Aïd, R., L. Campi, N. Langrené, and H. Pham (2014). A probabilistic numerical method for optimal multiple switching problem in high dimension. SIAM Journal on Financial Mathematics 5(1), 191–231.
Abergel, F. and G. Loeper (2013, April). Pricing and hedging contingent claims with liquidity costs and market impact. Working Paper, Available at SSRN: http://ssrn.com/abstract=2239498.
Acerbi, C. and G. Scandolo (2008). Liquidity risk theory and coherent measures of risk. Quantitative Finance 8, 681–692.
- Bao, C., Z. Zhu, N. Langrené, and G. Lee (2014). Multi-period dynamic portfolio optimization through least squares learning. In IAENG Transactions on Engineering Sciences, pp. 29–42.
Paper not yet in RePEc: Add citation now
- Boogert, A. and C. de Jong (2008). Gas storage valuation using a Monte Carlo method. The Journal of Derivatives 15(3), 81–98.
Paper not yet in RePEc: Add citation now
Bouchard, B. and X. Warin (2012). Monte-Carlo valorisation of American options: facts and new algorithms to improve existing methods. In P. Carmona, D. M. P., P. Hu, and N. Oudjane (Eds.), Numerical Methods in Finance, Volume 12, Heidelberg, pp. 215–255. Springer Proceedings in Mathematics.
Brandt, M., A. Goyal, P. Santa-Clara, and J. Stroud (2005). A simulation approach to dynamic portfolio choice with an application to learning about return predictability. Review of Financial Studies 18, 831–873.
- Broadie, M. and P. Glasserman (2004). A stochastic mesh method for pricing high-dimensional American options. Journal of Computational Finance 7, 35–72.
Paper not yet in RePEc: Add citation now
Brown, D. and J. Smith (2011). Dynamic portfolio optimization with transaction costs: Heuristics and dual bounds. Management Science 57(10), 1752–1770.
- Brumm, J., D. Mikushin, S. Scheidegger, and O. Schenk (2015). Scalable high-dimensional dynamic stochastic economic modeling. Journal of Computational Science 11, 12–25.
Paper not yet in RePEc: Add citation now
Cai, Y., K. L. Judd, and R. Xu (2013). Numerical solution of dynamic portfolio optimization with transaction costs. NBER Working Paper No. w18709.
Cai, Y., K. L. Judd, G. Thain, and S. J. Wright (2015). Solving dynamic programming problems on a computational grid. Computational Economics 45(2), 261–284.
Carriere, J. (1996). Valuation of the early-exercise price for options using simulations and nonparametric regression. Insurance: Mathematics and Economics 19(1), 19–30.
- Collin-Dufresne, P., K. Daniel, C. C. Moallemi, and M. Saǧlam (2014). Dynamic asset allocation with predictable returns and transaction costs. Working Paper.
Paper not yet in RePEc: Add citation now
Cong, F. and C. W. Oosterlee (2016). Multi-period mean-variance portfolio optimization based on Monte Carlo simulation. Journal of Economic Dynamics and Control 64, 23–38.
Cui, X., J. Gao, X. Li, and D. Li (2014). Optimal multi-period mean-variance policy under no-shorting constraint. European Journal of Operational Research 234(2), 459–468.
Davis, M. and A. Norman (1990). Portfolio selection with transaction costs. Mathematics of Operations Research 15(4), 676–713.
- DeMiguel, V., X. Mei, and F. J. Nogales (2014). Multiperiod portfolio optimization with many risky assets and general transaction costs. Working Paper, Available at SSRN: http://ssrn.com/abstract=2295345.
Paper not yet in RePEc: Add citation now
- Friedman, J, H. (1991). Multivariate adaptive regression splines. The Annals of Statistics 19(1), 1–67.
Paper not yet in RePEc: Add citation now
Gârleanu, N. and L. H. Pedersen (2013). Dynamic trading with predictable returns and transaction costs. Journal of Finance 68(2309-2340).
Garlappi, L. and G. Skoulakis (2009). Numerical solutions to dynamic portfolio problems: The case for value function iteration using Taylor approximation. Computational Economics 33, 193–207.
Garlappi, L. and G. Skoulakis (2010). Solving consumption and portfolio choice problems: The state variable decomposition method. Review of Financial Studies 23, 3346–3400.
