Multimedia

Nous sommes heureux de vous offrir une séries de courtes vidéos pour vous présenter les plus importantes matières premières échangées dans le monde, quels sont les principaux producteurs et les quantités produites par an.




        VIX OPTIONS - Bibliographie

  1. Baldeaux, J., and Badran, A. - Consistent modelling of VIX and equity derivatives using a 3/2 plus jumps model. Applied Mathematical Finance, 21(4):299-312, 2014.
  2. Bates, D. - Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options. Review of Financial Studies, 9, 69-107, 1996.
  3. Bardgett, E., Gourier, M., and Leippold, M. - Inferring volatility dynamics and risk premia from theS&P 500 and VIX markets. Swiss Finance Institute, Research Paper Series No13-40, Universityof Zurich, 2014.
  4. Blair, B.J., Poon, S., and Taylor, S.J. - Forecasting S&P 100 Volatility: the Incremental, 2001.
  5. Brenner, M., and Galai, D. - New Financial Instruments for Hedging Changes in Volatility. Financial Analysts Journal July-August, 61-65, 1989.
  6. Brenner, M., and Galai, D. - Hedging Volatility in Foreign Currencies. Journal of Derivatives, 1, 53-59, 1993.
  7. Carr, P., and Madan, D. - Option pricing using the fast Fourier transform. Journal of Computational Finance, 4, 61-73, 1999.
  8. Carr, P., and Wu, L. - A Tale of two Indices. Journal of Derivatives 13, 13-29, 2006.
  9. Corrado, C.J., and Miller, T. - The Forecast Quality of CBOE Implied Volatility Indexes. Working Paper. Washington University, Olin School of Business, 2005.
  10. Detemple, J., and Osakwe, C. - The Valuation of Volatility Options. European Finance Review 4, 21-50, 2000.
  11. Dotsis, G., Psychoyios, D., and Skiadopoulos, G. - An Empirical Comparison of Continuous-Time Models of Implied Volatility Indices. Journal of Banking and Finance, 31, 3584-3603, 2007.
  12. Duan, J., and Yeh, C. - Jump and Volatility Risk Premiums Implied by VIX. Journal of Economic Dynamics and Control, 34, 2232-2244, 2010.
  13. Duan, J., and Yeh, C. - Price and Volatility Dynamics Implied by the VIX Term Structure, 2012.
  14. Fleming, J., Ostdiek, B., and Whaley, R. E. - Predicting Stock Market Volatility: A New Measure. Journal of Futures Markets 15, 265-302, 1995.
  15. Grünbichler, A., and Longstaff, F. - Valuing Futures and Options on Volatility. Journal of Banking and Finance 20, 985-1001, 1996.
  16. Heston, S. - A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options. Review of Financial Studies 6, 327343, 1993.
  17. Jiang, G., and Oomen, R. - Hedging Derivatives Risks: A Simulation Study. Working Paper. University of Warwick, 2001.
  18. Kou, S.G., and Wang, H. - Option Pricing Under a Double Exponential Jump Diffusion Process. Columbia: Columbia University, 2007.
  19. Moraux, F., Navatte, P., and Villa, C. - The Predictive Power of the French Market Volatility Index: A Multi Horizons Study. European Finance Review 2, 303-320, 1999.
  20. Papanicolaou, R., and Sircar, A. - A regime-switching Heston model for VIX and S&P 500 impliedvolatilities. Quantitative Finance, 14(10):1811-1827, 2014.
  21. Sepp, A. - VIX Option Pricing in a Jump-Di?usion Model. Risk, 84-89, 2008.
  22. Whaley, R., E. - Derivatives on Market Volatility: Hedging Tools Long Overdue. Journal of Derivatives1, 71-84, 1993.
  23. Whaley, R. E. - Understanding the VIX. Journal of Portfolio Management, 35, 98-105, 2009.
  24. Yang-Ho Park - The E?ects of Asymmetric Volatility and Jumps on the Pricing of VIX Derivatives. Finance and Economics Discussion Series, 2015.

        MACHINE LEARNING - Bibliographie

  1. Taiwo Oladipupo Ayodele - Types of Machine Learning Algorithms, University of Portsmouth United Kingdom, 2016.
  2. Gah-Yi Ban, Noureddine El Karoui, Andrew E.B. Lim - Machine Learning and Portfolio Optimization, Management Science Article, 2016.
  3. Christian Beck, Weinan E, and Arnulf Jentzen - Machine learning approximation algorithms for high-dimensional fully nonlinear partial di?erential equations and second-order backward stochastic di?erential equations, Working Paper, 2017.
  4. Y. Chali, S. R. - Complex Question Answering: Unsupervised Learning Approaches and Experiments. Journal of Artificial Intelligent Research , 1-47. Yu, 2009.
  5. Marco Lopez De Prado - Advances in Financial Machine Learning, Wiley, 2017.
  6. Li Deng - Deep Learning for AI from Machine Perception to Machine Cognition, A Plenary Presentation at IEEE-ICASSP, 2016.
  7. LISA lab - Deep Learning Tutorial , University of Montreal, 2015.
  8. Barnabás Poczo and Aarti Singh -Introduction to Machine Learning and Deep Learning, Carnegie Mellon, 2017.
  9. Shai Shalev-Shwartz and Shai Ben-David - Understanding Machine Learning: From Theory to Algorithms, Cambridge University Press, 2014.
  10. Alex Smola and S.V.N. Vishwanathan - Introduction to Machine Learning, Cambridge University Press, 2008.

