Testing the lag structure of assets' realized volatility dynamics
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/238542
en
A (conservative) test is constructed to investigate the optimal lag structure for forecasting realized volatility dynamics. The testing procedure relies on the recent theoretical results that show the ability of the adaptive least absolute shrinkage and selection operator (adaptive lasso) to combine efficient parameter estimation, variable selection, and valid inference for time series processes. In an application to several constituents of the S\&P 500 index it is shown that (i) the optimal significant lag structure is time-varying and subject to drastic regime shifts that seem to happen across assets simultaneously; (ii) in many cases the relevant information for prediction is included in the first 22 lags, corroborating previous results concerning the accuracy and the difficulty of outperforming out-of-sample the heterogeneous autoregressive (HAR) model; and (iii) some common features of the optimal lag structure can be identified across assets belonging to the same market segment or showing a similar beta with respect to the market index.
Realized volatility; Adaptive lasso; HAR model; Test for false positives; Lag structure
Audrino, Francesco
Camponovo, Lorenzo
Roth, Constantin
2015
2015
Audrino, Francesco ; Camponovo, Lorenzo ; Roth, Constantin: Testing the lag structure of assets' realized volatility dynamics. University of St. Gallen : SEPS Discussion Paper Series, 2015.
216969
Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/227469
en
urn:ISSN:0883-7252
doi:10.1002/jae.2378
Journal of Applied Econometrics
Motivated by the need of a positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and Expectation Maximization (KEM) algorithm. Iterating between the two EM steps, we obtain a covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive-semidefinite by construction. We show the performance of the KEM estimator using extensive Monte Carlo simulations that mimic the liquidity and market microstructure characteristics of the S&P 500 universe as well as in an high-dimensional application on US stocks. KEM provides very accurate covariance matrix estimates and significantly outperforms alternative approaches recently introduced in the literature.
High frequency data; Realized covariance matrix; Missing data; Kalman filter; EM algorithm.
Corsi, Fulvio
Peluso, Stefano
Audrino, Francesco
01-05-2015
2015
Corsi, Fulvio ; Peluso, Stefano ; Audrino, Francesco: Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation. In: Journal of Applied Econometrics 30 (2015), Nr. 3, S. 377-397, DOI:10.1002/jae.2378.
216969
Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/221836
en
urn:ISSN:0378-4266
doi:10.1016/j.jbankfin.2015.08.018
Journal of Banking and Finance
As a means of validating an option pricing model, we compare the ex-post intra-day realized variance of options with the realized variance of the associated underlying asset that would be implied using assumptions as in the Black and Scholes (BS) model, the Heston and the Bates model. Based on data for the S&P 500 index, we find that the BS model is strongly directionally biased due to the presence of stochastic volatility. The Heston model reduces the mismatch in realized variance between the two markets, but deviations are still significant. With the exception of short-dated options, we achieve best approximations after controlling for the presence of jumps in the underlying dynamics. Finally, we provide evidence that, although heavily biased, the realized variance based on the BS model contains relevant predictive information that can be exploited when option high-frequency data is not available.
Option pricing; high frequency data; realized variance; stochastic volatility;
Audrino, Francesco
Fengler, Matthias
28-08-2015
2015
Audrino, Francesco ; Fengler, Matthias: Are classical option pricing models consistent with observed option second-order moments? Evidence from high-frequency data. In: Journal of Banking and Finance 61 (2015), Nr. -, S. 46-63, DOI:10.1016/j.jbankfin.2015.08.018.
none
An Empirical Analysis of the Ross Recovery Theorem
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/234838
en
Building on the results of Ludwig (2012), we propose a method to construct robust time-homogeneous Markov chains that capture the risk-neutral transition of state prices from current snapshots of option prices on the S&P 500 index. Using the recovery theorem of Ross (2013), we then derive the market’s forecast of the real-world return density and investigate the predictive information content of its moments. We find that changes in the recovered moments can be used to time the index, yielding strategies that not only outperform the market, but are also significantly less volatile.
Risk-neutral density; real-world density; pricing kernel; risk aversion; predictive information; Ross recovery
Audrino, Francesco
Huitema, Robert
Ludwig, Markus
2014
2014
Audrino, Francesco ; Huitema, Robert ; Ludwig, Markus ; University of St. Gallen (Hrsg.): An Empirical Analysis of the Ross Recovery Theorem : SEPS Economic Working Paper Series, 2014.
none
Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/232154
en
urn:ISSN:0747-4938
Econometric Reviews
Realized volatility computed from high-frequency data is an important measure for many applications in finance and its dynamics have been widely investigated. Recent notable advances that perform well include the heterogeneous autoregressive (HAR) model which can approximate long memory, is very parsimonious, is easy to estimate, and features good out-of-sample performance.
We prove that the least absolute shrinkage and selection operator (lasso) recovers the lags structure of the HAR model asymptotically if it is the true model, and we present Monte Carlo evidence in finite samples. The HAR model's lags structure is not fully in agreement with the one found using the lasso on real data. Moreover, we provide empirical evidence that there are two clear breaks in structure for most of the assets we consider. These results bring into question the appropriateness of the HAR model for realized volatility. Finally, in an out-of-sample analysis we show equal performance of the HAR model and the lasso approach.
