EIB: Environmental Impacts Related to Finance (Topic)最新文献

{"title":"Options for Rebuilding the Economy and the Financial System","authors":"S. Turnbull","doi":"10.2139/ssrn.1322210","DOIUrl":"https://doi.org/10.2139/ssrn.1322210","url":null,"abstract":"This paper outlines four non-exclusive options for reforming the financial system. Three options are based on the re-introduction of cost carrying money supported by Gesell (1916), Fisher (1933) and Keynes (1936), but in electronic form. One variant is a government issue redeemable into official money as proposed by the US Bankhead-Pettengill Bill of 1933. A second option is to allow private issues redeemable into official money as occurred during the Great Depression in countries that included Germany, Austria and the US. The third option involves private currency issues convertible into specified commodities as occurred in Europe in the 1920’s. The tethering of a currency to the local value of Kilo-Watt-Hours of electricity generated from benign renewable energy resources is identified as a way to create “green” dollars. In this way a global unit of account could be created with a unit of value determined by the local endowment of benign sustainable energy resources. The investment cost per unit of output from renewable resources is typically around three times greater than burning carbon. This makes any compounding interest costs of renewable energy over three times that of carbon burning generators. One outcome of using cost carrying or negative interest rate money is to significantly improve the competitiveness of renewable energy to reduce the need for carbon taxing or trading. In addition, the value of green money tethered to the average cost of power from many generators in each bioregion would be relatively stable. Market prices in each region would become more predictable for investors and insulated from alien financial crises, speculators and terms of trade. The fourth option involves using existing fiat money to reduce: (i) the cost of seigniorage, (ii) interest on government debt; (iii) size of organisations considered too big to fail; (iv) tax incentives to favour equity rather than debt; (v) the different types of risks accepted by financial institutions, and (vi) ability of banks and “shadow” banks to create credit to finance derivatives many times greater than the GDP of the global economy.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129947088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting the CO2 Certificate Price Risk","authors":"W. Ehrenfeld, H. Dannenberg","doi":"10.2139/ssrn.1662356","DOIUrl":"https://doi.org/10.2139/ssrn.1662356","url":null,"abstract":"Modeling the price risk of CO2 certificates is one important aspect of integral corporate risk management related to emissions trading. The paper presents a risk model which may be the basis for evaluating the risk of emission certificate prices. We assume that the certificate price is determined by the expected marginal CO2 abatement costs prevailing at the current trade period and stochastically fluctuates around the respective level as returned from the mean reversion process. Due to uncertainties about future environmental states we suppose that within one trade period, erratic changes in the expected marginal abatement costs may occur leading to shifts in the price level. The aim of the work is to model the erratic changes of the expected reversion level and to estimate the parameters of the mean reversion process.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128048576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting Weekly Electricity Prices at Nord Pool","authors":"Hipòlit Torró","doi":"10.2139/ssrn.991532","DOIUrl":"https://doi.org/10.2139/ssrn.991532","url":null,"abstract":"This paper analyses the forecasting power of weekly futures prices at Nord Pool. The forecasting power of futures prices is compared to an ARIMAX model of the spot price. The time series model contains lagged external variables such as: temperature, precipitation, reservoir levels and the basis (futures price less the spot price); and generally reflects the typical seasonal patterns in weekly spot prices. Results show that the time series model forecasts significantly beat futures prices when using the Diebold and Mariano (1995) test. Furthermore, the average forecasting error of futures prices reveals that they are significantly above the settlement spot price at the 'delivery week' and their size increases as the time to maturity increases. Those agents taking positions in weekly futures contracts at Nord Pool might find the estimated ARIMAX model useful for improving their expectation formation process for the underlying spot price.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132042439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate Variables and Weather Derivatives: Gas Demand, Temperature and Seasonality Effects in the Italian Case","authors":"Giovanna Zanotti, G. Gabbi, Daniele Laboratore","doi":"10.2139/ssrn.488745","DOIUrl":"https://doi.org/10.2139/ssrn.488745","url":null,"abstract":"Weather derivatives are financial instrument that allow to hedge weather risk that is the financial gain or loss due to variability in climatic conditions. The market originated in 1998 when the US power community realised that the high volatility of revenues due to weather variability could be controlled and, since then, has grown rapidly both in terms of number of contracts concluded and notional value and in terms of variety of industry applications. The purpose of this study is to analyse the real hedging capabilities of weather derivatives on the Italian energy sector. This is achieved through the investigation of the existence of a robust statistically significant relation between energy, more specifically, gas consumption, and climate parameters. We investigate such a relation applying different models. The first is a simple regression where we estimate gas consumption, as the dependent variable, and temperature, rain, humidity and pressure as explicative variables. In the second model we introduce a derived temperature variable, the heating degree day function, in order to better capture the non linearity behaviour of gas consumption. In the third model we implement lagged, other than present, weather variables. In the fourth model we apply dummy variables in order to consider, daily, monthly and holiday patterns in gas consumption. In the fifth model, finally, we introduce an autoregressive structure in the error term. The paper is organised in five session. The first one summarises methodology and results of previous studies on this topic. Session three describes data. Session four presents methodology and results and session five reports our main conclusions.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133607490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structured Risk Assessment and Value-at-Risk","authors":"R. Brooks, J. Sullivan, Z. G. Stoumbos","doi":"10.2139/ssrn.332403","DOIUrl":"https://doi.org/10.2139/ssrn.332403","url":null,"abstract":"An important question for corporate finance officers is whether risk management systems, such as Value at Risk (VaR), currently are producing accurate results. In contrast to previous research on assessing the accuracy of risk systems or VaR, which has focused on backtesting a large sample of historical observations, we provide tools for real-time assessment, using a time window that varies adaptively with the data. The objective is to quickly signal if the estimation process is systematically biased, subject to a specified rate of false detections. For example, if the volatility is systematically underestimated by 25 percent our procedure detects this in an average of 25 observations. Previous techniques have often backtested thousands of observations. We also discuss the trade-off between increasing detection power at the risk of detecting meaningless errors and suggest a parameter to specify the balance desired for a specific application.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121891569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Taxes and Tradable Permits as Instruments for Controlling Pollution Theory and Practice","authors":"John Norregaard, Valérie Reppelin-Hill","doi":"10.5089/9781451842999.001.A001","DOIUrl":"https://doi.org/10.5089/9781451842999.001.A001","url":null,"abstract":"This paper examines the relative merits of two dominant economic instruments for reducing pollution-'green' taxes and tradable permits. Theoretically, the two instruments share many similarities, and on balance, neither seems preferable to the other. In practice, however, most countries have relied more on taxes than on permits to control pollution. The analysis suggests a number of lessons to be learned from country experiences regarding the design and implementation of both instruments. While many, particularly European countries, currently have long-term programs involving environmental taxes, a willingness to experiment with tradable permits seems to be growing, especially given the Kyoto protocol emission targets.","PeriodicalId":330217,"journal":{"name":"EIB: Environmental Impacts Related to Finance (Topic)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121584517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}