OECD COUNTRIES: Country Notes (3Rd Quarter 2020)
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Chapter 4 — Complete Markets
Chapter 4 — Complete Markets The Basic Complete-Market Problem There are N primary assets each with price pi and payoff Xsi is state s. There are also a complete set of S pure state securities each of which pays $1 in its own state s and 0 otherwise. These pure state securities are often called Arrow-Debreu securities. Assuming there is no arbi- trage, the price of the pure state s security must be qs, the state price. In a complete market like this, investors will be indifferent between choosing a portfolio from the S state securities and all N + S securities. A portfolio holding n shares of primary assets and η1 shares of the Arrow-Debreu securities will provide consumption c = Xn + η1 in the states at time 1. A portfolio holding η2 ≡ Xn + η1 of just the Arrow-Debreu securities obviously gives the same consumption. The costs of the two portfolios are q′c and p′n + q′η1. From the definition of c and the no-arbitrage result that p′ = q′X, these are obviously the same. Of course in equilibrium the original primary assets must actually be held. However this can be done by financial intermediaries like mutual funds. They buy all the primary shares finan- cing the purchases by issuing the Arrow-Debreu securities. By issuing h = Xn Arrow-Debreu securities where n is the aggregate supply of the primary assets, the intermediary is exactly hedged, and their role can be ignored. So with no loss of generality, we can therefore assume that individual investors only purchases Arrow-Debreu securities ignoring the primary assets. -
QR43, Introduction to Investments Class Notes, Fall 2004 I. Prices, Portfolios, and Arbitrage
QR43, Introduction to Investments Class Notes, Fall 2004 I. Prices, Portfolios, and Arbitrage A. Introduction 1. What are investments? You pay now, get repaid later. But can you be sure how much you will be repaid? Time and uncertainty are essential. Real investments, such as machinery, require an input of re- sources today and deliver an output of resources later. Financial investments,suchasstocksandbonds,areclaimstotheoutput produced by real investments. For example: A company issues shares of stock to investors. The proceeds of the share issue are used to build a factory and to hire workers. The factory produces goods, and the sales proceeds give the company revenue or sales. After paying the workers and set- ting aside money to replace the machinery and buildings when they wear out (depreciation), the company is left with earnings.The company keeps some earnings to make new real investments (re- tained earnings), and pays the rest to shareholders in the form of dividends. Later, the company decides to expand production and needs to raisemoremoneytofinance its expansion. Rather than issue new shares, it decides to issue corporate bonds that promise fixed pay- ments to bondholders. The expanded production increases revenue. However, interest payments on the bonds, and the setting aside of 1 money to repay the principal (amortization), are subtracted from revenue. Thus earnings may increase or decrease depending on the success of the company’s expansion. Financial investments are also known as capital assets or finan- cial assets. The markets in which capital assets are traded are known as capital markets or financial markets. Capital assets are commonly divided into three broad categories: Fixed-income securities promise to make fixed payments in the • future. -
Money and Prices Under Uncertainty1
Money and prices under uncertainty1 Tomoyuki Nakajima2 Herakles Polemarchakis3 Review of Economic Studies, 72, 223-246 (2005) 4 1We had very helpful conversations with Jayasri Dutta, Ronel Elul, John Geanakoplos, Demetre Tsomokos and Michael Woodford; the editor and referees made valuable comments and suggestions. The work of Polemarchakis would not have been possible without earlier joint work with Gaetano Bloise and Jacques Dr`eze. 2Department of Economics, Brown University; tomoyuki [email protected] 3Department of Economics, Brown University; herakles [email protected] 4Earlier versions appeared as \Money and prices under uncertainty," Working Paper No. 01- 32, Department of Economics, Brown University, September, 2001 and \Monetary equilibria with monopolistic competition and sticky prices," Working Paper No. 02-25, Department of Economics, Brown University, 2002 Abstract We study whether monetary economies display nominal indeterminacy: equivalently, whether monetary policy determines the path of prices under uncertainty. In a simple, stochastic, cash-in-advance economy, we find that indeterminacy arises and is characterized by the initial price level and a probability measure associated with state-contingent nom- inal bonds: equivalently, monetary policy determines an average, but not the distribution of inflation across realizations of uncertainty. The result does not derive from the stability of the deterministic steady state and is not affected essentially by price stickiness. Nom- inal indeterminacy may affect real allocations in cases we identify. Our characterization applies to stochastic monetary models in general, and it permits a unified treatment of the determinants of paths of inflation. Key words: monetary policy; uncertainty; indeterminacy; fiscal policy; price rigidities. JEL classification numbers: D50; D52; E31; E40; E50. -
