Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

Emerging strategy recognition in agile portfolios

Agile practices become increasingly popular for projects and project portfolios offering firms a higher flexibility to adapt to dynamic environments. This study investigates the antecedents and consequences of agile practices' relevance for strategy formulation in project portfolio management processes. Building on complex adaptive systems theory, we hypothesize a positive relationship between agile capabilities and emerging strategy initiatives and eventually portfolio success. Agile capabilities refer to both the project portfolio organization's intensity of and competence in applying agile practices. Using a sample of 135 portfolios and multiple informants for each portfolio, the results support entrepreneurial orientation and voice behavior as antecedents for agile capabilities. Furthermore, the findings support an agile portfolio's positive relationship with emergence recognition and overall portfolio success. The findings contribute to the literature by identifying two significant antecedents of agile capabilities as well as empirically demonstrating the positive relationship between agile portfolios and emerging strategy recognition. For practitioners, the study encourages the application of agile practices by stressing the general positive influence of agile capabilities and underlines entrepreneurial orientation and voice behavior as important methods of empowerment for agile portfolio processes.     

VaR and ES for linear portfolios with mixture of elliptic distributions risk factors

In this paper, we generalize the Linear VaR method from portfolios with normally distributed risk factors to portfolios with mixture of elliptically distributed ones. We treat both the Expected Shortfall and the Value-at-Risk of such portfolios. Special attention is given to the particular case of a mixture of multivariate t-distributions. This is a part of J. SADEFO-KAMDEM PhD Thesis[12] of the Université de Reims, France . It has been presented at the workshop on modelling and computation in Financial Engineering at Bad Herrenalb, Germany May 6-8, 2003. The author is an associate professor at the Department of mathematics, université d’Evry Val d’Essonne.     

考虑限制性卖空的多期模糊投资组合优化模型

在实际证券交易中, 卖空操作是一种重要的投资手段, 因此本文研究考虑限制性卖空的多期模糊投资组合优化问题。将风险资产的收益视为梯形模糊数。在允许卖空的情况下, 建立了带单期最低期望收益约束、破产控制约束和投资比例边界约束的多期可信性均值−下半方差−偏度投资组合优化模型。设计了一个改进的多种群粒子群算法对模型进行求解。最后, 采用真实股票数据进行数值算例分析, 说明了所提出的优化模型和算法的有效性。     

基于配额制的自备电厂参与新能源消纳日前交易模式

国内风电和光伏等新能源发电迅速发展,而部分地区本地消纳和电网外送能力均有限,当地自备电厂未充分发挥调峰作用,出现日趋严重的弃风弃光现象,因此难以完成配额制目标。为利用市场手段充分调动当地自备电厂参与新能源消纳,促进新能源配额制目标的完成,同时避免因强行完成指标导致的社会整体消纳成本升高的问题,提出了一种基于竞价摘牌的新能源日前交易模式。通过具有引导效应的市场化手段,调动具备自备电厂用户的主动消纳意愿,进而提升配额制目标完成度,并降低整体消纳成本。最后,以新疆地区算例为例,分析验证了所提交易模式在提升配额制目标完成度及在尽量降低社会整体消纳成本方面的价值,为新疆等类似地区电力市场建设提供了一种新的思路。     

Maximum principle for mean-field jump–diffusion stochastic delay differential equations and its application to finance

This paper investigates a stochastic optimal control problem with delay and of mean-field type, where the controlled state process is governed by a mean-field jump–diffusion stochastic delay differential equation. Two sufficient maximum principles and one necessary maximum principle are established for the underlying system. As an application, a bicriteria mean–variance portfolio selection problem with delay is studied to demonstrate the effectiveness and potential of the proposed techniques. Under certain conditions, explicit expressions are provided for the efficient portfolio and the efficient frontier, which are as elegant as those in the classical mean–variance problem without delays.     

电袋复合除尘器清灰系统的优化组合

目前，关于电袋复合除尘器清灰系统优化组合的研究很少，而清灰系统是其核心和关键，因此清灰系统的设计对除尘器来说十分重要。本文提出了电袋复合除尘器的清灰系统所面临的问题，并给出了解决方案，从而得出了清灰系统的优化组合。     

An integrated portfolio optimisation procedure based on data envelopment analysis,artificial bee colony algorithm and genetic programming

Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.     

多目标投资组合模型的理想点解法

对多目标证券组合投资模型进行了研究,该模型用于解决多目标线性优化问题,模型以绝对偏差和代替方差、以换手率刻画流动性。研究考虑到了投资者的效用函数,采用理想点法对模型进行了求解,便于实际操作;通过实例分析了该模型的应用价值。     

部分信息下的最优投资选择模型研究

在部分信息下研究了均值方差投资选择模型.投资者只能观察到风险资产的价格,漂移过程用一个高斯过程来刻画.本文的目的是使最终财富期望最大化,而使得最终财富的方差最小.本文模型中有一个债券及股票资产,在部分信息下推导出了最优策略及均值方差有效前沿.