Realized Volatility, Heterogeneous Autoregressive Model, Lasso, Model Selection
Audrino, Francesco
Knaus, Simon
13-06-2014
2014
Audrino, Francesco ; Knaus, Simon: Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics. In: Econometric Reviews (2014), Nr. forthcoming, S. 1-1.
216969
Monetary policy regimes: implications for the yield curve and bond pricing
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/227393
en
urn:ISSN:0304-405X
Journal of Financial Economics
We develop a multivariate dynamic term structure model, which takes into account the nonlinear (time-varying) relationship between interest rates and the state of the economy. In contrast to the classical term structure literature, where nonlinearities are captured by increasing the number of latent state variables, or by latent regime shifts, in our no-ï¿½arbitrage framework the regimes are governed by thresholds and are directly linked to economic fundamentals. Specifically, starting from a simple monetary policy model for the short rate, we introduce a parsimonious and tractable model for the yield curve, which takes into account the possibility of regime shifts in the behavior of the Federal Reserve. In our empirical analysis, we show the merit of our approach along the following dimensions: (i) interpretable bond dynamics; (ii) accurate short end yield curve pricing; (iii) yield curve implications.
Threshold regime switching model; Macroeconomic variables; Term structure of interest rates; Asset pricing; Nonlinear dynamics; Business cycles
Filipova, Kameliya
Audrino, Francesco
Giorgi, Enrico De
01-09-2014
2014
Filipova, Kameliya ; Audrino, Francesco ; De Giorgi, Enrico: Monetary policy regimes: implications for the yield curve and bond pricing. In: Journal of Financial Economics 3 (2014), Nr. 113, S. 427-454.
none
Bond Risk Premia Forecasting : A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/223242
en
urn:ISSN:0747-4938
doi:10.1080/07474938.2013.833809
Econometric Reviews
We propose a simple but effective estimation procedure to extract the level and the volatility dynamics of a latent macroeconomic factor from a panel of observable indicators. Our approach is based on a multivariate conditionally heteroscedastic exact factor model that can take into account the heteroscedasticity feature shown by most macroeconomic variables and relies on an iterated Kalman filter procedure. In simulations we show the unbiasedness of the proposed estimator and its superiority to different approaches introduced in the literature. Simulation results are confirmed in applications to real inflation data with the goal of forecasting long-term bond risk premia. Moreover, we find that the extracted level and conditional variance of the latent factor for inflation are strongly related to NBER business cycles.
Macroeconomic variables; Exact factor model; Kalman filter; Heteroscedasticity; Forecasting bond risk premia; Inflation measures; Business cycles
Audrino, Francesco
Corsi, Fulvio
Filipova, Kameliya
0-0-2014
2014
Audrino, Francesco ; Corsi, Fulvio ; Filipova, Kameliya: Bond Risk Premia Forecasting : A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators. In: Econometric Reviews 2014 (2014), Nr. online seit 08.13 - forthcoming, S. 1-43, DOI:10.1080/07474938.2013.833809.
none
Forecasting correlations during the late-2000s financial crisis : The short-run component, the long-run component, and structural breaks
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/223241
en
urn:ISSN:0167-9473
doi:10.1016/j.csda.2013.06.002
Computational Statistics & Data Analysis
The predictive power of recently introduced components affecting correlations is investigated. The focus is on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover, models allowing the correlation dynamics to be subjected to regime-shift caused by threshold-based structural breaks of a different nature are also considered. The results indicate that in some cases there may be a superimposition of the long-term and short-term movements in correlations. Therefore, care is called for in interpretations when estimating the two components. Testing the forecasting accuracy of correlations during the late-2000s financial crisis yields mixed results. In general, component models allowing for a richer correlation specification possess an increased predictive accuracy. Economically speaking, no relevant gains are found by allowing for more flexibility in the correlation dynamics.
Correlation forecasting; Component models; Threshold regime-switching models; Mixed data sampling; Performance evaluation.
Audrino, Francesco
0-08-2014
2014
Audrino, Francesco: Forecasting correlations during the late-2000s financial crisis : The short-run component, the long-run component, and structural breaks. In: Computational Statistics & Data Analysis 76 (2014), Nr. August 2014, S. 43-60, DOI:10.1016/j.csda.2013.06.002.
none
Oracle Properties and Finite Sample Inference of the Adaptive Lasso for Time Series Regression Models
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/226455
en
We derive new theoretical results on the properties of the adaptive least absolute shrinkage and selection operator (adaptive lasso) for time series regression models. In particular we investigate the question of how to conduct finite sample inference on the parameters given an adaptive lasso model for some fixed value of the shrinkage parameter. Central in this study is the test of the hypothesis that a given adaptive lasso parameter equals zero, which therefore tests for a false positive. To this end we construct a simple (conservative) testing procedure and show, theoretically and empirically through extensive Monte Carlo simulations, that the adaptive lasso combines efficient parameter estimation, variable selection, and valid finite sample inference in one step. Moreover, we analytically derive a bias correction factor that is able to significantly improve the empirical coverage of the test on the active variables. Finally, we apply the introduced testing procedure to investigate the relation between the short rate dynamics and the economy, thereby providing a statistical foundation (from a model choice perspective) to the classic Taylor rule monetary policy model.
Adaptive lasso; Time series; Oracle properties; Finite sample inference; Taylor rule monetary policy model.
