Payday Loans Magazine

Like the human spirit, ethereal organizational energy exists. Whether or not we are conscious of its influence, it is real and shapes what we do—it gives us a feeling of unity and common purpose.Have you ever seen people rally energy—as when a sports team is winning? We’ve all experienced occasions when team spirit seemed to propel the whole group toward extraordinary performance. On the other hand, maybe you can remember times when your group had low morale and couldn’t perform or lacked the energy to achieve anything noteworthy.

This is an important concept to keep in mind when creating partnerships.For the Partnership Continuum to work, you need to balance the energy in the alliance between the two aspects of partnering: tasks and relationships. If you don’t understand the relationship aspects of the organization, you won’t be able to find the necessary balance in partnering.

In the conceptual phase of the internal assessment, top leadership envisions the purpose, scope, and potential outcomes. Conceptual development must include the interests of those for whom the partnership is being created as well as a spiritual look at the organization. This requires the people involved to look at the organization’s heart and soul as well as its related material aspects.

By understanding the heart and soul of the organization, we become grounded with our internal security and have a foundation for our ethical standards. These ethereal qualities are what enable us to harness and connect the organization’s collective human energy to accomplish tasks—like an electronic grid. This energy motivates, focuses, and moves people in one direction or another. Have you ever walked into an office and felt the tension? The ethereal plane manifests itself in the morale of the organization. When morale is high, people show high productivity and creativity and solve problems easily. When morale is low, people struggle.

If you don’t understand these ethereal, less visible, aspects of the business, you may not understand why the visible aspects are not working very well. When forming a partnership, it’s important to understand them all. And in my experience, it’s actually the unseen aspects that have the greatest impact on an organization’s success. When reviewing the Holistic Organizational Model it is important to recognize the skills required in each realm.When leaders are operating in the ethereal realm they must use their relationship skills, such as those described by the Six Partnering Attributes. These are the relationship skills that enable people to connect to each other and the world around them.When leaders are operating in the material realm they must use managerial skills such as problem solving, process management, or project management. Leaders often confuse these two sets of skills and apply management skills instead of leadership skills when working with people. The same is true in partnerships. Partners must be able to identify and apply the correct set of skills, based on whether the issue is about task (managerial skills) or people (relationship skills).

Traditional approaches to organizational improvement tend to focus on the material realm of the business. They seek to manage the strategies, processes, products, and services the organization believes will most influence the bottom line. Recently the U.S. Postal Service overhauled its strategies and processes to defend itself in the competitive marketplace. But little attention was paid to the relationships between managers and employees. Managers, employees, and their unions acted as if their business was invulnerable. They were wrong. It is the energy of the people that will ultimately determine its success in the marketplace. How did you feel the last time you were in a post office and an indifferent clerk ignored you? This is not to say a business can have bad strategies and processes delivering unwanted goods and services. Rather, the goods and services will reflect on the organization’s ethereal energies—that is, its vision, values, and ethics, and the culture that results.

Because of the different approaches towards risk measurement the composition of the efficient portfolios should differ significantly. Asset classes with more negatively skewed or leptokurtic return distributions are expected to receive lower weightings in the shortfall risk and the Corning–Fisher framework. We will focus on the composition and risk/return profile of three portfolios with very special characteristics. The minimumrisk portfolio (MRP) minimizes the risk subject to the imposed short sales constraint. Furthermore, the tangency portfolio (TP) and an equal risk portfolio (ERP) are examined. The TP maximizes the ratio of excess return over the risk-free rate to portfolio risk, known as the Sharpe ratio. On a depiction of the efficient frontier the TP is determined by a tangency to the efficient frontier through the risk-free rate rf. As suggested by its name the ERP is designed to maximize return for a given level of risk, for example the volatility of a pure government portfolio. From the perspective of a government bond investor, it highlights the opportunity costs of neglecting the return opportunities associated with credits.