Meeting Carbon Budgets – 2014 Progress Report to Parliament Committee on Climate Change July 2014 |
Meeting Carbon Budgets Meeting Carbon Meeting Carbon Budgets – 2014 Progress Report to Parliament Committee on Climate Change July 2014 | 2014 Progress Report Parliament 2014 Progress to Committee on Climate Change 7 Holbein Place London SW1W 8NR www.theccc.org.uk @theCCCuk | Committee on Climate Change July 2014 on Climate Committee Meeting Carbon Budgets – 2014 Progress Report to Parliament Committee on Climate Change July 2014 Presented to Parliament pursuant to section 36(1) and 36(2) of the Climate Change Act 2008 Meeting Carbon Budgets | 2014 Progress Report to Parliament | Committee on Climate Change Preface The Committee on Climate Change (the Committee) is an independent statutory body which was established under the Climate Change Act (2008) to advise UK and devolved administration governments on setting and meeting carbon budgets, and preparing for climate change. Setting carbon budgets In December 2008 we published our first report, ‘Building a low-carbon economy – the UK’s contribution to tackling climate change’, containing our advice on the level of the first three carbon budgets and the 2050 target. This advice was accepted by the Government and legislated by Parliament in May 2009. In December 2010, we set out our advice on the fourth carbon budget, covering the period 2023-27, as required under Section 4 of the Climate Change Act. The fourth carbon budget was legislated in June 2011 at the level that we recommended. In April 2013 we published advice on reducing the UK’s carbon footprint and managing competitiveness risks. In November and December 2013 we published, in two parts, our review of the fourth carbon budget, as required under Section 22 of the Climate Change Act, as an input to the Government’s decision in 2014. -
Intermediation Markups and Monetary Policy Passthrough ∗
Intermediation Markups and Monetary Policy Passthrough ∗ Semyon Malamudyand Andreas Schrimpfz This version: December 12, 2016 Abstract We introduce intermediation frictions into the classical monetary model with fully flexible prices. Trade in financial assets happens through intermediaries who bargain over a full set of state-contingent claims with their customers. Monetary policy is redistributive and affects intermediaries' ability to extract rents; this opens up a new channel for transmission of monetary shocks into rates in the wider economy, which may be labelled the markup channel of monetary policy. Passthrough efficiency depends crucially on the anticipated sensitivity of future monetary policy to future stock market returns (the \Central Bank Put"). The strength of this put determines the room for maneuver of monetary policy: when it is strong, monetary policy is destabilizing and may lead to market tantrums where deteriorating risk premia, illiquidity and markups mutually reinforce each other; when the put is too strong, passthrough becomes fully inefficient and a surprise easing even begets a rise in real rates. Keywords: Monetary Policy, Stock Returns, Intermediation, Market Frictions JEL Classification Numbers: G12, E52, E40, E44 ∗We thank Viral Acharya, Markus Brunnermeier, Egemen Eren, Itay Goldstein, Piero Gottardi, Michel Habib, Enisse Kharroubi, Arvind Krishnamurthy, Giovanni Lombardo, Matteo Maggiori, Jean-Charles Rochet, Hyun Song Shin, and Michael Weber, as well as seminar participants at the BIS and the University of Zurich for helpful comments. Semyon Malamud acknowledges the financial support of the Swiss National Science Foundation and the Swiss Finance Institute. Parts of this paper were written when Malamud visited BIS as a research fellow. -
2008 Renewable Energy Data Book, July 2009
Energy Efficiency & Renewable Energy JULY 2009 2008 Renewable Energy Data Book Acknowledgments This report was produced by Rachel Gelman and Steve Hockett, edited by Michelle Kubik, and designed by Stacy Buchanan of the National Renewable Energy Laboratory (NREL). We greatly appreciate the input and reviews received from Jacques Beaudry-Losique, Sunita Satyapal, and Jesse Johnson of the U.S. Department of Energy; and Robert Remick, Fort Felker, Doug Arent, Nate Blair, and Selya Price of NREL. Photo on front page courtesy of NASA © 2009 U.S. Department of Energy Key Findings • Although renewable energy (excluding hydropower) is a relatively small portion of total energy supply both globally and in the United States, renewable energy installations in both the world and in the United States have nearly tripled between 2000 and 2008. • Including hydropower, renewable energy represents nearly 11% of total installed capacity and more than 9% of total generation in the United States in 2008. Installed renewable energy capacity (including hydropower) is 119 gigawatts (GW). Not including hydropower, 2008 renewable electricity installed capacity has reached about 42 GW in the United States. • In the United States, growth in sectors such as wind and solar photovoltaics (PV) signify an ongoing shift in the composition of our electricity supply. In 2008, cumulative wind capacity increased by 51% and cumulative solar PV capacity grew 44% from the previous year. Key Findings, continued • Worldwide, wind energy is the fastest growing renewable energy technology—between 2000 and 2008, wind energy generation worldwide increased by a factor of almost 7. The United States experienced even more dramatic growth, as installed wind energy capacity increased almost 10 times between 2000 and 2008. -
