Nowcasting GDP using machine-learning algorithms: A real-time assessment

Can machine-learning algorithms help central banks understand the current state of the economy? Our results say yes! We contribute to the emerging literature on forecasting macroeconomic variables using machine-learning algorithms by testing the nowcast performance of common algorithms in a full ‘real-time’ setting—that is, with real-time vintages of New Zealand GDP growth (our target variable) and real-time vintages of around 600 predictors. Our results show that machine-learning algorithms are able to significantly improve over a simple autoregressive benchmark and a dynamic factor model. We also show that machine-learning algorithms have the potential to add value to, and in one case improve on, the official forecasts of the Reserve Bank of New Zealand.     

Scandals,the mass media,and the politics of extreme visibility: conflict and controversy at the Niagara Parks Commission

This paper explores the political and media scrutiny of management-related activities at the Niagara Parks Commission (NPC) in Niagara Falls, Canada. This commission is the quasi-autonomous body responsible for the operation of tourism-oriented amenities around the Canadian Horseshoe Falls and along the Niagara River. Between 2009 and 2011, the management of the NPC became politically contentious and certain incidents were publicised by the media. There were accusations of impropriety with respect to the use of an expense account, disputes about untendered contracts, and complaints about conflicts of interest. These incidents could be described as scandals, breaches of accepted rules of conduct that are communicated to a wider audience via the mass media. Three dialectical tensions were identified when these scandals were analysed. The tensions, it is argued, are expressions of a wider trend: a politics of extreme visibility. Scandal-related visibility is different from the forms of visibility that have been previously addressed by tourism scholars. Publicity related to alleged misconduct is typically unwanted by tourism managers. Controversies about the management of the NPC demonstrate that practitioners must be alert to the damaging potential of extreme visibility. Fear of scandal, however, may simultaneously stifle enterprise. Managers must strike a careful balance.     

Dividend Policy Irrelevancy and the Construct of Earnings

This paper analyzes the characteristics of earnings in valuation settings where the dividend policy is irrelevant to equity value. The paper first demonstrates an equivalent characterization of dividend policy irrelevancy (DPI) in a general linear dynamic. It then proceeds to show how DPI leads to ideal and practical constructs of earnings and examines their analytical properties. We further demonstrate that earnings properties can be used to deduce the core approach in practical equity valuation – namely, measures of growth in expected earnings explain the price to forward earnings ratio. However, unlike dividends, free cash flow cannot generally be claimed to be irrelevant to value.     

Computation of Multivariate Barrier Crossing Probability and its Applications in Credit Risk Models

Abstract

In this paper we consider computational methods of finding exit probabilities for a class of multivariate diffusion processes. Although there is an abundance of results for one-dimensional diffusion processes, for multivariate processes one has to rely on approximations or simulation methods. We adopt a Large Deviations approach to approximate barrier crossing probabilities of a multivariate Brownian Bridge. We use this approach in conjunction with simulation methods to develop an efficient method of obtaining barrier crossing probabilities of a multivariate Brownian motion. Using numerical examples, we demonstrate that our method works better than other existing methods. We mainly focus on a three-dimensional process, but our framework can be extended to higher dimensions. We present two applications of the proposed method in credit risk modeling. First, we show that we can efficiently estimate the default probabilities of several correlated credit risky entities. Second, we use this method to efficiently price a credit default swap (CDS) with several correlated reference entities. In a conventional approach one normally adopts an arbitrary copula to capture dependency among counterparties. The method we propose allows us to incorporate the instantaneous variance-covariance structure of the underlying process into the CDS prices.     

A Review of: “ECONOMIA DELL'INGEGNERIA By Dino Zanobetti Casa Editrice - Professor Riccardo,Patron Bologna,Italy 1966 408 p.

Recently developed computer programs have greatly enhanced the application of decision analysis, especially in accounting for risk and uncertainty factors. Monte Carlo simulation and decision tree programs are now available from a wide variety of sources for both batch and time-sharing. The major programs, their features and capabilities, are summarized here. A table showing cost, computer requirements and where and how to obtain further information, is also included.