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72
Volatility Forecast Comparison Using Imperfect Volatility Proxies
- JOURNAL OF ECONOMETRICS
, 2010
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Evaluating Value-at-Risk Models with Desk-Level Data”, Fourth Joint Central Bank
- Research Conference on 9 Nov 2005, European Central Bank, Research Paper, Preliminary Version, Cited on 17.8.2006, [www.ecb.int/events/pdf/conferences/jcbrconf4/Christoffersen.pdf
, 2005
"... We present new evidence on disaggregated profit and loss and VaR forecasts obtained from a large international commercial bank. Our dataset includes daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed da ..."
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Cited by 67 (1 self)
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We present new evidence on disaggregated profit and loss and VaR forecasts obtained from a large international commercial bank. Our dataset includes daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. We also collected the corresponding daily, 1-day ahead VaR forecasts for each business line. Given this rich dataset, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. Our approach includes many existing backtesting techniques as special cases. In addition, we describe some new tests which are suggested by our framework. A thorough Monte Carlo comparison of the various methods is conducted to provide guidance as to which of these many tests have the best finite-sample size and power properties.
Financial asset returns, direction-of-change forecasting and volatility dynamics
, 2003
"... informs doi 10.1287/mnsc.1060.0520 ..."
Evaluating Volatility and Correlation Forecasts
- HANDBOOK OF FINANCIAL TIME SERIES
, 2007
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Heterogeneous Gain Learning and the Dynamics of Asset Prices
, 2010
"... This paper presents a new agent-based financial market. It is designed to be both simple enough to gain insights into the nature and structure of what is going on at both the agent and macro levels, but remain rich enough to allow for many interesting evolutionary experiments. The model is driven by ..."
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Cited by 18 (7 self)
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This paper presents a new agent-based financial market. It is designed to be both simple enough to gain insights into the nature and structure of what is going on at both the agent and macro levels, but remain rich enough to allow for many interesting evolutionary experiments. The model is driven by heterogeneous agents who put varying weights on past information as they design portfolio strategies. It faithfully generates many of the common stylized features of asset markets. It also yields some insights into the dynamics of agent strategies and how they yield market instabilities.
Realized volatility: A review
- Econometric Reviews
, 2008
"... This article reviews the exciting and rapidly expanding literature on realized volatility. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented in order to motivate the main results. A continuous time specification provides ..."
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Cited by 13 (2 self)
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This article reviews the exciting and rapidly expanding literature on realized volatility. After presenting a general univariate framework for estimating realized volatilities, a simple discrete time model is presented in order to motivate the main results. A continuous time specification provides the theoretical foundation for the main results in this literature. Cases with and without microstructure noise are considered, and it is shown how microstructure noise can cause severe problems in terms of consistent estimation of the daily realized volatility. Independent and dependent noise processes are examined. The most important methods for providing consistent estimators are presented, and a critical exposition of different techniques is given. The finite sample properties are discussed in comparison with their asymptotic properties. A multivariate model is presented to discuss estimation of the realized covariances. Various issues relating to modelling and forecasting realized volatilities are considered. The main empirical findings using univariate and multivariate methods are summarized.
Robust replication of volatility derivatives
, 2003
"... Postscript/PDF files of these overheads can be downloaded from: www.petercarr.net or www.math.nyu.edu\research\carrp\papers ..."
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Cited by 13 (5 self)
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Postscript/PDF files of these overheads can be downloaded from: www.petercarr.net or www.math.nyu.edu\research\carrp\papers
On the correlation structure of microstructure noise: A financial economic approach.
, 2010
"... We introduce the financial economics of market microstructure to the financial econometrics of asset return volatility estimation. In particular, we derive the crosscorrelation function between latent returns and market microstructure noise in several leading microstructure environments. We propose ..."
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Cited by 13 (2 self)
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We introduce the financial economics of market microstructure to the financial econometrics of asset return volatility estimation. In particular, we derive the crosscorrelation function between latent returns and market microstructure noise in several leading microstructure environments. We propose and illustrate several corresponding theory-inspired volatility estimators, which we apply to stock and oil prices. Our analysis and results are useful for assessing the validity of the frequently-assumed independence of latent price and microstructure noise, for explaining observed cross-correlation patterns, for predicting as-yet undiscovered patterns, and most importantly, for promoting improved microstructure-based volatility empirics and improved empirical microstructure studies. Simultaneously and conversely, our analysis is far from the last word on the subject, as it is based on stylized benchmark models; it comes with a "call to action" for development and use of richer microstructure models in volatility estimation and beyond.
General to Specific Modelling of Exchange Rate Volatility: A Forecast Evaluation
, 2006
"... The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and under ..."
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Cited by 12 (8 self)
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The general-to-specific (GETS) approach to modelling is widely employed in the modelling of economic series, but less so in financial volatility modelling due to computational complexity when many explanatory variables are involved. This study proposes a simple way of avoiding this problem and undertakes an out-of-sample forecast evaluation of the methodology applied to the modelling of weekly exchange rate volatility. Our findings suggest that GETS specifications are especially valuable in conditional forecasting, since the specification that employs actual values on the uncertain information performs particularly well.
