Portfolio Of Financial Assets Research Articles

A Comparative Analysis Of Global Pension Tax Arbitrage

In a company with defined benefit plans, pension assets often represent a sizable portfolio of financial assets. The intention is to examine whether pension tax arbitrage has the potential to add value to the sponsoring corporation with secondary benefits to plan participants, through a less volatile pension fund. To implement the arbitrage, it is recommended that the plans shift all assets to bonds. Replacing stocks with bonds reduces the risk of the firm, and the benefit stems from the creation of an additional tax deduction on the payment of interest with no increase in firm risk.

Governance Risks: How to Measure Them by Means of the Incremental Cash-Flow Model

Governance risks stem from the own governance of any organization. The paper puts forward an operational viewpoint of those risks, by mapping the most distinctive categories of governance analysis onto time-dependent governance variables.Afterwards, risks conveyed by the latter are measured against incremental cash flows. The procedure allows a joint analysis of the risky positions carried out by governance variables, tracking them down onto their natural drivers, the incremental cash flows related to assets, creditors, managers, stockholders, and the company’s portfolio of non-current financial assets

Avaliação de fundos de investimento utilizando o Índice de Sharpe AR-GARCH-M

The Sharpe ratio, a well known and widely used measure for ex post facto performance evaluation of diversified financial asset portfolios, has an important limitation, the assumption of normally and independently distributed (NID) daily excess log-returns. This paper proposes an econometric Sharpe ratio and an estimation method derived from an AR-GARCH-M model. The proposed Sharpe ratio is compared to the standard Sharpe ratio. Daily log-returns of mutual funds in the Brazilian market were used and Sharpe ratios were estimated for each. The Spearman rank correlation coefficient between proposed and standard Sharpe ratios was found to be positive, but the ratios led to different conclusions about the performance of the funds. The proposed Sharpe ratio relaxes the NID hypothesis for log-returns and includes as stylized facts conditional heteroskedasticity, autocorrelation and dependence between log-return and

Role of farm real estate in a globally diversified asset portfolio

PurposeThis paper seeks to examine the benefits of further diversifying a global portfolio of financial assets with New Zealand farm real estate (FRE).Design/methodology/approachThe paper compares efficient sets generated with and without FRE using portfolio theory.FindingsThe results show that given the predominantly negative correlation between FRE and financial assets, the risk‐return tradeoffs of portfolios of financial assets can be improved significantly. The diversification benefits measured in terms of risk reduction, return enhancement, and improvement in the Sharpe performance ratios are robust under a number of FRE risk‐return scenarios as well as under high and low inflationary periods. Using five and ten‐year rolling periods it also finds that FRE is a consistent part of risk efficient portfolios. Consistent with the results reported in Lee and Stevenson, for the UK real estate the risk reduction benefits of diversifying with FRE are larger than the risk enhancement benefits.Practical implicationsThe results suggest that FRE takes on a consistent role of risk‐reducer rather than a return‐enhancer in a globally diversified portfolio. FRE appears to deserve more serious consideration by investment practitioners that it has been accorded in the past.Originality/valueThe study examines the role of direct real estate in a globally diversified portfolio of financial assets.

Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models

The management and monitoring of very large portfolios of financial assets are routine for many individuals and organizations. The two most widely used models of conditional covariances and correlations in the class of multivariate GARCH models are BEKK and DCC. It is well known that BEKK suffers from the archetypal “curse of dimensionality,” whereas DCC does not. It is argued in this paper that this is a misleading interpretation of the suitability of the two models for use in practice. The primary purpose of this paper is to analyze the similarities and dissimilarities between BEKK and DCC, both with and without targeting, on the basis of the structural derivation of the models, the availability of analytical forms for the sufficient conditions for existence of moments, sufficient conditions for consistency and asymptotic normality of the appropriate estimators, and computational tractability for ultra large numbers of financial assets. Based on theoretical considerations, the paper sheds light on how to discriminate between BEKK and DCC in practical applications.

