Thematische Bibliographien / Capital assets pricing model

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Auswahl der wissenschaftlichen Literatur zum Thema „Capital assets pricing model“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 28. Juli 2024

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Zeitschriftenartikel zum Thema "Capital assets pricing model"

Chen, James Ming. „The Capital Asset Pricing Model“. Encyclopedia 1, Nr. 3 (03.09.2021): 915–33. http://dx.doi.org/10.3390/encyclopedia1030070.

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The capital asset pricing model (CAPM) is an influential paradigm in financial risk management. It formalizes mean-variance optimization of a risky portfolio given the presence of a risk-free investment such as short-term government bonds. The CAPM defines the price of financial assets according to the premium demanded by investors for bearing excess risk.

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Jiao, Dian. „Application of Deep Learning Method to Capital Assets Pricing“. Highlights in Business, Economics and Management 3 (20.01.2023): 136–39. http://dx.doi.org/10.54097/hbem.v3i.4713.

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The key problem of financial assets allocation is the price of assets. Assets pricing is the core content of Modern Finance, and revealing the law of assets pricing is always a hot spot of finance research. In recent years, deep learning technology has been applied in the research process of assets pricing and achieved good effect. This paper introduced the theory and characteristics of deep learning, started from extracting and utilizing nonlinear information, effectively processing time series data, and intellectual prediction model, and explored the application of deep learning method in the capital assets pricing. Meanwhile, this paper explores the applicability and limitations of deep learning methods and discusses possible future research trends in learning-based asset pricing.

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Yao, Wenjing, und Bin Mei. „Assessing forestry-related assets with the intertemporal capital asset pricing model“. Forest Policy and Economics 50 (Januar 2015): 192–99. http://dx.doi.org/10.1016/j.forpol.2014.06.006.

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He, Zhiguo, und Arvind Krishnamurthy. „Intermediary Asset Pricing“. American Economic Review 103, Nr. 2 (01.04.2013): 732–70. http://dx.doi.org/10.1257/aer.103.2.732.

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We model the dynamics of risk premia during crises in asset markets where the marginal investor is a financial intermediary. Intermediaries face an equity capital constraint. Risk premia rise when the constraint binds, reflecting the capital scarcity. The calibrated model matches the nonlinearity of risk premia during crises and the speed of reversion in risk premia from a crisis back to precrisis levels. We evaluate the effect of three government policies: reducing intermediaries borrowing costs, injecting equity capital, and purchasing distressed assets. Injecting equity capital is particularly effective because it alleviates the equity capital constraint that drives the model's crisis. (JEL E44, G12, G21, G23, G24)

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Takouachet, Rania. „Capital asset pricing model“. Finance and Business Economies Review 4, Nr. 1 (30.04.2020): 165–89. http://dx.doi.org/10.58205/fber.v4i1.645.

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This study aims to identify the model of capital asset pricing (CAPM), which occupies a privileged positionin the stock market because it is one of the analysis tools that take into account the relationship betweenreturn and risk in securities and capital investments in general. Which is considered one of the mostimportant discoveries in the modern financial economy where despite the many criticisms of this model, thebasic model has simplicity, speed and ease. This feature has kept this model in use today and on a largescale by most specialists in the financial field.

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Ye, Jialin. „Intangible Capital, Investor Structure and Stock Return from the Perspective of RBV“. Advances in Economics, Management and Political Sciences 72, Nr. 1 (24.05.2024): 139–47. http://dx.doi.org/10.54254/2754-1169/72/20240693.

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The current research suggests the presence of asset mispricing by indicating that stock prices may not necessarily reflect underlying fundamentals. Additionally, prior studies often underestimate the importance and overlook contributions from resources to the returns. In this article, we propose the effect of intangible assets into asset pricing in the context of varying investor sentiment and long-term investment horizon. Drawing from the recourse-based view of intangible assets within firms, we can better assess a firms growth and stock returns. We conclude that the Capital Asset Pricing Model (CAPM) should incorporate the influence of intangible assets. These assets can reduce operational risk, thus affecting idiosyncratic risk.

