WorldCat Identities

Bollerslev, Tim 1958-

Overview
Works: 79 works in 240 publications in 1 language and 1,125 library holdings
Roles: Editor, Honoree, Creator
Classifications: HB1, 330.0151955
Publication Timeline
Key
Publications about  Tim Bollerslev Publications about Tim Bollerslev
Publications by  Tim Bollerslev Publications by Tim Bollerslev
Most widely held works by Tim Bollerslev
Volatility and time series econometrics : essays in honor of Robert F. Engle ( Book )
13 editions published between 2009 and 2010 in English and held by 228 WorldCat member libraries worldwide
This volume celebrates and develops the work of Nobel Laureate Robert Engle. It includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics
Testing for market microstructure effects in intraday volatility : a reassessment of the Tokyo FX experiment by Torben G Andersen ( Book )
9 editions published in 1998 in English and held by 86 WorldCat member libraries worldwide
This paper develops mew robust inference procedures for analyzing the intraday return volatility patterns that constitute a focal point of much market microstructure theory. Our empirical analysis is motivated by the recent lifting of trading restrictions in the interbank foreign exchange (FX) market for Japanese banks during the Tokyo lunch period. Ito, Lyons, and Melvin (1998) (ILM) argue that this deregulation resulted in a highly significant shift in the volatility pattern across the entire Japanese trading day, indicating that private information is an important component of the price formation process in the FX market. In contrast, our robust analysis finds no evidence for any discernible change in the pattern outside of the Tokyo lunch period. Moreover, we document that the standard variance-ratio methodology inference in this high-frequency data context
DM-dollar volatility : intraday activity patterns, macroeconomic announcements, and longer run dependencies by Torben G Andersen ( Book )
9 editions published in 1996 in English and held by 84 WorldCat member libraries worldwide
This paper characterizes the volatility in the DM-dollar foreign exchange market using an annual sample of five-minute returns. Our modeling approach explicitly captures the pronounced intraday activity patterns, the strong macroeconomic announcement effects, and the volatility persistence, or ARCH effects, familiar from lower frequency returns. The different features are separately quantified and shown, in conjunction, to account for a substantial fraction of the realized return variability, both at the intradaily and daily levels. Moreover, we demonstrate how the high frequency returns, when properly modeled, constitute an extremely valuable and vastly underutilized resource for better understanding the volatility dynamics at the daily or lower frequencies
Heterogeneous information arrivals and return volatility dynamics : uncovering the long-run in high frequency returns by Torben G Andersen ( Book )
8 editions published in 1996 in English and held by 81 WorldCat member libraries worldwide
Recent empirical evidence suggests that the long-run dependence in financial market volatility is best characterized by a slowly mean-reverting fractionally integrated process. At the same time, much shorter-lived volatility dependencies are typically observed with high-frequency intradaily returns. This paper draws on the information arrival, or mixture-of-distributions hypothesis interpretation of the latent volatility process in rationalizing this behavior. By interpreting the overall volatility as the manifestation of numerous heterogeneous information arrivals, sudden bursts of volatility typically will have both short-run and long-run components. Over intradaily frequencies, the short-run decay stands out most clearly, while the impact of the highly persistent processes will be dominant over longer horizons. These ideas are confirmed by our empirical analysis of a one-year time series of intradaily five-minute Deutschemark - U.S. Dollar returns. Whereas traditional time series based measures for the temporal dependencies in the absolute returns give rise to very conflicting results across different intradaily sampling frequencies, the corresponding semiparametric estimates for the order of fractional integration remain remarkably stable. Similarly, the autocorrelogram for the low-pass filtered absolute returns, obtained by annihilating periods in excess of one day, exhibit a striking hyperbolic rate of decay
Answering the critics : yes, ARCH models do provide good volatility forecasts by Torben G Andersen ( Book )
9 editions published in 1997 in English and held by 78 WorldCat member libraries worldwide
Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good forecasts of future volatility are critical for the implementation and evaluation of asset pricing theories. In response to this, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily and lower frequencies using ARCH and stochastic volatility type models. Most of these studies find highly significant in-sample parameter estimates and pronounced intertemporal volatility persistence. Meanwhile, when judged by standard forecast evaluation criteria, based on the squared or absolute returns over daily or longer forecast horizons, ARCH models provide seemingly poor volatility forecasts. The present paper demonstrates that ARCH models, contrary to the above contention, produce strikingly accurate interdaily forecasts for the latent volatility factor that is relevant for most financial applications
Financial market efficiency tests by Tim Bollerslev ( Book )
8 editions published between 1992 and 1995 in English and held by 56 WorldCat member libraries worldwide
This paper provides a selective survey of the voluminous literature on tests for market efficiency. The ideas discussed include standard autocorrelation tests, multi-period regression tests and volatility tests. The formulation and estimation of models for time-varying volatility are also considered. Dependence in second-order moments plays an important role in implementing and understanding tests for market efficiency. All of the reported test statistics and model estimates are calculated with monthly data on value-weighted NYSE stock prices and dividends. The distributions of the test statistics under various alternatives, including fads and bubbles, are illustrated through the use of Monte Carlo methods. In addition to the standard constant discount rate present value model, we postulate and simulate a new fundamental price relationship that accounts for the time-varying uncertainty in the monthly dividend growth rates. Allowing the discount rate to be a function of the time-varying uncertainty in the dividend process results in a simulated fundamental price series that is broadly consistent with most of the sample statistics of the actual data