CSR, rationality and the ethical preferences of investors in a laboratory experiment

This experimental study aims to clarify to what extent and in which direction investors react to CSR (Corporate Social Responsibility) initiatives meant to upgrade the ethical standards of firms beyond the minimal requirements of law. Subjects in the laboratory were invited to invest their endowment in a portfolio of financial assets. We provided information on the expected returns of each stock and on its inclusion in an ethical index, or exclusion from it. Our findings show that subjects’ behavior appears to be a function not only of their individual pay-offs but also of the information on the ethical standards of the firms issuing stocks. Most of them, however, did not show a fully irrational behavior as they consistently correlated the share of stocks with their expected returns. We may conclude that the sizeable reaction of our investors to the inclusion of a stock in the ethical index, or its exclusion from it, is the fruit of a deliberate choice.

Dynamic Conditional Correlation Models in a Multiple Financial Asset Portfolio

A key concept in risk and portfolio management is diversification, which has recently come under intense scrutiny following dramatic market movements where historical correlation patterns have collapsed. To counter the devastating effects from these coordinated sell-off events, academics have developed several models to forecast correlation. This article examines two recent dynamic conditional correlation models: an asymmetric dynamic conditional correlation (ADCC) model and a dynamic equicorrelation (DECO) model. Previous research has demonstrated the merits of these advanced models in an artificial setting, but a study in a high-dimensional, though still artificial, setting was inconclusive on the merits. This article casts doubt on the merits of these models in a real-world setting. The results show that neither the ADCC model nor the DECO model provides any additional information over a sample-based approach when evaluated using a simple parametric covariance-variance value at risk (VaR) measurement. Used in risk monitoring, the models provide sound risk estimates but no additional insights into forecasting correlation spikes.

Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models

Large and very large portfolios of financial assets are routine for many individuals and organizations. The two most widely used models of conditional covariances and correlations are BEKK and DCC. BEKK suffers from the archetypal curse of dimensionality whereas DCC does not. This is a misleading interpretation of the suitability of the two models to be used in practice. The primary purposes of the paper are to define targeting as an aid in estimating matrices associated with large numbers of financial assets, analyze the similarities and dissimilarities between BEKK and DCC, both with and without targeting, on the basis of structural derivation, the analytical forms of the sufficient conditions for the existence of moments, and the sufficient conditions for consistency and asymptotic normality, and computational tractability for very large (that is, ultra high) numbers of financial assets, to present a consistent two step estimation method for the DCC model, and to determine whether BEKK or DCC should be preferred in practical applications.

How to Select the Best Portfolio of Oil and Gas Projects

Abstract The traditional analytical tool for selecting portfolios of financial assets is Markowitz's mean-variance model. The final product of this model is the efficient frontier. Markowitz's approach comes up with an infinite set of optimal portfolios in terms of risk and return (called the efficient frontier), but the mean-variance model does not recommend the best portfolio. This paper proposes an extension of the mean-variance model by the inclusion of a three-step approach:an estimation of the risk and return of each project;the estimation of a correlation between returns of each pair of selected prospects; and,the inclusion of corporate goals beyond simple economic return; that is, budget and operational constraints. We show that the selection of the optimal portfolio depends on the diversification level of the investor and the costs of financial distress faced by the oil company. Introduction The oil industry has currently been facing high volatility in price, plus technological and geological uncertainties that reduce cost predictability. Since these uncertain factors are all present in most oil and gas projects, they represent a clear motivation for the development of new tools for improving the rationality of decisions in the process of capital allocation. Some of these tools are for the selection of the best portfolio of upstream projects when the main difference between any two portfolios is risk and return. At this point, we wish to make it clear that the screening or selection of oil projects is a previous step and will not be considered in this paper. We assume that the problem consists of finding the best portfolio of already screened oil and gas projects. Not long ago, the selection of portfolios was based on indicators such as ranking and cut, internal rate of return and payback period. When we use any or all of these indicators, the conflicting, but necessary, risk-return trade-off is not considered, so that the optimal decision could have a very high return. On the other hand, however, its risk level may be unsupportable by management. In the past, in the job of finding and producing hydrocarbons, risk was always present, but there was not a systematic pressure policy towards its understanding, modelling and quantification. Presently, in most oil and gas companies, management is not only under pressure to deliver good indicators for the shareholders, but also to estimate the associated risk level. In the context of this paper we consider risk analysis as an integration of three steps. First is the identification of uncertain variables. Second is the probabilistic modelling of these uncertain variables. Third is the use of Monte Carlo simulation in order to get the frequency distribution of response variable, such as net present value (NPV). One reason for the widespread demand for risk analysis in the upstream industry is that trends of resource availability have pointed out that the largest remaining reserves of hydrocarbons are primarily situated in ultra-deep environments where the potential for return is higher but the risk is also huge.

