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Financial intermediaries typically offer derivatives to their customers only when they can hedge the exposures from these transactions. Baron and Lange show that parimutuel auctions can be used by financial intermediaries to offer derivatives without exposing themselves to risk.
This book introduces three innovative concepts and associated financial instruments with the potential to revolutionise real estate finance. The factorisation of commercial real estate with factor-based real estate derivatives is the first concept analysed in this book. Methodological issues pertaining to factors in real estate risk analysis are covered in detail with in-depth academic reference. The book then analyses the digitalisation of commercial real estate. The environment in which buildings operate is changing fast. Cities which used to be made up of inanimate architectural structures are growing digital skins and becoming smarter. Smart technologies applied to the built environment are fundamentally changing buildings’ role in cities and their interactions with their occupants. The book introduces the concept of smart space and analyses the emergence of ‘digital rights’ or property rights for smart buildings in smart environments. It proposes concepts and methods for identifying, pricing, and trading these new property rights which will dominate commercial real estate in the future. Finally, the tokenisation of commercial real estate is explored. Sometimes described as an alternative to securitisation, tokenisation is a new tool in financial engineering applied to real assets. The book suggests two innovative applications of tokenisation: private commercial real estate index tokenisation and data tokens for smart buildings. With factorisation, digitalisation, and tokenisation, commercial real estate is at the forefront of innovations. Real estate’s unique characteristics, stemming from its physicality, trigger new ways of thinking which might have a profound impact on other asset classes by paving the way for micro markets. Factor-based property derivatives, digital rights, and tokens embody how commercial real estate can push the boundaries of modern capitalism and, in doing so, move at the centre of tomorrow’s smart economies. This book is essential reading for all real estate, finance, and smart technology researchers and interested professionals.
This volume contains the papers presented at WINE 2009:the 5th International Workshop on Internet and Network Economics held December 14–18, 2009, in Rome,attheDepartmentofComputerandSystemSciences,SapienzaUniversity of Rome. Over the past decade there has been growing interaction between researchers in theoretical computer science, networking and security, economics, mathem- ics, sociology, and management sciences devoted to the analysis of problems arising in the Internet and the worldwide web. The Workshop on Internet and Network Economics (WINE) is an interdisciplinary forum for the exchange of ideas and results arising in these varied ?elds. There were 142 submissions to the workshop including regular and short - pers.Allsubmissionswererigorouslypeer reviewedandevaluatedonthebasisof the quality of their contribution, originality,soundness, and signi?cance. Almost all submissions were reviewed by at least three Program Committee members. The committee decided to accept 34 regular papers and 29 short papers. The Best Student Paper award sponsored by Google Inc. was given to Saeed Alaei and AzarakhshMalekianfor the paper “An Analysisof Troubled Assets Reverse Auction.” The program also included three invited talks by S. Muthukrishnan (Google Inc.and RutgersUniversity),H. PeytonYoung (OxfordandJohns Hopkins U- versity)andEvaTardos(CornellUnversity).Threetutorialswerealsoo?eredon the days before the workshop, from Andrei Broder (Yahoo! Research) on C- putational Advertising, Nikhil Devanur and Kamal Jain (Microsoft Research) on Computational Issues in Market Equilibria, and Tim Roughgarden(Stanford University) on Bayesian and Worst-Case Revenue Maximization.
How does one effectively aggregate disparate pieces of information that are spread among many different individuals? In other words, how does one best access the ‘wisdom of the crowd’? Prediction markets, which are essentially speculative markets created for the purpose of aggregating information and making predictions, offer the answer to this question. The effective use of these markets has the potential not only to help forecast future events on a national and international level, but also to assist companies, for example, in providing improved estimates of the potential market size for a new product idea or the launch date of new products and services. The markets have already been used to forecast uncertain outcomes ranging from influenza to the spread of infectious diseases, to the demand for hospital services, to the box office success of movies, climate change, vote shares and election outcomes, to the probability of meeting project deadlines. The insights gained also have many potentially valuable applications for public policy more generally. These markets offer substantial promise as a tool of information aggregation as well as forecasting, whether alone or as a supplement to other mechanisms like opinion surveys, group deliberations, panels of experts and focus groups. Moreover, they can be applied at a macroeconomic and microeconomic level to yield information that is valuable for government and commercial policy-makers and which can be used for a number of social purposes. This volume of original readings, contributed by many of the leading experts in the field, marks a significant addition to the base of knowledge about this fascinating subject area. The book should be of interest to anyone looking at monetary economics, economic forecasting and microeconomics.
Today’s financial sector faces multiple challenges stemming from ecological, societal, and technological risks such as climate change, political extremism, and cyber-attacks. However, these non-traditional risks are yet to be fully identified and measured, in order to ensure their successful management. This edited collection sheds light on the topic by examining the unique measurement and modelling challenges associated with each of these risks, and their interaction with finance. Offering a comprehensive analysis of non-traditional finance risks, the authors provide the basis for developing appropriate risk management techniques. With new approaches to protect against emerging threats to the financial sector, this edited collection will appeal to academics researching sustainability, development finance, and risk management, as well as policy-makers and practitioners within the banking sector.
How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization. The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not “microprediction,” whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit—and also give back. In an engaging, colloquial style, Cotton argues that market-inspired “superminds” are likely to be very effective compared with other orchestration mechanisms in the domain of microprediction. He presents an ambitious yet practical alternative to the expensive “artisan” data science that currently drains money from firms. Challenging the machine learning revolution and exposing a contradiction at its heart, he offers engineers a new liberty: no longer reliant on quantitative experts, they are free to create intelligent applications using general-purpose application programming interfaces (APIs) and libraries. He describes work underway to encourage this approach, one that he says might someday prove to be as valuable to businesses—and society at large—as the internet.
The aim of this book is to bring students of economics and finance who have only an introductory background in mathematics up to a quite advanced level in the subject, thus preparing them for the core mathematical demands of econometrics, economic theory, quantitative finance and mathematical economics, which they are likely to encounter in their final-year courses and beyond. The level of the book will also be useful for those embarking on the first year of their graduate studies in Business, Economics or Finance. The book also serves as an introduction to quantitative economics and finance for mathematics students at undergraduate level and above. In recent years, mathematics graduates have been increasingly expected to have skills in practical subjects such as economics and finance, just as economics graduates have been expected to have an increasingly strong grounding in mathematics. The authors avoid the pitfalls of many texts that become too theoretical. The use of mathematical methods in the real world is never lost sight of and quantitative analysis is brought to bear on a variety of topics including foreign exchange rates and other macro level issues.