- Gobet, E., J.-P. Lemor, and X. Warin (2005). A regression-based Monte Carlo method to solve Backward Stochastic Differential Equations. The Annals of Applied Probability 15(3), 2172–2202.
Paper not yet in RePEc: Add citation now
He, H. and H. Mamaysky (2005). Dynamic trading with price impact. Journal of Economic Dynamics and Control 29(5), 891–930.
Judd, K., L., L. Maliar, S. Maliar, and R. Valero (2014, July). Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain. Journal of Economic Dynamics and Control 44, 92–123.
Kharroubi, I., N. Langrené, and H. Pham (2014). A numerical algorithm for fully nonlinear HJB equations: an approach by control randomization. Monte Carlo Methods and Applications 20(2), 145–165.
Krueger, D. and F. Kubler (2004, April). Computing equilibrium in OLG models with stochastic production. Journal of Economic Dynamics and Control 28(7), 1411–1436.
- Lim, A. and P. Wimonkittiwat (2014). Dynamic portfolio selection with market impact costs. Operations Research Letters 42(5), 299–306.
Paper not yet in RePEc: Add citation now
Liu, H. (2004). Optimal consumption and investment with transaction costs and multiple risky assets. Journal of Finance 59(1), 289–338.
Longstaff, F. and E. Schwartz (2001). Valuing American options by simulation: A simple least-squares approach. Review of Financial Studies 14(1), 681–692.
Lynch, A., W. and S. Tan (2010). Multiple risky assets, transaction costs and return predictability: Allocation rules and implication for U.S. investors. Journal of Financial and Quantitative Analysis 45(4), 1015–1053.
Mei, X. and F. J. Nogales (2015). Portfolio selection with proportional transaction costs and predictability.
Merton, R. (1971). Optimum consumption and portfolio rules in a continuous-time model. Journal of Economic Theory 3, 373–413.
Merton, R. C. (1969). Lifetime portfolio selection under uncertainty: the continuous-time case. Review of Economics and Statistics 51(3), 247–257.
- Moallemi, C. C. and M. Saǧlam (2015). Dynamic portfolio choice with linear rebalancing rules. Working Paper, Available at SSRN: http://ssrn.com/abstract=2011605.
Paper not yet in RePEc: Add citation now
Moro, R., J. Vicente, G. Moyano, L., A. Gerig, J. D. Farmer, G. Vaglica, and F. Lillo (2009). Market impact and trading profile of hidden orders in stock markets. Physical Review E 80, 066102–1– 066102–8.
Mossin, J. (1968). Optimal multiperiod portfolio policies. Journal of Business 41(2), 215–229.
Muthuraman, K. and H. Zha (2008). Simulation-based portfolio optimization for large portfolios with transaction costs. Mathematical Finance 18(1), 115–134.
Samuelson, P. (1969). Lifetime portfolio selection by dynamic stochastic programming. Review of Economics and Statistics 51, 239–46.
- Shreve, S., E. and M. Soner, H. (1994). Optimal investment and consumption with transaction costs. The Annals of Applied Probability 4(3), 609–692.
Paper not yet in RePEc: Add citation now
Tian, Y., R. Rood, and C. Oosterlee (2013). Efficient portfolio valuation incorporating liquidity risk.
- Tibshirani, R. (1996). Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58(1), 267–288.
Paper not yet in RePEc: Add citation now
- Tsitsiklis, J. and B. Van Roy (2001). Regression methods for pricing complex American-style options. IEEE Transactions on Neural Networks 12(4), 694–703.
Paper not yet in RePEc: Add citation now
- Tsoukalas, G., J. Wang, and K. Giesecke (2015). Dynamic portfolio execution. Working Paper, Available at SSRN: http://ssrn.com/abstract=2089837.
Paper not yet in RePEc: Add citation now
Van Binsbergen, J. H. and M. Brandt (2007). Solving dynamic portfolio choice problems by recursing on optimized portfolio weights or on the value function? Computational Economics 29, 355–367.
Vath, V., M. Mnif, and H. Pham (2007). A model of optimal portfolio selection under liquidity risk and price impact. Finance and Stochastics 11(1), 51–90.
Winschel, V. and M. Kraetzig (2010). Solving, estimating, and selecting nonlinear dynamic models without the curse of dimensionality. Econometrica 78(2), 803–821.