        VWAP - Bibliographie

  1. Almgren, R., and Chriss, N. - Optimal execution of portfolio transactions, Journal of Risk 3 5-40, 2000.
  2. Berkowitz, S. A., Logue, D. E., and Noser Jr., E. A. - The total cost of transactions on theNYSE. The Journal of Finance 43, 97-112, 1988.
  3. Bertsimas, D., and Lo, A. - Optimal Control of Execution Costs, Journal of Financial Markets 1, 1-50, 1988.
  4. Bialkowski, J., Darolles, S., and Le Fol, G. - Improving VWAP strategies: A dynamic volume approach. Journal of Banking and Finance 32, 1709-1722, 2008.
  5. Brownlees, C. T., Cipollini, F., and Gallo, G. M. - Intra-daily volume modeling and predic-tion for algorithmic trading. Journal of Financial Econometrics 9, 489-518, 2011.
  6. Busti, E., and Boyd, S. - Volume Weighted Average Price Optimal Execution. Working Paper, 2015.
  7. Cartea, A., and Jaimungal, S. - A closed-form execution strategy to target volume weighted average price. SIAM Journal of Financial Mathematics, 7:760785, 2016.
  8. Cheng, X., Di Giacinto, M., and Wang, T. - Optimal execution with uncertain order ?lls in Almgren-Chriss framework. Quantitative Finance, 17(1):55-69, 2017.
  9. Darolles, S., and Le fol, G. - Decomposing Volume for VWAP strategies. Working Paper, CREST, 2005.
  10. Fräenkle, J., Rachev, S. T., and Scherrer, C. - Market Impact Measurement of a VWAP Trading Algorithm. Review: Algorithmic trading. (1), 7-20, 2011.
  11. Frei, C., and Westray, N. - Optimal execution of a VWAP order: a stochastic control approach, working paper, 2012.
  12. Gatheral, J., and Schied, A. - Optimal trade execution under geo- metric Brownian motion in the Almgren and Chriss framework, Int. J. Theoretical Appl. Finance 14, 353-368, 2011.
  13. Guéant , O., and Royer, G. - VWAP execution and guaranteed VWAP. Working Paper, 2012.
  14. Gouriéroux, C., Jasiak, J., and Le Fol, G. - Intraday market activity, Journal of Financial Markets 2, 193-226, 1999.
  15. Humphery-Jenner, M. L. - Optimal VWAP trading under noisy conditions. Journal ofBanking and Finance 35, 2319-2329, 2011.
  16. Kakade, S., Kearns, M. J., Mansour, Y., and Ortiz, L. E. - Competitive algorithms forVWAP and limit order trading. ACM Conference on Electronic Commerce pp. 189-198, 2004.
  17. Konishi, H. - Optimal slice of a VWAP trade. Journal of Financial Markets 5, 197-221, 2002.
  18. Madhavan, A. N. - VWAP Strategies Transaction Performance: The Changing Face ofTrading, Institutional Investor Inc., pp. 32-38, 2002.
  19. McCulloch, J., and Kazakov, V. - Optimal VWAP trading strategy and optimal volume. Working Paper, 2012.
  20. Perold, A. - The implementation shortfall: Paper versus reality. Journal of Portfolio Management, 14, 4-9, 1988.

        COMMODITY - Bibliographie

  1. Ana Luiza Abrao and Roriz Soares de Carvalho - Calibration of the Schwartz-Smith Model for Commodity Prices, Instituto de Matema´tica Pura e Aplicada, 2010.
  2. Carol Alexander - Commodity Options, ICMA Centre University of Reading, 2008.
  3. Petter Bjerksund and Gunnar Stensland - Closed form spread option valuation, Working Paper, 2006.
  4. Brennan M.J. and Crew N. - Hedging long maturity commodity commitments with short-dated futures contracts, in M. Dempster & S. Pliska (Eds), Mathematics of derivatives securities, pp 165- 190, Cambridge: Cambridge University Press, 1997.
  5. Gabillon J. - The term structure of oil futures prices, Working Paper, Oxford Institute for Energy Studies, 1992.
  6. H. Geman - Commodity and Commodity Derivatives. Wiley, 2005.
  7. Kristian R. Miltersen and Eduardo S. Schwartz - Pricing of options on commodity futures with stochastic term structures of convenience yields and interest rates. Journal of Financial and Quantitative Analysis, 33:33-59, 1998.
  8. Tristan Perez, Graham C. Goodwin and Boris Godoy - Parameter Estimation of Structural Commodity Price Models, 15th IFAC Symposium on System Identification, 2009.
  9. Routledge B.R., Seppi D.J. and Spatt C.S. - Equilibrium Forward Curves for Commodities, Journal of Finance, 55(3), 1297-1338, 2000.
  10. E. Schwartz -The stochastic behavior of commodity prices: Implications for valuation andhedging, Journal of Finance, 52: 923-973, 1997.
  11. E. Schwartz and J.E. Smith - Short-term variations and long-term dynamics in commodity prices, Management Science, 46(7):893-911, 2000.
  12. Tolmasky C. and Hindanov D. - Principal component analysis for correlated curves and seasonal commodities: the case of the petroleum market. Journal of Futures Markets, 22 (11), 1019-1035, 2002.
  13. Veld-Merkoulova Y.V. and de Roon F.A. - Hedging long-term commodity risk. Journal of Futures Markets, 23(2), 109-133, 2003.
  14. Yan X. -Valuation of commodity derivatives in a new multi-factor model. Review of Derivatives Research, 5, 251-271, 2002.
  15. Philipp Erb, David Luthi and Simon Otziger - Schwartz 1997 Two-Factor Model Technical Document, Working Paper, 2014.

        Bibliograhie

Bibliographie

top