There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This paper proposes a very tractable approach to modeling changes in regime. The parameters of an autoregression are viewed as the outcome of a discrete-state Markov process. For example, the mean growth rate of a nonstationary series may be subject to occasional, discrete shifts. The econometrician is presumed not to observe these shifts directly, but instead must draw probabilistic inference about whether and when they may have occurred based on the observed behavior of the series. The paper presents an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter

A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Machine Learning : A Probabilistic Perspective

Forecasting with artificial neural networks: the state of the art

Recurrence plots for the analysis of complex systems

In Enelow and Hinich (1982, 1984a), the spatial theory of elections is augmented to incorporate nonspatial candidate characteristics in the voter's candidate evaluations. In this extension, nonpolicy characteristics are represented by an additive term independent of the policy portion of the voter's evaluation. In Grofman (1985), an interactive voting model is introduced, in which nonpolicy characteristics affect the voter's evaluation of the candidate only through the candidate's policy positions. An empirical question is raised by these two contrasting approaches: do nonpolicy candidate qualities affect voter choice independently of candidate policies, interactively with candidate policies, or through both means? This paper is designed to answer that question. An extended form of the Enelow-Hinich model is specified with both main and interaction terms. The model is then used to predict voter choice in the 1972, 1976, and 1980 presidential elections. Statistical evidence for the existence of interaction...

An Empirical Evaluation of Alternative Spatial Models of Elections

The present study proposes the use of nonlinear serial dependencies in the returns series for assessing market responses to new information. Unlike the standard event study methodology, this paper advocates a reserve form that let data analysis to first detect those periods with significant nonlinearity, and then identify whether their occurrences can be associated with major economic or political events. Our proposed research framework involves the application of the Hinich (1996) portmanteau bicorrelation test statistic in a moving time windows setting. Using the Malaysian stock market as a case study, our empirical application is able to detect not only the presence of nonlinear serial dependencies in the KLCI intraday ten-minute returns, but also the time periods when they occurred. The next stage of event-matching managed to identify major events that unsettled the local stock market in all cases except one. In particular, the Russian crisis, the unorthodox capital control measures and the Brazilian crisis are found to be responsible for the short burst of nonlinear behavior. However, the paper noted that factors that shook the market need not be news announcement in the media. It could be due to, among others, rumors, speculations, expectations, or worries prevail in the investment communities.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID912603_code635857.pdf?abstractid=912603

Events that Shook the Market: An Insight from Nonlinear Serial Dependencies in Intraday Returns

Analytical politics: Glossary

This article advocates a particular view regarding modeling aggregation methodology. That view is perhaps best represented within the federal government by the activities of the research staff at the Bureau of Labor Statistics (BLS). Within academic research circles, the view is maintained by aggregation and index number theorists as well as by a growing number of microfoundations and rational expectations theorists. The intent of the approach is to assure that the construction of data and its use within models are all internally consistent with rational optimizing behavior by economic agents. We advocate the application of this modern approach to data construction, model specification, and model estimation in monetary economics.

Monitoring Monetary Aggregates Under Risk Aversion

This study employs the Hinich portmanteau bicorrelation test (Hinich 1996; Hinich and Patterson 1995) as a diagnostic tool to determine the adequacy of Generalised Autoregressive Conditional Hetero...

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Melvin J. Hinich

Papers

An Empirical Evaluation of Alternative Spatial Models of Elections

Events that Shook the Market: An Insight from Nonlinear Serial Dependencies in Intraday Returns

Analytical politics: Glossary

Monitoring Monetary Aggregates Under Risk Aversion

Statistical Inadequacy of GARCH Models for Asian Stock Markets: Evidence and Implications