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1

Wüthrich, Mario V., Hans Bühlmann, and Hansjörg Furrer. Market-Consistent Actuarial Valuation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14852-1.

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Wüthrich, Mario V. Market-Consistent Actuarial Valuation. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46636-1.

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3

Hans, Bühlmann, and Furrer Hansjörg, eds. Market-consistent actuarial valuation. 2nd ed. Berlin: Springer, 2010.

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4

Taggart, Robert A. Consistent valuation and cost of capital expressions with corporate and personal taxes. Cambridge, MA: National Bureau of Economic Research, 1989.

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5

Diamond, Peter A. Testing the internal consistency of contingent valuation surveys. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1993.

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6

Garrod, Guy. Contingent valuation techniques: A review of their unbiasedness, efficiency and consistency. Newcastle upon Tyne: Countryside Change Unit, Dept. of Agricultural Economics & Food Marketing, University of Newcastle upon Tyne, 1990.

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7

Garrod, Guy. Contingent valuation techniques: A review of their unbiasedness, efficiency and consistency. Newcastle upon Tyne: Countryside Change Unit, Dept. of Agricultural Economics & Food Marketing, University of Newcastle upon Tyne, 1990.

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8

Bateman, I. J. Consistency between contingent valuation estimates: A comparison of two studies of UK national parks. Newcastle upon Tyne: Countryside Change Unit, Dept. of Agricultural Economics & Food Marketing, University of Newcastle upon Tyne, 1993.

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9

Market-Consistent Actuarial Valuation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-73643-1.

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10

Market-Consistent Actuarial Valuation. Springer, 2016.

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11

Hans B. Hlmann,Mario Valentin W. Thrich,Hansj Rg Furrer. Market-Consistent Actuarial Valuation. Springer, 2008.

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12

Hans B. Hlmann,Hansj Rg Furrer,Mario V. W. Thrich. Market-Consistent Actuarial Valuation. Springer, 2010.

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13

Market-Consistent Actuarial Valuation. Springer, 2010.

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14

Market-Consistent Actuarial Valuation (EAA Series). Springer Berlin Heidelberg, 2007.

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15

Bühlmann, Hans, Mario Valentin Wüthrich, and Hansjörg Furrer. Market-Consistent Actuarial Valuation (EAA Lecture Notes). Springer, 2007.

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16

Rüfenacht, Nils. Implicit Embedded Options in Life Insurance Contracts: A Market Consistent Valuation Framework. Physica, 2012.

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17

Implicit Embedded Options In Life Insurance Contracts A Market Consistent Valuation Framework. Physica-Verlag HD, 2012.

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18

Rüfenacht, Nils. Implicit Embedded Options in Life Insurance Contracts: A Market Consistent Valuation Framework. Physica-Verlag, 2012.

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Rüfenacht, Nils. Implicit Embedded Options in Life Insurance Contracts: A Market Consistent Valuation Framework. Physica-Verlag, 2014.

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20

Béreau, Sophie, Jean-Yves Gnabo, Malik Kerkour, and Hélène Raymond. Sovereign Wealth Fund Investments and Industry Performance. Edited by Douglas Cumming, Geoffrey Wood, Igor Filatotchev, and Juliane Reinecke. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198754800.013.7.

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In the past decade, sovereign wealth funds (SWFs) have been very active in western economies with massive liquidity injections and numerous stakes in various strategic areas. While a vast literature has documented their influence on firms’ behavior and equity valuation, their impact on the whole economy has been largely unexplored. This chapter investigates the aggregate impact of SWFs’ investments at the industrial level. Using a panel of ten European countries from 2006 to 2012, a relevant instrumental variables strategy is used to circumvent potential double causality between returns of the recipient countries’ stock market indices and SWFs’ investments. The results show a positive and significant impact of SWFs’ investments for five sectoral indices out of ten. Looking at conditional effects, it does not find that this relationship is affected by either the availability of alternative sources of financing in the economy—consistent with the liquidity argument—or different volatility regimes.
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21

Baker, H. Kent, Greg Filbeck, and Andrew C. Spieler, eds. Debt Markets and Investments. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190877439.001.0001.

