Portfolio Management Methods Research Articles

A Portfolio of Japanese Equities Weighted by YKS Patent Values

Recently, the value of intangible assets has become increasingly important in estimating the value of an enterprise. In the practical business of asset management, however, compared to the analysis of financial statements, relatively few opportunities exist to quantify intangible assets and thus estimate the value of enterprises. In addition, few passive managers rely on value-weighted intangible assets. In this study, we propose an equities portfolio management method of weighting by patent values, which are calculated by the YKS method developed by Kudo and Associates. Importantly, the method presented here does not use market information or financial statements. The annualized excess return of the YK value-weighted portfolio is 6.1%, which significantly outperforms the market capitalization-weighted portfolio, and there is no extended period of negative underperformance in the periods examined in this study. Most investors are unaware that industries with overweight YK value-weighted portfolios have valuable patents, and that the market capitalization of these sectors may not include the value of these patents’. Our study shows that the annualized average growth rate of the weighted recurring profit of the YKP is higher than the growth rates of the market capitalization-weighted portfolio and a composite of the financial value-weighted portfolio.

Applying technology road‐maps in project selection and planning

PurposeThe purpose of this paper is to show that existing project portfolio management methods have failed to take firms' long‐term strategies into account. To overcome this limitation, it is proposed to suggest technology road‐maps (TRMs) as a tool to assist with project selection and planning.Design/methodology/approachBased on bibliographic and qualitative analysis, the paper develops a systematic process of building TRMs for project portfolio management. The proposed process was applied to the project selection and planning process of a Korean government R&D program.FindingsThe paper finds that the suggested process can support strategic planning by assuring that an organization is implementing the right projects at the right time. During this process, the selection of experts, the flexibility of the process, the periodical updating of the TRM, and TRM standardization are regarded as critical issues for high‐quality technology road‐mapping.Research limitations/implicationsThe approach in the paper does not deal with the cost and profitability aspects of a project as part of its evaluation, nor does it consider complex relations between technologies in different projects.Practical implicationsThe findings in the paper are expected to be helpful in establishing R&D strategy and setting priorities among projects, and in fostering coordination in project implementation.Originality/valueThis paper is one of the earliest attempts to systemize TRM methods specifically for project portfolio management, and is expected to make it easier for companies to adopt and apply TRMs effectively.

Customer portfolio management using Z-ranking of customer segments and the LTV perturbation method

Customer lifetime value (LTV) models have long been used to focus direct marketing campaigns by allocating resources to those customers who are deemed to offer the most value to the company. Traditionally, customers are rank-ordered by their lifetime value and more marketing resources are targeted towards the customers with the greatest value. In this paper, a framework for visualising customer segments, called Z-ranking, is developed, along with a method for customer portfolio management, called the Life Time Value Perturbation Technique. Rather than viewing a customer's LTV as a quantity that is immutable, this framework adopts the point of view that the LTV can be perturbed, via application of appropriate customer management strategies. Through a series of ‘What-if’ scenario analyses, a firm can focus scarce resources on those investments that lead to the greatest increase in the value provided by a customer portfolio. The LTV perturbation technique is further embedded in a four-phase procedure that forms the basis for customer portfolio management, enabling the strategic marketer to continually identify and improve customer management strategies that lead to the greatest impact on direct marketing performance.

Risk Diversification on the Polish Capital Market

The basics of portfolio management theory and methods of efficient selection of assets and their financing have been created by Markowitz and Sharpe. They propose that risk diversification consists, generally speaking, of the increase in the number of securities in a portfolio. So, authors try to answer the question of how many securities have to be bought on a given market to assure a well-diversified portfolio, where the increase in the number of securities does not lead to a significant decrease in portfolio risk. To evaluate such a purpose on the Polish capital market, 20 companies were surveyed that are included in the WIG20 index in the period January 2–October 10, 2001. The returns were estimated on a weekly basis. The research shows that a portfolio of securities constructed, according to the Sharpe Model, has a wide application to the Polish capital market.