Audrino, Francesco
Camponovo, Lorenzo
2013
2013
Audrino, Francesco ; Camponovo, Lorenzo: Oracle Properties and Finite Sample Inference of the Adaptive Lasso for Time Series Regression Models : SEPS Discussion paper series, 2013.
none
Monetary Policy Regimes: Implications for the Yield Curve and Bond Pricing
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/221675
en
We develop a multivariate dynamic term structure model, which takes into account the nonlinear (time-varying) relationship between interest rates and the state of the economy. In contrast to the classical term structure literature, where nonlinearities are captured by increasing the number of latent state variables, or by latent regime shifts, in our no-arbitrage framework the regimes are governed by thresholds and are directly linked to different economic fundamentals. Specifically, starting from a simple monetary policy model for the short rate, we introduce a parsimonious and tractable model for the yield curve, which takes into account the possibility of regime shifts in the behavior of the Federal Reserve. In our empirical analysis, we show the merit of our approach along four dimensions: (i) interpretable bond dynamics; (ii) accurate short end yield curve pricing; (iii) yield curve implications; (iv) superior out-of-sample short rate forecasting performance.
Threshold regime switching model, Macroeconomic variables, Term structure of interest rates, Asset pricing, Nonlinear dynamics, Business cycles
Filipova, Kameliya
Audrino, Francesco
Giorgi, Enrico De
2013
2013
Filipova, Kameliya ; Audrino, Francesco ; De Giorgi, Enrico: Monetary Policy Regimes: Implications for the Yield Curve and Bond Pricing : http://ssrn.com/abstract=2232742, 2013.
none
Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/221837
en
Realized volatility computed from high-frequency data is an important measure for many applications in finance. However, its dynamics are not well understood to date. Recent notable advances that perform well include the heterogeneous autoregressive (HAR) model which is economically interpretable and but still easy to estimate. It also features good out-of-sample performance and has been extremely well received by the research community. We present a data driven approach based on the absolute shrinkage and selection operator (lasso) which should identify the aforementioned model. We prove that the lasso indeed recovers the HAR model asymptotically if it is the true model, and we present Monte Carlo evidence in finite sample. The HAR model is not recovered by the lasso on real data. This, together with an empirical out-of-sample analysis that shows equal performance of the HAR model and the lasso approach, leads to the conclusion that the HAR model may not be the true model but it captures a linear footprint of the true volatility dynamics.
Realized Volatility; Heterogeneous Autoregressive Model; Lasso; Model Selection;
Audrino, Francesco
Knaus, Simon
2012
2012
Audrino, Francesco ; Knaus, Simon ; HSG (Hrsg.): Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics. Discussion paper series. St. Gallen : SEPS, 2012.
216969
Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/210621
en
urn:ISSN:1479-8409
doi:10.1093/jjfinec/nbs007
Journal of Financial Econometrics
This paper presents two classes of tick-by-tick covariance estimators adapted to the case of rounding in the price time stamps to a frequency lower than the typical arrival rate of tick prices. Through Monte Carlo simulations we investigate the behavior of such estimators under realistic market microstructure conditions analogous to those of the financial data examined in this paper’s empirical section, that is, non-synchronous trading, general ARMA structure for microstructure noise, and true lead-lag cross-covariance.
Simulation results show the robustness of the proposed tick-by-tick covariance estimators to time stamp rounding, and their overall performance is superior to competing covariance estimators under empirically realistic microstructure conditions. These results are confirmed in the empirical application where the economic benefits of the proposed estimators are evaluated with volatility timing strategies applied to a bivariate portfolio of S&P 500 futures and 30-year US treasury bond futures.
High frequency data; Realized covariance; Market microstructure; Bias correction; Portfolio selection; Volatility timing.
Audrino, Francesco
Corsi, Fulvio
0-09-2012
2012
Audrino, Francesco ; Corsi, Fulvio: Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects. In: Journal of Financial Econometrics 10 (2012), Nr. 4, S. 591-616, DOI:10.1093/jjfinec/nbs007.
none
HAR Modeling for Realized Volatility Forecasting
Buchkapitel
https://www.alexandria.unisg.ch/Publikationen/209933
en
urn:ISBN:978-0-470-87251-2
Audrino, Francesco
Corsi, Fulvio
Reno, Roberto
2012
2012
Audrino, Francesco ; Corsi, Fulvio ; Reno, Roberto: HAR Modeling for Realized Volatility Forecasting. In: Handbook of Volatility Models and their Applications. Hoboken, N.J. : Wiley, 2012, S. 363-382. - ISBN 978-0-470-87251-2.
none
Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/209167
en
Motivated by the need for an unbiased and positive-semidefinite estimator of multivariate realized covariance matrices, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then estimate the covariance matrix of the latent states through a Kalman smoother and Expectation Maximization (KEM) algorithm. In the expectation step, by means of the Kalman filter with missing data, we reconstruct the smoothed and synchronized series of the latent price processes. In the maximization step, we search for covariance matrices that maximize the expected likelihood obtained with the reconstructed price series. Iterating between the two EM steps, we obtain a KEM-improved covariance matrix estimate which is robust to both asynchronicity and microstructure noise, and positive-semidefinite by construction.
Extensive Monte Carlo simulations show the superior performance of the KEM estimator over several alternative covariance matrix estimates introduced in the literature. The application of the KEM estimator in practice is illustrated on a 10-dimensional US stock data set.
