scholarly journals Optimal Stopping Time, Consumption, Labour, and Portfolio Decision for a Pension Scheme

2019 ◽  
Author(s):  
Francesco Menoncin ◽  
Sergio Vergalli
Keyword(s):  
Optimal Stopping ◽  
Stopping Time ◽  
Pension Scheme ◽  
Optimal Stopping Time ◽  
Time Consumption ◽  
Portfolio Decision

scholarly journals Optimal stopping time, consumption, labour, and portfolio decision for a pension scheme

2020 ◽  
Author(s):  
Francesco Menoncin ◽  
Sergio Vergalli
Keyword(s):  
Optimal Stopping ◽  
Labour Supply ◽  
Stopping Time ◽  
Risky Asset ◽  
Pension Scheme ◽  
Optimal Stopping Time ◽  
Martingale Approach ◽  
Portfolio Problem ◽  
Portfolio Decision ◽  
Hamilton Jacobi Bellman

Abstract In this work we solve in a closed form the problem of an agent who wants to optimise the inter-temporal recursive utility of both his consumption and leisure by choosing: (1) the optimal inter-temporal consumption, (2) the optimal inter-temporal labour supply, (3) the optimal share of wealth to invest in a risky asset, and (4) the optimal retirement age. The wage of the agent is assumed to be stochastic and correlated with the risky asset on the financial market. The problem is split into two sub-problems: the optimal consumption, labour, and portfolio problem is solved first, and then the optimal stopping time is approached. We compute the solution through both the so-called martingale approach and the solution of the Hamilton–Jacobi–Bellman partial differential equation. In the numerical simulations we compare two cases, with and without the opportunity, for the agent, to work after retirement, at a lower wage rate.

Optimal Stopping Time for Geometric Random Walks with Power Payoff Function

2020 ◽  
Vol 81 (7) ◽  
pp. 1192-1210
Author(s):  
O.V. Zverev ◽  
V.M. Khametov ◽  
E.A. Shelemekh
Keyword(s):  
Random Walks ◽  
Optimal Stopping ◽  
Stopping Time ◽  
Payoff Function ◽  
Optimal Stopping Time

scholarly journals A Forward Algorithm for Solving Optimal Stopping Problems

2006 ◽  
Vol 43 (01) ◽  
pp. 102-113
Author(s):  
Albrecht Irle
Keyword(s):  
State Space ◽  
Optimal Stopping ◽  
Stopping Time ◽  
The State ◽  
Optimal Stopping Problem ◽  
Forward Algorithm ◽  
Optimal Stopping Time ◽  
Entrance Time ◽  
Markov Sequence ◽  
Optimal Stopping Problems

We consider the optimal stopping problem for g(Z n ), where Z n , n = 1, 2, …, is a homogeneous Markov sequence. An algorithm, called forward improvement iteration, is presented by which an optimal stopping time can be computed. Using an iterative step, this algorithm computes a sequence B 0 ⊇ B 1 ⊇ B 2 ⊇ · · · of subsets of the state space such that the first entrance time into the intersection F of these sets is an optimal stopping time. Various applications are given.

ε - Optimal Stopping Time for Genetic Algorithms

1998 ◽  
Vol 35 (1-4) ◽  
pp. 91-111 ◽  
Author(s):  
C.A. Murthy ◽  
Dinabandhu Bhandari ◽  
Sankar K. Pal
Keyword(s):  
Genetic Algorithms ◽  
Optimal Stopping ◽  
Stopping Time ◽  
Optimal Stopping Time

On Pricing American Put Option on a Fixed Term: A Monte Carlo Approach

2021 ◽  
pp. 2050010
Author(s):  
Perpetual Andam Boiquaye
Keyword(s):  
Monte Carlo ◽  
Optimal Stopping ◽  
Geometric Mean ◽  
Option Price ◽  
Stopping Time ◽  
Optimal Stopping Time ◽  
American Put Option ◽  
Put Option ◽  
One Year ◽  
American Put

This paper focuses primarily on pricing an American put option with a fixed term where the price process is geometric mean-reverting. The change of measure is assumed to be incorporated. Monte Carlo simulation was used to calculate the price of the option and the results obtained were analyzed. The option price was found to be $94.42 and the optimal stopping time was approximately one year after the option was sold which means that exercising early is the best for an American put option on a fixed term. Also, the seller of the put option should have sold $0.01 assets and bought $ 95.51 bonds to get the same payoff as the buyer at the end of one year for it to be a zero-sum game. In the simulation study, the parameters were varied to see the influence it had on the option price and the stopping time and it showed that it either increases or decreases the value of the option price and the optimal stopping time or it remained unchanged.

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