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Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
by
Silva, Thuener
, Poggi, Marcus
, Davi Valladão
in
Asset allocation
/ Costs
/ Dynamic programming
/ Economic models
/ Investment strategy
/ Lower bounds
/ Markov chains
/ Operations research
/ Optimization
/ Portfolio management
/ Risk allocation
/ Studies
/ Time dependence
2019
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Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
by
Silva, Thuener
, Poggi, Marcus
, Davi Valladão
in
Asset allocation
/ Costs
/ Dynamic programming
/ Economic models
/ Investment strategy
/ Lower bounds
/ Markov chains
/ Operations research
/ Optimization
/ Portfolio management
/ Risk allocation
/ Studies
/ Time dependence
2019
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Do you wish to request the book?
Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
by
Silva, Thuener
, Poggi, Marcus
, Davi Valladão
in
Asset allocation
/ Costs
/ Dynamic programming
/ Economic models
/ Investment strategy
/ Lower bounds
/ Markov chains
/ Operations research
/ Optimization
/ Portfolio management
/ Risk allocation
/ Studies
/ Time dependence
2019
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Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
Journal Article
Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns
2019
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Overview
Dynamic portfolio optimization has a vast literature exploring different simplifications by virtue of computational tractability of the problem. Previous works provide solution methods considering unrealistic assumptions, such as no transactional costs, small number of assets, specific choices of utility functions and oversimplified price dynamics. Other more realistic strategies use heuristic solution approaches to obtain suitable investment policies. In this work, we propose a time-consistent risk-constrained dynamic portfolio optimization model with transactional costs and Markovian time-dependence. The proposed model is efficiently solved using a Markov chained stochastic dual dynamic programming algorithm. We impose one-period conditional value-at-risk constraints, arguing that it is reasonable to assume that an investor knows how much he is willing to lose in a given period. In contrast to dynamic risk measures as the objective function, our time-consistent model has relatively complete recourse and a straightforward lower bound, considering a maximization problem. We use the proposed model for approximately solving: (i) an illustrative problem with 3 assets and 1 factor with an autoregressive dynamic; (ii) a high-dimensional problem with 100 assets and 5 factors following a discrete Markov chain. In both cases, we empirically show that our approximate solution is near-optimal for the original problem and significantly outperforms selected (heuristic) benchmarks. To the best of our knowledge, this is the first systematic approach for solving realistic time-consistent risk-constrained dynamic asset allocation problems.
Publisher
Springer Nature B.V
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