High frequency data; Realized covariance matrix; Market microstructure noise; Missing data; Kalman filter; EM algorithm; Maximum likelihood
Audrino, Francesco
Corsi, Fulvio
Peluso, Stefano
2012
2012
Audrino, Francesco ; Corsi, Fulvio ; Peluso, Stefano: Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation. St. Gallen : SEPS Working Paper Series, 2012.
none
What drives short rate dynamics? A functional gradient descent approach
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/207833
en
urn:ISSN:0927-7099
doi:10.1007/s10614-011-9310-y
Computational Economics
Functional gradient descent, a recent technique coming from computational statistics, is applied to the estimation of the conditional moments of the short rate process with the goal of finding the main drivers of the drift and volatility dynamics. Functional gradient descent can improve the accuracy of some reasonable starting estimates obtained using classical short rate models introduced in the literature. It exploits the predictive information of an enlarged set of variables, including yields at other maturities, time, and macroeconomic indicators. Fitting this methodology to the time series of monthly US 3-month Treasury bill rates, we find that the drift dynamics react mostly in a non-linear way to changes in macroeconomic variables, whereas volatility dynamics are subjected to time-dependent regime-switches. Finally we show the superior performance of the final predictions obtained by applying functional gradient descent in a forecasting exercise.
Functional gradient descent; Short rate process; Macroeconomic variables; Time-varying drift and volatility dynamics.
Audrino, Francesco
0-03-2012
2012
Audrino, Francesco: What drives short rate dynamics? A functional gradient descent approach. In: Computational Economics 39 (2012), Nr. 3, S. 315-335, DOI:10.1007/s10614-011-9310-y.
none
Option strategies based on semi-parametric implied volatility surface prediction
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/207130
en
urn:ISSN:1460-1559
Journal of Investment Strategies
We investigate whether a more sophisticated technique able to forecast accurately the future movements of the implied volatility surface may help in improving the performance of basic option strategies. To this goal we construct a set of strategies using predicted option returns for a forecasting period of ten trading days and form profitable hold-to-expiration, equally weighted, zero-cost portfolios with one month at-the-money options. The accurate predictions of the implied volatility surface dynamics are obtained using a statistical machine learning procedure based on regression trees. These forecasts assist in obtaining reliable option returns used as trading signals in our strategies. We test the performance of the proposed strategies on options on the S\&P100 and on its constituents between 2002 and 2006 getting positive annualized returns of up to more than 50\%. Comparing such performance to the ones obtained without using any complex model for the implied volatility surface we show that in most cases differences are small.
Audrino, Francesco
Colangelo, Dominik
0-12-2011
2011
Audrino, Francesco ; Colangelo, Dominik: Option strategies based on semi-parametric implied volatility surface prediction. In: Journal of Investment Strategies 1 (2011), Nr. 1, S. 3-41.
none
Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/205649
en
We empirically investigate the predictive power of the various components affecting correlations that have been recently introduced in the literature. We focus on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover, we also allow the correlation dynamics to be subjected to regime-shift caused by threshold-based structural breaks of a different nature. Our results indicate that in some cases there may be a superimposition of the long- and short-term movements in correlations. Therefore, care is called for in interpretations when estimating the two components. Testing the forecasting accuracy of correlations during the late-2000s financial crisis yields mixed results. In general component models allowing for a richer correlation specification possess an increased predictive accuracy. Economically speaking, no relevant gains are found by allowing for more flexibility in the correlation dynamics.
Correlation forecasting; Component models; Threshold regime-switching models; Mixed data sampling; Performance evaluation.
Audrino, Francesco
2011
2011
Audrino, Francesco: Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks. Discussion papers in economics : SEPS-UNISG, 2011.
none
Modeling and forecasting short-term interest rates : The benefits of smooth regimes, macroeconomic variables, and bagging
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/57802
en
urn:ISSN:0883-7252
doi:10.1002/jae.1171
Journal of Applied Econometrics
In this paper we propose a smooth transition tree model for both the
conditional mean and variance of the short-term interest rate process. The estimation of such models is addressed and the asymptotic properties of the quasi-maximum likelihood estimator are derived. Model specification is also discussed. When the model is applied to the US short-term interest rate we find (1) leading indicators for inflation and real activity are the most relevant predictors in characterizing the multiple regimes' structure; (2) the optimal model has three limiting regimes. Moreover, we provide empirical evidence of the power of the model in forecasting the first two conditional moments when it is used in connection with bootstrap aggregation (bagging).
short-term interest rate, regression tree, smooth
transition, conditional variance, bagging, asymptotic theory.
Audrino, Francesco
Medeiros, Marcelo C.
0-09-2011
2011
Audrino, Francesco ; Medeiros, Marcelo C.: Modeling and forecasting short-term interest rates : The benefits of smooth regimes, macroeconomic variables, and bagging. In: Journal of Applied Econometrics 26 (2011), Nr. 6, S. 999-1022, DOI:10.1002/jae.1171.
none
A General Multivariate Threshold GARCH Model for Dynamic Correlations
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/57801
en
urn:ISSN:0735-0015
doi:10.1198/jbes.2010.08117
Journal of Business and Economic Statistics
We introduce a new multivariate GARCH model with multivariate thresholds in conditional correlations and develop a two-step
estimation procedure that is feasible in large dimensional applications. Optimal threshold functions are estimated endogenously from the data, and the model conditional covariance matrix is ensured to be positive definite. We study the empirical performance of our model in two applications using US stock and bond market data. In both applications our model has, in terms of statistical and economic significance, higher forecasting power than several other multivariate GARCH models for conditional correlations
Multivariate GARCH models; Dynamic conditional correlations; Tree-structured GARCH models.
