Download or read book Forecasting Volatility and Option Prices of the S P 500 Index written by Jaesun Noh and published by . This book was released on 1994 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Test of Efficiency for the S P 500 Index Option Market Using Variance Forecasts written by Jaesun Noh and published by . This book was released on 1993 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: To forecast future option prices, autoregressive models of implied volatility derived from observed option prices are commonly employed [see Day and Lewis (1990), and Harvey and Whaley (1992)]. In contrast, the ARCH model proposed by Engle (1982) models the dynamic behavior in volatility, forecasting future volatility using only the return series of an asset. We assess the performance of these two volatility prediction models from S&P 500 index options market data over the period from September 1986 to December 1991 by employing two agents who trade straddles, each using one of the two different methods of forecast. Straddle trading is employed since a straddle does not need to be hedged. Each agent prices options according to her chosen method of forecast, buying (selling) straddles when her forecast price for tomorrow is higher (lower) than today's market closing price, and at the end of each day the rates of return are computed. We find that the agent using the GARCH forecast method earns greater profit than the agent who uses the implied volatility regression (IVR) forecast model. In particular, the agent using the GARCH forecast method earns a profit in excess of a cost of $0.25 per straddle with the near-the-money straddle trading.

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 Forecasting Future Volatility from Option Prices written by Allen M. Poteshman and published by . This book was released on 2000 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the Samp;P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk.

Download or read book Predictable Dynamics in the S P 500 Index Options Implied Volatility Surface written by Sílvia Gonçalves and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: One key stylized fact in the empirical option pricing literature is the existence of an implied volatility surface (IVS). The usual approach consists of fitting a linear model linking the implied volatility to the time to maturity and the moneyness, for each cross section of options data. However, recent empirical evidence suggests that the parameters characterizing the IVS change over time. In this paper, we study whether the resulting predictability patterns in the IVS coefficients may be exploited in practice. We propose a two-stage approach to modeling and forecasting the Samp;P 500 index options IVS. In the first stage, we model the surface along the cross-sectional moneyness and time-to-maturity dimensions, similarly to Dumas, et. al., (1998). In the second-stage, we model the dynamics of the cross-sectional first-stage implied volatility surface coefficients by means of vector autoregression models. We find that not only the Samp;P 500 implied volatility surface can be successfully modeled, but also that its movements over time are highly predictable in a statistical sense. We then examine the economic significance of this statistical predictability with mixed findings. Whereas profitable delta-hedged positions can be set up that exploit the dynamics captured by the model under moderate transaction costs and when trading rules are selective in terms of expected gains from the trades, most of this profitability disappears when we increase the level of transaction costs and trade multiple contracts off wide segments of the IVS. This suggests that predictability of the time-varying Samp;P 500 implied volatility surface may be not inconsistent with market efficiency.

Download or read book Forecasting Volatility in the Presence of Limits to Arbitrage written by Lu Hong and published by . This book was released on 2014 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we develop a novel model to forecast the volatility of S&P 500 futures returns by considering measures of limits to arbitrage. When arbitrageurs face constraints on their trading strategies, option prices can become disconnected from fundamentals, resulting in a distortion that reflects the limits to arbitrage. The corresponding market based implied volatility will therefore also contain these distortions. Our contributions are both conceptual and empirical. Conceptually, the limits to arbitrage framework can shed light on relative asset prices as exemplified by this particular study. Empirically, our volatility forecasting model explains 71% of the variation in realized volatility, a substantial improvement over a naive forecast based only on lagged realized volatility, which produces an R2 of 53%.

Download or read book Can Standard Preferences Explain the Prices of Out of the Money S P 500 Put Options written by Luca Benzoni and published by . This book was released on 2005 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prior to the stock market crash of 1987, Black-Scholes implied volatilities of S & P 500 index options were relatively constant across moneyness. Since the crash, however, deep out-of-the-money S & P 500 put options have become 'expensive' relative to the Black-Scholes benchmark. Many researchers (e.g., Liu, Pan and Wang (2005)) have argued that such prices cannot be justified in a general equilibrium setting if the representative agent has 'standard preferences' and the endowment is an i.i.d. process. Below, however, we use the insight of Bansal and Yaron (2004) to demonstrate that the 'volatility smirk' can be rationalized if the agent is endowed with Epstein-Zin preferences and if the aggregate dividend and consumption processes are driven by a persistent stochastic growth variable that can jump. We identify a realistic calibration of the model that simultaneously matches the empirical properties of dividends, the equity premium, the prices of both at-the-money and deep out-of-the-money puts, and the level of the risk-free rate. A more challenging question (that to our knowledge has not been previously investigated) is whether one can explain within a standard preference framework the stark regime change in the volatility smirk that has maintained since the 1987 market crash. To this end, we extend the model to a Bayesian setting in which the agent updates her beliefs about the average jump size in the event of a jump. Note that such beliefs only update at crash dates, and hence can explain why the volatility smirk has not diminished over the last eighteen years. We find that the model can capture the shape of the implied volatility curve both pre- and post-crash while maintaining reasonable estimates for expected returns, price-dividend ratios, and risk-free rates.

