C. J. Corrado and T. W. Miller, The forecast quality of cboe implied volatility indexes, Journal of Futures Markets, vol.25, issue.4, pp.339-373, 2005.

W. Abdelmalek, S. B. Hamida, and F. Abid, Selecting the best forecasting-implied volatility model using genetic programming, Journal of Applied Mathematics and Decision Sciences, 2009.

S. B. Hamida, W. Abdelmalek, and F. Abid, Applying dynamic training-subset selection methods using genetic programming for forecasting implied volatility, Computational Intelligence, 2014.
URL : https://hal.archives-ouvertes.fr/hal-02286864

R. Coulom, Efficient selectivity and backup operators in Monte-Carlo tree search, Computers and Games, 5th International Conference, vol.4630, pp.72-83, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00116992

L. Kocsis and C. Szepesvári, Bandit based Monte-Carlo planning, 17th European Conference on Machine Learning (ECML'06), ser. LNCS, vol.4212, pp.282-293, 2006.

T. Cazenave, Nested Monte-Carlo Search, pp.456-461, 2009.
URL : https://hal.archives-ouvertes.fr/hal-02310192

D. Kinny, A new approach to the snake-in-the-box problem, ECAI 2012, pp.462-467, 2012.

S. Eliahou, C. Fonlupt, J. Fromentin, V. Marion-poty, D. Robilliard et al., Investigating monte-carlo methods on the weak schur problem, Evolutionary Computation in Combinatorial Optimization -13th European Conference, pp.191-201, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01406479

T. Cazenave, F. Balbo, and S. Pinson, Monte-Carlo bus regulation, pp.340-345, 2009.

A. Rimmel, F. Teytaud, and T. Cazenave, Optimization of the nested monte-carlo algorithm on the traveling salesman problem with time windows, Applications of Evolutionary Computation -EvoApplications 2011: EvoCOMNET, EvoFIN, EvoHOT, EvoMUSART, EvoSTIM, and EvoTRANSLOG, pp.501-510, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00563668

S. M. Poulding and R. Feldt, Generating structured test data with specific properties using nested monte-carlo search, Genetic and Evolutionary Computation Conference, GECCO '14, pp.1279-1286, 2014.

C. D. Rosin, Nested rollout policy adaptation for Monte Carlo tree search, IJCAI, pp.649-654, 2011.

S. Edelkamp, M. Gath, T. Cazenave, and F. Teytaud, Algorithm and knowledge engineering for the TSPTW problem, 2013 IEEE Symposium on Computational Intelligence in Scheduling, pp.44-51, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01406484

S. Edelkamp and Z. Tang, Monte-carlo tree search for the multiple sequence alignment problem, Eighth Annual Symposium on Combinatorial Search, 2015.

F. Black and M. Scholes, The pricing of options and corporate liabilities, Journal of Political Economy, vol.81, issue.3, pp.637-654, 1973.

R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of united kingdom inflation, Econometrica, vol.50, issue.4, pp.987-1007, 1982.

T. Bollerslev, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, vol.31, issue.3, pp.307-327, 1986.

I. Ma, T. Wong, and T. Sanker, An engineering approach to forecast volatility of financial indices, International Journal of Computational Intelligence, vol.3, issue.1, pp.23-35, 2006.

T. Cazenave, Nested monte-carlo expression discovery, ECAI 2010 -19th European Conference on Artificial Intelligence, pp.1057-1058, 2010.
URL : https://hal.archives-ouvertes.fr/hal-02092940

, Monte-carlo expression discovery, International Journal on Artificial Intelligence Tools, vol.22, issue.1, 2013.

J. A. Walker and J. F. Miller, Predicting prime numbers using cartesian genetic programming, Genetic Programming, vol.4445, pp.205-216, 2007.

L. Spector, D. M. Clark, I. Lindsay, B. Barr, and J. Klein, Genetic programming for finite algebras, Genetic And Evolutionary Computation Conference, pp.1291-1298, 2008.

J. R. Koza, Genetic Programming: On the Programming of Computers by Natural Selection, 1992.

E. Burke, S. Gustafson, and G. Kendall, A puzzle to challenge genetic programming, Genetic Programming, vol.2278, pp.136-147, 2002.

W. B. Langdon and R. Poli, An analysis of the max problem in genetic programming, pp.222-230, 1997.

J. Méhat and T. Cazenave, Combining UCT and Nested Monte Carlo Search for single-player general game playing, IEEE Transactions on Computational Intelligence and AI in Games, vol.2, issue.4, pp.271-277, 2010.

S. Chen and C. Yeh, Using genetic programming to model volatility in financial time series: the cases of nikkei 225 and s&p 500, Genetic programming 1997: Proceedings of the second annual conference, 1997.

G. Zumbach, O. V. Pictet, and O. Masutti, Genetic programming with syntactic restrictions applied to financial volatility forecasting, Computational Methods in Decision-Making, pp.557-581, 2002.

C. J. Neely and P. A. Weller, Predicting exchange rate volatility: Genetic programming vs. garch and risk metrics, Louis Working Paper Series, 2001.