Audrino, Francesco
Trojani, Fabio
0-01-2011
2011
Audrino, Francesco ; Trojani, Fabio: A General Multivariate Threshold GARCH Model for Dynamic Correlations. In: Journal of Business and Economic Statistics 29 (2011), Nr. 1, S. 138-149, DOI:10.1198/jbes.2010.08117.
none
Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/62217
en
http://ideas.repec.org/p/usg/dp2010/2010-09.html
Audrino, Francesco
2010
2010
Audrino, Francesco: Bond Risk Premia Forecasting: A Simple Approach for Extracting Macroeconomic Information from a Panel of Indicators. VWA Discussion Paper Series : Economic Deparment, University of St. Gallen, 2010.
none
Modeling tick-by-tick realized correlations
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/57803
en
urn:ISSN:0167-9473
doi:10.1016/j.csda.2009.09.033
Computational Statistics and Data Analysis
A tree-structured heterogeneous autoregressive (tree-HAR) process is
proposed as a simple and parsimonious model for the estimation and prediction of tick-by-tick realized correlations. The model can account for different time and other relevant predictors' dependentregime shifts in the conditional mean dynamics of the realized correlation series. Testing the model on S&P 500 Futures and 30-year Treasury Bond Futures realized correlations, empirical evidence that the tree-HAR model reaches a good compromise between simplicity and flexibility is provided. The model yields accurate single- and multi-step out-of-sample forecasts. Such forecasts are also better than those obtained from other standard approaches, in particular when the final goal is multi-period forecasting
High frequency data; Realized correlation;
Stock-bond correlation; Tree-structured models; HAR; Regimes.
Audrino, Francesco
Corsi, Fulvio
01-11-2010
2010
Audrino, Francesco ; Corsi, Fulvio: Modeling tick-by-tick realized correlations. In: Computational Statistics and Data Analysis 54 (2010), Nr. 11, S. 2372-2382, DOI:10.1016/j.csda.2009.09.033.
none
Semi-parametric forecasts of the implied volatility surface using regression trees
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/53839
en
urn:ISSN:0960-3174
doi:10.1007/s11222-009-9134-y
Statistics and Computing
We present a new semi-parametric model for the prediction of implied volatility surfaces that can be estimated using machine learning algorithms. Given a reasonable starting model, a boosting algorithm based on regression trees sequentially minimizes generalized residuals computed as differences between observed and estimated implied volatilities. To overcome the poor predictive power of existing models, we include a grid in the region of interest, and implement a cross-validation strategy to find an optimal stopping value for the boosting procedure. Back testing the out-of-sample performance on a large data set of implied volatilities from S&P 500 options, we provide empirical evidence of the strong predictive power of our model.
Implied Volatility, Implied Volatility Surface, Option Pricing, Forecasting,
Tree Boosting, Regression Tree, Functional Gradient Descent
Audrino, Francesco
Colangelo, Dominik
20-09-2010
2010
Audrino, Francesco ; Colangelo, Dominik: Semi-parametric forecasts of the implied volatility surface using regression trees. In: Statistics and Computing 20 (2010), Nr. 4, S. 421-434, DOI:10.1007/s11222-009-9134-y.
none
Yield Curve Predictability, Regimes, and Macroeconomic Information : A Data-Driven Approach
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/53838
en
http://ideas.repec.org/p/usg/dp2009/2009-10.html
Audrino, Francesco
Filipova, Kameliya
2009
2009
Audrino, Francesco ; Filipova, Kameliya ; University of St. Gallen Department of Economics (Hrsg.): Yield Curve Predictability, Regimes, and Macroeconomic Information : A Data-Driven Approach. University of St. Gallen Department of Economics working paper series 2009. St. Gallen : University of St. Gallen, 2009.
none
Splines for Financial Volatility
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/48831
en
urn:ISSN:1369-7412
Journal of the Royal Statistical Society, Series B
Audrino, Francesco
Bühlmann, Peter
06-06-2009
2009
Audrino, Francesco ; Bühlmann, Peter: Splines for Financial Volatility. In: Journal of the Royal Statistical Society, Series B 71 (2009), Nr. 3, S. 655-670.
none
Smooth Regimes, Macroeconomic Variables, and Bagging for the Short-Term Interest Rate Process : Discussion papers
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/47866
en
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1233942
http://ideas.repec.org/p/usg/dp2008/2008-16.html
Audrino, Francesco
Madeiros, Marcelo C.
