Good : A book that has been read but is in good condition. Inside VolatilityArbitrage can help them do this. Author and financial expertAlireza Javaheri uses the classic approach to evaluating volatility-- time series and financial econometrics -- in a way that hebelieves is superior to methods presently used by marketparticipants. He also suggests that there may be "skewness" tradingopportunities that can be used to trade the markets moreprofitably.
Filled with in-depth insight and expert advice, Inside Volatility Arbitrage will help traders discover when"skewness" may present valuable trading opportunities as well aswhy it can be so profitable. Contributions and Further Research.
Data and Programs. Chapter 1: The Volatility Problem. The Stock Market. The Stock Price Process. Historic Volatility. The Derivatives Market. The Black-Scholes Approach. The Cox-Ross-Rubinstein Approach. Jump Diffusion and Level-Dependent Volatility. Jump Diffusion. Level-Dependent Volatility.
Local Volatility. The Dupire Approach. The Derman-Kani Approach. Stability Issues. Calibration Frequency. Stochastic Volatility. Stochastic Volatility Processes. The Market Price of Volatility Risk. The Generalized Fourier Transform. The Transform Technique.
Special Cases. The Mixing Solution.
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The Romano-Touzi Approach. The Long-Term Asymptotic Case. The Deterministic Case. The Stochastic Case. A Series Expansion on Volatility-of-Volatility. Pure-Jump Models. Variance Gamma. Variance Gamma with Stochastic Arrival. Variance Gamma with Gamma Arrival Rate. Chapter 2: The Inference Problem. Using Option Prices. Direction Set Powell Method.
Numeric Tests. The Distribution of the Errors. Using Stock Prices. The Likelihood Function. The Simple and Extended Kalman Filters.
The Unscented Kalman Filter. Kushner's Nonlinear Filter. Parameter Learning. Parameter Estimation via MLE. Particle Filtering. Comparing Heston with Other Models. The Performance of the Inference Tools. The Bayesian Approach. Using the Characteristic Function. Introducing Jumps. Pure Jump Models. Model Identification. Convergence Issues and Solutions. In Section 1: The Volatility Problem, Javaheri introduces the concept of various parametric SV models and examines literature on the subject of non—deterministic volatility. In Section 2: The Inference Problem, Javaheri tackles the notion of inference or parameter estimation for parametric SV models—briefly analyzing cross—sectional inference and then focusing on time—series inference.
Finally, in Section 3: The Consistency Problem, Javaheri shows you how to apply parametric inference methodologies to a few assets. He also reveals why you should question the consistency of information contained in the options markets and the stock market. Access 30 Terabyte Data 3. Inside Volatility Arbitrage can help them do this. 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.
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Inside Volatility Arbitrage: The Secrets of Skewness - Alireza Javaheri - Google книги
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