Methodological aspects of evaluating a company’s investment attractiveness

The actual problems of choosing tools for risk assessment and predicted profitability (attractiveness) of an investment object are studied. There is a close relationship between the financial multipliers DIV/FCF, P/E Shiller, EV/EBITDA and risk indicators, which gives the investor the opportunity to make additional operational forecasts when analyzing an investment project. A number of key financial multipliers (P/S, EV/S, P/OCF, P/FCF) have been identified, and it is not entirely correct to use them as criteria for making an investment decision. The expediency of using the EV/EBITDA multiplier for making forecasts about the volatility of the return on shares of a certain company is justified, since this is the only indicator among the financial multipliers selected for analysis that has a relationship with the beta coefficient. Recommendations for forming a sample of necessary indicators (multipliers) when making investment decisions by various stakeholders are proposed.

Present operational long range forecasting system for southwest monsoon rainfall over India and its performance during 2010

At present, India Meteorological Department (IMD) issues various monthly and seasonal operational forecasts for the south-west monsoon season using models based on latest statistical techniques with useful skill. Operational models are reviewed regularly and improved through in house research activities. For the forecasting of the south-west monsoon season (June – September) rainfall over the country as a whole, a newly introduced statistical ensemble forecasting system is used. In addition, models have been developed for the forecast of the monsoon season rainfall over four geographical regions (NW India, NE India, Central India and South Peninsula) of the country and forecast for the rainfall over the second half of the monsoon season over the country as a whole. Models have also been developed for issuing operational forecast for the monthly rainfall for the months of July, August & September over the country as a whole. Operational forecasts issued by IMD for 2010 south-west monsoon rainfall have been discussed and verified. In addition, the experimental forecasts for the season rainfall over the country as a whole based on bothstatistical and dynamical models received from various climate research institutes within the country other than IMD arealso discussed. The operational monthly and seasonal long range forecasts issued for the 2010 southwest monsoon season for the country as a whole were accurate. However, forecasts for the season rainfall over the 4 geographical regions (Northwest India, Central India, Northeast India and south Peninsular India) were not accurate as the forecast for South Peninsular India overestimated the actual rainfall and that for northeast India underestimated the actual rainfall. The experimental forecasts for the season rainfall over the country as whole from various climate research institutes within the country showed large variance (91 % - 112% of LPA).

Self-limiting earthquake dynamics and spatio-temporal clustering of seismicity enabled by off-fault plasticity

Earthquakes are among nature’s deadliest and costliest hazards. Understanding mechanisms for earthquake nucleation, propagation, and arrest is key for developing reliable operational forecasts and next generation seismic hazard models. While significant progress has been made in understanding source processes in linear elastic domains, the response of the rocks near the fault is complex and likely to be inelastic due to the extreme stresses and deformations associated with fault slip. The effect of this more realistic fault zone response on seismic and aseismic fault slip is poorly understood. Here, we simulate sequence of earthquake and aseismic slip of a fault embedded in an elastic-viscoplastic bulk subject to slow tectonic loading. We show that off-fault plasticity significantly influences the source characteristics. Specifically, off-fault plasticity may lead to partial ruptures and emergence of spatial segmentation as well as hierarchical temporal seismic clustering. Furthermore, co-evolution of fault slip and off-fault bulk plasticity may lead to heterogeneous rupture propagation and results in pockets of slip deficit. While the energy dissipated through plastic deformation remains a small fraction of the total energy budget, its impact on the source characteristics is disproportionally large through the redistribution of stresses and viscous relaxation. Our results suggest a new mechanism of dynamic heterogeneity in earthquake physics that can be active for both small and large earthquakes and may have important implications on earthquake size distribution and energy budget. Furthermore, this plasticity-induced self-limiting crack dynamics may be relevant for other dynamic fracture applications and design of dynamically tough materials.

Refining an ensemble of volcanic ash forecasts using satellite retrievals: Raikoke 2019

Volcanic ash advisories are produced by specialised forecasters who combine several sources of observational data and volcanic ash dispersion model outputs based on their subjective expertise. These advisories are used by the aviation industry to make decisions about where it is safe to fly. However, both observations and dispersion model simulations are subject to various sources of uncertainties that are not represented in operational forecasts. Quantification and communication of these uncertainties are fundamental for making more informed decisions. Here, we develop a data assimilation technique which combines satellite retrievals and volcanic ash transport and dispersion model (VATDM) output, considering uncertainties in both data sources. The methodology is applied to a case study of the 2019 Raikoke eruption. To represent uncertainty in the VATDM output, 1000 simulations are performed by simultaneously perturbing the eruption source parameters, meteorology and internal model parameters (known as the prior ensemble). The ensemble members are filtered, based on their level of agreement with Himawari satellite retrievals of ash column loading, to produce a posterior ensemble that is constrained by the satellite data and its uncertainty. For the Raikoke eruption, filtering the ensemble skews the values of mass eruption rate towards the lower values within the wider parameters ranges initially used in the prior ensemble (mean reduces from 1 Tg h−1 to 0.1 Tg h−1). Furthermore, including satellite observations from subsequent times increasingly constrains the posterior ensemble. These results suggest that the prior ensemble leads to an overestimate of both the magnitude and uncertainty in ash column loadings. Based on the prior ensemble, flight operations would have been severely disrupted over the Pacific Ocean. Using the constrained posterior ensemble, the regions where the risk is overestimated are reduced potentially resulting in fewer flight disruptions. The data assimilation methodology developed in this paper is easily generalisable to other short duration eruptions and to other VATDMs and retrievals of ash from other satellites.