2008
2008
Audrino, Francesco ; Madeiros, Marcelo C.: Smooth Regimes, Macroeconomic Variables, and Bagging for the Short-Term Interest Rate Process : Discussion papers. 2008. St. Gallen : Volkswirtschaftliche Abteilung Universität St. Gallen, 2008.
none
Modeling Tick-by-Tick Realized Correlations : Discussion Papers
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/43622
en
http://ideas.repec.org/p/usg/dp2008/2008-05.html
Audrino, Francesco
Corsi, Fulvio
2008
2008
Audrino, Francesco ; Corsi, Fulvio: Modeling Tick-by-Tick Realized Correlations : Discussion Papers. 2008. St. Gallen : Volkswirtschaftliche Abteilung Universität St. Gallen, 2008.
none
Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects : Discussion papers
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/43621
en
http://ideas.repec.org/p/usg/dp2008/2008-04.html
Audrino, Francesco
Corsi, Fulvio
2008
2008
Audrino, Francesco ; Corsi, Fulvio: Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects : Discussion papers. 2008. St. Gallen : Volkswirtschaftliche Abteilung Universität St. Gallen, 2008.
none
Forecasting Implied Volatility Surfaces
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/45861
en
http://ideas.repec.org/p/usg/dp2007/2007-42.html
Audrino, Francesco
Colangelo, Dominik
2007
2007
Audrino, Francesco ; Colangelo, Dominik: Forecasting Implied Volatility Surfaces. VWA Discussion Papers Series : University of St. Gallen, 2007.
none
Forecasting Implied Volatility Surfaces
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41484
en
http://ideas.repec.org/p/usg/dp2007/2007-42.html
Audrino, Francesco
Colangelo, Dominik
2007
2007
Audrino, Francesco ; Colangelo, Dominik: Forecasting Implied Volatility Surfaces : 2007-42, VWA Discussion Papers Series, HSG St. Gallen, 2007.
none
A general multivariate threshold GARCH model with dynamic conditional correlations (Revised Version of Paper no. 2005-04)
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41447
en
http://ideas.repec.org/p/usg/dp2005/2005-04.html
Audrino, Francesco
Trojani, Fabio
2007
2007
Audrino, Francesco ; Trojani, Fabio: A general multivariate threshold GARCH model with dynamic conditional correlations (Revised Version of Paper no. 2005-04) : 2007-25, VWA Discussion Papers Series, HSG St. Gallen, 2007.
https://www.alexandria.unisg.ch/export/DL/55191.pdf
none
Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41446
en
http://ideas.repec.org/p/usg/dp2007/2007-24.html
Audrino, Francesco
Trojani, Fabio
2007
2007
Audrino, Francesco ; Trojani, Fabio: Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent : 2007-24, VWA Discussion Papers Series, HSG St. Gallen, 2007.
none
Splines for Financial Volatility
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41443
en
http://ideas.repec.org/p/usg/dp2007/2007-11.html
Audrino, Francesco
Bühlmann, Peter
2007
2007
Audrino, Francesco ; Bühlmann, Peter: Splines for Financial Volatility : 2007-11, VWA Discussion Papers Series, HSG St. Gallen, 2007.
none
Realized Correlation Tick-by-Tick
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41441
en
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=957997
Audrino, Francesco
Corsi, Fulvio
2007
2007
Audrino, Francesco ; Corsi, Fulvio: Realized Correlation Tick-by-Tick : 2007-02, VWA Discussion Papers Series, HSG St. Gallen, 2007.
none
Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/40070
en
urn:ISSN:1479-8409
doi:10.1093/jjfinec/nbm011
Journal of Financial Econometrics
We propose a multivariate nonparametric technique for generating reliable short-term historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest rate series. It is computationally feasible in large dimensions and it can account for nonlinearities in the dependence of interest rates at all available maturities. Based on FGD we apply filtered historical simulation to compute reliable out-of-sample yield curve scenarios and confidence intervals. We back-test our methodology on daily USD bond data for forecasting horizons from 1 to 10 days. Based on several statistical performance measures we find significant evidence of a higher predictive power of our method when compared to scenarios generating techniques based on (i) factor analysis, (ii) a multivariate CCC-GARCH model, or (iii) an exponential smoothing covariances estimator as in the RiskMetricsTM approach.
Audrino, Francesco
Trojani, Fabio
0-08-2007
2007
Audrino, Francesco ; Trojani, Fabio: Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent. In: Journal of Financial Econometrics 5 (2007), Nr. 4, S. 591-623, DOI:10.1093/jjfinec/nbm011.
none
Beta regimes for the Yield Curve
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/40068
en
urn:ISSN:1479-8409
doi:10.1093/jjfinec/nbm007
Journal of Financial Econometrics
We propose an affine term structure model which accommodates nonlinearities in the drift and volatility function of the short-term interest rate. Such nonlinearities are a consequence of discrete beta-distributed regime shifts constructed on multiple thresholds. We derive iterative closed-form formula for the whole yield curve dynamics that can be estimated using a linearized Kalman filter. Fitting the model on US data, we collect empirical evidence of its potential in estimating conditional volatility and correlation across yields.
Audrino, Francesco
Giorgi, Enrico De
08-05-2007
2007
Audrino, Francesco ; De Giorgi, Enrico: Beta regimes for the Yield Curve. In: Journal of Financial Econometrics 5 (2007), Nr. 3, S. 456-490, DOI:10.1093/jjfinec/nbm007.
none
A forecasting model for stock market diversity
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/36413
en
urn:ISSN:1614-2446
Annals of Finance
Audrino, Francesco
Fernholz, Robert
Ferretti, Roberto
0-0-2007
2007
Audrino, Francesco ; Fernholz, Robert ; Ferretti, Roberto: A forecasting model for stock market diversity. In: Annals of Finance 3 (2007), S. 213-240.
none
Average Conditional Correlation and Tree Structures for Multivariate GARCH Models
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/36416
en
urn:ISSN:0277-6693
doi:10.1002/for.1014
Journal of Forecasting
We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back-test the models on a six-dimensional exchange-rate time series using different goodness-of-fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures.