Lecture 02: One Period Model
Fin 501: Asset Pricing Lecture 02: One Period Model Prof. Markus K. Brunnermeier 10:37 Lecture 02 One Period Model Slide 2-1 Fin 501: Asset Pricing Overview 1. Securities Structure • Arrow-Debreu securities structure • Redundant securities • Market completeness • Completing markets with options 2. Pricing (no arbitrage, state prices, SDF, EMM …) 10:37 Lecture 02 One Period Model Slide 2-2 Fin 501: Asset Pricing The Economy s=1 • State space (Evolution of states) s=2 Two dates: t=0,1 0 S states of the world at time t=1 … • Preferences s=S U(c0, c1, …,cS) (slope of indifference curve) • Security structure Arrow-Debreu economy General security structure 10:37 Lecture 02 One Period Model Slide 2-3 Fin 501: Asset Pricing Security Structure • Security j is represented by a payoff vector • Security structure is represented by payoff matrix • NB. Most other books use the transpose of X as payoff matrix. 10:37 Lecture 02 One Period Model Slide 2-4 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 One A-D asset e1 = (1,0) c2 This payoff cannot be replicated! Payoff Space <X> c1 Markets are incomplete ) 10:37 Lecture 02 One Period Model Slide 2-5 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 Add second A-D asset e2 = (0,1) to e1 = (1,0) c2 c1 10:37 Lecture 02 One Period Model Slide 2-6 Fin 501: Asset Pricing Arrow-Debreu Security Structure in R2 Add second A-D asset e2 = (0,1) to e1 = (1,0) c2 Payoff space <X> c1 Any payoff can be replicated with two A-D securities 10:37 Lecture 02 One Period Model Slide 2-7 Fin 501: Asset -
Finance: a Quantitative Introduction Chapter 7 - Part 2 Option Pricing Foundations
The setting Complete Markets Arbitrage free markets Risk neutral valuation Finance: A Quantitative Introduction Chapter 7 - part 2 Option Pricing Foundations Nico van der Wijst 1 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation 1 The setting 2 Complete Markets 3 Arbitrage free markets 4 Risk neutral valuation 2 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation Recall general valuation formula for investments: t X Exp [Cash flowst ] Value = t (1 + discount ratet ) Uncertainty can be accounted for in 3 different ways: 1 Adjust discount rate to risk adjusted discount rate 2 Adjust cash flows to certainty equivalent cash flows 3 Adjust probabilities (expectations operator) from normal to risk neutral or equivalent martingale probabilities 3 Finance: A Quantitative Introduction c Cambridge University Press The setting Complete Markets Arbitrage free markets Risk neutral valuation Introduce pricing principles in state preference theory old, tested modelling framework excellent framework to show completeness and arbitrage more general than binomial option pricing Also introduce some more general concepts equivalent martingale measure state prices, pricing kernel, few more Gives you easy entry to literature (+ pinch of matrix algebra, just for fun, can easily be omitted) 4 Finance: A Quantitative Introduction c Cambridge University Press The setting Time and states Complete -
Annex B Glossary and Acronyms
Annex B Glossary and Acronyms Anthracite Within this publication, anthracite is coal classified as such by UK coal producers and importers of coal. Typically it has a high heat content making it particularly suitable for certain industrial processes and for use as a domestic fuel. Associated Gas Natural gas found in association with crude oil in a reservoir, either dissolved in the oil or as a cap above the oil. Autogeneration Generation of electricity by companies whose main business is not electricity generation, the electricity being produced mainly for that company’s own use. Aviation spirit A light hydrocarbon oil product used to power piston-engined aircraft power units. Aviation turbine fuel The main aviation fuel used for powering aviation gas-turbine power units (jet aircraft engine). Backflows These are finished or semi-finished products, which are returned from final consumers to refineries for processing, blending or sale. They are usually by-products of petrochemical manufacturing. BEIS Department for Business, Energy and Industrial Strategy Benzole A colourless liquid, flammable, aromatic hydrocarbon by-product of the iron and steel making process. It is used as a solvent in the manufacture of styrenes and phenols but is also used as a constituent of motor fuel. BETTA British Electricity Trading and Transmission Arrangements (BETTA) refer to changes to electricity generation, distribution and supply licences. On 1 April 2005, the England and Wales trading arrangements were extended to Scotland by the British Electricity Trading and Transmission Arrangements creating a single GB market for trading of wholesale electricity, with common arrangements for access to and use of GB transmission system. -
