. Pearson
Risk budgeting: Portfolio Problem Solving with Value at Risk: 2002
Reference
The minimal length uncertainty and the quantum model for the stock market
P. Pedram
Physica A, 391: 2100-2105, 2012
Reference
Measuring expected shortfall under semi-parametric expected shortfall approaches: a case study of selected Southern European/Mediterranean countries
N. Radivojević
Journal of Operational Risk, 14: 43-76, 2019
Reference
The new hybrid VaR approach based on EVT
N. Radivojevic
Estudios de Economia, 43: 29-52, 2016a
Reference
esting value at risk models in emerging markets during crises: a case study on Southeastern European countries
N. Radivojevic
Journal of Risk Model Validation, 10: 57-81, 2016b
Reference
Market crises and Basel capital requirements: Could Basel III have been different? Evidence from Portugal, Ireland, Greece and Spain (PIGS)
F.A. Rossignolo
Journal of Banking & Finance, 37: 1323-1339, 2013
Reference
Value-at-Risk models and Basel capital charges Evidence from Emerging and Frontier stock markets
F.A. Rossignolo
Journal of Financial Stability, 8: 303-319, 2012
Reference
Simulating Stock Prices Using Geometric Brownian Motion: Evidence from Australian Companies
K. Reddy
Australasian Accounting, Business and Finance Journal, 10: 23-47, 2016
Reference
Value at Risk models and Basel capital charges Evidence from Emerging and Frontier stock markets
F. A. Rossignolo
Journal of Financial Stability, 8: 303-319, 2012
Reference
Market crises and Basel capital requirements: Could Basel III have been different? Evidence from Portugal, Ireland, Greece and Spain (PIGS)
F. A. Rossignolo
Journal of Banking & Finance, 37: 1323-1339, 2013
Reference
Brownian markets
T. Roumen
Chinese Physics Letter, 30: 2013
Reference
Machine learning for quantitative finance applications: A survey
F. Rundo
Applied Sciences, 9: 1-20, 2019
Reference
Modern Risk Management: A History
O. Scaillet
Modern Risk Management: A History: 151-158, 2003
Reference
Nonparametric estimation and sensitivity analysis of expected shortfall
O. Scaillet
Mathematical Finance, 14: 115-129, 2004
Reference
Stock market analysis: A review and taxonomy of prediction techniques
D. Shah
International Journal of Financial Studies, 7: 1-26, 2019
Reference
Ranking the predictive performances of value-at-risk estimation methods
E. Şener
International Journal of Forecasting, 28: 849-873, 2012
Reference
Financial time series forecasting with deep learning: A systematic literature review: 2005-2019
O.B. Sezer
Intelligent Automation and Soft Computing, 26: 323-334, 2020
Reference
A comparison of statistical tests for the adequacy of a neural network regression model
N.S. Thomaidis
Quantitative Finance, 12: 437-449, 2012
Reference
A quantum anharmonic oscillator model for the stock market
G. Tingting
Physica A: Statistical Mechanics and its Applications, 468(C): 307-314, 2017
Reference
On the Interconnectedness of Schrodinger and Black-Scholes Equation
O. Vukovic
Journal of Applied Mathematics and Physics, 3: 2015
Reference
Long-term memory of the returns in the Chinese stock indices
J. Wan
Frontiers of Physics in China, 3: 489-494, 2008
Reference
Mathematica
Wolfram Research
Mathematica: 2022
Reference
Nonlinear Schrödinger approach to European option pricing
M. Wróblewski
Open Physics, 15: 280-291, 2017
Reference
Natural language-based financial forecasting: a survey
F.Z. Xing
Artificial Intelligence Review, 50: 49-73, 2018
Reference
Non-classical oscillator model for persistent fluctuations in stock markets
C . Ye
Physica A, 387: 1255-1263, 2008
Reference
A quantum model for the stock market
C. Zhang
Physica A, 389: 5769-5775, 2010
Reference
Power tails of index distributions in Chinese stock marke
W. Zhang
Physica A, 377: 166-172, 2007
Reference
Ranking of VaR and ES models: performance in developed and emerging markets
S. Zikovic
Czech Journal of Economics and Finance, 63: 327-359, 2013
The article was received on Wed, 31 Aug 2022, accepted on Fri, 31 Mar 2023, and published on .
Copyright & License
Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons
Author
Vladimir M. Markovic
Faculty of Science, University of Kragujevac, Serbia, Serbia
Author
Nikola Radivojevic
Academy at applied studies Sumadia in Kragujevac, Serbia, Serbia
Author
Tatjana Ivanovic
Faculty of Agriculture, University of Pristina, Serbia, Serbia
Author
Slobodan Radisic
Faculty of Technical Sciences, University of Novi Sad, Serbia, Serbia
Author
Nenad Novakovic
Faculty of Technical Sciences, University of Novi Sad, Serbia, Serbia