The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform

Johannes G. E. M. Fraaije - One of the best experts on this subject based on the ideXlab platform.

  • Physical Review E - Stochastic quasi-Newton molecular simulations.
    Physical Review E, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B = JJ T and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J. The new algorithm requires O(n 2 ) multiplications per time step instead of the O(n 3 ) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

  • Stochastic quasi-Newton molecular simulations.
    Physical review. E Statistical nonlinear and soft matter physics, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B=JJ(T) and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J . The new algorithm requires O(n2) multiplications per time step instead of the O(n3) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

C. D. Chau - One of the best experts on this subject based on the ideXlab platform.

  • Physical Review E - Stochastic quasi-Newton molecular simulations.
    Physical Review E, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B = JJ T and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J. The new algorithm requires O(n 2 ) multiplications per time step instead of the O(n 3 ) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

  • Stochastic quasi-Newton molecular simulations.
    Physical review. E Statistical nonlinear and soft matter physics, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B=JJ(T) and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J . The new algorithm requires O(n2) multiplications per time step instead of the O(n3) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

G. J. A. Sevink - One of the best experts on this subject based on the ideXlab platform.

  • Physical Review E - Stochastic quasi-Newton molecular simulations.
    Physical Review E, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B = JJ T and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J. The new algorithm requires O(n 2 ) multiplications per time step instead of the O(n 3 ) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

  • Stochastic quasi-Newton molecular simulations.
    Physical review. E Statistical nonlinear and soft matter physics, 2010
    Co-Authors: C. D. Chau, G. J. A. Sevink, Johannes G. E. M. Fraaije
    Abstract:

    We report a new and efficient factorized algorithm for the determination of the adaptive compound mobility matrix B in a stochastic quasi-Newton method (S-QN) that does not require additional potential evaluations. For one-dimensional and two-dimensional test systems, we previously showed that S-QN gives rise to efficient configurational space sampling with good thermodynamic consistency [C. D. Chau, G. J. A. Sevink, and J. G. E. M. Fraaije, J. Chem. Phys. 128, 244110 (2008)]. Potential applications of S-QN are quite ambitious, and include structure optimization, analysis of correlations and automated extraction of cooperative modes. However, the potential can only be fully exploited if the computational and memory requirements of the original algorithm are significantly reduced. In this paper, we consider a factorized mobility matrix B=JJ(T) and focus on the nontrivial fundamentals of an efficient algorithm for updating the noise multiplier J . The new algorithm requires O(n2) multiplications per time step instead of the O(n3) multiplications in the original scheme due to Choleski Decomposition. In a recursive form, the update scheme circumvents matrix storage and enables limited-memory implementation, in the spirit of the well-known limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, allowing for a further reduction of the computational effort to O(n). We analyze in detail the performance of the factorized (FSU) and limited-memory (L-FSU) algorithms in terms of convergence and (multiscale) sampling, for an elementary but relevant system that involves multiple time and length scales. Finally, we use this analysis to formulate conditions for the simulation of the complex high-dimensional potential energy landscapes of interest.

David A. Bessler - One of the best experts on this subject based on the ideXlab platform.

  • The International Price Transmission in Stock Index Futures Markets
    Economic Inquiry, 2004
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    I. INTRODUCTION Numerous studies have investigated market linkages and price transmission mechanisms in major international equity markets, employing the analytical framework of the vector autoregression (VAR) or its variant, the error-correction model (ECM). (1) Studies such as Von Furstenberg and Jeon (1989), Eun and Shim (1989), and Koch and Koch (1991) focus on the short-run dynamic pattern of price transmission; others like Taylor and Tonks (1989) and Francis and Leachman (1998) are primarily interested in the long-run pattern of price transmission. More recently, an increasing number of studies explore both long- and short-run patterns of price transmission. Included in this last set are the works of Malliaris and Urrutia (1992), Arshanapalli and Doukas (1993), Masih and Masih (2001), and Bessler and Yang (2003), among others. This study extends the examination of international price transmission to stock index futures markets. The article contributes to the existing literature in three aspects. First, a relatively new empirical framework is applied to allow for inferences of price transmission at three different time horizons: instantaneous, the short run, and the long run. Building on recent advances in statistical analysis of causal modeling using directed acyclic graphs (DAGs) as in Spirtes et al. (2000), Pearl (1995, 2000), and Swanson and Granger (1997), this study is able to explore the contemporaneous causal pattern underlying the correlations among market innovations. The existence of strong contemporaneous correlations among market innovations has been well documented in the United States and international stock markets by Agmon (1972), Eun and Shim (1989), Koch and Koch (1991), Housbrouk (1995), and Bessler and Yang (2003). It is also well recognized by Agmon (1972, 849) and Eun and Shim (1989, 246) that contemporaneous correlations among market innovations reflect the phenomenon that new information in one market is transmitted and shared by other markets in contemporaneous time, due to immediate response to price changes between markets. However, more in-depth analysis on exactly how instantaneous price transmission among market innovations is conducted in international equity markets has not yet been well addressed in the existing literature. Although Bessler and Yang (2003) touch on the issue, the necessity of imposing constraints in the spirit of the block-recursive structure noted by Koch and Koch (1991) in the DAG analysis of VAR innovations is proposed and discussed thoroughly in this study. Second, innovation accounting analysis is more thoroughly explored in the study. Innovation accounting tools (i.e., impulse response analysis and forecast error variance Decomposition) have been commonly used to summarize the dynamic pattern of price transmission among international financial markets. The importance of the factorization of innovations (i.e., VAR residuals) in yielding sound inference has been well acknowledged theoretically by Bernanke (1986), Sims (1986), and Swanson and Granger (1997). The application of the DAG technique, as discussed in Swanson and Granger (1997) and explained in the next section, is further key to innovation accounting analysis. In this study, the instantaneous price transmission pattern between market innovations (as identified by the DAG analysis) provides a data-determined solution to the basic problem of orthogonalization of residuals from the ECM and thus is critical to impulse response analysis or forecast error variance Decompositions. Swanson and Granger (1997) argue that compared to the Choleski Decomposition, the DAG-based structural Decomposition is sensible but not subjective, because it allows for the properties exhibited by the data. Although several recent studies, such as those by Bessler and Yang (2003), Bessler et al. (2003), Haigh and Bessler (forthcoming), and Yang (2003), have used the DAG-based structural Decomposition in a similar setting, the study is the first attempt responding to the suggestion by Swanson and Granger (1997, 364) of investigating the empirical implications of the DAG-based contemporaneous causal modeling. …