Kernel methods for short-term portfolio management

Portfolio optimization problem has been studied extensively. In this paper, we look at this problem from a different perspective. Several researchers argue that the USA equity market is efficient. Some of the studies show that the stock market is not efficient around the earning season. Based on these findings, we formulate the problem as a classification problem by using state of the art machine learning techniques such as minimax probability machine (MPM) and support vector machines (SVM). The MPM method finds a bound on the misclassification probabilities. On the other hand, SVM finds a hyperplane that maximizes the distance between two classes. Both methods prove similar results for short-term portfolio management.

Multi-Moments Method for Portfolio Management: Generalized Capital Asset Pricing Model in Homogeneous and Heterogeneous Markets

We use a new set of consistent measures of risks, in terms of the semi-invariants of pdf's, such that the centered moments and the cumulants of the portfolio distribution of returns that put more emphasis on the tail the distributions. We derive generalized efficient frontiers, based on these novel measures of risks and present the generalized CAPM, both in the cases of homogeneous and heterogeneous markets. Then, using a family of modified Weibull distributions, encompassing both sub-exponentials and super-exponentials, to parameterize the marginal distributions of asset returns and their natural multivariate generalizations, we offer exact formulas for the moments and cumulants of the distribution of returns of a portfolio made of an arbitrary composition of these assets. Using combinatorial and hypergeometric functions, we are in particular able to extend previous results to the case where the exponents of the Weibull distributions are different from asset to asset and in the presence of dependence between assets. In this parameterization, we treat in details the problem of risk minimization using the cumulants as measures of risks for a portfolio made of two assets and compare the theoretical predictions with direct empirical data. Our extended formulas enable us to determine analytically the conditions under which it is possible to have your cake and eat it too, i.e., to construct a portfolio with both return and smaller larger risks.

Portfolio Management in the Social Rented Sector: Valuation, Risk Analysis and Strategy Development

The financial aspects of social housing management are becoming more important for housing associations in Western Europe, due to changes in their economic and institutional context. As part of a trend towards the privatisation and decentralisation of public services, housing associations are becoming more self-reliant. Government financial support is decreasing and parts of the housing market are changing in response to low demand. To ensure that housing associations run an economic, efficient and financially sound business, knowledge of the financial performance of their stock is becoming more important for their investment policy. In the Netherlands, these general changes in housing policy, management and market have been a prominent feature of the last decade, and have resulted in a variety of responses under the general heading of asset and portfolio management. This paper describes methods for valuation, risk analysis and portfolio management for housing associations. The paper sets out the context within which Dutch housing associations operate. Existing methods for valuation and risk analysis are evaluated for their applicability to social landlords. These methods are placed within the business planning process to show how the methods can be used to inform asset management strategy. Finally the paper reflects on the implications for practice in social housing management.

Best Practices for Managing R&D Portfolios

OVERVIEW:R&D portfolio management is a challenging task for most executives. The findings of this study suggest that although many companies are struggling with portfolio management, some organizations are achieving better results in terms of six portfolio performance metrics. Top performers indicated better results on alignment with objectives and strategy, achieving high-value portfolios, cycle time, and portfolio balance. The leaders are using a hybrid approach that combines different traditional approaches; they rely far less on financial methods for portfolio management, and have an explicit and established approach to portfolio management with management buy-in and support.

Robust optimization models for managing callable bond portfolios

A major sector of the bond markets is currently represented by instruments with embedded call options. The complexity of bonds with call features, coupled with the recent increase in volatility, has raised the risks as well as the potential rewards for bond holders. These complexities, however, make it difficult for the portfolio manager to evaluate individual securities and their associated risks in order to successfully construct bond portfolios. Traditional bond portfolio management methods are inadequate, particularly when interest-rate-dependent cashflows are involved. In this paper we integrate traditional simulation models for bond pricing with recent developments in robust optimization to develop tools for the management of portfolios of callable bonds. Two models are developed: a single-period model that imposes robustness by penalizing downside tracking error, and a multi-stage stochastic program with recourse. Both models are applied to create a portfolio to track a callable bond index. The models are backtested using ex poste market data over the period from January 1992 to March 1993, and they perform constistently well.