Uncertainty, learning and growth

The paper extends Blackburn and Galindev's (Economics Letters, Vol. 79 (2003), pp. 417-421) stochastic growth model in which productivity growth entails both external and internal learning behaviour with a constant relative risk aversion utility function and productivity shocks. Consequently, the relationship between long-term growth and short-term volatility depends not only on the relative importance of each learning mechanism but also on a parameter measuring individuals' attitude towards risk.

Genetic Algorithm Search for Predictive Patterns in Multidimensional Time Series

Based on an algorithm for pattern matching in character strings, we implement a pattern matching machine that searches for occurrences of patterns in multidimensional time series. Before the search process takes place, time series are encoded in user-designed alphabets. The patterns, on the other hand, are formulated as regular expressions that are composed of letters from these alphabets and operators. Furthermore, we develop a genetic algorithm to breed patterns that maximize a user-defined fitness function. In an application to financial data, we show that patterns bred to predict high exchange rates volatility in training samples retain statistically significant predictive power in validation samples.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Towards an understanding of the causes and effects of software requirements change: two case studies

Changes to software requirements not only pose a risk to the successful delivery of software applications but also provide opportunity for improved usability and value. Increased understanding of the causes and consequences of change can support requirements management and also make progress towards the goal of change anticipation. This paper presents the results of two case studies that address objectives arising from that ultimate goal. The first case study evaluated the potential of a change source taxonomy containing the elements ‘market’, ‘organisation’, ‘vision’, ‘specification’, and ‘solution’ to provide a meaningful basis for change classification and measurement. The second case study investigated whether the requirements attributes of novelty, complexity, and dependency correlated with requirements volatility. While insufficiency of data in the first case study precluded an investigation of changes arising due to the change source of ‘market’, for the remainder of the change sources, results indicate a significant difference in cost, value to the customer and management considerations. Findings show that higher cost and value changes arose more often from ‘organisation’ and ‘vision’ sources; these changes also generally involved the co-operation of more stakeholder groups and were considered to be less controllable than changes arising from the ‘specification’ or ‘solution’ sources. Results from the second case study indicate that only ‘requirements dependency’ is consistently correlated with volatility and that changes coming from each change source affect different groups of requirements. We conclude that the taxonomy can provide a meaningful means of change classification, but that a single requirement attribute is insufficient for change prediction. A theoretical causal account of requirements change is drawn from the implications of the combined results of the two case studies.

Why and how FDI stocks are a biased measure of MNE affiliate activity

Many international business (IB) studies have used foreign direct investment (FDI) stocks to measure the aggregate value-adding activity of multinational enterprises (MNE) affiliates in host countries. We argue that FDI stocks are a biased measure of that activity, because the degree to which they overestimate or underestimate affiliate activity varies systematically with host-country characteristics. First, most FDI into countries that serve as tax havens generate no actual productive activity; thus FDI stocks in such countries overestimate affiliate activity. Second, FDI stocks do not include locally raised external funds, funds widely used in countries with well-developed financial markets or volatile exchange rates, resulting in an underestimation of affiliate activity in such countries. Finally, the extent to which FDI translates into affiliate activity increases with affiliate labor productivity, so in countries where labor is more productive, FDI stocks also result in an underestimation of affiliate activity. We test these hypotheses by first regressing affiliate value-added and affiliate sales on FDI stocks to calculate a country-specific mismatch, and then by regressing this mismatch on a host country's tax haven status, level of financial market development, exchange rate volatility, and affiliate labor productivity. All hypotheses are supported, implying that FDI stocks are a biased measure of MNE affiliate activity, and hence that the results of FDI-data-based studies of such activity need to be reconsidered. [ABSTRACT FROM AUTHOR]

Quantitative and qualitative trapping of volatile methylated selenium species entrained through nitric acid

Quantification and speciation of volatile selenium (Se) fluxes in remote areas has not been feasible previously, due to the absence of a simple and easily transportable trapping technique that preserves speciation. This paper presents a chemo-trapping method with nitric acid (HNO3) for volatile Se species, which preserves speciation of trapped compounds. The recovery and speciation of dimethylselenide (DMSe) and dimethyl diselenide (DMDSe) entrained through both concentrated nitric acid and hydrogen peroxide (H2O2) were compared by HPLC-ICP-MS and HPLC-HG-AFS analyses. It was demonstrated that trap reproducibility was better for nitric acid and a recovery of 65.2 +/- 1.9% for DMSe and 81.3 +/- 3.9% for DMDSe was found in nitric acid traps. HPLC-ES-MS identified dimethyl selenoxide (DMSeO) as the trapped product of DMSe. Methylseleninic acid (MSA) was identified to be the single product of DMDSe trapping. These oxidized derivatives have a high stability and low volatility, which makes nitric acid a highly attractive trapping liquid for volatile Se species and enables reconstruction of the speciation of those species. The presented trapping method is simple, quantifiable, reproducible, and robust and can potentially be applied to qualitatively and quantitatively study Se volatilization in a wide range of natural environments.

