Download or read book Forecasting VIX written by Stavros Antonios Degiannakis and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implied volatility index of the S&P500 is considered as a dependent variable in a fractionally integrated ARMA model, whereas volatility measures based on interday and intraday datasets are considered as explanatory variables. The next trading day's implied volatility forecasts provide positive average daily profits. All the forecasting information is provided by the VIX index itself. There is no incremental predictability from both realized volatility computed from intraday data and conditional volatility extracted from an Arch model. Hence, neither the interday volatility nor the use of intraday data yield any added value in forecasting the S&P 500 implied volatility index. However, an agent cannot utilize VIX predictions in creating abnormal returns in implied volatility futures market.
Download or read book The Causal Relationship between the S P 500 and the VIX Index written by Florian Auinger and published by Springer. This book was released on 2015-02-13 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Florian Auinger highlights the core weaknesses and sources of criticism regarding the VIX Index as an indicator for the future development of financial market volatility. Furthermore, it is proven that there is no statistically significant causal relationship between the VIX and the S&P 500. As a consequence, the forecastability is not given in both directions. Obviously, there must be at least one additional variable that has a strong influence on market volatility such as emotions which, according to financial market experts, are considered to play a more and more important role in investment decisions.
Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Download or read book Trading VIX Derivatives written by Russell Rhoads and published by John Wiley & Sons. This book was released on 2011-07-11 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to using the VIX to forecast and trade markets Known as the fear index, the VIX provides a snapshot of expectations about future stock market volatility and generally moves inversely to the overall stock market. Trading VIX Derivatives will show you how to use the Chicago Board Options Exchange's S&P 500 volatility index to gauge fear and greed in the market, use market volatility to your advantage, and hedge stock portfolios. Engaging and informative, this book skillfully explains the mechanics and strategies associated with trading VIX options, futures, exchange traded notes, and options on exchange traded notes. Many market participants look at the VIX to help understand market sentiment and predict turning points. With a slew of VIX index trading products now available, traders can use a variety of strategies to speculate outright on the direction of market volatility, but they can also utilize these products in conjunction with other instruments to create spread trades or hedge their overall risk. Reviews how to use the VIX to forecast market turning points, as well as reveals what it takes to implement trading strategies using VIX options, futures, and ETNs Accessible to active individual traders, but sufficiently sophisticated for professional traders Offers insights on how volatility-based strategies can be used to provide diversification and enhance returns Written by Russell Rhoads, a top instructor at the CBOE's Options Institute, this book reflects on the wide range of uses associated with the VIX and will interest anyone looking for profitable new forecasting and trading techniques.
Download or read book S P 500 Index Realized Volatility and VIX Forecasting The Information Content of VIX VIX Options and VVIX written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book VIX Forecasting written by Utkarsh Majmudar and published by . This book was released on 2004 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The celebrated Black-Scholes model for valuing options uses a number of inputs - current stock price, risk-free interest rate, exercise price, time to maturity and volatility of returns. One critical input is the volatility of returns. Historical volatility is of little use as what is relevant is future volatility. Assuming efficient markets, a good source of volatility estimate is the implied volatility. Among the inputs to the Black-Scholes model all except volatility are known in advance. The output - the current call price is also known. Implied volatility is arrived at using the current call prices and all other inputs in the Black-Scholes formula to ascertain the volatility. This is a forward looking volatility estimate. We forecast volatility using VIX data obtained from CBOE. This paper adds value to extant literature by forecasting the revised VIX using a variety of forecasting tools like GARCH, EGARCH, APARCH, GJR and IGARCH. The EGARCH model is selected as it performs well on forecast accuracy. Using combinations of options, it is possible to trade volatility as if it were any other commodity, so that accurate predictions of future volatility give the forecaster the potential to make a more direct profit.
Download or read book Price Forecasting Models for Vix VIX Stock written by Ton Viet Ta and published by . This book was released on 2021-03-10 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: https: //www.dinhxa.com One-Week Free Trial (subject to change) Do you want to earn up to a 4677397% annual return on your money by two trades per day on Vix ^VIX Stock? Reading this book is the only way to have a specific strategy. This book offers you a chance to trade ^VIX Stock at predicted prices. Eight methods for buying and selling ^VIX Stock at predicted low/high prices are introduced. These prices are very close to the lowest and highest prices of the stock in a day. All methods are explained in a very easy-to-understand way by using many examples, formulas, figures, and tables. The BIG DATA of the 7346 consecutive trading days (from January 2, 1992 to March 4, 2021) are utilized. The methods do not require any background on mathematics from readers. Furthermore, they are easy to use. Each takes you no more than 30 seconds for calculation to obtain a specific predicted price. The methods are not transient. They cannot be beaten by Mr. Market in several years, even until the stock doubles its current age. They are traits of Mr. Market. The reason is that the author uses the law of large numbers in the probability theory to construct them. In other words, you can use the methods in a long time without worrying about their change. The efficiency of the methods can be checked easily. Just compare the predicted prices with the actual price of the stock while referring to the probabilities of success which are shown clearly in the book (click the LOOK INSIDE button to read more information before buying this book). The book is very useful for Investors who have decided to buy the stock and keep it for a long time (as the strategy of Warren Buffett), or to sell the stock and pay attention to other stocks. The methods will help them to maximize profits for their decision. Day traders who buy and sell the stock many times in a day. Although each method is valid one time per day, the information from the methods will help the traders buy/sell the stock in the second time, third time or more in a day. Beginners to ^VIX Stock. The book gives an insight about the behavior of the stock. They will surely gain their knowledge of ^VIX Stock after reading the book. Everyone who wants to know about the U.S. stock market. https: //www.dinhxa.com includes a software (app) for stock price forecasting using the methods in this book. The software gives 114 predictions while this book gives 16. One-Week Free Trial (subject to change)
Download or read book Modeling and Forecasting the VIX Index written by Katja Ahoniemi and published by . This book was released on 2008 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper models the implied volatility of the Samp;P 500 index, with the aim of producing useful forecasts for option traders. Numerous time-series models of the VIX index are estimated, and daily out-of-sample forecasts are calculated from all relevant models. The directional accuracy of the forecasts is evaluated with market-timing tests. Option trades are simulated based on the forecasts, and their profitability is also used to rank the models. The results indicate that an ARIMA (1,1,1) model enhanced with exogenous regressors has predictive power regarding the directional change in the VIX index. GARCH terms are statistically significant, but do not improve forecasts. The best models predict the direction of change correctly for over 60 percent of the trading days. Out-of-sample option trading over a period of fifteen months yields positive returns when the forecasts from the best models are used as the basis for investment decisions.