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Григорий Георгиевич, Сидоренко, Сидоренко Олег Георгиевич und Термосесов Дмитрий Сергеевич. „STOCK MARKET PRICING: CAPITAL ASSET RETURNS MODEL (CAPM) AND FAMA-FRENCH MODEL“. STATE AND MUNICIPAL MANAGEMENT SCHOLAR NOTES 1, Nr. 2 (Juni 2022): 135–41. http://dx.doi.org/10.22394/2079-1690-2022-1-2-135-141.

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. Subject / topic: This article examines the issues of pricing in the stock market in order to help institutional investors to preserve their own capital and increase it based on the study of capital asset return models (CAPM) and Fama-French model. The tasks of collecting the necessary statistical data, analyzing them, as well as applying the model to assess various assets and analyzing the accuracy of their application have been solved. The use of this model makes it possible to reliably predict the prices of assets on the stock market, however, it does not guarantee 100% accuracy, and therefore, its use still entails the risks of capital loss. Goals / objectives: The aim of the study is to compare the accuracy of the studied models, as well as to identify their advantages and disadvantages. Methodology: The methodological basis of the study is made up of both general and particular scientific methods of cognition. Used such methods as induction and deduction, methods of comparison and generalization. Results / conclusions: The authors found that the use of the five-factor Fama-French model makes it possible to fairly reliably predict asset prices in the stock market, but does not guarantee 100% accuracy, so its use still entails the risk of capital loss.

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Naqvi, Hassan. „On the validity of the Capital Asset Pricing Model“. LAHORE JOURNAL OF ECONOMICS 5, Nr. 1 (01.01.2000): 73–92. http://dx.doi.org/10.35536/lje.2000.v5.i1.a4.

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One of the most important developments of modern finance is the Capital Asset Pricing Model (CAPM) of Sharpe, Lintner and Mossin. Although the model has been the subject of several academic papers, it is still exposed to theoretical and empirical criticisms. The CAPM is based on Markowitz’s (1959) mean variance analysis. Markowitz demonstrated that rational investors would hold assets, which offer the highest possible return for a given level of risk, or conversely assets with the minimum level of risk for a specific level of return.

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Riaz, Amna, Nauman Riaz Chaudhry, Reema Choudhary, Mohsin Riaz und Muhammad Suhail. „Capital Asset Pricing Model for the Stock Market in Pakistan“. Qlantic Journal of Social Sciences 5, Nr. 2 (30.06.2024): 76–84. http://dx.doi.org/10.55737/qjss.139458386.

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The Capital Asset Pricing Model (CAPM), within modern financial theory, offers a theoretical framework for pricing assets with uncertain returns. CAPM assesses systematic risk and proposes a linear relationship between risk and expected returns for any asset. It serves as a potent tool for pricing risky assets. In this present study, the trade-off between risk-return was investigated within the framework of CAPM and its validity was tested on the daily returns of companies listed in the chemical, textile and food sectors of the Pakistan stock market during the period July 2004- Feb 2014. The results of empirical testing by regression analysis supported the CAPM’s validity for these sectors in Pakistan and found CAPM β as a single factor which was priced by the market. The KSE-100 index was used as a market, and the year treasury-bills return rate was taken as a risk-free rate.

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Johnston, Mark. „Extension of the Capital Asset Pricing Model to Non-normal Dependence Structures“. ASTIN Bulletin 37, Nr. 01 (Mai 2007): 35–52. http://dx.doi.org/10.2143/ast.37.1.2020797.

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The Capital Asset Pricing Model arises in an economy where agents have exponential utility functions and aggregate consumption is normally distributed, and gives the prices of assets with payoffs which are jointly normal with consumption. Such assets have normal marginal distributions and have dependence with consumption characterised by a normal copula. Wang has derived a transform which extends the CAPM by allowing pricing of assets in such an economy which have non-normal marginal distributions but still are normal-copula with consumption.Here we set out the stochastic discount factors corresponding to this version of the CAPM and to Wang’s transform, and show how to calculate stochastic discount factors and hence asset prices for assets whose dependence with consumption is non-normal. We show that the impact of dependency structure on asset prices is significant.

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Dissertationen zum Thema "Capital assets pricing model"

Luo, Dan, und 罗丹. „Two essays on asset pricing“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48199357.

