Value, Business and Globalisation – Sketching a Critical Conceptual Framework

Value is a basic concept in economics, ethics and sociology. Locke made labour the source of value, whereas Smith referred to an ideal exchange and Kant specified that commodities only have a market price, no intrinsic value. One can distinguish two modern concepts of value, an economic one trying to explain value in terms of utility, interest or preferences, and an ideal one considering values as ends in themselves. On this basis, Durkheim constructed his theory of value, which was developed by his followers Mauss and Bouglé and further by Bataille. Their line of thought makes it possible to develop a conceptual framework, which can be used to criticise neo-liberalism, big business and the effects of globalisation, while at the same time defending the moral value of business and giving an interpretation of the anti-globalisation protests.     

Choosing the Best Volatility Models: The Model Confidence Set Approach*

This paper applies the model confidence set (MCS) procedure of Hansen, Lunde and Nason (2003) to a set of volatility models. An MCS is analogous to the confidence interval of a parameter in the sense that it contains the best forecasting model with a certain probability. The key to the MCS is that it acknowledges the limitations of the information in the data. The empirical exercise is based on 55 volatility models and the MCS includes about a third of these when evaluated by mean square error, whereas the MCS contains only a VGARCH model when mean absolute deviation criterion is used. We conduct a simulation study which shows that the MCS captures the superior models across a range of significance levels. When we benchmark the MCS relative to a Bonferroni bound, the latter delivers inferior performance.     

A Realized Variance for the Whole Day Based on Intermittent High-Frequency Data

We consider the problem of deriving an empirical measure ofdaily integrated variance (IV) in the situation where high-frequencyprice data are unavailable for part of the day. We study threeestimators in this context and characterize the assumptionsthat justify their use. We show that the optimal combinationof the realized variance and squared overnight return can bedetermined, despite the latent nature of IV, and we discussthis result in relation to the problem of combining forecasts.Finally, we apply our theoretical results and construct fouryears of daily volatility estimates for the 30 stocks of theDow Jones Industrial Average.     

Completion time structures of stock price movements

Summary This paper proposes to model movements in more than a century of daily US stock prices as the outcome of a multi-state marked point process and studies the time it takes for stock prices to complete an up or a down move of a certain size. We present a new econometric specification for a class of dynamic models that account for autoregressive conditional duration effects. We also present a method to account for the effect of time-varying state variables that may change within a duration.We find strong evidence of dynamic dependencies in the direction and speed of stock price movements. Past interest rates are also found to affect the speed and direction of completion times. Out-of-sample prediction results show that forecasts of the direction of moves in stock prices can be greatly improved by including covariates such as interest rates and allowing for dynamics in the econometric specification.We thank an anonymous referee, an associate editor, Rob Engle, Mark Machina and Ruth Williams for helpful conversations. We are grateful to INQUIRE UK for financial support for this research.