Download or read book Forecasting Index Option Prices Using Implied Volatility and the Implications for the Efficiency of Options Markets written by Zhina Zhang and published by . This book was released on 2004 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Forecasting Volatility written by Stephen Figlewski and published by . This book was released on 1997 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predicting the Volatility of the S P 500 Equity Index written by Robert L. Geske and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents empirical tests of seven alternative estimators for the volatility of the Samp;P 500 equity index. Two of the estimators are the implied volatilities derived from the option models of Geske (1979) and Black-Scholes (1973) and using market prices for options. The Geske volatility estimator is stochastic, and this paper presents its first empirical tests. The Black-Scholes estimator in theory is deterministic, but herein when computed daily it is ad hoc allowed to change randomly with changes in the index level. The other five estimators are empirical, based on sample data. Four of the empirical estimators are GARCH approaches (GARCH11, EGARCH, TGARCH, and Heston-Nandi GARCH) which accommodate stochastic volatilities, and the fifth empirical estimator is simply the sample variance viewed as an historical estimate. All seven estimators are used to predict the actual realized volatility over the life of each option. If the market processes information efficiently, when the actual realized volatility over the option life is regressed on each estimator, the slope coefficient and intercept should be 1.0 and 0.0, respectively. In the case of the implied volatility estimators, this can be considered a test of these models. Our results show that in all cases the slope coefficients and intercepts of the implied volatilities are much closer to 1.0, more highly significant, have intercepts closer to 0.0 which are insignificant, and exhibit higher R2 than the empirical estimators. Furthermore, the Geske estimator appears better in these respects than this ad hoc Black-Scholes estimator. Encompassing regressions are run paring the Geske estimator separately with each of the five empirical estimators. In every encompassing regression test the slope coefficients and intercepts of the Geske estimator remain much closer to 1.0 and 0.0, respectively, while the competing estimators slope coefficients are much reduced from 1.0 toward 0.0, and are often insignificant. Thus, the Geske stochastic volatility estimator appears to capture a very significant portion but not all of the information relevant for predicting the volatility of the Samp;P 500 equity index.

Download or read book A Horse Race Among Competing Option Pricing Models Using S P 500 Index Options written by Minqiang Li and published by . This book was released on 2008 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last three decades have witnessed a whole array of option pricing models. We compare the predictive performances of a selection of models by carrying out a horse race on Samp;P 500 index options along the lines of Jackwerth and Rubinstein (2001). The models we consider include: Black-Scholes, trader rules, Heston's stochastic volatility model, Merton's jump diffusion models with and without stochastic volatility, and more recent Levy type models. Trader rules still dominate mathematically more sophisticated models, and the performance of the trader rules is further improved by incorporating the stable index skew pattern documented in Li and Pearson (2005). Furthermore, after incorporating the stable index skew pattern, the Black-Scholes model beats all mathematically more sophisticated models in almost all cases. Mathematically more sophisticated models vary in their overall performance and their relative accuracy in forecasting future volatility levels and future volatility skew shapes.

Download or read book Option Pricing Under Time Varying Risk Aversion with Applications to Risk Forecasting written by Ruediger Kiesel and published by . This book was released on 2015 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: We present a new option-pricing model, which explicitly captures the difference in the persistence of volatility under historical and risk-neutral probabilities. The model also allows to capture the empirical properties of pricing kernels, such as time-variation and the typical S-shape. We apply our model for two purposes. First, we analyze the risk preferences of market participants invested in S&P 500 index options during 2001-2009. We find that risk-aversion strongly increases during stressed market conditions and relaxes during normal market conditions. Second, we extract forward-looking information from S&P 500 index options and perform out-of-sample Value-at-Risk (VaR) forecasts during the period of the subprime mortgage crises. We compare the VaR forecasting performance of our model with four alternative VaR models and find that 2-Factor Stochastic Volatility models have the best forecasting performance.

Download or read book Construction and Interpretation of Model free Implied Volatility written by Torben G. Andersen and published by . This book was released on 2007 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Predicting Implied Volatility Surface and Prices of S P 500 Index Options written by Yi Sun 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 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 Learning and Forecasts about Option Returns Through the Volatility Risk Premium written by Alejandro Bernales and published by . This book was released on 2019 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: We use learning in an equilibrium model to explain the puzzling predictive power of the volatility risk premium (VRP) for option returns. In the model, a representative agent follows a rational Bayesian learning process in an economy under incomplete information with the objective of pricing options. We show that learning induces dynamic differences between probability measures P and Q, which produces predictability patterns from the VRP for option returns. The forecasting features of the VRP for option returns, obtained through our model, exhibit the same behaviour as those observed in an empirical analysis with S&P 500 index options.

Download or read book The Information Content of Implied Volatilities and Model Free Volatility Expectations written by Stephen J. Taylor and published by . This book was released on 2008 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volatility information content of stock options for individual firms is measured using option prices for 149 U.S. firms during the period from January 1996 to December 1999. Volatility forecasts defined by historical stock returns, at-the-money (ATM) implied volatilities and model-free (MF) volatility expectations are compared for each firm. The recently developed model-free volatility expectation incorporates information across all strike prices, and it does not require the specification of an option pricing model.Our analysis of ARCH models shows that, for one-day-ahead estimation, historical estimates of conditional variances outperform both the ATM and the MF volatility estimates extracted from option prices for more than one-third of the firms. This result contrasts with the consensus about the informational efficiency of options written on stock indices; several recent studies find that option prices are more informative than daily stock returns when estimating and predicting index volatility. However, for the firms with the most actively traded options, we do find that the option forecasts are nearly always more informative than historical stock returns. When the prediction horizon extends until the expiry date of the options, our regression results show that the option forecasts are more informative than forecasts defined by historical returns for a substantial majority (86%) of the firms. Although the model-free (MF) volatility expectation is theoretically more appealing than alternative volatility estimates and has been demonstrated to be the most accurate predictor of realized volatility by Jiang and Tian (2005) for the Samp;P 500 index, the results for our firms show that the MF expectation only outperforms both the ATM implied volatility and the historical volatility for about one-third of the firms. The firms for which the MF expectation is best are not associated with a relatively high level of trading in away-from-the-money options.