Portfolio Optimization under Lower Partial Risk Measures

Portfolio management using lower partial risk (downside risk) measures is attracting more attention of practitioners in recent years. The purpose of this paper is to review important characteristics of these riskmeasures and conduct simulation using four alternative measures, lower semi-variance, lower semi-absolute deviation, first order below targetrisk and conditional value-at-risk.We will show that these risk measures are useful to control downside risk whenthe distribution of assets is non-symmetric. Further, we will propose a computational scheme to resolve the difficultyassociated with solving a large dense linear programming problems resulting from these models. We will demonstrate that this method can in fact solve problems consisting of10⁴ assets and 10⁵ scenarios within a practical amount of CPU time.     

An information-based trade off between foreign direct investment and foreign portfolio investment

The paper develops a model of foreign direct investments (FDI) and foreign portfolio investments (FPI). FDI enables the owner to obtain refined information about the firm. This superiority, relative to FPI, comes with a cost: a firm owned by the FDI investor has a low resale price because of asymmetric information between the owner and potential buyers. The model can explain several stylized facts regarding foreign equity flows, such as the larger ratio of FDI to FPI inflows in developing countries relative to developed countries, and the greater volatility of FDI net inflows relative to FPI net inflows.     

BLACK–SCHOLES REPRESENTATION FOR ASIAN OPTIONS

Asian options are securities with a payoff that depends on the average of the underlying stock price over a certain time interval. We identify three natural assets that appear in pricing of the Asian options, namely a stock S, a zero coupon bond B^T with maturity T, and an abstract asset A (an “average asset”) that pays off a weighted average of the stock price number of units of a dollar at time T. It turns out that each of these assets has its own martingale measure, allowing us to obtain Black–Scholes type formulas for the fixed strike and the floating strike Asian options. The model independent formulas are analogous to the Black–Scholes formula for the plain vanilla options; they are expressed in terms of probabilities under the corresponding martingale measures that the Asian option will end up in the money. Computation of these probabilities is relevant for hedging. In contrast to the plain vanilla options, the probabilities for the Asian options do not admit a simple closed form solution. However, we show that it is possible to obtain the numerical values in the geometric Brownian motion model efficiently, either by solving a partial differential equation numerically, or by computing the Laplace transform. Models with stochastic volatility or pure jump models can be also priced within the Black–Scholes framework for the Asian options.     

Flow Signals: Evidence from Patent and Alliance Portfolios in the US Biopharmaceutical Industry

Integrating signalling theory and the portfolio diversity literature, we theorize that diversity in a firm's patent and alliance portfolios sends contrasting flow signals impacting its market value in a nuanced way. Diversity in an alliance portfolio mediates the patent portfolio diversity – market value relationship by suppressing the negative effect of patent portfolio diversity creating an overall positive effect. We test our mediation model on a longitudinal set of 225 US biopharmaceutical firms that were awarded 17,078 patents and participated in 37,744 alliances between 1990 and 2006. Our theory and findings contribute three novel insights. First, we demonstrate the value of a temporal lens in explaining why diversity in a firm's patent and alliance portfolios send flow signals that establish expectations among market observers and have performance implications. Second, establishing that patent and alliance portfolio diversity are temporally sequenced provides compelling evidence for the value of studying multiple types of portfolios, their temporal relationships and effects on firm outcomes. Third, since diversity in a firm's portfolios can send contrasting flow signals conditioned on the cognitive demands and proximity involved in interpreting the signals, firms that do not maintain a ‘signalling fit’ with market observers increase the probability of unintentional negative signalling effects.     

Why do firms delete brands? Insights from a qualitative study

Large consumer goods firms manage and market an assortment of brands and consistently deal with strategic challenges related to brand portfolio management, such as creating or acquiring brands, growing brand equity, managing brands in the portfolio and deleting brands. There is substantial research on several areas of brand portfolio management except in the area of brand deletion. This situation exists despite the fact that deleting weak brands has important implications for a firm and its brand portfolio. Therefore, it is critical to understand why firms delete brands from their portfolios. This research applies a qualitative approach using semi-structured interviews and thematic analysis in the context of firms that adopt a ‘house of brands’ brand architecture and presents findings guided by the strategic decision-making literature.     

THE NUMÉRAIRE PROPERTY AND LONG‐TERM GROWTH OPTIMALITY FOR DRAWDOWN‐CONSTRAINED INVESTMENTS

We consider the portfolio choice problem for a long‐run investor in a general continuous semimartingale model. We combine the decision criterion of pathwise growth optimality with a flexible specification of attitude toward risk, encoded by a linear drawdown constraint imposed on admissible wealth processes. We define the constrained numéraire property through the notion of expected relative return and prove that drawdown‐constrained numéraire portfolio exists and is unique, but may depend on the investment horizon. However, when sampled at the times of its maximum and asymptotically as the time‐horizon becomes distant, the drawdown‐constrained numéraire portfolio is given explicitly through a model‐independent transformation of the unconstrained numéraire portfolio. The asymptotically growth‐optimal strategy is obtained as limit of numéraire strategies on finite horizons.     

套期保值与企业价值的文献回顾

论文对套期保值与企业价值的理论和实证研究文献作了系统的回顾,全面地归纳和总结了企业套期保值的动因,套期保值同企业价值的关系以及企业利用衍生工具进行套期保值的各种机制。大部分的实证结果表明,套期保值在不同程度上提高了企业的价值。论文的贡献在于对已有的研究方法进行了稳健性分析,并提出进一步的研究方向,包括扩展研究企业套期保值的工具和套期保值的程度;不同套期保值机制及其组合;对实证模型的变量及其关系做进一步的研究和分析;以及将套期保值的成本和损益作为实证模型中的控制变量,以使模型更完整。     

Equally Weighted Strategic Allocation and Balanced Funds in Brazil

This article analyzes equally weighted strategic asset allocation portfolios in Brazil between 2004 and 2016 and shows that their average returns are not always statistically greater than those of balanced funds, with significance changing in sub-periods. Fixed-income portfolios frequently outperform balanced funds, whose active management underperforms their declared benchmark portfolios. Balanced funds underperformed probably because they deviated from their investment policy. Transaction costs and other rebalancing frequencies do not change the conclusions. Robustness tests indicate that this evidence is valid out-of-the-sample. Investors can mimic balanced-fund policy and possibly do better by means of indexing according to this policy.     

Semistatic hedging and pricing American floating strike lookback options

We price an American floating strike lookback option under the Black–Scholes model with a hypothetic static hedging portfolio (HSHP) composed of nontradable European options. Our approach is more efficient than the tree methods because recalculating the option prices is much quicker. Applying put–call duality to an HSHP yields a tradable semistatic hedging portfolio (SSHP). Numerical results indicate that an SSHP has better hedging performance than a delta-hedged portfolio. Finally, we investigate the model risk for SSHP under a stochastic volatility assumption and find that the model risk is related to the correlation between asset price and volatility.