Methodological Approaches to Forecasting Bread Prices in Ukraine

The article examines the current state of the bread and bakery market in Ukraine on the basis of the exponential smoothing method. An important aspect of the analysis of the bakery industry state is the issue of pricing for the number one product in Ukraine – bread and bakery products. The purpose of this study was to analyze the level of bread prices in the regional context, to identify trends and factors influencing them and to propose models on the basis of which it is advisable to make operational forecasts of bread prices. The study was performed on the basis of monitoring data of average consumer prices for wheat bread from first grade flour by months of 2017 and 2018 in the selected regions, Kyiv and Ukraine as a whole. The choice of areas is done due to their territorial location, and the choice of bread type – due to steady popularity among consumers. The dynamics of product prices, in particular in the regional aspect, was analyzed. The example of wheat bread made from first grade flour shows significant differences in the price level for these products by regions. Trends in price changes and their dependence on such factors as the price of flour, the price of gasoline A-95, wages have been identified. The expediency of using for the estimation of bread prices of models based on series of dynamics by exponential smoothing is shown. High accuracy of the received models is confirmed. The proposed approach in this study can be used by industry to construct models of product price forecasting as a benchmark for making management decisions about the real price. Performing these calculations online on a computer will provide businesses with particular advantages over their competitors, as well as the ability to plan their economic performance at the desired level

THE ROLE OF TECHNOGENIC IMPACT IN THE DEVELOPMENT OF DANGEROUS GEOLOGICAL PROCESSES IN THE MOUNTAIN REGIONS OF THE NORTHERN CAUCASUS

The article presents an assessment of technogenic impact on the development of hazardous geological processes in the mountainous regions of the Northern Caucasus in the current century. Technogenic impact is determined by the stability of rock formations that make up the Krasnodar Territory, Kabardino-Balkaria, and North Ossetia relative to the impacts of other forces. It is also noted that the activity of hazardous geological processes is largely determined by the interaction of climatic conditions, which determine their speed, and technogenesis. Examples of problematic territories of the North Caucasus are given. To assess climatic changes and major catastrophes, a typology of atmospheric circulation in the Northern Hemisphere was developed under the leadership of B.L. Dzerdzeevsky. Typification materials from the period between 1899 and 2018 are posted in the public domain, at www.atmospheric-circulation.ru. The largest catastrophes, in which landslides and mudflows became more active, and the interaction of natural and man-made factors in these disasters are considered.Hazardous geological processes can disrupt the sustainable development of individual regions with their negative impact on the environment. The assessment of their danger is therefore of special current relevance. The article considers the possibility of predicting catastrophes associated with these processes. Long-term forecasts of landslides, mudflows and other processes continue to be important. The methodology of such forecasting was previously developed in sufficient detail. The greatest importance is assigned to operational forecasts that will make it possible to warn of possible danger hours or even days ahead.

Progress and Challenges of Demand-Led Co-Produced Sub-Seasonal-to-Seasonal (S2S) Climate Forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products.We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users' trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria.

PSTEP: project for solar–terrestrial environment prediction

Although solar activity may significantly impact the global environment and socioeconomic systems, the mechanisms for solar eruptions and the subsequent processes have not yet been fully understood. Thus, modern society supported by advanced information systems is at risk from severe space weather disturbances. Project for solar–terrestrial environment prediction (PSTEP) was launched to improve this situation through synergy between basic science research and operational forecast. The PSTEP is a nationwide research collaboration in Japan and was conducted from April 2015 to March 2020, supported by a Grant-in-Aid for Scientific Research on Innovative Areas from the Ministry of Education, Culture, Sports, Science and Technology of Japan. By this project, we sought to answer the fundamental questions concerning the solar–terrestrial environment and aimed to build a next-generation space weather forecast system to prepare for severe space weather disasters. The PSTEP consists of four research groups and proposal-based research units. It has made a significant progress in space weather research and operational forecasts, publishing over 500 refereed journal papers and organizing four international symposiums, various workshops and seminars, and summer school for graduate students at Rikubetsu in 2017. This paper is a summary report of the PSTEP and describes the major research achievements it produced.

OpenIFS@home version 1: a citizen science project for ensemble weather and climate forecasting

Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organizations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales by running these models at high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems. In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home, and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climateprediction.net (https://www.climateprediction.net/, last access: 1 June 2021) and weather@home systems. In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of Tropical Cyclone Karl from September 2016 studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet streak near Scotland and heavy rainfall over Norway. For the validation we use a 2000-member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF's forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts and discuss the use of large ensembles in the context of forecasting extreme events.