Testing the Martingale Difference Hypothesis Using Neural Network Approximations

The martingale difference restriction is an outcome of many theoretical analyses in economics and finance. A large body of econometric literature deals with tests of that restriction. We provide new tests based on radial basis function neural networks. Our work is based on the test design of Blake and Kapetanios (2000, 2003a,b). However, unlike that work we can provide a formal theoretical justification for the validity of these tests using approximation results from Kapetanios and Blake (2007). These results take advantage of the link between the algorithms of Blake and Kapetanios (2000, 2003a,b) and boosting. We carry out a Monte Carlo study of the properties of the new tests and find that they have superior power performance to all existing tests of the martingale difference hypothesis we consider. An empirical application to the S&P500 constituents illustrates the usefulness of our new test.Martingale difference hypothesis, Neural networks, Boosting

Testing for Neglected Nonlinearity in Cointegrating Relationships

This paper proposes pure significance tests for the absence of nonlinearity in cointegrating relationships. No assumption of the functional form of the nonlinearity is made. It is envisaged that the application of such tests could form the first step towards specifying a nonlinear cointegrating relationship for empirical modelling. The asymptotic and small sample properties of our tests are investigated, where special attention is paid to the role of nuisance parameters and a potential resolution using the bootstrap.Cointegration, Nonlinearity, Neural networks, Bootstrap

Boosting Estimation of RBF Neural Networks for Dependent Data

This paper develops theoretical results for the estimation of radial basis function neural network specifications, for dependent data, that do not require iterative estimation techniques. Use of the properties of regression based boosting algorithms is made. Both consistency and rate results are derived. An application to nonparametric specification testing illustrates the usefulness of the results.Neural Networks, Boosting

Testing for ARCH in the Presence of Nonlinearity of Unknown Form in the Conditional Mean

Tests of ARCH are a routine diagnostic in empirical econometric and financial analysis. However, it is well known that misspecification of the conditional mean may lead to spurious rejections of the null hypothesis of no ARCH. Nonlinearity is a prime example of this phenomenon. There is little work on the extent of the effect of neglected nonlinearity on the properties of ARCH tests. This paper provides some such evidence and also new ARCH testing procedures that are robust to the presence of neglected nonlinearity. Monte Carlo evidence shows that the problem is serious and that the new methods alleviate this problem to a very large extent.Nonlinearity, ARCH, Neural networks

MAGNITUDE ESTIMATION: AN APPLICATION TO FARMERS' RISK-INCOME PREFERENCES

Magnitude estimation, a technique developed by psychology for obtaining ratio scaled values, was used to derive risk-income preferences of ninety-one central Indiana farmers. Both variability-income and bankruptcy-income measures were developed and related to farmers' socio-economic attributes. Wealth and education had limited effects compared with off-farm employment, percent debt and expected levels of income, percent debt and net worth growth. Magnitude estimation provided reliable estimates of preferences. Farmers gave greater importance to the bankruptcy-income measure of risk-income preferences, but only a small portion of the variation of either measure could be explained.Farm Management, Risk and Uncertainty,

Research Note, July 1972

This is issue 11: The Effect of Piling and Burning Versus Chopping of Logging Residues on Natural Regeneration of Serotinous Lodgepole Pine Forestshttps://scholarworks.umt.edu/montana_forestry_notes/1010/thumbnail.jp

Research Note, November 1969

This is issue 8: A Cost Analysis of the 1967 Hand-Planting Projects in the Northern Rocky Mountain Regionhttps://scholarworks.umt.edu/montana_forestry_notes/1007/thumbnail.jp

Hybridization of Western and Subalpine Larch

Paper published as Bulletin 37 in the UM Bulletin Forestry Series.https://scholarworks.umt.edu/umforestrybulletin/1021/thumbnail.jp

The Electronic Commerce Course: An Early Vision of Learning in a Networked World

This session combines a tutorial on electronic commerce with another on the use of the Internet and world wide web to support teaching and learning. The session provides an opportunity to introduce participants to the use of ISWorld Net for purposes of teaching. In particular, it will rely on one of the deeper knowledge structures within ISWorld Net, the electronic commerce course page (url = http\u27.//www.cox.smu.edu/isworld/ecourse/isw34111.html), and the ECOMMCOURSE discussion list to provide a learning resource center for faculty throughout the world. Together these tools provide an evolving repository of knowledge and a shared community of faculty and advisors. Thus, the tutorial, although focused on the electronic commerce course, should be of interest to any faculty concernedwithensuringthattheyefficientlydesignanddeliverahighqualityeducationalexperiencefortheirstudents. Itwillalso provide an opportunity to reflect on the overarching changes to education that these technologies will engender, in particular, the movement of control to the student and the new openness of all aspects of the education process. The tutorial will consist of the following major sections