Understanding the mismatch between income poverty and deprivation: A dynamic comparative analysis

In this paper we seek to shed light on the mismatch between income poverty and deprivation through a comparative and dynamic analysis of both forms of disadvantage. By extending analysis over five waves of the ECHP we are able to take into account the key dimensions characterizing poverty profiles overtime. Our conclusions turn out to be remarkably stable across countries. While persistent income poverty measures are systematically related to both cross-sectional and longitudinal measures of deprivation, the scale of mismatch is no less at the latter than at the former level. There is some evidence that although rates of volatility for income and deprivation measures are roughly similar, the processes of change themselves are somewhat different. Further light is shed on the underlying processes by cross-classifying the forms of deprivation. Those exposed to both types of deprivation are differentiated from others in terms of need and resource variables. Conclusions relating to the socio-demographic influences on risk levels are influenced by choice and combination of indicators. The results of our analysis confirm the need to devote considerably more attention than heretofore to the analysis of multi-dimensional poverty dynamics.

A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework

This paper proposes a new non-parametric method for estimating model-free, time-varying liquidity betas which builds on realized covariance and volatility theory. Working under a liquidity-adjusted CAPM framework we provide evidence that liquidity risk is a factor priced in the Greek stock market, mainly arising from the covariation of individual liquidity with local market liquidity, however, the level of liquidity seems to be an irrelevant variable in asset pricing. Our findings provide support to the notion that liquidity shocks transmitted across securities can cause market-wide effects and can have important implications for portfolio diversification strategies. ©2012 Elsevier B.V. All rights reserved.

Modified Information Criteria and Selection of Long Memory Time Series Models

The problem of model selection of a univariate long memory time series is investigated once a semi parametric estimator for the long memory parameter has been used. Standard information criteria are not consistent in this case. A Modified Information Criterion (MIC) that overcomes these difficulties is introduced and proofs that show its asymptotic validity are provided. The results are general and cover a wide range of short memory processes. Simulation evidence compares the new and existing methodologies and empirical applications in monthly inflation and daily realized volatility are presented.

The Greek Debt Crisis and Southern Europe: Majoritarian Pitfalls?

Although widely debated in broader socioeconomic terms, the Eurozone crisis has not received adequate scholarly attention with regards to the impact of alternative political systems. This article revisits the debate on majoritarian and consensus democracies drawing on recent evidence from the Eurozone debacle. Greece is particularly interesting both with regards to its potential ‘global spillover effects’ and choice of political system. Despite facing comparable challenges as Portugal and Spain, the country has become polarized socially and politically, seeing a record number of MP defections, electoral volatility and the rise of the militant extreme right. The article explains why Greece, the country that relied most extensively on majoritarian institutions, entered the global financial crisis in the most vulnerable position while subsequently faced insurmountable political and institutional obstacles in its management. The article points to the paradox of majoritarianism: in times of economic stress, the first ‘casualties’ are its strongest elements – centrist parties (bi-partisanship) and cabinet stability.

Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks

In this paper, we re-examine two important aspects of the dynamics of relative primary commodity prices, namely the secular trend and the short run volatility. To do so, we employ 25 series, some of them starting as far back as 1650 and powerful panel data stationarity tests that allow for endogenous multiple structural breaks. Results show that all the series are stationary after allowing for endogenous multiple breaks. Test results on the Prebisch–Singer hypothesis, which states that relative commodity prices follow a downward secular trend, are mixed but with a majority of series showing negative trends. We also make a first attempt at identifying the potential drivers of the structural breaks. We end by investigating the dynamics of the volatility of the 25 relative primary commodity prices also allowing for endogenous multiple breaks. We describe the often time-varying volatility in commodity prices and show that it has increased in recent years.

Optimal Time Series Momentum

We develop a continuous-time asset price model to capture the timeseries momentum documented recently. The underlying stochastic delay differentialsystem facilitates the analysis of effects of different time horizons used bymomentum trading. By studying an optimal asset allocation problem, we find thatthe performance of time series momentum strategy can be significantly improvedby combining with market fundamentals and timing opportunity with respect tomarket trend and volatility. Furthermore, the results also hold for different timehorizons, the out-of-sample tests and with short-sale constraints. The outperformanceof the optimal strategy is immune to market states, investor sentiment andmarket volatility.

Ionic liquids for efficient hydrogen sulfide and thiol scavenging

Functionalised pyridinium and ammonium ionic liquids bearing a Michael acceptor are shown to scavenge H₂S gas and various thiols, in most cases, without the aid of any added bases. Utilising the effective non-volatility of ionic liquids and ‘tagging’ malodourous substances to an ionic matrix renders them odourless.

Time-Varying Liquidity and Momentum Profits

A basic intuition is that arbitrage is easier when markets are most liquid. Surprisingly, we find that momentum profits are markedly larger in liquid market states. This finding is not explained by variation in liquidity risk, time-varying exposure to risk factors, or changes in macroeconomic condition, cross-sectional return dispersion, and investor sentiment. The predictive performance of aggregate market illiquidity for momentum profits uniformly exceed that of market return and market volatility states. While momentum strategies are unconditionally unprofitable in US, Japan, and Eurozone countries in the last decade, they are substantial following liquid market states.