Global optimization of higher order moments in portfolio selection

We discuss the global optimization of the higher order moments of a portfolio of financial assets. The proposed model is an extension of the celebrated mean variance model of Markowitz. Asset retur...

Engineering and contracting projects: A value at risk based approach to portfolio balancing

The approach proposed focuses on the bid/no bid decision linked to the portfolio management issue for an Engineering and Contracting company. A first step is the transposition of the financial concept of Value at Risk to the world of Engineering and Contracting projects. The distribution of the project Net Present Value over the project lifecycle has been considered, in a similar way as the distribution of return for a portfolio of financial assets over a specified time horizon, in order to define a synthetic measure of risk for an Engineering and Contracting project. The second step is the use of measures of risk based on the Value at Risk concept to support bid no bid decision-making processes in order to obtain a better balancing of the overall portfolio of projects for a company operating in the Engineering and Contracting industry. The proposed framework has been tested as a decision support tool on a power plant project.

Inside Information and the Own Company Stock Puzzle

U.S. investors allocate 30–40% of their financial asset portfolio in the stock of the company they work for. Such a portfolio flies in the face of standard portfolio theory, which prescribes that an investor should hold less of a financial asset that is positively correlated with her undiversified labor income. Nevertheless, we propose a rational explanation that prescribes a long position in own company stock. Precisely because the own company stock is positively correlated with the investor's labor income, any information the investor learns about her earnings is a partial information advantage in her own company stock. When confronted with a choice of what information to acquire, employees may choose to learn about their own firm. Learning lowers the employee's risk of holding own-firm equity, which raises its risk-adjusted returns and makes a long position optimal. (JEL: F30, G11, D82)

Risk estimation using the multivariate normal inverse Gaussian distribution

Appropriate modeling of time-varying dependencies is very important for quantifying financial risk, such as the risk associated with a portfolio of financial assets. Most of the papers analyzing financial returns have focused on the univariate case. The few that are concerned with their multivariate extensions are mainly based on the multivariate normal assumption. The idea of this paper is to use the multivariate normal inverse Gaussian (MNIG) distribution as the conditional distribution for a multivariate GARCH model. The MNIG distribution belongs to a very flexible family of distributions that captures heavy tails and skewness in the distribution of individual stock returns, as well as the asymmetry in the dependence between stocks observed in financial time series data. The usefulness of the MNIG GARCH model is highlighted through a value-at-risk (VAR) application on a portfolio of European, American and Japanese equities. Backtesting shows that for a one-day holding period this model outperforms a Gaussian GARCH model and a Student’s t GARCH model. Moreover, it is slightly better than a skew Student’s t GARCH model.

Single-Family Housing and Wealth Portfolios

Executive Summary. This paper explores the risk and return of a portfolio of single-family housing during 1978:1-2001:4 in the context of a portfolio of financial assets. Homeownership offers higher returns to those who have higher tax brackets, longer investment horizons and use more financial leverage. Housing returns are positively correlated with large-stock returns and negatively correlated with returns on small stocks and debt securities. Portfolio allocation to housing is large in a minimum variance portfolio, and it increases with longer holding periods and higher tax brackets. Homeownership risk and return vary widely among the forty-two MSAs studied, and within an MSA, housing returns exhibit substantial variation.

The value of language: concept, perspectives, and policies

PurposeThree distinct trends are evolving that characterize the challenges facing corporate planners in managing language as a corporate asset. These are the evolution of the knowledge economy, the globalization of business and economy, and the increasing diversity of the workforce. These trends call for attention to the role language plays in the creation of intellectual and organizational capital. Linguists have been hampered by their inability to model how linguistic conditions affect economic processes. They have long attempted to assess the economic value of language as a commodity, but with little success. The purpose of this article is to describe language as an asset, and argue that recent advances in decision sciences have sufficiently removed the deficit in theoretical and empirical research that challenged the linguists.Design/methodology/approachDrawing an analogy between language and currency, this article identifies the functions that language must perform in terms of exchange, accounting and storage of information, knowledge and know‐how.FindingsFactors that contribute to the value of a language are discussed through comparative analysis of these functions from the perspectives of linguists, economists and decision analysts. Based on the Social Judgment Theory, the article develops a judgment‐analytic framework for the assessment of the value of a language.Practical implicationsConcluding that the corporate and community planning perspectives are divergent, the paper identifies the direction for future research to inform formulation of language policies. The value of a language may be affected by the degree to which the language is used in the demographic community defining an organization's strategic environment, the investment in the language relative to other available languages, demand for the language as a commodity within the organization's strategic community, and so on.Originality/valueWith such conception of language, corporations can begin to think in terms of a portfolio of language assets much in the same way as it thinks of portfolio of financial currency assets.