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This book provides an objective look into the dynamic world of debt markets, products, valuation, and analysis. It also provides an in-depth understanding about this subject from experts in the field, both practitioners and academics. The coverage extends from discussing basic concepts and their application to increasingly intricate and real-world situations. This volume spans the gamut from theoretical to practical, while attempting to offer a useful balance of detailed and user-friendly coverage. The book has several distinguishing features. It blends the contributions of a global array of scholars and practitioners into a single review of some of the most important topics in this area. The book follows an internally consistent approach in format and style. Hence, it is collectively much more than a compilation of chapters from an array of different authors. It presents theory without unnecessary abstraction, quantitative techniques using basic bond mathematics, and conventions at a useful level of detail. It also incorporates how investment professionals analyze and manage fixed income portfolios. The book emphasizes empirical evidence involving debt securities and markets so it is understandable to a wide array of readers. Each chapter contains discussion questions to help reinforce key concepts. The end of the book contains guideline answers to each question. Readers interested in a broad survey will benefit as will those looking for more in-depth presentations of specific areas within this field of study. In summary, the book provides a fresh look at this intriguing and dynamic but often complex subject.
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22

De Laurentis, Giacomo, Eugenio Alaio, Elisa Corsi, Emanuelemaria Giusti, Marco Guairo, Carlo Palego, Luca Paulicelli, et al. Rischio di credito 2.0. AIFIRM, 2021. http://dx.doi.org/10.47473/2016ppa00030.

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The EBA Guidelines on loan origination and monitoring (hereinafter "GL LOM") undoubtedly represent a substantially new piece of the banking regulatory framework. In fact, for the first time, the regulator moves into a topic that was traditionally outside the scope of financial regulation, so far almost exclusively focused on aspects directly linked to both micro- and macro-prudential stability, notably through capital and liquidity management requirements and guidelines on Business Model and Internal Governance. The credit management process, and in particular loan origination and monitoring, has always been typically considered as a business issue under sole responsibility of banks, as it is considered one of the "core" processes (if not the "core" process) of the banking business. As a matter of fact, since the issue of the capital requirement regulation (i.e., Basel II and Basel III), and the introduction of the use requirements for the rating systems, the regulator moved very close, but not yet, to prescribe specific credit assessment criteria, while dictating methodological and organizational requirements for the authorization of the rating systems, and leaving substantial freedom to banks to define their own models and embedded assessment criteria and indicators. With the GL LOM, the regulator takes a further step, remarkably beyond its traditional remit, dictating principles and rules for the evaluation of the credit quality of borrowers. The starting point for this new approach from the regulator can be found in the ECB guidelines on Non-Performing Loans, later endorsed by the Bank of Italy Guidelines for Less Significant Banks, aimed at encouraging banks to define their NPL management processes and establish reduction plans to achieve NPL ratio targets in line with the regulator's expectations. Consistently with the focus on NPL, the regulation on Calendar Provisioning, amending the CRR was issued; as being a Regulation, it involves all banks, and not only significant ones (for which the ECB Addendum also applies). In addition, the new definition of default (the so-called "new Dod") has defined stricter criteria for the transition of exposures to the default status and also made the return of "cured" exposures to the performing status more difficult. The combined effect of these regulatory changes has been to make the default of counterparties not only more probable but also much more "expensive" for the banks. The natural “next step” of these regulatory changes was to "move backward" into the management process covering loan origination and monitoring . The EBA's stated objective with the issuance of the GL LOM is to define "robust and prudent" standards of lending practices so as to maintain a low level of NPLs in the future. Therefore, the focus of the GL LOM is the definition of requirements (some outlined as prescriptions, others in terms of principles) for the creditworthiness assessment of counterparties and for the management of the related data and information. Notwithstanding the fact that the Final Report has articulated the principle of proportionality much more clearly as compared to the Consultation Paper, the GLs set out three macro-categories of counterparties for which specific requirements are defined: • Individuals • Micro and small businesses • Medium and large companies. The GL LOM also provide recommendations about the valuation of guarantees both at origination and during ongoing monitoring, encouraging the use of advanced statistical models. The GL LOM focus on real estate guarantees, while financial collateral is outside the scope of the GL LOM. In the mind of the regulator, the GL LOM should not only reflect industry practices, but also incorporate the latest supervisory guidance on lending, and provide the stimulus to include ESG, AML/CTF and the use of innovative technologies into banking origination and, where applicable, monitoring processes.
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23

Sobczyk, Eugeniusz Jacek. Uciążliwość eksploatacji złóż węgla kamiennego wynikająca z warunków geologicznych i górniczych. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN, 2022. http://dx.doi.org/10.33223/onermin/0222.

