JAVAHERI, ALIREZA (36 risultati)

Condizione: Good. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.

Hardcover. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.3.

Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Condizione: new.

Hardcover. Condizione: gebraucht; wie neu. (507-3).

Hardcover. Condizione: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Condizione: good. This book is in Good condition. There may be some notes and highligting but otherwise the book is in overall good condition.

first printing ed. hardback very good condition in a very good dust jacket -.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. In.

Hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Hardcover. Condizione: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority!

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. Author and financial expert Alireza Javaheri uses the classic approach to evaluating volatility--time series and financial econometrics--in a way that he believes is superior to methods presently used by market participants. He also suggests that there may .

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days. 547.

Hardback. Condizione: New. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate dataIntegrate past observation with Bayesian probabilityExploit posterior distribution of the hidden state for optimal estimationBoost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.

Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

Condizione: New. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Series: Wiley Finance. Num Pages: 320 pages, illustrations. BIC Classification: KJMV1. Category: (P) Professional & Vocational. Dimension: 234 x 172 x 27. Weight in Grams: 528. . 2015. 2nd Edition. Hardcover. . . . .

Condizione: New. pp. 288.

Hardback. Condizione: New. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate dataIntegrate past observation with Bayesian probabilityExploit posterior distribution of the hidden state for optimal estimationBoost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation.

Hardcover. Condizione: New.

Condizione: New. pp. 288 2nd Edition.

Hardcover. Condizione: new. Hardcover. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate dataIntegrate past observation with Bayesian probabilityExploit posterior distribution of the hidden state for optimal estimationBoost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condizione: new. Hardcover. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Based on the idea of "filtering", this book lays out a two-step framework involving a Chapman-Kolmogorov prior distribution followed by Bayesian posterior distribution to develop a robust estimation based on all available information. This new second edition includes guidance toward basing estimations on historic option prices instead of stocks, as well as Wiener Chaos Expansions and other spectral approaches. The author's statistical trading strategy has been expanded with more in-depth discussion, and the companion website offers new topical insight, additional models, and extra charts that delve into the profitability of applied model calibration. You'll find a more precise approach to the classical time series and financial econometrics evaluation, with expert advice on turning data into profit. Financial markets do not always behave according to a normal bell curve. Skewness creates uncertainty and surprises, and tarnishes trading performance, but it's not going away. This book shows traders how to work with skewness: how to predict it, estimate its impact, and determine whether the data is presenting a warning to stay away or an opportunity for profit. Base volatility estimations on more accurate dataIntegrate past observation with Bayesian probabilityExploit posterior distribution of the hidden state for optimal estimationBoost trade profitability by utilizing "skewness" opportunities Wall Street is constantly searching for volatility assessment methods that will make their models more accurate, but precise handling of skewness is the key to true accuracy. Inside Volatility Filtering shows you a better way to approach non-normal distributions for more accurate volatility estimation. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Buch. Condizione: Neu. Neuware - Author and financial expert Alireza Javaheri uses the classic approach to evaluating volatility--time series and financial econometrics--in a way that he believes is superior to methods presently used by market participants. He also suggests that there may be 'skewness' trading opportunities that can be sued to trade the markets mroe profitably. Filed with in-depth insight and expert advice, this book will focus on the idea of filtering.The idea behind filtering is to obtain the best possible estimation of a hidden state given all the available information up to that point. This estimation is done in an iterative manner in two stages: The first step is a time update in which the prior distribution from all the past information via a Chapman-Kolmogorov equation. The second step would then involve a measurement update where this prior distribution is used together with the conditional likelihood of the newest observation in order to compute the posterior distribution of the hidden state. The Bayes rule is used for this purpose. Once the posterior distribution is determined, it can be exploited for the optimal estimation of the hidden state.For practitioners and students, the author is adding content on:\* estimation from historic option prices instead of stocks, as the observation quality is better\* spectral approaches and in particular Wiener Chaos Expansions\* on the statistical trading strategy in section 3.

Condizione: New. A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to volatility estimation, using financial econometrics based on a more accurate estimation of the hidden state. Series: Wiley Finance. Num Pages: 320 pages, illustrations. BIC Classification: KJMV1. Category: (P) Professional & Vocational. Dimension: 234 x 172 x 27. Weight in Grams: 528. . 2015. 2nd Edition. Hardcover. . . . . Books ship from the US and Ireland.

Condizione: New.