Roughing it up including jump components in the measurement, modeling and forecasting of return volatility by Torben G Andersen ( )
8 editions published in 2005 in English and held by 56 WorldCat member libraries worldwide
"A rapidly growing literature has documented important improvements in financial return volatility measurement and forecasting via use of realized variation measures constructed from high-frequency returns coupled with simple modeling procedures. Building on recent theoretical results in Barndorff-Nielsen and Shephard (2004a, 2005) for related bi-power variation measures, the present paper provides a practical and robust framework for non-parametrically measuring the jump component in asset return volatility. In an application to the DM/$ exchange rate, the S & P500 market index, and the 30-year U.S. Treasury bond yield, we find that jumps are both highly prevalent and distinctly less persistent than the continuous sample path variation process. Moreover, many jumps appear directly associated with specific macroeconomic news announcements. Separating jump from non-jump movements in a simple but sophisticated volatility forecasting model, we find that almost all of the predictability in daily, weekly, and monthly return volatilities comes from the non-jump component. Our results thus set the stage for a number of interesting future econometric developments and important financial applications by separately modeling, forecasting, and pricing the continuous and jump components of the total return variation process"--National Bureau of Economic Research web site
No-arbitrage semi-Martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise theory and testable distributional implications by Torben G Andersen ( )
5 editions published in 2007 in English and held by 44 WorldCat member libraries worldwide
"We develop a sequential procedure to test the adequacy of jump-diffusion models for return distributions. We rely on intraday data and nonparametric volatility measures, along with a new jump detection technique and appropriate conditional moment tests, for assessing the import of jumps and leverage effects. A novel robust-to-jumps approach is utilized to alleviate microstructure frictions for realized volatility estimation. Size and power of the procedure are explored through Monte Carlo methods. Our empirical findings support the jump-diffusive representation for S & P500 futures returns but reveal it is critical to account for leverage effects and jumps to maintain the underlying semi-martingale assumption"--National Bureau of Economic Research web site
Parametric and nonparametric volatility measurement by Torben G Andersen ( )
8 editions published in 2002 in English and held by 43 WorldCat member libraries worldwide
Volatility has been one of the most active areas of research in empirical finance and time series econometrics during the past decade. This chapter provides a unified continuous-time, frictionless, no-arbitrage framework for systematically categorizing the various volatility concepts, measurement procedures, and modeling procedures. We define three different volatility concepts: (i) the notional volatility corresponding to the ex-post sample-path return variability over a fixed time interval, (ii) the ex-ante expected volatility over a fixed time interval, and (iii) the instantaneous volatility corresponding to the strength of the volatility process at a point in time. The parametric procedures rely on explicit functional form assumptions regarding the expected and/or instantaneous volatility. In the discrete-time ARCH class of models, the expectations are formulated in terms of directly observable variables, while the discrete- and continuous-time stochastic volatility models involve latent state variable(s). The nonparametric procedures are generally free from such functional form assumptions and hence afford estimates of notional volatility that are flexible yet consistent (as the sampling frequency of the underlying returns increases). The nonparametric procedures include ARCH filters and smoothers designed to measure the volatility over infinitesimally short horizons, as well as the recently-popularized realized volatility measures for (non-trivial) fixed-length time intervals
Volatility and time series econometrics : essays in honor of Robert Engle ( Book )
7 editions published between 2009 and 2010 in English and held by 40 WorldCat member libraries worldwide
This volume celebrates and develops the work of Nobel Laureate Robert Engle. It includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics
A framework for exploring the macroeconomic determinants of systematic risk ( )
5 editions published in 2005 in English and held by 21 WorldCat member libraries worldwide
We selectively survey, unify and extend the literature on realized volatility of financial asset returns. Rather than focusing exclusively on characterizing the properties of realized volatility, we progress by examining economically interesting functions of realized volatility, namely realized betas for equity portfolios, relating them both to their underlying realized variance and covariance parts and to underlying macroeconomic fundamentals
Real-time price discovery in stock, bond and foreign exchange markets ( )
5 editions published between 2004 and 2005 in English and held by 21 WorldCat member libraries worldwide
We characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. Our analysis is based on a unique data set of high-frequency futures returns for each of the markets. We find that news surprises produce conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals. The details of the linkages are particularly intriguing as regards equity markets. We show that equity markets react differently to the same news depending on the state of the economy, with bad news having a positive impact during expansions and the traditionally-expected negative impact during recessions. We rationalize this by temporal variation in the competing "cash flow" and "discount rate" effects for equity valuation. This finding helps explain the time-varying correlation between stock and bond returns, and the relatively small equity market news effect when averaged across expansions and recessions. Lastly, relying on the pronounced heteroskedasticity in the high-frequency data, we document important contemporaneous linkages across all markets and countries over-and-above the direct news announcement effects. Klassifikation: F3, F4, G1, C5
Practical volatility and correlation modeling for financial market risk management ( )
