Massively parallel processing of recursive multi-period portfolio models

Östermark, Ralf

doi:10.1016/j.ejor.2016.10.009

Cited by 5 publications

(1 citation statement)

References 54 publications

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“…[10] informs that finding a multiperiod portfolio optimization solution is very difficult and complicated. Nevertheless, then along with the development of computers can help solve these problems, including using dynamic programming with the Bellman equation [4], the Monte Carlo algorithm [11], and parallel processing [12].…”

Section: Introductionmentioning

confidence: 99%

The Implementation of the Multiperiod Mean-Variance for Asset Allocation of Pension Fund

Irawan¹,

Siahaan²

2021

Proceedings of the 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020)

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This paper investigates the application of multi-period mean-variance methods for optimal asset allocation in pension fund institutions by considering mortality factors and changes in contributions. The selection of assets used to find portfolios is using Treasury Bills as a risk-free asset and using stock included in the LQ45 index as risk assets that have the best performance during the period 2014 -2018. The multi-period mean-variance method's main purpose is to obtain the minimum variance with optimal returns at the end of the period. This result indicates that the smallest return is owned by the asset allocation model without contribution because, without additional membership fees, the amount of funds that can be invested is more limited. Hence, the ex-pected wealth terminal is smaller than other asset allocation models. The asset allocation without the mortality factor gives higher expected terminal wealth compared to other asset allocation models. This is because the absence of mortality factor in the pension fund investment will not be forced to stop before the retirement pe-riod ends so that the portfolio return obtained is higher than other asset allocation models. While the asset al-location model using the risk-free asset as references has a higher risk with the same return compared with as-set allocation using risk assets as a reference. This indicates that the asset reference used affects the return and risk on the allocation of assets of the Pension Fund at the end of the period investment.

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Section: Introductionmentioning

confidence: 99%

The Implementation of the Multiperiod Mean-Variance for Asset Allocation of Pension Fund

Irawan¹,

Siahaan²

2021

Proceedings of the 5th Global Conference on Business, Management and Entrepreneurship (GCBME 2020)

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A general framework for pricing Asian options under stochastic volatility on parallel architectures

Corsaro

Kyriakou

Marazzina

et al. 2019

European Journal of Operational Research

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In this paper, we present a transform-based algorithm for pricing discretely monitored arithmetic Asian options with remarkable accuracy in a general affine stochastic volatility framework.The accuracy is justified both theoretically and experimentally. In addition, to speed up the valuation process, we employ high-performance computing technologies. More specifically, we develop a parallel option pricing system that can be easily reproduced on parallel computers, also realized as a cluster of personal computers. Numerical results showing the accuracy and efficiency of the procedure are reported in the paper.

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