Carnegie Mellon University

About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Population & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.

The Monte Carlo Method

Abstract: This chapter is aimed at describing the Monte Carlo method for the simulation of grain growth and recrystallization. It has also been extended to phase transformations and hybrid versions (Monte Carlo coupled with Cellular Automaton) of the model can also accommodate diffusion. If reading this chapter inspires you to program your own version of the algorithm and try to solve some problems, then we will have succeeded! The method is simple to implement and it is fairly straightforward to apply variable material properties such as anisotropic grain boundary energy and mobility. There are, however, some important limitations of the method that must be kept in mind. These limitations include an inherent lattice anisotropy that manifests itself in various ways. For many purposes, however, if you pay attention to what has been found to previous work, the model is robust and highly efficient from a computational perspective. In many circumstances, it is best to use the model to gain insight into a physical system and then obtain a new theoretical understanding, in preference to interpreting the results as being directly representative of a particular material. Please also keep in mind that the “Monte Carlo Method” described herein is a small subset of the broader use of Monte Carlo methods for which an excellent overview can be found in the book by Landau and Binder (2000).

Optimal Investment, Growth Options, and Security Returns

Abstract: As a consequence of optimal investment choices, a firm's assets and growth options change in predictable ways. Using a dynamic model, we show that this imparts predictability to changes in a firm's systematic risk, and its expected return. Simulations show that the model simultaneously reproduces: (i) the time-series relation between the book-to-market ratio and asset returns; (ii) the cross-sectional relation between book-to-market, market value, and return; (iii) contrarian effects at short horizons; (iv) momentum effects at longer horizons; and (v) the inverse relation between interest rates and the market risk premium. RECENT EMPIRICAL RESEARCH IN FINANCE has focused on regularities in the cross section of expected returns that appear anomalous relative to traditional models. Stock returns are related to book-to-market, and market value.1 Past returns have also been shown to predict relative performance, through the documented success of contrarian and momentum strategies.2 Existing explanations for these results are that they are due to behavioral biases or risk premia for omitted state variables.3 These competing explanations are difficult to evaluate without models that explicitly tie the characteristics of interest to risks and risk premia. For example, with respect to book-to-market, Lakonishok et al. (1994) argue: "The point here is simple: although the returns to the B/M strategy are impressive, B/M is not a 'clean' variable uniquely associated with eco

Industry Life Cycles

Abstract: Evidence on entry, exit, firm survival, innovation and firm structure in new industries is reviewed to assess whether industries proceed through regular cycles as they age. A leading depiction of the evolution of new industries, the product life cycle, is used to organize the evidence it is shown that the product life cycle captures the way many industries evolve through their formative eras, but regular patterns occur when industries are mature that are not predicted by the product life cycle. Regularities in entry, exit, firm survival and firm structure are also developed for industries whose evolution departs significantly from the product life cycle. Opportunities for further research on the nature of industry life cycles and the factors that condition which life cycle pattern an industry follows are discussed. Copyright 1997 by Oxford University Press.

Optimal portfolio and consumption decisions for a “small investor” on a finite horizon

Abstract: A general consumption/investment problem is considered for an agent whose actions cannot affect the market prices, and who strives to maximize total expected discounted utility of both consumption ...