Hooked on Oil: Breaking the Habit with a Windfall
Hooked on oil: breaking the habit with a windfall tax The UK Exchequer’s dependence on fossil fuel income P the world’s largest and most experienced independent conservation organisation; P a truly global network, working in more than 90 countries; P a challenging, constructive, science-based organisation that addresses issues from the survival of species and habitats to climate change, sustainable business and environmental education; P a charity dependent upon its five million supporters worldwide – some two-thirds of our income derives from individual donations. P an organisation that makes a difference nef is an independent think-and-do tank that inspires and demonstrates real economic well-being. We aim to improve quality of life by promoting innovative solutions that challenge mainstream thinking on economic, environmental and social issues. We work in partnership and put people and the planet first. nef (the new economics foundation) is a registered charity founded in 1986 by the leaders of The Other Economic Summit (TOES), which forced issues such as international debt onto the agenda of the G7/G* summit meetings. It has taken a lead in helping establish new coalitions and organisations such as the Jubilee 2000 debt campaign; the Ethical Trading Initiative; the UK Social Investment Forum; and new ways to measure social and economic well-being. Hooked on oil: breaking the habit with a windfall tax The UK Exchequer’s dependence on fossil fuel income – a briefing from nef (the new economics foundation) for WWF Contents Executive summary -
Green Taxation in China: a Possible Consolidated Transport Fuel Tax to Promote Clean Air?
Fordham Environmental Law Review Volume 21, Number 2 2010 Article 5 Green Taxation in China: A Possible Consolidated Transport Fuel Tax to Promote Clean Air? Xu Yan∗ ∗Fordham University School of Law Copyright c 2010 by the authors. Fordham Environmental Law Review is produced by The Berkeley Electronic Press (bepress). http://ir.lawnet.fordham.edu/elr GREEN TAXATION IN CHINA: A POSSIBLE CONSOLIDATED TRANSPORT FUEL TAX TO PROMOTE CLEAN AIR? Xu Yan * I. INTRODUCTION In the 1960s, due to rapid industrial development, a series of grave environmental accidents occurred in a number of countries.' Man- made environmental harms, such as dangerous water and air pollution, destruction and depletion of irreplaceable resources, have posed a major threat to the existence and development of mankind.2 * Post-doctoral Fellow, Faculty of Law, The University of Hong Kong (HKU). The author would like to thank Professor Richard Cullen for his helpful comments. An earlier draft of this paper was presented at the Green Taxation Conference held by the Taxation Law Research Programme (of the HKU Faculty of Law's Asian Institute of International Financial Law) in January, 2010. Papers presented at the Conference will be published, in due course, as a book by Edward Elgar. The author also would like to thank the participants at the Conference for their comments. 1. See, e.g., Neil Gunningham, Environment Law, Regulation and Governance: Shifting Architectures, 21 J. ENVTL. L. 179, 182 (2009) (noting that America saw several environmental disasters in the 1960s, in particular oil spills in California, and the Cuyahoga River fire in 1969 (in Ohio)); Michael C. -
State Prices and Implementation of the Recovery Theorem
J. Risk Financial Manag. 2015, 8, 2-16; doi:10.3390/jrfm8010002 OPEN ACCESS Journal of Risk and Financial Management ISSN 1911-8074 www.mdpi.com/journal/jrfm Article State Prices and Implementation of the Recovery Theorem Alex Backwell Department of Actuarial Science and the African Collaboration for Quantitative Finance and Risk Research, University of Cape Town, Rondebosch, Cape Town 7700, South Africa; E-Mail: [email protected]; Tel.: +27-21-650-2474 Academic Editor: Michael McAleer Received: 29 October 2014 / Accepted: 5 January 2015 / Published: 19 January 2015 Abstract: It is generally held that derivative prices do not contain useful predictive information, that is, information relating to the distribution of future financial variables under the real-world measure. This is because the market’s implicit forecast of the future becomes entangled with market risk preferences during derivative price formation. A result derived by Ross [1], however, recovers the real-world distribution of an equity index, requiring only current prices and mild restrictions on risk preferences. In addition to being of great interest to the theorist, the potential practical value of the result is considerable. This paper addresses implementation of the Ross Recovery Theorem. The theorem is formalised, extended, proved and discussed. Obstacles to application are identified and a workable implementation methodology is developed. Keywords: Recovery Theorem; Ross recovery; real-world measure; predictive information; state prices; state-price matrix 1. Introduction Financial derivatives are forward-looking in nature, and therefore one may ask whether inferences about the future can be made from liquid derivative prices. In particular, one may aim to make deductions about the real-world, or natural, probability measure.