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010   $a1-4939-8835-2
024 7 $a10.1007/978-1-4939-8835-8
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035   $a(MiAaPQ)EBC5598627
035   $a(DE-He213)978-1-4939-8835-8
035   $a(PPN)231458320
035   $a(EXLCZ)994100000007102481
100   $a20181025d2018      u|             0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aDynamic Markov Bridges and Market Microstructure$b[electronic resource] $eTheory and Applications /$fby Umut Çetin, Albina Danilova
205   $a1st ed. 2018.
210  1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2018.
215   $a1 online resource (xiv, 234 pages)
225 1 $aProbability Theory and Stochastic Modelling,$x2199-3130 ;$v90
311   $a1-4939-8833-6 
327   $aMarkov processes -- Stochastic Differential Equations and Martingale Problems -- Stochastic Filtering -- Static Markov Bridges and Enlargement of Filtrations -- Dynamic Bridges -- Financial markets with informational asymmetries and equilibrium -- Kyle-Back model with dynamic information: no default case -- Appendix A.
330   $aThis book undertakes a detailed construction of Dynamic Markov Bridges using a combination of theory and real-world applications to drive home important concepts and methodologies. In Part I, theory is developed using tools from stochastic filtering, partial differential equations, Markov processes, and their interplay. Part II is devoted to the applications of the theory developed in Part I to asymmetric information models among financial agents, which include a strategic risk-neutral insider who possesses a private signal concerning the future value of the traded asset, non-strategic noise traders, and competitive risk-neutral market makers. A thorough analysis of optimality conditions for risk-neutral insiders is provided and the implications on equilibrium of non-Gaussian extensions are discussed. A Markov bridge, first considered by Paul Lévy in the context of Brownian motion, is a mathematical system that undergoes changes in value from one state to another when the initial and final states are fixed. Markov bridges have many applications as stochastic models of real-world processes, especially within the areas of Economics and Finance. The construction of a Dynamic Markov Bridge, a useful extension of Markov bridge theory, addresses several important questions concerning how financial markets function, among them: how the presence of an insider trader impacts market efficiency; how insider trading on financial markets can be detected; how information assimilates in market prices; and the optimal pricing policy of a particular market maker. Principles in this book will appeal to probabilists, statisticians, economists, researchers, and graduate students interested in Markov bridges and market microstructure theory.
410  0$aProbability Theory and Stochastic Modelling,$x2199-3130 ;$v90
606   $aProbabilities
606   $aEconomics, Mathematical 
606   $aStatistics 
606   $aProbability Theory and Stochastic Processes$3https://scigraph.springernature.com/ontologies/product-market-codes/M27004
606   $aQuantitative Finance$3https://scigraph.springernature.com/ontologies/product-market-codes/M13062
606   $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010
615  0$aProbabilities.
615  0$aEconomics, Mathematical .
615  0$aStatistics .
615 14$aProbability Theory and Stochastic Processes.
615 24$aQuantitative Finance.
615 24$aStatistics for Business, Management, Economics, Finance, Insurance.
676   $a519.24
700   $aÇetin$b Umut$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767949
702   $aDanilova$b Albina$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910300114603321
996   $aDynamic Markov Bridges and Market Microstructure$92056065
997   $aUNINA