The hardware technology that underlies computer systems has improved so rapidly and continuously for more than four decades that the ground rules for system design are constantly subject to change. It takes many years for knowledge and experience to be compiled, digested, and presented in the form of a book, so books about computer systems often seem dated or obsolete by the time they appear in print.
Even though some underlying principles are unchanging, the rapid obsolescence of details acts to discourage prospective book authors, and as a result some important ideas are never documented in books. For this reason, an essential part of the study of computer systems is found in current and, frequently, older technical papers, professional journal articles, research reports, and occasional, unpublished memoranda that circulate among active workers in the field.
In an economy with perfectly competitive capital and labor markets, we derive the optimal labor contract for firms with both equity and debt, and show that it implies employees will become entrenched and therefore face large human costs of bankruptcy. The firm’s optimal capital structure emerges from a trade-off between these human costs and the tax benefits of debt. Our model delivers optimal debt levels consistent with those observed in practice without relying on frictions such as moral hazard or asymmetric information. In line with existing empirical evidence, our model implies persistent idiosyncratic differences in leverage across firms, and shows that wages should have explanatory power for firm leverage.
Ever since Modigliani and Miller (1958) first showed that capital structure is irrelevant in a frictionless economy, financial economists have puzzled over exactly what frictions make the capital structure decision so important in reality. Over the years a consensus has emerged that at least two frictions are important: corporate income taxes and bankruptcy costs.
Nowadays, it is well known that investing in Mutual Funds, on average, underperform passive investment strategies. One class commonly called Hedge Funds are defined as pooled investment vehicles that are privately organized, and not widely available to the general investing public. Hedge Funds are private partnerships that use advanced investment strategies and can use derivatives, leverage and short selling. Over the last few years, Hedge Funds have become the favorites of many private as well as institutional investors. Hedge Funds follow investment strategies that are substantially different from the non-leveraged, long-only strategies conventionally followed by investors. During alternative investment seminars and conferences, Hedge Fund managers boast about their ability to produce something they refer to as “alpha”or “absolute return”in the sense that performance is not due to primary asset classes performance. They do not aim to track and try to beat a certain benchmark, but instead are focused on pure return generation. Hence Hedge Funds generate alpha, as opposed to depending on beta and performance should normally result from active management decisions combined with the skills of their advisors. However statistical analysis shows that many of them retain significant exposure to different types of market risk factors.
Consequently, it is essential for qualified investors to determine whether or not these strategies are sensitive to the market and whether they can find alpha through the manager’s skill. For these reasons, an increasing focus has been directed to the performance of Hedge Funds and their factor exposures.
