The Journal of Finance

Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility

Published: 03/01/1996   |   DOI: 10.1111/j.1540-6261.1996.tb05206.x

TORBEN G. ANDERSEN

The paper develops an empirical return volatility‐trading volume model from a microstructure framework in which informational asymmetries and liquidity needs motivate trade in response to information arrivals. The resulting system modifies the so‐called “Mixture of Distribution Hypothesis” (MDH). The dynamic features are governed by the information flow, modeled as a stochastic volatility process, and generalize standard ARCH specifications. Specification tests support the modified MDH representation and show that it vastly outperforms the standard MDH. The findings suggest that the model may be useful for analysis of the economic factors behind the observed volatility clustering in returns.

Do Bonds Span Volatility Risk in the U.S. Treasury Market? A Specification Test for Affine Term Structure Models

Published: 03/19/2010   |   DOI: 10.1111/j.1540-6261.2009.01546.x

TORBEN G. ANDERSEN, LUCA BENZONI

We propose using model‐free yield quadratic variation measures computed from intraday data as a tool for specification testing and selection of dynamic term structure models. We find that the yield curve fails to span realized yield volatility in the U.S. Treasury market, as the systematic volatility factors are largely unrelated to the cross‐section of yields. We conclude that a broad class of affine diffusive, quadratic Gaussian, and affine jump‐diffusive models cannot accommodate the observed yield volatility dynamics. Hence, the Treasury market per se is incomplete, as yield volatility risk cannot be hedged solely through Treasury securities.

Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long‐Run in High Frequency Returns

Published: 04/18/2012   |   DOI: 10.1111/j.1540-6261.1997.tb02722.x

TORBEN G. ANDERSEN, TIM BOLLERSLEV

Recent empirical evidence suggests that the interdaily volatility clustering for most speculative returns are best characterized by a slowly mean‐reverting fractionally integrated process. Meanwhile, much shorter lived volatility dynamics are typically observed with high frequency intradaily returns. The present article demonstrates, that by interpreting the volatility as a mixture of numerous heterogeneous short‐run information arrivals, the observed volatility process may exhibit long‐run dependence. As such, the long‐memory characteristics constitute an intrinsic feature of the return generating process, rather than the manifestation of occasional structural shifts. These ideas are confirmed by our analysis of a one‐year time series of five‐minute Deutschemark‐U.S. Dollar exchange rates.

Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.85732

Torben G. Andersen, Tim Bollerslev

This paper provides a detailed characterization of the volatility in the deutsche mark–dollar foreign exchange market using an annual sample of five‐minute returns. The approach captures the intraday activity patterns, the macroeconomic announcements, and the volatility persistence (ARCH) known from daily returns. The different features are separately quantified and shown to account for a substantial fraction of return variability, both at the intraday and daily level. The implications of the results for the interpretation of the fundamental “driving forces” behind the volatility process is also discussed.

Short‐Term Market Risks Implied by Weekly Options

Published: 02/23/2017   |   DOI: 10.1111/jofi.12486

TORBEN G. ANDERSEN, NICOLA FUSARI, VIKTOR TODOROV

We study short‐maturity (“weekly”) S&P 500 index options, which provide a direct way to analyze volatility and jump risks. Unlike longer‐dated options, they are largely insensitive to the risk of intertemporal shifts in the economic environment. Adopting a novel seminonparametric approach, we uncover variation in the negative jump tail risk, which is not spanned by market volatility and helps predict future equity returns. As such, our approach allows for easy identification of periods of heightened concerns about negative tail events that are not always “signaled” by the level of market volatility and elude standard asset pricing models.

Variance‐ratio Statistics and High‐frequency Data: Testing for Changes in Intraday Volatility Patterns

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00326

Torben G. Andersen, Tim Bollerslev, Ashish Das

Variance‐ratio tests are routinely employed to assess the variation in return volatility over time and across markets. However, such tests are not statistically robust and can be seriously misleading within a high‐frequency context. We develop improved inference procedures using a Fourier Flexible Form regression framework. The practical significance is illustrated through tests for changes in the FX intraday volatility pattern following the removal of trading restrictions in Tokyo. Contrary to earlier evidence, we find nodiscernible changes outside of the Tokyo lunch period. We ascribe the difference to the fragile finite‐sample inference of conventional variance‐ratio procedures and a single outlier.

An Empirical Investigation of Continuous‐Time Equity Return Models

Published: 12/17/2002   |   DOI: 10.1111/1540-6261.00460

Torben G. Andersen, Luca Benzoni, Jesper Lund

This paper extends the class of stochastic volatility diffusions for asset returns to encompass Poisson jumps of time‐varying intensity. We find that any reasonably descriptive continuous‐time model for equity‐index returns must allow for discrete jumps as well as stochastic volatility with a pronounced negative relationship between return and volatility innovations. We also find that the dominant empirical characteristics of the return process appear to be priced by the option market. Our analysis indicates a general correspondence between the evidence extracted from daily equity‐index returns and the stylized features of the corresponding options market prices.