Описание: Financial Markets Theory presents classical asset pricing theory, a theory composed of milestones such as portfolio selection, risk aversion, fundamental asset pricing theorem, portfolio frontier, CAPM, CCAPM, APT, the Modigliani-Miller Theorem, no arbitrage/risk neutral evaluation and information in financial markets. Starting from an analysis of the empirical tests of the above theories, the author provides a discussion of the most recent literature, pointing out the main advancements within classical asset pricing theory and the new approaches designed to address open problems (e.g. behavioural finance). It is the only textbook to address the economic foundations of financial markets theory from a mathematically rigorous standpoint, and to offer a self-contained critical discussion, based on empirical results. Financial Markets Theory is an advanced book, well-suited for a first graduate course in financial markets, economics or financial mathematics. It is self-contained and introduces topics in a setting accessible to economists and practitioners equipped with a basic mathematical background. For those not acquainted with standard microeconomic theory, the tools needed to follow the analysis are presented early in the book. The approach makes this a vital handbook for practitioners in insurance, banking, investment funds and financial consultancy, as well as an excellent graduate-reference textbook.
Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools adequate to measure and anticipate the amplitude of potential swings in the financial markets--from ordinary stock price and interest rate moves, to defaults, to those increasingly frequent "rare events" fashionably called black swan events. Yet many on Wall Street continue to rely on standard models based on artificially simplified assumptions that can lead to systematic (and sometimes catastrophic) underestimation of real risks.
In Practical Methods of Financial Engineering and Risk Management, Dr. Rupak Chatterjee-- former director of the multi-asset quantitative research group at Citi--introduces finance professionals and advanced students to the latest concepts, tools, valuation techniques, and analytic measures being deployed by the more discerning and responsive Wall Street practitioners, on all operational scales from day trading to institutional strategy, to model and analyze more faithfully the real behavior and risk exposure of financial markets in the cold light of the post-2008 realities. Until one masters this modern skill set, one cannot allocate risk capital properly, price and hedge derivative securities realistically, or risk-manage positions from the multiple perspectives of market risk, credit risk, counterparty risk, and systemic risk.
The book assumes a working knowledge of calculus, statistics, and Excel, but it teaches techniques from statistical analysis, probability, and stochastic processes sufficient to enable the reader to calibrate probability distributions and create the simulations that are used on Wall Street to valuate various financial instruments correctly, model the risk dimensions of trading strategies, and perform the numerically intensive analysis of risk measures required by various regulatory agencies.
Описание: Models & Methods for Project Selection systematically examines in this book treatment the latest work in the field of project selection modeling. The models presented are drawn from mathematical programming, decision theory, and finance. These models are examined in two categorical streams: the management science stream and the financial model stream. The book describes the assumptions and limitations of each model and provides appropriate solution methodologies. Its organization follows three main themes: *Criteria for Choice: Chapters 1-3 investigate the effect of the choice of optimization criteria on the results of the portfolio optimization problem. This group of chapters examines the multiobjective linear programming approach, discusses the appropriate methods for adjusting for time and risk in the project selection problem, and expands on the discussion of optimization models and NPV. *Risk and Uncertainty: Chapters 4-7 deal with uncertainty in the project selection problem. The models developed in this section are based on probability distribution assumptions or estimates and deal with uncertainty in some aspect of the project selection model. *Non-Linearity and Interdependence: These chapters deal with problems of non-linearity and interdependence as they arise in the project selection problem. The ability to handle non-linear problems allows the application of the methodology to a far wider range of problems. Similarly, the ability to model interdependence between projects - as in the Information Technology models - is an important step in generalization. Chapters 8, 9 and 10 present solution methodologies, which can be used to solve these most general project selection models.
Описание: Within an environment made difficult by the continuing economic crisis, the Italian model for crisis management and resolution has helped to avoid many difficulties faced by intermediaries across the globe.
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