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This thesis centers around the pricing and risk-return tradeoff of credit and equity derivatives. The first essay studies the pricing in the CDS Index (CDX) tranche market, and whether these instruments have been reasonably priced and integrated within the financial market generally, both before and during the financial crisis. We first design a procedure to value CDO tranches using an intensity-based model which falls into the affine model class. The CDX tranche spreads are efficiently explained by a three-factor version of this model, before and during the crisis period. We then construct tradable CDX tranche portfolios, representing the three default intensity factors. These portfolios capture the same exposure as the S&P 500 index optionmarket, to a market crash. We regress these CDX factors against the underlying index, the volatility factor, and the smirk factor, extracted from the index option returns, and against the Fama-French market, size and book-to-market factors. We finally argue that the CDX spreads are integrated in the financial market, and their issuers have not made excess returns. The second essay explores the specifications of jumps for modeling stock price dynamics and cross-sectional option prices. We exploit a long sample of about 16 years of S&P500 returns and option prices for model estimation. We explicitly impose the time-series consistency when jointly fitting the return and option series. We specify a separate jump intensity process which affords a distinct source of uncertainty and persistence level from the volatility process. Our overall conclusion is that simultaneous jumps in return and volatility are helpful in fitting the return, volatility and jump intensity time series, while time-varying jump intensities improve the cross-section fit of the option prices. In the formulation with time-varying jump intensity, both the mean jump size and standard deviation of jump size premia are strengthened. Our MCMC approach to estimate the models is appropriate, because it has been found to be powerful by other authors, and it is suitable for dealing with jumps. To the best of our knowledge, our study provides the the most comprehensive application of the MCMC technique to option pricing in affine jump-diffusion models.
published_or_final_version
Economics and Finance
Doctoral
Doctor of Philosophy

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Jordan-Wagner, James M. (James Michael). „Arbitrage Pricing Theory and the Capital Asset Pricing Model: Evidence from the Eurodollar Bond Market“. Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc330578/.

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Monthly returns on twenty-seven Eurobonds from July 1982 to June 1986 were examined. There were no consistent differences in returns based on the country in which a firm is located. There were consistent differences due to industry classification, with energy-related firms exhibiting higher average returns and variances. Excess returns were calculated using the capital asset pricing model and arbitrage pricing theory. The results from calculation of mean average deviation, root mean square, and R2 all indicate that the arbitrage pricing theory was a better descriptor of the Eurobond market. The excess returns were also examined using stochastic dominance. Arbitrage pricing theory never dominated the capital asset pricing model using first-order criteria, but consistently dominated using second-order criteria. The results were discussed in terms of the implications for investors and portfolio managers.

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Sekeris, Evangelos. „Information and learning in asset pricing“. Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1320955391&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Lee, Kuan-Hui. „Liquidity risk and asset pricing“. Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1155146069.

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Janse, Van Rensburg S. „Modelling of size-based portfolios using a mixture of normal distributions“. Thesis, Nelson Mandela Metropolitan University, 2009. http://hdl.handle.net/10948/985.

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From option pricing using the Black and Scholes model, to determining the signi cance of regression coe cients in a capital asset pricing model (CAPM), the assumption of normality was pervasive throughout the eld of nance. This was despite evidence that nancial returns were non-normal, skewed and heavy- tailed. In addition to non-normality, there remained questions about the e ect of rm size on returns. Studies examining these di erences were limited to ex- amining the mean return, with respect to an asset pricing model, and did not consider higher moments. Janse van Rensburg, Sharp and Friskin (in press) attempted to address both the problem of non-normality and size simultaneously. They (Janse van Rens- burg et al in press) tted a mixture of two normal distributions, with common mean but di erent variances, to a small capitalisation portfolio and a large cap- italisation portfolio. Comparison of the mixture distributions yielded valuable insight into the di erences between the small and large capitalisation portfolios' risk. Janse van Rensburg et al (in press), however, identi ed several shortcom- ings within their work. These included data problems, such as survivorship bias and the exclusion of dividends, and the questionable use of standard statistical tests in the presence of non-normality. This study sought to correct the problems noted in the paper by Janse van Rensburg et al (in press) and to expand upon their research. To this end survivorship bias was eliminated and an e ective dividend was included into the return calculations. Weekly data were used, rather than the monthly data of Janse van Rensburg et al (in press). More portfolios, over shorter holding periods, were considered. This allowed the authors to test whether Janse van Rensburg et al's (in press) ndings remained valid under conditions di erent to their original study. Inference was also based on bootstrapped statistics, in order to circumvent problems associated with non-normality. Additionally, several di erent speci cations of the normal mixture distribution were considered, as opposed to only the two-component scale mixture. In the following, Chapter 2 provided a literature review of previous studies on return distributions and size e ects. The data, data preparation and portfolio formation were discussed in Chapter 3. Chapter 4 gave an overview of the statistical methods and tests used throughout the study. The empirical results of these tests, prior to risk adjustment, were presented in Chapter 5. The impact of risk adjustment on the distribution of returns was documented in Chapter 6. The study ended, Chapter 7, with a summary of the results and suggestions for future research.