Using Extreme Value Theory to Model Electricity Price Risk with an Application to the Alberta Power Market

Value-at-risk (VaR) is a measure of the maximum potential change in value of a portfolio of financial assets with a given probability over a given time horizon. VaR has become a standard measure of market risk and a common practice is to compute VaR by assuming that changes in value of the portfolio are conditionally normally distributed. However, assets returns usually come from heavy-tailed distributions, so computing VaR under the assumption of conditional normality can be an important source of error. We illustrate in our application to competitive electric power prices in Alberta, Canada, that VaR estimates based on extreme value theory models, in particular the generalized Pareto distribution are, more accurate than those produced by alternative models such as normality or historical simulation.

Risk and Return Properties of Portfolios Based on Directional Forecasts

In this study, a formula is derived for the period specific beta (market risk) for a portfolio of financial assets that has been formed on the basis of directional forecasts. This is an important contribution to the literature since measuring the risk of an actively managed portfolio is problematic due to the fact that managers may change fund risk conditional on market expectations. The period‐specific nature of the measure is a significant advantage since historical fund returns are not required and the beta is not influenced by prior fund returns' deviations from the bench mark. The methodology employed allows for the development of a time series of fund betas that permits investigation into a number of important empirical issues. This study is also of practical interest from the perspective of risk management and for both portfolio performance and attribution. Finally, there are many active strategies based on directional forecasts and the approach used here encompasses a significant proportion of these.

The Effect of Misestimating Correlation on Value at Risk

Value at risk (VaR) is an estimate of the worst loss over a target horizon with a given level of confidence. Despite its shortcomings, the Basel Committee on Banking Supervision has chosen it as the standard method to measure the market risk of a portfolio of financial assets. This measure of risk is widely used by practitioners and regulators because of its conceptual simplicity and flexibility. This article examines the systematic relationship between correlation misestimation and the corresponding value-at-risk miscalculation. To this end, first a semi-parametric approach, and then a parametric approach is developed. Both approaches are based on a simulation setup. Various linear and non-linear portfolios are considered, as well as variance-covariance and Monte-Carlo simulation methods are employed. Results show that the VaR error increases significantly as the correlation error increases, particularly in the case of well-diversified linear portfolios. In the case of option portfolios, this effect is more pronounced for short-maturity, in-the-money options. The use of MC simulation to calculate VaR magnifies the correlation bias effect. These results have important implications for measuring market risk accurately.

How does political violence affect confidence in a local currency? Evidence from Egypt

In this paper we estimate a time-series model of the financial asset portfolio shares in Egypt, distinguishing between assets of varying degrees of liquidity and between domestic currency and foreign currency deposits. While financial liberalization and financial stability are found to have encouraged domestic residents to increase the share of their portfolio composed of domestic currency assets, these effects have been offset by an increase in the number of violent political incidents arising from conflict between radical Islamic groups and the Egyptian state. Greater violence has led to lower domestic asset demand and substitution into foreign currency deposits. The link between political events and financial outcomes provides a rationale for economic policy interventions by Bretton Woods institutions in response to increases in political instability. Copyright © 2005 John Wiley & Sons, Ltd.

Major Policy Challenges in Trade and Finance in the Asia-Pacific Region

By every measure, the Asia-Pacific region is extremely important not only for the world economy, but for Korea as well. Given this importance, the paper identifies two major policy issues to be addressed by countries in this region. In trade, the recent proliferation of regional trading arrangements poses a serious threat to the continuation of economic growth in the region. In finance, the lack of capaciry of the financial system in East Asia in particular has given rise to an unhealthy portfolio of financial assets held by East Asian countries. The policy suggestions by the author include the strengthening of the WfO discipline on regional trading arrangements and closer financial cooperation among countries in the Asia-Pacific.