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1. |
Record Nr. |
UNINA9910139861403321 |
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Autore |
Agarwal Monty <1968-> |
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Titolo |
The future of hedge fund investing [[electronic resource] ] : a regulatory and structural solution for a fallen industry / / Monty Agarwal |
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Pubbl/distr/stampa |
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Hoboken, New Jersey : , : John Wiley & Sons, , 2009 |
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ISBN |
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1-282-30219-1 |
9786612302190 |
1-118-25818-5 |
0-470-55726-5 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (206 p.) |
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Collana |
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Disciplina |
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Soggetti |
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Hedge funds |
Mutual funds |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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The Future of Hedge Fund Investing: A Regulatory and Structural Solution for a Fallen Industry; Contents; Foreword; Introduction; Chapter 1: Recent Hedge Fund Scandals; Chapter 2: The Players; Chapter 3: Hedge Funds; Chapter 4: Hedge Fund Strategies; Chapter 5: Hedge Fund Service Providers and Regulators; Chapter 6: Funds of Hedge Funds; Chapter 7: An Expert Failure; Chapter 8: Remodeling the Funds of Hedge Funds; Chapter 9: Correct Risk Due Diligence; Chapter 10: Interviewing a Hedge Fund Manager; Chapter 11: Hedge Fund Industry's Role in 2008 Market Crisis; Chapter 12: The End; Bibliography |
Index |
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Sommario/riassunto |
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A detailed look at how to fix the hedge fund industry The Future of Hedge Fund Investing spells out in refreshingly stark terms exactly how the industry let down its clients, and the changes needed to restore their confidence. Written by Monty Agarwal, the founder of Predator Capital Management, this insider's guide gives a full assessment of the |
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business, including the advantages of hedge funds, their pitfalls, and, most importantly, how to avoid these missteps. The book begins by describing the hedge fund universe, which includes funds and fund of funds; fund regulators, ma |
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2. |
Record Nr. |
UNINA9910349318203321 |
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Autore |
Gómez Víctor |
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Titolo |
Linear Time Series with MATLAB and OCTAVE / / by Víctor Gómez |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (XVII, 339 p. 128 illus. in color.) |
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Collana |
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Statistics and Computing, , 1431-8784 |
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Disciplina |
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Soggetti |
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Statistics |
Econometrics |
Computer software |
Statistics and Computing/Statistics Programs |
Statistics for Social Sciences, Humanities, Law |
Mathematical Software |
Statistics for Business, Management, Economics, Finance, Insurance |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Preface -- Software Installation -- Stationarity, VARMA and ARIMA Models -- VARMAX and Transfer Function Models -- Unobserved Components in Univariate Series -- Spectral Analysis -- Computing Echelon Forms by Polynomial Methods -- Multivariate Structural Models -- Cointegrated VARMA Models -- Simulation of Common Univariate and Multivariate Models -- The State Space Model -- SSMMATLAB Examples by Subject -- Author Index -- Subject Index. |
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Sommario/riassunto |
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This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details. . |
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