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Author: Jeff Fleming Publisher: ISBN: Category : Languages : en Pages : 48
Book Description
Recent work suggests that intradaily returns can be used to construct estimates of daily return volatility that are more precise than those constructed using daily returns. We measure the economic value of this quot;realizedquot; volatility approach in the context of investment decisions. Our results indicate that the value of switching from daily to intradaily returns to estimate the conditional covariance matix can be substantial. We estimate that a risk-averse investor would be willing to pay 50 to 200 basis points per year to capture the observed gains in portfolio performance. Moreover,these gains are robust to transaction costs, estimation risk regarding expected returns, and the performance measurement horizon.
Author: Jeff Fleming Publisher: ISBN: Category : Languages : en Pages : 48
Book Description
Recent work suggests that intradaily returns can be used to construct estimates of daily return volatility that are more precise than those constructed using daily returns. We measure the economic value of this quot;realizedquot; volatility approach in the context of investment decisions. Our results indicate that the value of switching from daily to intradaily returns to estimate the conditional covariance matix can be substantial. We estimate that a risk-averse investor would be willing to pay 50 to 200 basis points per year to capture the observed gains in portfolio performance. Moreover,these gains are robust to transaction costs, estimation risk regarding expected returns, and the performance measurement horizon.
Author: Madhu Kalimipalli Publisher: ISBN: Category : Languages : en Pages : 49
Book Description
We examine the economic benefits of using high frequency volatility measures for pricing, trading and hedging in the Samp;P 500 index options market. Using the encompassing regression framework, we generate volatility forecasts combining information from long memory high-frequency volatility specifications and option-based implied volatilities. We conduct out-of-sample tests of the volatility forecasts by examining option pricing performance, trading performance based on volatility timing strategies, and the performance of covered options positions for index option writers. Our results support combining forecasts of implied volatility and realized volatility and illustrate that the realized volatility approach has economic value in the context of option pricing and risk management.
Author: Ingmar Nolte Publisher: ISBN: Category : Languages : en Pages : 49
Book Description
This paper comprehensively investigates the role of realized jumps detected from high frequency data in predicting future volatility from both statistical and economic perspectives. Using seven major jump tests, we show that separating jumps from diffusion improves volatility forecasting both in-sample and out-of-sample. Moreover, we show that these statistical improvements can be translated into economic value. We find a risk-averse investor can significantly improve her portfolio performance by incorporating realized jumps into a volatility timing based portfolio strategy. Our results hold true across the majority of jump tests, and are robust to controlling for microstructure effects and transaction costs.
Author: Jeff Fleming Publisher: ISBN: Category : Languages : en Pages : 32
Book Description
Numerous studies report that standard volatility models have low explanatory power, leading some researchers to question whether these models have economic value. We examine this question by using conditional mean-variance analysis to assess the value of volatility timing to short-horizon investors. We find that the volatility timing strategies outperform the unconditionally efficient static portfolios that have the same target expected return and volatility. This finding is robust to estimation risk and transaction costs.
Author: Ray Y. Chou Publisher: ISBN: Category : Languages : en Pages : 31
Book Description
There is growing interest in utilizing the range data of asset prices to study the role of volatility in financial markets. In this paper, a new range-based volatility model is used to examine the economic value of volatility timing in a mean-variance framework. We compare its performance with a return-based dynamic volatility model in both in-sample and out-of-sample volatility timing strategies. For a risk-averse investor, it is shown that the predictable ability captured by the dynamic volatility models is economically significant, and that the range-based volatility model performs better than the return-based one.
Author: Wing H. Chan Publisher: ISBN: Category : Languages : en Pages : 42
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.
Author: Wei Liu Publisher: ISBN: Category : Languages : en Pages :
Book Description
This thesis investigates the economic value of incorporating intraday volatility estimators into the volatility forecasting process. The increased reliance on volatility forecasting in the financial industry has intensified the need for more rigorous analysis from an economic perspective instead of merely statistical point of view. A better understanding of the available methods has implications for portfolio optimization, volatility trading and risk management. More recently, volatility of asset returns was once again under spotlight during the 2008-2009 financial crisis. The study contributes to the extant volatility forecasting literature in three areas. First, it addresses the question of how to practically and effectively exploit intraday price information for variance and covariance modelling and forecasting. Second, it addresses the development of an 'optimal' intraday volatility model that accommodates market practitioners preferences. Third, it evaluates the economic value of combining realized (intraday) volatility estimators for utilizing unique information embedded in each estimator. The thesis is organised as follows. One of the most visible indicators of the crisis that captured the attention of the financial industry was the extremely high level of asset return volatility. This uncertainty prompted much interest for a more accurate, yet practically applicable approach for volatility forecasting. Chapter 2 introduces the various realized volatility estimators, volatility forecasting procedures and their corresponding realized extensions used in our subsequent empirical investigations. Chapter 3 evaluates the economic value of various intraday covariance estimation approaches for mean-variance portfolio optimization. Economic loss functions overwhelmingly favour intraday covariance matrix models instead of their daily counterparts. The constant conditional correlation (CCC) augmented with realized volatility produces the highest economic value when applied with a time-varying volatility timing strategy. Chapter 4 compares the practical value of intraday based single index (univariate) and portfolio (multivariate) models through the lens of Value-at-Risk (VaR) forecasting. VaR predictions are generated from standard daily univariate or multivariate GARCH models, as well as GARCH models extended with ARFIMA forecasted realized measures. Conditional coverage test results indicate that intraday models, both univariate and multivariate ones, outperform their daily counterparts by providing more accurate VaR forecasts. Chapter 5 investigates the economic value of combining intraday volatility estimators for volatility trading. The simulated option trading results indicate that a naive combination of an intraday estimator and implied volatility cannot be outperformed by the best individual estimator. In addition, trading performance can be further boosted by applying more complex combination models such as a regression based combination of 42 single volatility estimators.
Author: Torben Gustav Andersen Publisher: Springer Science & Business Media ISBN: 3540712976 Category : Business & Economics Languages : en Pages : 1045
Book Description
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Author: Kevin D. Hoover Publisher: Springer Science & Business Media ISBN: 940110669X Category : Business & Economics Languages : en Pages : 575
Book Description
Each chapter of Macroeconometrics is written by respected econometricians in order to provide useful information and perspectives for those who wish to apply econometrics in macroeconomics. The chapters are all written with clear methodological perspectives, making the virtues and limitations of particular econometric approaches accessible to a general readership familiar with applied macroeconomics. The real tensions in macroeconometrics are revealed by the critical comments from different econometricians, having an alternative perspective, which follow each chapter.
Author: Jeff Fleming
Author: Jeff Fleming
Author: Madhu Kalimipalli
Author: Ingmar Nolte
Author: Jeff Fleming
Author: Ray Y. Chou
Author: Wing H. Chan
Author: Luc Bauwens
Author: Wei Liu
Author: Torben Gustav Andersen
Author: Kevin D. Hoover