| Description |
1 online resource (xi, 152 pages) |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
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text file |
| Bibliography |
Includes bibliographical references and index. |
| Note |
Vendor-supplied metadata. |
| Summary |
This book presents a crisis scenario generator with black swans, black butterflies and worst case scenarios. It is the most useful scenario generator that can be used to manage assets in a crisis-prone period, offering more reliable values for Value at Risk (VaR), Conditional Value at Risk (CVaR) and Tail Value at Risk (TVaR). Hazardous Forecasts and Crisis Scenario Generator questions how to manage assets when crisis probability increases, enabling you to adopt a process for using generators in order to be well prepared for handling crises. |
| Contents |
Ch. 1 Risk-oriented Philosophy, Forecast-based Philosophy and Process -- 1.1.A risk-oriented philosophy and a forecast-based philosophy -- 1.1.1. Why a risk-oriented philosophy? -- 1.1.2. Management by crisis is the philosophy of global capitalism -- 1.1.3.A forecast-based philosophy and risk evaluation processes -- 1.1.4. One-year scenarios and leading indicators -- 1.1.5. Forecasting ability is limited by exogenous shock risks -- 1.1.6. The necessity of scenario building -- 1.1.7. The importance of crisis propagation scenarios -- 1.2. Rational expectations theory and the efficient market hypothesis -- 1.2.1. Rational expectations hypothesis and geopolitical risks -- 1.2.2. Imperfect knowledge and forecasts imply surprises -- 1.2.3. Rational expectations hypothesis and imperfect forecasts in a crisis-prone period -- 1.2.4. How could the homo economicus be rational with media advice as the only information? -- 1.3. Irrational crisis behaviors make previous expectation hypotheses dangerous -- 1.3.1. Irrational crisis behavior and fear -- 1.3.2. Irrational crisis behavior and bubbles -- 1.3.3. Irrational crisis behaviors and mimesis -- 1.3.4. Irrational crisis behavior and illiquid markets with mimesis and some fears -- 1.3.5. Market efficiency is not easy to study during a crisis -- 1.3.6. Economic scenario generates can take care of rational and irrational behaviors with some fears and mimesis in a crisis-prone period -- 1.4. How large is the rational hypothesis validity field? -- 1.4.1. US mutual fund record and rational hypothesis validity field -- 1.4.2. To judge the rational hypothesis validity field is complex -- 1.5. Conclusion -- ch. 2 Scenario Building Processes -- 2.1. Most asset managers have only one or two scenarios in mind -- 2.2. Long-term scenarios and geopolitical surprises -- 2.2.1. Climate change scenarios and surprises -- 2.2.2. Climate changes and migrations -- 2.2.3. Geopolitical scenarios and surprises -- 2.2.4. Long-term demographic impact -- 2.2.5. Economic emergence of the African continent -- 2.2.6. Long-term risk valuation methods -- 2.3. Five-year scenarios -- 2.3.1. Many five-year crisis scenarios are possible in Europe -- 2.3.2. Some kinds of Japanese deflationary processes -- 2.3.3. Different kinds of deflationary processes in Europe -- 2.3.4. Different kinds of systemic banking crisis processes -- 2.4. An efficient five-year scenario generator -- 2.4.1.Combination of two 5-year generators -- 2.4.2. Specific treatment of a social crisis scenario -- 2.5. Details on several scenarios -- 2.5.1. Scenarios for the Eurozone -- 2.5.2. Scenarios for English-speaking countries -- 2.5.3. Scenarios for Asia -- 2.6. An efficient one-year scenario generator -- 2.6.1. One-year generator for negative scenarios -- 2.6.2. One-year generator for positive scenarios -- 2.6.3. Other issues -- ch. 3 How to Use These Scenarios for Asset Management? -- 3.1. Philosophy of equity portfolio optimization -- 3.1.1. Optimization and risk-oriented philosophy -- 3.1.2. How and how frequently should we use an economic scenario generator? -- 3.1.3. Economic scenario generator for a crisis-prone period -- 3.2. Which classic optimization processes are well fitted? -- 3.2.1. Capital asset pricing model -- 3.2.2. Screening or optimization by arbitrage pricing theory -- 3.2.3. Black -- Litterman (1992) for more stable results -- 3.2.4. Optimization based on benchmarks -- 3.2.5. Active management methodology -- 3.3. Risk aversion and utility function -- 3.3.1. Which risk measures for utility optimization? -- 3.3.2. Optimization with classic or not so classic measures of risk -- 3.3.3. Is a polynomial utility an improvement? -- 3.4. Better fit processes for a crisis -- 3.4.1. Markov regime switching optimization best fit for a crisis -- 3.4.2. What could be said about the cost when the method is changed? -- 3.4.3. Risk diversification: risk parity or risk budgeting? -- 3.4.4. Minimum variance policy -- 3.4.5. Resilient equity portfolio construction with same weight stock allocation -- 3.5. Crisis process for equity portfolio optimization -- 3.5.1. What kind of generator to optimize? -- 3.5.2. Optimization with risk budgets for crisis resilience control -- 3.5.3. Insightful comparisons between optimized portfolios -- 3.5.4. ESG and stock management -- 3.6. Resilient bond portfolio building -- 3.6.1. How could a rate trend turn around? -- 3.6.2.A protective bond management -- 3.6.3. ESG and bond management -- 3.7. Application -- 3.8. Conclusion. |
| Subject |
Economic forecasting.
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International finance -- Forecasting.
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Globalization -- Economic aspects.
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Prévision économique.
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Mondialisation.
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globalism.
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BUSINESS & ECONOMICS -- Economics -- General.
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BUSINESS & ECONOMICS -- Reference.
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Economic forecasting
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Globalization -- Economic aspects
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International finance -- Forecasting
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| Added Author |
Fraysse, Hervé, author.
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| Other Form: |
Print version: Clément-Grandcourt, Arnaud. Hazardous forecasts and crisis scenario generator. London, England ; Oxford, England : ISTE Press : Elsevier, ©2015 xi, 152 pages 9781785480287 |
| ISBN |
9780081007778 (electronic bk.) |
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0081007779 (electronic bk.) |
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9781785480287 |
| Standard No. |
AU@ 000056747895 |
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AU@ 000066135300 |
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AU@ 000068480890 |
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CHBIS 010796085 |
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CHNEW 001013175 |
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CHVBK 403949807 |
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DEBBG BV044026813 |
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DEBSZ 48246769X |
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GBVCP 879391006 |
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