Modelling the frequency and severity of extreme exchange rate returns

Risk managers are often concerned about tail probabilities of asset return distributions, in particular the frequency and severity of extreme returns. In this article, we propose a model that integrates extreme value theory and point processes to model the frequency and severity of exchange rate returns. The proposed model is applied to daily spot exchange rate series and the parameters of interest, such as the tail index, the mean size and rate of occurrence of extreme returns, are estimated using maximum likelihood estimation. We study the impact of recent currency crises on the frequency and severity of the series and find that, during 1995–9, the frequency of extreme daily Japanese yen–US dollar spot exchange rate returns increases twofold, and the time duration of high volatility persists longer for the Japanese yen series than for the Swiss franc and Danish krone series. Copyright © 2001 John Wiley & Sons, Ltd.     

Residual income,non‐earnings information,and information content

We extend Ohlson's (1995) model and examine the relationship between returns and residual income that incorporate analysts' earnings forecasts and other non‐earnings information variables in the balance sheet, namely default probability and agency cost of a debt covenant contract. We further divide the sample based on bankruptcy (agency) costs, earnings components and growth opportunities of a firm to explore how these factors affect the returns–residual income link. We find that the relative predictive ability for contemporaneous stock price by considering other earnings and non‐earnings information is better than that of models without non‐earnings information. If the bankruptcy (agency) cost of a firm is higher, its information role in the firm's equity valuation becomes more important and the accuracy of price prediction is therefore higher. As for non‐earnings information, if bankruptcy (agency) cost is lower, the information role becomes more relevant, and the earnings response coefficient is hence higher. Moreover, the decomposition of unexpected residual income into permanent and transitory components induces more information than that of the unexpected residual income alone. The permanent component has a larger impact than the transitory component in explaining abnormal returns. The market and industry properties and growth opportunity also have incremental explanatory power in valuation. Copyright © 2008 John Wiley & Sons, Ltd.     

Unprotected Drosophila melanogaster telomeres activate the spindle assembly checkpoint

In both yeast and mammals, uncapped telomeres activate the DNA damage response (DDR) and undergo end-to-end fusion. Previous work has shown that the Drosophila HOAP protein, encoded by the caravaggio (cav) gene, is required to prevent telomeric fusions. Here we show that HOAP-depleted telomeres activate both the DDR and the spindle assembly checkpoint (SAC). The cell cycle arrest elicited by the DDR was alleviated by mutations in mei-41 (encoding ATR), mus304 (ATRIP), grp (Chk1) and rad50 but not by mutations in tefu (ATM). The SAC was partially overridden by mutations in zw10 (also known as mit(1)15) and bubR1, and also by mutations in mei-41, mus304, rad50, grp and tefu. As expected from SAC activation, the SAC proteins Zw10, Zwilch, BubR1 and Cenp-meta (Cenp-E) accumulated at the kinetochores of cav mutant cells. Notably, BubR1 also accumulated at cav mutant telomeres in a mei-41-, mus304-, rad50-, grp- and tefu-dependent manner. Our results collectively suggest that recruitment of BubR1 by dysfunctional telomeres inhibits Cdc20-APC function, preventing the metaphase-to-anaphase transition.     

Political manoeuvrings as sources of measurement errors in forecasts

We test the extent to which political manoeuvrings can be the sources of measurement errors in forecasts. Our objective is to examine the forecast error based on a simple model in which we attempt to explain deviations between the March budget forecast and the November forecast, and deviations between the outcome and the March budget forecast in the UK. The analysis is based on forecasts made by the general government. We use the forecasts of the variables as alternatives to the outcomes. We also test for political spins in the GDP forecast updates and the GDP forecast errors. We find evidence of partisan and electoral effects in forecast updates and forecast errors. Copyright © 2005 John Wiley & Sons, Ltd.     

Microdeletions in the human H19 DMR result in loss of IGF2 imprinting and Beckwith-Wiedemann syndrome

The overgrowth- and tumor-associated Beckwith-Wiedemann syndrome results from dysregulation of imprinted genes on chromosome 11p15.5. Here we show that inherited microdeletions in the H19 differentially methylated region (DMR) that abolish two CTCF target sites cause this disease. Maternal transmission of the deletions results in hypermethylation of the H19 DMR, biallelic IGF2 expression, H19 silencing and Beckwith-Wiedemann syndrome, indicative of loss of function of the IGF2-H19 imprinting control element.     

A note on in‐sample and out‐of‐sample tests for Granger causality

This paper studies in‐sample and out‐of‐sample tests for Granger causality using Monte Carlo simulation. The results show that the out‐of‐sample tests may be more powerful than the in‐sample tests when discrete structural breaks appear in time series data. Further, an empirical example investigating Taiwan's investment–saving relationship shows that Taiwan's domestic savings may be helpful in predicting domestic investments. It further illustrates that a possible Granger causal relationship is detected by out‐of‐sample tests while the in‐sample test fails to reject the null of non‐causality. Copyright © 2005 John Wiley & Sons, Ltd.     

Can cointegration‐based forecasting outperform univariate models? An application to Asian exchange rates

Conventional wisdom holds that restrictions on low‐frequency dynamics among cointegrated variables should provide more accurate short‐ to medium‐term forecasts than univariate techniques that contain no such information; even though, on standard accuracy measures, the information may not improve long‐term forecasting. But inconclusive empirical evidence is complicated by confusion about an appropriate accuracy criterion and the role of integration and cointegration in forecasting accuracy. We evaluate the short‐ and medium‐term forecasting accuracy of univariate Box–Jenkins type ARIMA techniques that imply only integration against multivariate cointegration models that contain both integration and cointegration for a system of five cointegrated Asian exchange rate time series. We use a rolling‐window technique to make multiple out of sample forecasts from one to forty steps ahead. Relative forecasting accuracy for individual exchange rates appears to be sensitive to the behaviour of the exchange rate series and the forecast horizon length. Over short horizons, ARIMA model forecasts are more accurate for series with moving‐average terms of order >1. ECMs perform better over medium‐term time horizons for series with no moving average terms. The results suggest a need to distinguish between ‘sequential’ and ‘synchronous’ forecasting ability in such comparisons. Copyright © 2002 John Wiley & Sons, Ltd.