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Emeny, Matthew. „The book-to-market effect and the behaviour of stock returns in the Australian equity market“. Title page, contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09ECM/09ecme533.pdf.

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"August 1998" Bibliography: leaves 74-78. The relationship between the returns to a stock, and ratio of book equity to market equity of the firm, are tested for the Australian stock market, and statistically significant evidence is found in support if the :book to market effect". Several tests are performed to determine whether this return premium is the result of additional risk or market inefficiency. No evidence is found to suggest that high book-to-market stocks are associated with additional risk, and only weak evidence is found to suggest that return premium is a result of investor over-reaction. An alternative explanation IS offered, relying on the dynamic behavior of firms and the process by which investors value the stocks of these firms.

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Kam, Wai-hung Simon. „Capital asset pricing model : is it relevant in Hong Kong /“. [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13570456.

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Zhou, Yi. „Leverage, asset pricing and its implications“. Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1692099801&sid=19&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Kam, Wai-hung Simon, und 甘偉雄. „Capital asset pricing model: is it relevant in Hong Kong“. Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31265686.

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Suh, Daniel. „Stock returns, risk factor loadings, and model predictions a test of the CAPM and the Fama-French 3-factor model /“. Morgantown, W. Va. : [West Virginia University Libraries], 2009. http://hdl.handle.net/10450/10744.

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Thesis (Ph. D.)--West Virginia University, 2009.
Title from document title page. Document formatted into pages; contains x, 146 p. : col. ill. Includes abstract. Includes bibliographical references.

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Bücher zum Thema "Capital assets pricing model"

Jianping, Mei, und Liao Hsien-hsing, Hrsg. Asset pricing. New Jersey: World Scientific, 2003.

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Levy, Haim. The capital asset pricing model in the 21st century: Analytical, empirical, and behavioral perspectives. Cambridge: Cambridge University Press, 2012.

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Advanced asset pricing theory. London: Imperial College Press, 2011.

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Ma, Chenghu. Advanced asset pricing theory. London: Imperial College Press, 2011.

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Jagannathan, Ravi. Do we need CAPM for capital budgeting? Cambridge, MA: National Bureau of Economic Research, 2002.

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Balduzzi, Pierluigi. Asset-pricing models and economic risk premia. [Atlanta, Ga.]: Federal Reserve Bank of Atlanta, 2005.

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Schulz, Paul E. Financial asset pricing: Theory, global policy and dynamics. Hauppauge, N.Y: Nova Science Publishers, 2010.

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1975-, Mu Qiguo, Hrsg. Zi chan ding jia yan jiu: Asset pricing. Beijing: Ke xue chu ban she, 2008.

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Bernd, Meyer. Intertemporal asset pricing: Evidence from Germany. New York: Physica-Verlag, 1999.

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Lewellen, Jonathan. The conditional CAPM does not explain asset-pricing anomalies. Cambridge, Mass: National Bureau of Economic Research, 2003.

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Buchteile zum Thema "Capital assets pricing model"

Severini, Thomas A. „Capital Asset Pricing Model“. In Introduction to Statistical Methods for Financial Models, 197–220. Boca Raton, FL : CRC Press, [2018]: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/b21962-7.

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De Luca, Pasquale. „Capital Asset Pricing Model“. In Analytical Corporate Valuation, 237–57. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93551-5_6.

