A Novel Forecasting Model for the Baltic Dry Index Utilizing Optimal Squeezing

Marine transport has grown rapidly as the result of globalization and sustainable world growth rates. Shipping market risks and uncertainty have also grown and need to be mitigated with the development of a more reliable procedure to predict changes in freight rates. In this paper, we propose a new forecasting model and apply it to the Baltic Dry Index (BDI). Such a model compresses, in an optimal way, information from the past in order to predict freight rates. To develop the forecasting model, we deploy a basic set of predictors, add lags of the BDI and introduce additional variables, in applying Bayesian compressed regression (BCR), with two important innovations. First, we include transition functions in the predictive set to capture both smooth and abrupt changes in the time path of BDI; second, we do not estimate the parameters of the transition functions, but rather embed them in the random search procedure inherent in BCR. This allows all coefficients to evolve in a time-varying manner, while searching for the best predictors within the historical set of data. The new procedures predict the BDI with considerable success

Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models.

During the past few years investigators have found evidence indicating that various time-series representing business cycles, such as production and unemployment, may be nonlinear. In this paper it is assumed that if the time-series is nonlinear, then it can be adequately described by a smooth transition autoregressive (STAR) model. The paper describes the application of these models to quarterly logarithmic production indices for 13 countries and "Europe." Tests reject linearity for most of these series, and estimated.STAR models indicate that the nonlinearity is needed mainly to describe the responses of production to large negative shocks such as oil price shocks. Copyright 1992 by John Wiley & Sons, Ltd.

Nonlinear Correlograms and Partial Autocorrelograms

This paper proposes neural network-based measures of predictability in conditional mean, and then uses them to construct nonlinear analogues to autocorrelograms and partial autocorrelograms. In contrast to other measures of nonlinear dependence that rely on nonparametric estimation of densities or multivariate integration, our autocorrelograms are simple to calculate and appear to work well in relatively small samples. Copyright 2005 Blackwell Publishing Ltd.

Uncertainty and Export Performance: Evidence from 18 Countries

We study a sample of nine developed and nine developing countries to evaluate the questions of how foreign income uncertainty and real exchange rate (RER) uncertainty impact international trade and how those impacts vary according to stage of development. RER uncertainty has a negative and significant impact on export growth for six of the nine less developed countries in our sample, while it has an insignificant effect for a majority of the developed countries. In both groups, foreign income uncertainty has a more pervasively significant (and frequently larger) influence on trade than does RER uncertainty. Copyright 2007 The Ohio State University.

A New Econometric Model of Index Arbitrage

"This paper introduces a new econometric model of the mispricing associated with (contemporaneous) differences between spot and futures prices. Like existing models, this model assumes that the level of arbitrage activity is positively related to the magnitude of absolute mispricing. However, unlike existing models, the new model assumes that a parameter governing a key feature of this relationship varies over time. Specifically, several versions of a smooth transition model of mispricing are introduced that each allow the shape of the transition function to be determined by a set of explanatory variables. Using high frequency data from the S&P 500 spot and futures market, the results show that the nature of the non-linearity in mispricing corresponds to arbitrageur behaviour that varies (in a periodic fashion) over the trading day. This is evinced by the superior fit of the new model of mispricing, in comparison to the results based on existing econometric models of mispricing. Finally, the observed periodicity in arbitrageur behaviour indicates that arbitrageurs prefer to trade during certain periods within the trading day - a result that contradicts the findings obtained when using existing econometric models of mispricing." Copyright 2007 The Author Journal compilation (c) 2007 Blackwell Publishing Ltd.