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A two-stage method has been developed for calculating and forecasting the annual volumes of glacial runoff feeding mountainous rivers. At the first stage, the series of morphological characteristics of glaciers are reconstructed using limited data from regional glaciation monitoring. An example of a numerical description and analysis of the annual reconstructed dynamics of glaciation parameters in the upper Rhone River (Switzerland) is presented. Similar results of reconstruction of annual values of the morphological characteristics were obtained for the basins of tributaries of the Terek River (North Caucasus) and the Western Kyzylsu River (Pamir). At the second stage, the calculation and forecast of the time series of the average summer air temperature Ts(Zmean) at the height of Zmean is performed, which is used as an argument for determining the ablation layer by the formula Ab = f(Ts) on the glaciation area Fgl. The annual vertical profiles of mean air temperature of April T4 = T4(Z), summer ones Ts = Ts(Z), and formulas for calculating Ts as a function of T4 are constructed and used for the calculations. Thus, on a regional scale, it was established for the first time that the April air temperature T4 allows calculating a thickness of the annual ablation layer Ab = f(Ts) with a month earliness the forecast at the average height Zmean of the glacier. The reconstructed Fgl(t) series is used to obtain annual volumes of glacial alimentation. A regional study of variability of the index of glacial alimentation δ (Schultz, 1965) with time t was carried out using long-period measurements of runoff in the river basins of Eurasia, North America, Central Europe, and Central Asia. The index δ is equal to the ratio between the volumes W of flow or the average water discharges Q for the periods July-September (Q7–9) and March-June (Q3–6).As a result of the analysis of the expression δ = δ(t), it was found that the gradient of the linear trend equation for the δ index in all the above river basins is negative, which is indicative of a reduction in glacial-snow alimentation, or more precisely – in only its glacial component. Notwithstanding this, the annual runoff Qyear decreased only in three basins, and in the others Qyear, increased due to the growth of Q3–6, which overlapped decreasing of Q7–9. Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.

We examine analysts' forecast timing when issuing negative opinions. When management withholds bad news, good news become more abundant but relatively uninformative. We theoretically predict and empirically document that analysts treat observed bad news as having higher precision and respond to it by issuing forecasts more quickly and accurately than for good news forecasts. These results hold to various robustness checks. This study improves our understanding of negative information dissemination in capital markets. • Financial analysts are rewarded from accuracy as well as the timeliness of their forecasts. • Firms are reluctant to release bad news to markets. • Bad news forecasts by analysts are released earlier and have lower absolute forecast errors than good news forecasts. • Investors consider bad news forecasts by analysts as being more informative and react more strongly to them. [ABSTRACT FROM AUTHOR]

Empirical evidence shows that a significant proportion of analysts issue their forecasts at the time of an earnings announcement (Ivković and Jegadeesh 2004). These forecasts are commonly regarded as analyst interpretations of earnings news contained in the announcement (Schipper 1991). Although analytical studies suggest that market reaction to news from earnings announcement could be affected by analysts' interpretation information (Kim and Verrecchia 1994, 1997), the vast majority of previous research has ignored whether and how these analysts' interpreting forecasts affect the market reaction to the earnings announcements. Our empirical results show that sensitivity of trading volume reaction to earnings announcements is increasing in the number of announcement period analyst forecasts. The sensitivity of trading volume reaction is greater when there is small analyst forecast dispersion. We also find that stock return sensitivity is also increasing with the number of analyst forecasts. In general, our results suggests that analysts' interpretation help disseminate new information contained in earnings announcement to the market. [ABSTRACT FROM AUTHOR]