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Brennan, M. J. „Capital Asset Pricing Model“. In The New Palgrave Dictionary of Economics, 1277–86. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_553.

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Brennan, M. J. „Capital Asset Pricing Model“. In The New Palgrave Dictionary of Economics, 1–9. London: Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1057/978-1-349-95121-5_553-1.

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Brennan, M. J. „Capital Asset Pricing Model“. In The New Palgrave Dictionary of Economics, 1–10. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_553-2.

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Brennan, M. J. „Capital Asset Pricing Model“. In Finance, 91–102. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20213-3_9.

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Kolari, James W., Wei Liu und Jianhua Z. Huang. „Capital Asset Pricing Models“. In A New Model of Capital Asset Prices, 25–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65197-8_2.

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Schwartz, Eduardo S., und Michael J. Brennan. „Asset Pricing in a Small Economy: A Test of the Omitted Assets Model“. In Capital Market Equilibria, 163–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-70995-1_6.

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Kolari, James W., Wei Liu und Jianhua Z. Huang. „Asset Pricing Evolution“. In A New Model of Capital Asset Prices, 3–21. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65197-8_1.

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Bhutta, Nousheen Tariq, Biagio Simonetti und Viviana Ventre. „Does Islamic Capital Asset Pricing Model Outperform Conventional Capital Asset Pricing Model?“ In Studies in Systems, Decision and Control, 471–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30659-5_27.

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Konferenzberichte zum Thema "Capital assets pricing model"

Li, Xinzhu. „Applicability Evaluation to Capital Asset Pricing Model“. In 2012 National Conference on Information Technology and Computer Science. Paris, France: Atlantis Press, 2012. http://dx.doi.org/10.2991/citcs.2012.4.

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Mosoiu, Ovidiu, Catalin Cioaca und Ion Balaceanu. „USING THE CAPITAL ASSET PRICING MODEL IN INFORMATION SECURITY INVESTMENTS“. In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-220.

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Interest in real option theory has intensified over the last decade due to the high uncertainty faced by some private and public organizations when deciding to make a strategic investment (competitive environment) or when faced with an external requirement of the organizational environment (ensuring security standards). Traditional methods of investment analysis define the existence of investment opportunity by net present value (NPV), ignoring the possibility that an investment will start from a certain moment in the future. In this way, it is not possible to capture the phenomenon in dynamics, which leads to limiting the possibility of solving the existing uncertainty over the time regarding the optimal use of resources. The need to optimize managerial strategies and give some flexibility to decision-makers in relation to the changes in the organization's external environment has triggered the real options analysis (ROA). By using ROA, a win-win situation is created in which the available policy options mitigate uncertainty fluctuations of updated net worth (based on new information available) and, at the same time, by applying the best strategy, maximize earnings. Information security systems are designed on a layered architecture and the decision to improve performance on each layer is the responsibility of strategic management. Being a modular system, it is recommended to build the architecture by stages, depending on the value of the assets. Also, the relatively long duration and costs of implementation, limited resources, irreversible character, and project risks determine the value and evaluation of the investment, involving its representation as a combined option associated with a succession of decisions. The proposed model is inspired from the theory of financial and real options, but also from the fuzzy logic. This approach seeks to anchor specific mechanisms for the study of asymmetric risk events in the security market (perfect market assumptions are of course limiting but provide a quick overview, which is essential for the proposed application). Using the capital asset pricing model (CAPM), the return on investments in the security of IT & C systems, by reference to the investment risk as the estimated value, is defined. Investors can take risks that can be broken down into two components: systematic risks and non-systemic risks. Systematic risk refers to the variability of income caused by external factors (macroeconomic conditions), being a measure of the relative market volatility of relative incomes. Unsystematic risk refers to income variability caused by unpredictable factors (mismanagement decisions, abrupt technologies overtaken). The depreciation of security investments is inherent and leads to the dilemma of small and frequent investments or major and rare investments. On this issue, the proposed model can provide solutions to decision-makers. Uncertainty, irreversibility, growth potential and competition are factors that influence the behavior and investment decision. We consider that by using the capital asset pricing model in the security investments associated with eLerning training systems, we can increase the precision of optimal investment in terms of risk and opportunity balancing.

