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相关论文: Theory of Performance Participation Strategies

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Constant Proportion Portfolio Insurance (CPPI) is an investment strategy designed to give participation in the performance of a risky asset while protecting the invested capital. This protection is however not perfect and the gap risk must…

证券定价 · 定量金融 2010-02-10 Louis Paulot , Xavier Lacroze

In the present paper we provide a two-step principal protection strategy obtained by combining a modification of the Constant Proportion Portfolio Insurance (CPPI) algorithm and a classical Option Based Portfolio Insurance (OBPI) mechanism.…

投资组合管理 · 定量金融 2019-02-19 L. Di Persio , I. Oliva. K. Wallbaum

Constant Proportion Portfolio Insurance (CPPI) is a strategy designed to give participation in a risky asset while protecting the invested capital. Some gap risk due to extreme events is often kept by the issuer of the product: a put option…

计算金融 · 定量金融 2009-01-12 Louis Paulot , Xavier Lacroze

We consider the problem of portfolio optimization with a correlation constraint. The framework is the multiperiod stochastic financial market setting with one tradable stock, stochastic income and a non-tradable index. The correlation…

最优化与控制 · 数学 2020-01-01 Aditya Maheshwari , Traian Pirvu

In this paper, we solve portfolio rebalancing problem when security returns are represented by uncertain variables considering transaction costs. The performance of the proposed model is studied using constant-proportion portfolio insurance…

投资组合管理 · 定量金融 2018-12-20 Mostafa Zandieh , Seyed Omid Mohaddesi

In this paper, we investigate an optimal investment problem associated with proportional portfolio insurance (PPI) strategies in the presence of jumps in the underlying dynamics. PPI strategies enable investors to mitigate downside risk…

投资组合管理 · 定量金融 2024-08-01 Katia Colaneri , Daniele Mancinelli , Immacolata Oliva

Designing dynamic portfolio insurance strategies under market conditions switching between two or more regimes is a challenging task in financial economics. Recently, a promising approach employing the value-at-risk (VaR) measure to assign…

计算金融 · 定量金融 2023-05-23 Peyman Alipour , Ali Foroush Bastani

Portfolio management problems are often divided into two types: active and passive, where the objective is to outperform and track a preselected benchmark, respectively. Here, we formulate and solve a dynamic asset allocation problem that…

投资组合管理 · 定量金融 2018-07-31 Ali Al-Aradi , Sebastian Jaimungal

We consider Constant Proportion Portfolio Insurance (CPPI) and its dynamic extension, which may be called Dynamic Proportion Portfolio Insurance (DPPI). It is shown that these investment strategies work within the setting of F\"ollmer's…

投资组合管理 · 定量金融 2014-01-17 Alexander Schied

The fundamental principle in Modern Portfolio Theory (MPT) is based on the quantification of the portfolio's risk related to performance. Although MPT has made huge impacts on the investment world and prompted the success and prevalence of…

投资组合管理 · 定量金融 2021-02-15 Shi Yu , Haoran Wang , Chaosheng Dong

We provide analytical results for a static portfolio optimization problem with two coherent risk measures. The use of two risk measures is motivated by joint decision-making for portfolio selection where the risk perception of the portfolio…

投资组合管理 · 定量金融 2021-01-19 Tahsin Deniz Aktürk , Çağın Ararat

Modern portfolio theory(MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk,…

统计力学 · 物理学 2009-11-07 Morrel H. Cohen , Vincent D. Natoli

In this article, inspired by Shi, et al. we investigate the optimal portfolio selection with one risk-free asset and one risky asset in a multiple period setting under cumulative prospect theory (CPT). Compared with their study, our novelty…

投资组合管理 · 定量金融 2019-03-26 Liurui Deng , Traian A. Pirvu

This is the second part of a two-part paper on data-based distributionally robust stochastic optimal power flow (OPF). The general problem formulation and methodology have been presented in Part I [1]. Here, we present extensive numerical…

最优化与控制 · 数学 2018-10-29 Yi Guo , Kyri Baker , Emiliano Dall'Anese , Zechun Hu , Tyler H. Summers

We introduce predictable relative forward performance processes (PRFPP) as a new framework for studying portfolio management within a competitive and incomplete market environment. Each agent trades a distinct stock following a binomial…

数理金融 · 定量金融 2026-05-08 Gechun Liang , Moris S. Strub , Yuwei Wang

Parametric Portfolio Policies (PPP) estimate optimal portfolio weights directly as functions of observable signals by maximizing expected utility, bypassing the need to model asset returns and covariances. However, PPP ignores policy risk.…

投资组合管理 · 定量金融 2026-02-25 Miguel C. Herculano

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize expected tail loss and investigate both asset allocation (AA) and the selection effect (SE)…

风险管理 · 定量金融 2021-03-09 Yuan Hu , W. Brent Lindquist

We develop a new analysis for portfolio optimisation with options, tackling the three fundamental issues with this problem: asymmetric options' distributions, high dimensionality and dependence structure. To do so, we propose a new…

投资组合管理 · 定量金融 2024-09-10 Jonathan Raimana Chan , Thomas Huckle , Antoine Jacquier , Aitor Muguruza

This paper studies a variable proportion portfolio insurance (VPPI) strategy. The objective is to determine the risk multiplier by maximizing the extended Omega ratio of the investor's cushion, using a binary stochastic benchmark. When the…

综合经济学 · 经济学 2024-03-21 Guohui Guan , Lin He , Zongxia Liang , Litian Zhang

In this work, we introduce Modern Portfolio Theory using basic concepts from linear algebra, differential calculus, statistics, and optimization. This theory allows us to measure the return and risk of an investment portfolio, serving as a…

最优化与控制 · 数学 2024-07-30 Orizon P. Ferreira , Guilherme. A. Franca , Max V. Lemes
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