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The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.
Vacant urban land--the product of land market activity, the actions of private agents, and the policies of public agents--is an important challenge for policy makers. Vacant lots on the urban fringe and in central and interstitial areas have affected growth patterns in Latin America. Contributors to this book analyze the problems and opportunities related to vacant urban land in five cities: Buenos Aires, Argentina; Rio de Janeiro, Brazil; Quito, Ecuador; Lima, Perú; and San Salvador, El Salvador.