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Li, Gang. „Idiosyncratic Volatility and the Intertemporal Capital Asset Pricing Model“. In 10th International Conference on Modern Research in Management, Economics and Accounting. Acavent, 2020. http://dx.doi.org/10.33422/10th.mea.2020.03.56.

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Chen, Yu, Chaoyi She, Qinglin Wu und Huang Wang. „The Ineffectiveness of Capital Asset Pricing Model and Its Possible Solutions“. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/aebmr.k.220307.017.

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Wang, Zhen. „The Process of Test the Single-factor Capital Asset Pricing Model“. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/aebmr.k.220307.338.

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Li, Yibo, und Yuyuan Gu. „The Applicability of Capital Asset Pricing Model in Shenzhen A-shares“. In Proceedings of the 2nd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2023, May 26–28, 2023, Nanjing, China. EAI, 2023. http://dx.doi.org/10.4108/eai.26-5-2023.2334337.

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KEYI, ZHANG. „Multinational Company Registration Country's Control over Overseas Operations——based on Capital Asset Pricing Model“. In 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME). IEEE, 2020. http://dx.doi.org/10.1109/icemme51517.2020.00100.

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Ledwith, Michael J. „An agent based modeling framework to evaluate the Capital Asset Pricing Model“. In 2009 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2009. http://dx.doi.org/10.1109/sieds.2009.5166145.

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Li, Qian, Kunze Liu, Zehao Ma und Wang Zhu. „An analysis in Chinese stock market using the capital asset pricing model“. In International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2022), herausgegeben von Yuanchang Zhong. SPIE, 2022. http://dx.doi.org/10.1117/12.2646598.

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Chen, Zhiliang. „The Applicability of Classic Capital Asset Pricing Model in Chinese Stock Market“. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/aebmr.k.220307.201.

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Berichte der Organisationen zum Thema "Capital assets pricing model"

Barberis, Nicholas, Robin Greenwood, Lawrence Jin und Andrei Shleifer. X-CAPM: An Extrapolative Capital Asset Pricing Model. Cambridge, MA: National Bureau of Economic Research, Juni 2013. http://dx.doi.org/10.3386/w19189.

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Lo, Andrew, und Jiang Wang. Trading Volume: Implications of An Intertemporal Capital Asset Pricing Model. Cambridge, MA: National Bureau of Economic Research, Oktober 2001. http://dx.doi.org/10.3386/w8565.

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Giovannini, Alberto, und Philippe Weil. Risk Aversion and Intertemporal Substitution in the Capital Asset Pricing Model. Cambridge, MA: National Bureau of Economic Research, Januar 1989. http://dx.doi.org/10.3386/w2824.

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Farmer, Roger. Pricing Assets in a Perpetual Youth Model. Cambridge, MA: National Bureau of Economic Research, Januar 2018. http://dx.doi.org/10.3386/w24261.

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Guidolin, Massimo, und Francesca Rinaldi. A Simple Model of Trading and Pricing Risky Assets Under Ambiguity: Any Lessons for Policy-Makers? Federal Reserve Bank of St. Louis, 2009. http://dx.doi.org/10.20955/wp.2009.020.

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Rozenberg, Julie, Stephane Hallegatte und Adrien Vogt-Schilb. Instrument Choice and Stranded Assets in the Transition to Clean Capital. Inter-American Development Bank, März 2017. http://dx.doi.org/10.18235/0011781.

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To mitigate climate change, some governments opt for instruments focused on investment, like performance standards or feebates, instead of carbon prices. We compare these policies in a Ramsey model with clean and polluting capital, irreversible investment and a climate constraint. Alternative instruments imply different transitions to the same balanced growth path. The optimal carbon price minimizes the discounted social cost of the transition to clean capital, but imposes immediate private costs that disproportionately affect the current owners of polluting capital, in particular in the form of stranded assets. A phased-in carbon price can avoid stranded assets but still result in a drop of income for the owners of polluting capital when it is implemented. Second-best standards or feebates on new investment lead to higher total costs but avoid stranded assets, preserve the revenues of vested interests, and smooth abatement costs over individuals and time. These results suggest a trade-off between political feasibility and cost-effectiveness of environmental policies.

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