5 editions published in 2005 in English and held by 21 WorldCat member libraries worldwide
What do academics have to offer market risk management practitioners in financial institutions? Current industry practice largely follows one of two extremely restrictive approaches: historical simulation or RiskMetrics. In contrast, we favor flexible methods based on recent developments in financial econometrics, which are likely to produce more accurate assessments of market risk. Clearly, the demands of real-world risk management in financial institutions -- in particular, real-time risk tracking in very high-dimensional situations -- impose strict limits on model complexity. Hence we stress parsimonious models that are easily estimated, and we discuss a variety of practical approaches for high-dimensional covariance matrix modeling, along with what we see as some of the pitfalls and problems in current practice. In so doing we hope to encourage further dialog between the academic and practitioner communities, hopefully stimulating the development of improved market risk management technologies that draw on the best of both worlds
Volatility forecasting ( )
5 editions published in 2005 in English and held by 21 WorldCat member libraries worldwide
Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly
Some like it smooth, and some like it rough untangling continuous and jump components in measuring, modeling, and forecasting asset return volatility by Torben G Andersen ( )
4 editions published in 2003 in English and held by 19 WorldCat member libraries worldwide
A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high-frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on recent theoretical results from Barndorff-Nielsen and Shephard (2003c,d) for related bi-power variation measures involving the sum of high-frequency absolute returns, the present paper provides a practical framework for non-parametrically measuring the jump component in realized volatility measurements. Exploiting these ideas for a decade of high-frequency five-minute returns for the DM/$ exchange rate, the S&P500 market index, and the 30-year U.S. Treasury bond yield, we find the jump component of the price process to be distinctly less persistent than the continuous sample path component. Explicitly including the jump measure as an additional explanatory variable in an easy-to-implement reduced form model for realized volatility results in highly significant jump coefficient estimates at the daily, weekly and quarterly forecast horizons. As such, our results hold promise for improved financial asset allocation, risk management, and derivatives pricing, by separate modeling, forecasting and pricing of the continuous and jump components of total return variability. Klassifikation: C1, G1
High frequency data, frequency domain inference and volatility forecasting by Jonathan H Wright ( Book )
5 editions published in 1999 in English and held by 19 WorldCat member libraries worldwide
Realized beta persistence and predictability ( )
2 editions published in 2004 in English and held by 15 WorldCat member libraries worldwide
A large literature over several decades reveals both extensive concern with the question of time-varying betas and an emerging consensus that betas are in fact time-varying, leading to the prominence of the conditional CAPM. Set against that background, we assess the dynamics in realized betas, vis-à-vis the dynamics in the underlying realized market variance and individual equity covariances with the market. Working in the recently-popularized framework of realized volatility, we are led to a framework of nonlinear fractional cointegration: although realized variances and covariances are very highly persistent and well approximated as fractionally-integrated, realized betas, which are simple nonlinear functions of those realized variances and covariances, are less persistent and arguably best modeled as stationary I(0) processes. We conclude by drawing implications for asset pricing and portfolio management. Klassifikation: C1, G1
Estimating stochastic volatility diffusion using conditional moments of integrated volatility by Tim Bollerslev ( Book )
5 editions published in 2001 in English and held by 15 WorldCat member libraries worldwide
Volatility puzzles : a unified framework for gauging return-volatility regressions by Tim Bollerslev ( Book )
6 editions published in 2003 in English and held by 12 WorldCat member libraries worldwide
"This paper provides a simple unified framework for assessing the empirical linkages between returns and realized and implied volatilities. First, we show that whereas the volatility feedback effect as measured by the sign of the correlation between contemporaneous return and realized volatility depends importantly on the underlying structural model parameters, the correlation between return and implied volatility is unambiguously positive for all reasonable parameter configurations. Second, the lagged return-volatility asymmetry, or the leverage effect, is always stronger for implied than realized volatility. Third, implied volatilities generally provide downward biased forecasts of subsequent realized volatilities. Our results help explain previous findings reported in the extant empirical literature, and is further corroborated by new estimation results for a sample of monthly returns and implied and realized volatilities for the aggregate S & P market index"--Federal Reserve Board web site
Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities by Tim Bollerslev ( Book )
5 editions published in 2004 in English and held by 12 WorldCat member libraries worldwide
"This paper proposes a method for constructing a volatility risk premium, or investor risk aversion, index. The method is intuitive and simple to implement, relying on the sample moments of the recently popularized model-free realized and option-implied volatility measures. A small-scale Monte Carlo experiment suggests that the procedure works well in practice. Implementing the procedure with actual S & P 500 option-implied volatilities and high-frequency five-minute-based realized volatilities results in significant temporal dependencies in the estimated stochastic volatility risk premium, which we in turn relate to a set of underlying macro-finance state variables. We also find that the extracted volatility risk premium helps predict future stock market returns"--Federal Reserve Board web site
 
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Alternative Names
Bollerslev, T. 1958-
Bollerslev, Tim P. 1958-
Bollerslev, Tim Peter
Bollerslev, Tim Peter, 1958-
Languages
English (131)
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