Altogether, the adjusted VaR has the desired properties to cope with nonnormal return distributions. Moreover, in conjunction with the correlation matrix of asset returns it allows to calculate the optimal portfolios with an algorithm similar to the quadratic programming algorithm used in the mean–variance framework. For the description of further transformations interested readers may refer to Mina and Ulmer (1999) and Li (2000).

Despite the obvious advantages of the VaR concept, investors should be careful when applying this approach for portfolio optimization. Although VaR fulfils our requirements with respect to reflecting downside risk, Artzner et al. (1997) have shown that it does not comply with one of the basic requirements of a satisfactory risk measure. In mathematical terms, it is not necessarily coherent, meaning that the condition of sub-additiveness is hurt. In other words, under certain circumstances the optimization problem has multiple local solutions. Convergence towards the one and only global optimum cannot be achieved with the usual Newton-style descent algorithms.

The statistical properties of bond returns do not correspond with one of the basic assumptions of modern portfolio theory. As indicated by the descriptive statistics the empirical distributions of bond returns significantly deviate from a normal distribution. Keeping in mind this deficiency we nevertheless provide the results of the classical mean–variance framework as a benchmark in the empirical part of this chapter. As an alternative, two techniques are introduced that explicitly take account of skewness and kurtosis during the process of portfolio construction.

Downside risk measures apply to the intuitive understanding of risk of most investors. They associate risk with below-target returns. Typical targets are “preservation of nominal or real capital invested”. By utilizing below-target returns, lower partial moments are measuring the amount of negative skewness of an empirical distribution.

Our study demonstrates that all of the examined bond indices exhibit negative skewness and excess kurtosis, both of which increase the probability of extreme negative returns. For all asset classes except for the most liquid sector, government bonds, significant autocorrelation is identified in monthly index returns. Therefore, sample estimators of standard deviation, skewness and kurtosis are biased. Hence, the results of common tests for normality of returns should be interpreted carefully. For reason of completeness the results of one test of normality are provided. The Jarque–Bera (1987) test for the normality of observations can only be rejected for the mortgage-backed securities and high-yield sector. However, it should be noted that the distribution of returns of single corporate bond issuers is highly skewed. But the broad diversification on the index level mitigates this effect.

The most important macroeconomic variables which have an effect on high-yield spreads are highlighted as we proceed. The economic cycle has a large impact on the performance of high-yield bonds. High-yield companies have usually either a tight liquidity plan or operate with a high business risk. Small changes to their profit outlook will immediately have an effect on their credit profile. During periods of weak economic growth, spreads in the high-yield market tend to widen.

There is a correlation between the ratings cycle and GDP growth. In strong growth periods the majority of companies will use part of their free cash flows to pay down debt and hence will improve their credit profile. This translates into better credit ratings. In an environment of slow economic growth companies with a weak credit profile will find it difficult servicing their debt and a fast deterioration of their credit profile can occur. We could find a correlation of 56 percent between GDP growth and highyield spreads which is statistically significant. The relationship is not stronger because high yield has a strong component of nonsystematic risk (credit specific risk) rather than systematic risk.

Another way of showing the predominant risks in lower rated (BBB-B) corporate bonds is to observe the price migration over a 1-year horizon after the bond price fell below 90 percent of par for the first time. Consider this study conducted by CSFB for 1247 corporate bonds between 1993 and 2000.and the downside risk faced by every bond investor. In fact, there is a high probability for a bond price to decline further once it has fallen below a certain threshold (e.g. 80 percent of par). This probability increases in a very volatile environment when the risk appetite for credit products is declining.

An important measure for the current state of the high-yield market is also the outstanding total amount split up by price buckets, for example, percentage trading at or above par, between par and 90, 90 and 80, and so on. This is helpful for projections about expected total returns since the two components of total returns are capital appreciation and coupon payments.

Low-priced debt has a more symmetric total return potential but will experience greater standard deviation of total returns.