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Hard coal mining is characterised by features that pose numerous challenges to its current operations and cause strategic and operational problems in planning its development. The most important of these include the high capital intensity of mining investment projects and the dynamically changing environment in which the sector operates, while the long-term role of the sector is dependent on factors originating at both national and international level. At the same time, the conditions for coal mining are deteriorating, the resources more readily available in active mines are being exhausted, mining depths are increasing, temperature levels in pits are rising, transport routes for staff and materials are getting longer, effective working time is decreasing, natural hazards are increasing, and seams with an increasing content of waste rock are being mined. The mining industry is currently in a very difficult situation, both in technical (mining) and economic terms. It cannot be ignored, however, that the difficult financial situation of Polish mining companies is largely exacerbated by their high operating costs. The cost of obtaining coal and its price are two key elements that determine the level of efficiency of Polish mines. This situation could be improved by streamlining the planning processes. This would involve striving for production planning that is as predictable as possible and, on the other hand, economically efficient. In this respect, it is helpful to plan the production from operating longwalls with full awareness of the complexity of geological and mining conditions and the resulting economic consequences. The constraints on increasing the efficiency of the mining process are due to the technical potential of the mining process, organisational factors and, above all, geological and mining conditions. The main objective of the monograph is to identify relations between geological and mining parameters and the level of longwall mining costs, and their daily output. In view of the above, it was assumed that it was possible to present the relationship between the costs of longwall mining and the daily coal output from a longwall as a function of onerous geological and mining factors. The monograph presents two models of onerous geological and mining conditions, including natural hazards, deposit (seam) parameters, mining (technical) parameters and environmental factors. The models were used to calculate two onerousness indicators, Wue and WUt, which synthetically define the level of impact of onerous geological and mining conditions on the mining process in relation to: —— operating costs at longwall faces – indicator WUe, —— daily longwall mining output – indicator WUt. In the next research step, the analysis of direct relationships of selected geological and mining factors with longwall costs and the mining output level was conducted. For this purpose, two statistical models were built for the following dependent variables: unit operating cost (Model 1) and daily longwall mining output (Model 2). The models served two additional sub-objectives: interpretation of the influence of independent variables on dependent variables and point forecasting. The models were also used for forecasting purposes. Statistical models were built on the basis of historical production results of selected seven Polish mines. On the basis of variability of geological and mining conditions at 120 longwalls, the influence of individual parameters on longwall mining between 2010 and 2019 was determined. The identified relationships made it possible to formulate numerical forecast of unit production cost and daily longwall mining output in relation to the level of expected onerousness. The projection period was assumed to be 2020–2030. On this basis, an opinion was formulated on the forecast of the expected unit production costs and the output of the 259 longwalls planned to be mined at these mines. A procedure scheme was developed using the following methods: 1) Analytic Hierarchy Process (AHP) – mathematical multi-criteria decision-making method, 2) comparative multivariate analysis, 3) regression analysis, 4) Monte Carlo simulation. The utilitarian purpose of the monograph is to provide the research community with the concept of building models that can be used to solve real decision-making problems during longwall planning in hard coal mines. The layout of the monograph, consisting of an introduction, eight main sections and a conclusion, follows the objectives set out above. Section One presents the methodology used to assess the impact of onerous geological and mining conditions on the mining process. Multi-Criteria Decision Analysis (MCDA) is reviewed and basic definitions used in the following part of the paper are introduced. The section includes a description of AHP which was used in the presented analysis. Individual factors resulting from natural hazards, from the geological structure of the deposit (seam), from limitations caused by technical requirements, from the impact of mining on the environment, which affect the mining process, are described exhaustively in Section Two. Sections Three and Four present the construction of two hierarchical models of geological and mining conditions onerousness: the first in the context of extraction costs and the second in relation to daily longwall mining. The procedure for valuing the importance of their components by a group of experts (pairwise comparison of criteria and sub-criteria on the basis of Saaty’s 9-point comparison scale) is presented. The AHP method is very sensitive to even small changes in the value of the comparison matrix. In order to determine the stability of the valuation of both onerousness models, a sensitivity analysis was carried out, which is described in detail in Section Five. Section Six is devoted to the issue of constructing aggregate indices, WUe and WUt, which synthetically measure the impact of onerous geological and mining conditions on the mining process in individual longwalls and allow for a linear ordering of longwalls according to increasing levels of onerousness. Section Seven opens the research part of the work, which analyses the results of the developed models and indicators in individual mines. A detailed analysis is presented of the assessment of the impact of onerous mining conditions on mining costs in selected seams of the analysed mines, and in the case of the impact of onerous mining on daily longwall mining output, the variability of this process in individual fields (lots) of the mines is characterised. Section Eight presents the regression equations for the dependence of the costs and level of extraction on the aggregated onerousness indicators, WUe and WUt. The regression models f(KJC_N) and f(W) developed in this way are used to forecast the unit mining costs and daily output of the designed longwalls in the context of diversified geological and mining conditions. The use of regression models is of great practical importance. It makes it possible to approximate unit costs and daily output for newly designed longwall workings. The use of this knowledge may significantly improve the quality of planning processes and the effectiveness of the mining process.
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