Hedging in the Possible Presence of Unspanned Stochastic Volatility: Evidence from Swaption Markets

This paper examines whether higher order multifactor models, with state variables linked solely to underlying LIBOR‐swap rates, are by themselves capable of explaining and hedging interest rate derivatives, or whether models explicitly exhibiting features such as unspanned stochastic volatility are necessary. Our research shows that swaptions and even swaption straddles can be well hedged with LIBOR bonds alone. We examine the potential benefits of looking outside the LIBOR market for factors that might impact swaption prices without impacting swap rates, and find them to be minor, indicating that the swaption market is well integrated with the LIBOR‐swap market.     

Managerial judgment and forecast combination: An experimental study

This paper examines the role of managerial judgment in forming a final forecast, or judging the achievability of a critical level of sales, when multiple forecasts or opinions are available to the decision maker. Several factors that can help improve the quality of human intervention are identified and incorporated in a decision aid. Experimental results show that aided combination can help the decision maker exploit her relevant private information and mitigate the generally observed negative effects of human intervention. Further, the results suggest that emphasizing expected sales, even when the organization is primarily interested in go/no-go decisions, helps improve performance. Several suggestions for future research are presented.

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Rural-urban migration,informal sector and development policies: a theoretical analysis

"A theoretical model of rural-urban migration has been developed with special reference to the informal sector. The wage rate and employment in the informal sector are determined endogenously. The paper shows the simultaneous existence of open unemployment and informal sector in the urban area in migration equilibrium. The effects of alternative subsidy policies on unemployment and welfare of the workers are studied." The model is intended primarily for use in analyzing trends and policies in developing countries.     

How does the corporate bond market value capital investments and accruals?

This paper examines whether the mispricing of accruals documented in equity markets extends to bond markets. The paper finds that corporate bonds of firms with high operating accruals underperform corporate bonds of firms with low operating accruals. In the first year after portfolio formation, the underperformance is 115 basis points using an accrual measure that includes capital investments and 93 basis points using an accrual measure that is based only on working capital investments. The Sharpe ratios of the zero-investment bond accrual portfolios are comparable to those of the corresponding zero-investment stock accrual portfolios. The results are also robust to risk adjustments based on both a factor model consisting of the Fama and French (J. Financial Econ 33 (1993) 3) stock and bond market factors and a characteristics model based on bond ratings and duration. Cross-sectional Fama–MacBeth regressions that use individual bond data and control for stock and bond issuances in addition to ratings and duration also confirm the time-series portfolio findings. Overall, our results reveal an accrual anomaly among bonds similar to that observed among stocks.

Inter-firm learning and knowledge-sharing in multinational networks: An outsourced organization's perspective

This research provides insights into how learning and knowledge are exchanged multinationally between customer firms and their outsourced suppliers who provide non-core, yet essential, services. The paper seeks to understand: (1) how information is exchanged in these networks; (2) how cumulative knowledge adds value in these networks; and (3) how boundary-spanners assist in the dissemination of knowledge and learning within the network. Based on a pharmaceutical industry case, the results suggest that: (a) multinational firms operate more effectively and interact by sharing knowledge with outsourced firms which reflect the customers' structure and fit; (b) networked firms benefit from interactions through economies of scope, but knowledge is not necessarily shared equally among partners; (c) learning and knowledge-sharing interactions are tightly coupled at the product development stage; and (d) outsourced firms interact with external boundary-spanners as needed. The research provides insights for managers of multinational organizations and managers of firms from where essential services are outsourced.     

Was the recent downturn in US real GDP predictable?

This article uses a small set of variables – real GDP, the inflation rate and the short-term interest rate – and a rich set of models – atheoretical (time series) and theoretical (structural), linear and nonlinear, as well as classical and Bayesian models – to consider whether we could have predicted the recent downturn of the US real GDP. Comparing the performance of the models to the benchmark random-walk model by root mean-square errors, the two structural (theoretical) models, especially the nonlinear model, perform well on average across all forecast horizons in our ex post, out-of-sample forecasts, although at specific forecast horizons certain nonlinear atheoretical models perform the best. The nonlinear theoretical model also dominates in our ex ante, out-of-sample forecast of the Great Recession, suggesting that developing forward-looking, microfounded, nonlinear, dynamic stochastic general equilibrium models of the economy may prove crucial in forecasting turning points.     

Forecasting US real house price returns over 1831–2013: evidence from copula models

Given the existence of nonnormality and nonlinearity in the data generating process of real house price returns over the period of 1831–2013, this article compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1874–2013, based on an in-sample of 1831–1873. Overall, our results provide overwhelming evidence in favour of the copula models (Normal, Student’s t, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’s t-copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for nonnormality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data.     

Stock market interdependence between Australia and its trading partners: does trade intensity matter?

We investigate the extent and manner of stock market interdependence between Australia and its trading partners and examine whether this is affected by trade intensity. Based on trade intensity, we classify Australia’s trading partners into major, medium and minor partners. We hypothesize that markets with greater (lower) trade intensity will be more (less) interdependent with Australia. We perform correlation (unconditional and conditional) analyses between Australia and its trading partners. Our results indicate that most of the markets that are highly correlated with Australia are its major trading partners. We conduct panel regression analysis to investigate whether trade intensity has any impact on the stock market correlations between Australia and its trading partners. The results show that trade intensity significantly and positively affect the correlations of Australia with its major trading partners. Thus, the results confirm our hypothesis that trade intensity drives stock market interdependence between Australia and its trading partners.     

Understanding consumers' perspectives on food labelling in India

This study aims at identifying the factors influencing consumers' perception on food labelling and its impact on food purchase decision making, through personal interviews of 631 respondents using a structured questionnaire. To analyse the consumers' perceptions on food labelling, factor analysis has been carried out to identify the underlying dimensions among a set of food labelling attributes using the principal component analysis. Based on factor analysis, four sets of components/factors have emerged, that is, (i) serving method; (ii) quality and nutrition; (iii) production and storage; and (iv) product identification, which explain 66.271% of the variance. Logit regression analysis indicates that among the socio‐demographic indicators, the estimated coefficients for gender, education, income and location of residence are statistically significant. Similarly, information on quality and nutrition, production and storage processes, and basic information of the product is found to be significant, implying that these factors are more likely to influence the use of food labels in making informed purchase decisions by the consumers. The findings of the study give practical insights on food labelling issues for the food processors and policy makers.