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We are pleased to present a series of videos about commodity products featuring what exactly the product is, the world production and the major producing countries.




        VIX OPTIONS - Bibliography

  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 - Bibliography

  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 - Bibliography

  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 - Bibliography

  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.

        Bibliography

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