The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets

The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets PDF Author:
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ISBN:
Category :
Languages : en
Pages :

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The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets

The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets PDF Author: Thomas Busch
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Forecasting Volatility in the Financial Markets

Forecasting Volatility in the Financial Markets PDF Author: John L. Knight
Publisher: Butterworth-Heinemann
ISBN: 9780750655156
Category : Business & Economics
Languages : en
Pages : 428

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Book Description
This text assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modeling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.

Forecasting Volatility in the Financial Markets

Forecasting Volatility in the Financial Markets PDF Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080471420
Category : Business & Economics
Languages : en
Pages : 428

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Book Description
Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling

Forecasting the Volatility of Stock Market and Oil Futures Market

Forecasting the Volatility of Stock Market and Oil Futures Market PDF Author: Dexiang Mei
Publisher: Scientific Research Publishing, Inc. USA
ISBN: 164997048X
Category : Business & Economics
Languages : en
Pages : 139

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Book Description
The volatility has been one of the cores of the financial theory research, in addition to the stock markets and the futures market are an important part of modern financial markets. Forecast volatility of the stock market and oil futures market is an important part of the theory of financial markets research.

Construction and Interpretation of Model-free Implied Volatility

Construction and Interpretation of Model-free Implied Volatility PDF Author: Torben G. Andersen
Publisher:
ISBN:
Category : Assets (Accounting)
Languages : en
Pages : 48

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Book Description
The notion of model-free implied volatility (MFIV), constituting the basis for the highly publicized VIX volatility index, can be hard to measure with accuracy due to the lack of precise prices for options with strikes in the tails of the return distribution. This is reflected in practice as the VIX index is computed through a tail-truncation which renders it more compatible with the related concept of corridor implied volatility (CIV). We provide a comprehensive derivation of the CIV measure and relate it to MFIV under general assumptions. In addition, we price the various volatility contracts, and hence estimate the corresponding volatility measures, under the standard Black-Scholes model. Finally, we undertake the first empirical exploration of the CIV measures in the literature. Our results indicate that the measure can help us refine and systematize the information embedded in the derivatives markets. As such, the CIV measure may serve as a tool to facilitate empirical analysis of both volatility forecasting and volatility risk pricing across distinct future states of the world for diverse asset categories and time horizons.

The Economic Value of Using Realized Volatility in Forecasting Future Implied Volatility

The Economic Value of Using Realized Volatility in Forecasting Future Implied Volatility PDF Author: Wing H. Chan
Publisher:
ISBN:
Category :
Languages : en
Pages : 42

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Book Description
We examine the economic benefits of using realized volatility to forecast future implied volatility for pricing, trading, and hedging in the Samp;P 500 index options market. We propose an encompassing regression approach to forecast future implied volatility and hence future option prices by combining historical realized volatility and current implied volatility. An analysis of delta-neutral straddles and naked and delta-hedged option positions shows that the statistical superiority of historical realized volatility demonstrated in the encompassing regressions and option pricing errors does not translate into economic gains, when trading and hedging in the options markets, after considering trading costs.

Implied Volatilities as Forecasts of Future Volatility, Time-Varying Risk Premia, and Returns Variability

Implied Volatilities as Forecasts of Future Volatility, Time-Varying Risk Premia, and Returns Variability PDF Author: Mikhail Chernov
Publisher:
ISBN:
Category :
Languages : en
Pages : 32

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Book Description
The unbiasedness tests of implied volatility as a forecast of future realized volatility have found implied volatility to be a biased predictor. We explain this puzzle by recognizing that option prices contain a market risk premium not only on the asset itself, but also on its volatility. Hull and White (1987) show using a stochastic volatility model that a call option price can be represented as an expected value of the Black-Scholes formula evaluated at the average integrated volatility. If we allow volatility risk to be priced, this expectation should be taken under the risk-neutral probability measure, and can be decomposed into the expectation with respect to the physical measure and the risk-premium term. This term is just a linear function of the unobservable spot volatility. The decomposition explains the bias documented in the empirical literature and shows that the realized and historical volatility, which are used in the tests, are in fact the estimates of the unobserved quadratic variation and spot volatility of the stock-return generating process. Therefore, the use of these estimates generates the error-in-the-variables problem. We generalize the above results from a stochastic volatility model to a model with multiple volatility and jump factors. We provide an empirical illustration based on two US equity indices and three foreign currency rates. We find, that when we take into an account the risk-premium and use efficient methods to estimate volatility, the unbiasedness hypothesis can not be rejected, and the point estimate of the loading on the implied volatility in the traditional regression is equal to 1.

The Sensitivity of Implied Volatility to Expectations of Jumps in Volatility

The Sensitivity of Implied Volatility to Expectations of Jumps in Volatility PDF Author: Aku Penttinen
Publisher:
ISBN:
Category :
Languages : en
Pages : 59

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Book Description
The apparent bias in implied volatility as a forecast of the subsequently realized volatility is a well-documented empirical puzzle. As suggested by e.g. Feinstein (1989), Jackwerth and Rubinstein (1996), and Bates (1997), we test whether unrealized expectations of jumps in volatility could explain this phenomenon. Our findings show that expectations of infrequently occurring jumps in volatility are priced in implied volatility, which has two important consequences. First, implied volatility will slightly exceed realized volatility most of the time only to be considerably lower than realized volatility during infrequently occurring periods of very high volatility. Second, the slope coefficient in the classic forecasting regression of realized volatility on implied volatility is very sensitive to the discrepancy between the ex ante expected and ex post realized jump frequencies. If the in-sample frequency of positive volatility jumps is lower than ex ante assessed by the market, the slope coefficient will be biased downward and the classic regression test will erroneously reject the hypothesis of no bias even if the market is informationally efficient. Since the inferences of almost all previous studies on the forecasting power of implied volatility have been based on data from a period of historically low volatility, our results provide a rational explanation for the illusory bias in implied volatility.

Beast on Wall Street

Beast on Wall Street PDF Author: Robert A. Haugen
Publisher: Pearson
ISBN:
Category : Business & Economics
Languages : en
Pages : 170

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Book Description
It is now abundantly clear that stock volatility is a contagious disease that spreads virulently from market to market around the world. Price changes in one market drive subsequent price changes in that market as well as in others. In Beast, Haugen makes a compelling case for the fact that even under normal conditions, fully 80 percent of stock volatility is price driven. Moreover, this volatility is far from benign. It acts to reduce the level of investment spending and constitutes a significant and permanent drag on economic growth. Price-driven volatility is unstable. Dramatic and unpredictable explosions in price-driven volatility can send stock markets in a downward spiral and cause significant disruptions in economic activity. Haugen argues that this indeed happened in 1929 and 1930. If volatility in Asian markets persists, it can easily become the source of the problem rather than merely a symptom.