This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynam… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Buch (fremdspr.) Baosheng Yuan Taschenbuch, LAP LAMBERT Academic Publishing, 30.07.2010, LAP LAMBERT Academic Publishing, 2010<
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This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and d… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Trade Books>Trade Paperback>Business>Business & Economics>Economics, LAP Lambert Academic Publishing Core >1<
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(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and d… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Trade Books>Trade Paperback>Business>Business & Economics>Economics, KS OmniScriptum Publishing Core >1<
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[ED: Kartoniert / Broschiert], [PU: LAP LAMBERT Academic Publishing], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yuan … Mehr…
[ED: Kartoniert / Broschiert], [PU: LAP LAMBERT Academic Publishing], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yuan BaoshengBaosheng is Vice President of Great Eastern Life Assurance Group Investment Management. Baosheng developes strategic and tactical, DE, [SC: 0.00], Neuware, gewerbliches Angebot, Taschenbuch, 232, [GW: 345g], 1. Auflage, Banküberweisung, PayPal, [CT: Englischsprachige Bücher / Sonstiges - Englisch]<
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This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynam… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Buch (fremdspr.) Baosheng Yuan Taschenbuch, LAP LAMBERT Academic Publishing, 30.07.2010, LAP LAMBERT Academic Publishing, 2010<
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This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and d… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Trade Books>Trade Paperback>Business>Business & Economics>Economics, LAP Lambert Academic Publishing Core >1<
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and d… Mehr…
This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk. Trade Books>Trade Paperback>Business>Business & Economics>Economics, KS OmniScriptum Publishing Core >1<
[ED: Kartoniert / Broschiert], [PU: LAP LAMBERT Academic Publishing], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yuan … Mehr…
[ED: Kartoniert / Broschiert], [PU: LAP LAMBERT Academic Publishing], Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Yuan BaoshengBaosheng is Vice President of Great Eastern Life Assurance Group Investment Management. Baosheng developes strategic and tactical, DE, [SC: 0.00], Neuware, gewerbliches Angebot, Taschenbuch, 232, [GW: 345g], 1. Auflage, Banküberweisung, PayPal, [CT: Englischsprachige Bücher / Sonstiges - Englisch]<
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This thesis studies three most important and difficult problems in financial risk: 1). Scaling, clustering and dynamics of volatility of financial asset returns; 2). Statistical and dynamical properties of the market; and 3). Driven force underlying the market volatility. The Value at Risk (VaR) measure currently used in financial industry is far from a reliable tool due to its lack of volatility clustering measure. This thesis presents a solution to this problem. Next, the dynamics of the market is studied from the perspective of interacting and competing agents with self-segregation or herding behaviors. This model shows that investor's winning strategy depends on the market dynamics: active when market is highly volatile and clustered and inactive otherwise. Last, a heterogeneous agent-based model is developed to investigate the impact of investor's sentiments on asset price dynamics. The simulation results show that investor's dynamical risk aversion is the primary driven force that gives rise to the excess and clustered volatility. All these results are the keys to understanding, quantifying and managing financial risk.
Detailangaben zum Buch - Key to Understanding Financial Market Risk Baosheng Yuan Author
EAN (ISBN-13): 9783838359045 ISBN (ISBN-10): 3838359046 Gebundene Ausgabe Taschenbuch Erscheinungsjahr: 2010 Herausgeber: LAP Lambert Academic Publishing Core >1 232 Seiten Gewicht: 0,362 kg Sprache: eng/Englisch
Buch in der Datenbank seit 2008-08-21T09:07:30+02:00 (Berlin) Detailseite zuletzt geändert am 2024-04-18T15:53:51+02:00 (Berlin) ISBN/EAN: 9783838359045
ISBN - alternative Schreibweisen: 3-8383-5904-6, 978-3-8383-5904-5 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: yüan, yuan Titel des Buches: markets risk, scaling