Download or read book Forecasting the VIX to Improve VIX Derivatives Trading written by Chrilly Donninger and published by . This book was released on 2016 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: Konstantinidi et. al. state in their broad survey of Volatility-Index forecasting: "The question whether the dynamics of implied volatility indices can be predicted has received little attention". The overall result of this and the quoted papers is: The VIX is too a very limited extend (R2 is typically 0.01) predictable, but the effect is economically not significant.This paper confirms this finding if (and only if) the forecast horizon is limited to one day. But there is no practical need to do so. One can - and usually does - hold a VIX Future or Option several trading days. It is shown that a simple model has a highly significant predictive power over a longer time horizon. The forecasts improve realistic trading strategies.
Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Forecasting VIX the Illusion of Forecast Evaluation Criteria written by Stavros Degiannakis and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Ability of VIX Futures to Predict S P 500 Volatility written by Peter Williams and published by . This book was released on 2018 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper examines the ability of futures on the CBOE Volatility Index (VIX) to predict realized S&P 500 volatility up to seven months into the future. These forecasts are found to be significantly biased. The imposition of a priori theoretically motivated restrictions can substantially improve forecast accuracy, especially when the VIX futures are augmented with the variance risk premium. When VIX futures are compared with out-of-sample forecasts from a GJR-GARCH model, the VIX-based forecasts are found to robustly outperform during periods of high volatility. In more normal states this out-performance is less significant but still present.
Download or read book Forecasting and Trading VIX Futures written by 高振添 and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Forecasting Volatility in the Financial Markets written by John L. Knight and published by Butterworth-Heinemann. This book was released on 2002 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Is the VIX Futures Market Able to Predict the VIX Index A Test of the Expectation Hypothesis written by Marcus Nossman and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper tests the expectation hypothesis by using the volatility index VIX and the futures written on that index. Because the VIX index is negatively correlated with the Samp;P 500 index returns, the VIX futures price should contain a negative risk premium, which we do confirm in this study. When the futures price is not adjusted with the risk premium, the expectation hypothesis is rejected at the 5 percent significance level for 20 of 21 forecast horizons. However when we adjust the futures price with the risk premium, obtained from a stochastic volatility model, the expectation hypothesis cannot be rejected. Further, we find that the risk premium adjusted futures price forecasts the direction of the VIX index well. The one day ahead forecast predicts the direction correctly in 73 percent of the times.
Download or read book Do VIX and Trading Volume Subsume Incremental Information Above GARCH Type Models for the Volatility Forecast written by Fan Li and published by . This book was released on 2019 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: The VIX index and trading volume (VO) can subsume information of the future volatility in financial markets, and therefore, have been commonly used as volatility forecasting instruments. Previous studies have identified superior VIX- and VO-based forecasts compared to various GARCH-type models, while contradictory evidence for the outperformance of GARCH-based forecasts rises controversies about the optimal forecast. To evaluate whether VIX and VO may subsume incremental information over GARCH-type models, this paper evaluates the volatility forecast efficiency of VIX, VO and GARCH.Latest daily VIX, VO and SPX during 01/01/2006-17/07/2017 are sorted from Bloomberg. To access the forecast efficiency, Mincer-Zarnowitz (MZ, 1969) regression, the forecast encompassing test and root-mean-square error (RMSE) are to be applied. The present empirical result indicates incremental information in VIX, while VO seems to subsume little or no additional information over GARCH, which contradicts previous findings of Kambouroudis and McMillan (2016).Recent concerns about the influence of financial turmoil on the volatility forecast have generated a considerable body of research; however, most previous investigations of the volatility forecast efficiency have not addressed this issue. Hence, this paper is motivated to identify the effect of 2008 financial crisis on the volatility estimates. Current findings confirm a negative crisis dilution effect occurred in 2012, especially for VO-based predictions. The identified dilution effect demonstrated a negative influence of turmoil on volatility forecasts due to the disruption of the economic condition during the post-crisis period. Further work is recommended on validating this issue in various financial markets, such as foreign exchange markets.
Download or read book Modeling and Forecasting Volatility and Prices for SET50 Index Options written by Chanyapat Wiphatthanananthakul and published by LAP Lambert Academic Publishing. This book was released on 2018-06-19 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 2003, the Chicago Board Options Exchange (CBOE) made two key enhancements to the volatility index (VIX) methodology based on S&P options. The new VIX methodology seems to be based on a complicated formula to calculate expected volatility. In this book, with the use of Thailand's SET50 Index Options data, we modify the apparently complicated VIX formula to a simple relationship, which has a higher negative correlation between the VIX for Thailand (TVIX) and SET50 Index Options. We show that TVIX provides more accurate forecasts of option prices than the simple expected volatility (SEV) index, but the SEV index outperforms TVIX in forecasting expected volatility. Therefore, the SEV index would seem to be a superior tool as a hedging diversification tool because of the high negative correlation with the volatility index.