Audrino, Francesco
Adesi, Giovanni Barone
01-12-2006
2006
Audrino, Francesco ; Barone Adesi, Giovanni: Average Conditional Correlation and Tree Structures for Multivariate GARCH Models. In: Journal of Forecasting 25 (2006), Nr. 8, S. 579-600, DOI:10.1002/for.1014.
none
A dynamic model of expected bond returns: A functional gradient descent approach
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32658
en
urn:ISSN:0167-9473
doi:10.1016/j.csda.2006.07.024
Computational Statistics & Data Analysis
A multivariate methodology based on functional gradient descent to estimate and forecast time-varying expected bond returns is presented and discussed. Backtesting this procedure on US monthly data, empirical evidence of its strong forecasting potential in terms of the accuracy of the predictions is collected. The proposed methodology clearly outperforms the classical univariate analysis used in the literature.
Term structure;
Bond returns;
Functional gradient descent;
Semi-parametric VAR-GARCH models
Audrino, Francesco
Adesi, Giovanni Barone
15-12-2006
2006
Audrino, Francesco ; Barone Adesi, Giovanni: A dynamic model of expected bond returns: A functional gradient descent approach. In: Computational Statistics & Data Analysis 51 (2006), Nr. 4, S. 2267-2277, DOI:10.1016/j.csda.2006.07.024.
none
Tree-structured multiple regimes in interest rates
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32657
en
urn:ISSN:0735-0015
Journal of Business & Economic Statistics
This article develops a generalized tree-structured (GTS) model of the short-term interest rate that accommodates regime-dependent mean reversion and regime-dependent volatility clustering and level effects in the conditional variance. The model is constructed using the idea of multivariate tree-structured thresholds and nests the popular generalized autoregressive conditional heteroscedasticity and square root processes as simple special cases. It allows us to estimate the optimal number of regimes endogenously from the data and to exploit possible additional information in the term structure and in other macroeconomic variables. We provide empirical evidence of the strong potential of the GTS model in forecasting conditional first and second moments, also in comparison with alternative models of the short rate.
Studies;
Economic models;
Interest rates;
Forecasting;
Variance analysis
Audrino, Francesco
0-07-2006
2006
Audrino, Francesco: Tree-structured multiple regimes in interest rates. In: Journal of Business & Economic Statistics 24 (2006), Nr. 3, S. 338-353.
none
Estimating and predicting multivariate volatility thresholds in global stock markets
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32653
en
urn:ISSN:0883-7252
doi:10.1002/jae.869
Journal of Applied Econometrics
Audrino, Francesco
Trojani, Fabio
0-04-2006
2006
Audrino, Francesco ; Trojani, Fabio: Estimating and predicting multivariate volatility thresholds in global stock markets. In: Journal of Applied Econometrics 21 (2006), Nr. 3, S. 345-369, DOI:10.1002/jae.869.
none
The impact of general non-parametric volatility functions in multivariate GARCH models
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32652
en
urn:ISSN:0167-9473
doi:10.1016/j.csda.2005.06.006
Computational Statistics & Data Analysis
Recent studies have revealed that financial volatilities and correlations move together over time across assets and markets. The main effort has been on improving the flexibility of conditional correlation dynamics, while maintaining computational feasibility for large estimation problems. However, since in such models conditional covariances are the product of conditional correlations and individual volatilities, it is plausible that improving the estimation of individual volatilities will lead to better covariance forecasts, too. Functional gradient descent (FGD) has already been shown to improve substantially in-sample and out-of-sample covariance accuracy in the very simple constant conditional correlation (CCC) setting. Following this direction, the impact of FGD volatility estimates is tested in several multivariate GARCH settings, both at the multivariate and at the univariate portfolio levels. In particular, improving conditional correlations and improving individual volatilities are compared, to establish which effect produces the best fits and predictions for conditional covariances.
Multivariate GARCH models;
Asymmetric non-linear volatility;
Dynamic conditional correlations;
Functional gradient descent (FGD) estimation
Audrino, Francesco
0-07-2006
2006
Audrino, Francesco: The impact of general non-parametric volatility functions in multivariate GARCH models. In: Computational Statistics & Data Analysis 50 (2006), Nr. 11, S. 3032-3052, DOI:10.1016/j.csda.2005.06.006.
none
A general multivariate threshold GARCH model with dynamic conditional correlations
Arbeitspapier
https://www.alexandria.unisg.ch/Publikationen/41439
en
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=487942
Audrino, Francesco
Trojani, Fabio
2005
2005
Audrino, Francesco ; Trojani, Fabio: A general multivariate threshold GARCH model with dynamic conditional correlations : 2005-04, VWA Discussion Papers Series, HSG St. Gallen, 2005.
none
Local Likelihood for non paramentric ARCH(1) models
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32656
en
urn:ISSN:0143-9782
doi:10.1111/j.1467-9892.2005.00400.x
Journal of Time Series Analysis
We propose a non-parametric local likelihood estimator for the log-transformed autoregressive conditional heteroscedastic (ARCH) (1) model. Our non-parametric estimator is constructed within the likelihood framework for non-Gaussian observations: it is different from standard kernel regression smoothing, where the innovations are assumed to be normally distributed. We derive consistency and asymptotic normality for our estimators and show, by a simulation experiment and some real-data examples, that the local likelihood estimator has better predictive potential than classical local regression. A possible extension of the estimation procedure to more general multiplicative ARCH(p) models with p > 1 predictor variables is also described.
Audrino, Francesco
01-03-2005
2005
Audrino, Francesco: Local Likelihood for non paramentric ARCH(1) models. In: Journal of Time Series Analysis 26 (2005), Nr. 2, S. 251-278, DOI:10.1111/j.1467-9892.2005.00400.x.
none
A multivariate FGD technique to improve VaR computation in equity markets
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32651
en
urn:ISSN:1619-697X
doi:10.1007/s10287-004-0028-3
Computational Management Science
It is difficult to compute Value-at-Risk (VaR) using multivariate models able to take into account the dependence structure between large numbers of assets and being still computationally feasible. A possible procedure is based on functional gradient descent (FGD) estimation for the volatility matrix in connection with asset historical simulation. Backtest analysis on simulated and real data provides strong empirical evidence of the better predictive ability of the proposed procedure over classical filtered historical simulation, with a resulting significant improvement in the measurement of risk.
Audrino, Francesco
Adesi, Giovanni Barone
01-03-2005
2005
Audrino, Francesco ; Barone Adesi, Giovanni: A multivariate FGD technique to improve VaR computation in equity markets. In: Computational Management Science 2 (2005), Nr. 2, S. 87-106, DOI:10.1007/s10287-004-0028-3.
none
The stability of factor models of interest rates
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32649
en
urn:ISSN:1479-8409
doi:10.1093/jjfinec/nbi019
Journal of Financial Econometrics
The daily term structure of interest rates is filtered to reduce the influence of cross-correlations and autocorrelations on its factors. A three-factor model is fitted to the filtered data. We perform statistical tests, finding that factor loadings are unstable through time for daily data. This finding is not due to the presence of outliers nor to the selected number of factors. Such an instability problem can be solved when applying the factor analysis on multivariate scaled residuals, filtered using a nonparametric technique based on functional gradient descent.
factor analysis
FGD
robust regression
term structure
Audrino, Francesco
Adesi, Giovanni Barone
Mira, Antonietta
0-0-2005
2005
Audrino, Francesco ; Barone Adesi, Giovanni ; Mira, Antonietta: The stability of factor models of interest rates. In: Journal of Financial Econometrics 3 (2005), Nr. 3, S. 422-441, DOI:10.1093/jjfinec/nbi019.
none
Functional gradient descent for financial time series with an application to the measurement of market risk
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32647
en
urn:ISSN:0378-4266
doi:10.1016/j.jbankfin.2004.08.008
Journal of Banking & Finance
The estimation and forecast of the volatility matrix are two of the main tasks of financial econometrics since they are essential ingredients in many practical applications. Unfortunately the use of classical multivariate methods in large dimensions is difficult because of the curse of dimensionality. We present a general semiparametric technique, based on functional gradient descent (FGD) and able to overcome most problems associated with a multivariate GARCH-type estimation. By testing the accuracy of the volatility estimates for the measurement of market risk on real data we provide empirical evidence of the strong predictive potential of the FGD approach, also in comparison to other standard methods.
Audrino, Francesco
Adesi, Giovanni Barone
01-04-2005
2005
Audrino, Francesco ; Barone Adesi, Giovanni: Functional gradient descent for financial time series with an application to the measurement of market risk. In: Journal of Banking & Finance 29 (2005), Nr. 4, S. 959-977, DOI:10.1016/j.jbankfin.2004.08.008.
none
Synchronizing multivariate financial time series
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32655
en
urn:ISSN:1465-1211
Journal of Risk
Audrino, Francesco
Bühlmann, Peter
0-0-2004
2004
Audrino, Francesco ; Bühlmann, Peter: Synchronizing multivariate financial time series. In: Journal of Risk 6 (2004), Nr. 2, S. 81-106.
none
Volatility estimation with functional gradient descent for very high-dimensional financial time series
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32654
en
urn:ISSN:1742–7185
Journal of Computational Finance
Audrino, Francesco
Bühlmann, Peter
0-0-2003
2003
Audrino, Francesco ; Bühlmann, Peter: Volatility estimation with functional gradient descent for very high-dimensional financial time series. In: Journal of Computational Finance 6 (2003), Nr. 3, S. 65-89.
none
Tree-structured generalized autoregressive conditional heteroscedastic models
Artikel (wissenschaftliche Zeitschrift)
https://www.alexandria.unisg.ch/Publikationen/32631
en
urn:ISSN:1369-7412
Journal of the Royal Statistical Society, Series B
We propose a new generalized autoregressive conditional heteroscedastic (GARCH) model with tree-structured multiple thresholds for the estimation of volatility in financial time series. The approach relies on the idea of a binary tree where every terminal node parameterizes a (local) GARCH model for a partition cell of the predictor space. The fitting of such trees is constructed within the likelihood framework for non-Gaussian observations: it is very different from the well-known regression tree procedure which is based on residual sums of squares. Our strategy includes the classical GARCH model as a special case and allows us to increase model complexity in a systematic and flexible way. We derive a consistency result and conclude from simulation and real data analysis that the new method has better predictive potential than other approaches.
Audrino, Francesco
Bühlmann, Peter
01-12-2001
2001
Audrino, Francesco ; Bühlmann, Peter: Tree-structured generalized autoregressive conditional heteroscedastic models. In: Journal of the Royal Statistical Society, Series B 63 (2001), Nr. 4, S. 727-744.
none