  • The International Price Transmission in Stock Index Futures Markets
    SSRN Electronic Journal, 2003
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    This study explores dynamic price relationships among nine major stock index futures markets, combining an error correction model with directed acyclic graph (DAG) analysis. DAG-based innovation accounting results show that the Japanese market is isolated from other major stock index futures markets. The U.S. and the UK appear to share leadership roles in stock index futures markets. The UK and German markets rather than the US exert significant influences on most European markets, which indicates a pattern of regional integration in Europe. Innovation accounting results based on widely used Choleski Decomposition are found to be seriously misleading.

  • The International Price Transmission in Stock Index Futures Markets
    1
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    This study explores dynamic price relationships among nine major stock index futures markets, combining an error-correction model with directed acyclic graph (DAG) analysis. DAG-based innovation accounting results show that the Japanese market is isolated from other major stock index futures markets. The United States and the United Kingdom appear to share leadership roles in stock index futures markets. The UK and German markets rather than the U.S. exert significant influences on most European markets, which indicates a pattern of regional integration in Europe. Innovation accounting results based on widely used Choleski Decomposition are found to be seriously misleading. (JEL G15, C32) Copyright 2004, Oxford University Press.

Jian Yang - One of the best experts on this subject based on the ideXlab platform.

  • The International Price Transmission in Stock Index Futures Markets
    Economic Inquiry, 2004
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    I. INTRODUCTION Numerous studies have investigated market linkages and price transmission mechanisms in major international equity markets, employing the analytical framework of the vector autoregression (VAR) or its variant, the error-correction model (ECM). (1) Studies such as Von Furstenberg and Jeon (1989), Eun and Shim (1989), and Koch and Koch (1991) focus on the short-run dynamic pattern of price transmission; others like Taylor and Tonks (1989) and Francis and Leachman (1998) are primarily interested in the long-run pattern of price transmission. More recently, an increasing number of studies explore both long- and short-run patterns of price transmission. Included in this last set are the works of Malliaris and Urrutia (1992), Arshanapalli and Doukas (1993), Masih and Masih (2001), and Bessler and Yang (2003), among others. This study extends the examination of international price transmission to stock index futures markets. The article contributes to the existing literature in three aspects. First, a relatively new empirical framework is applied to allow for inferences of price transmission at three different time horizons: instantaneous, the short run, and the long run. Building on recent advances in statistical analysis of causal modeling using directed acyclic graphs (DAGs) as in Spirtes et al. (2000), Pearl (1995, 2000), and Swanson and Granger (1997), this study is able to explore the contemporaneous causal pattern underlying the correlations among market innovations. The existence of strong contemporaneous correlations among market innovations has been well documented in the United States and international stock markets by Agmon (1972), Eun and Shim (1989), Koch and Koch (1991), Housbrouk (1995), and Bessler and Yang (2003). It is also well recognized by Agmon (1972, 849) and Eun and Shim (1989, 246) that contemporaneous correlations among market innovations reflect the phenomenon that new information in one market is transmitted and shared by other markets in contemporaneous time, due to immediate response to price changes between markets. However, more in-depth analysis on exactly how instantaneous price transmission among market innovations is conducted in international equity markets has not yet been well addressed in the existing literature. Although Bessler and Yang (2003) touch on the issue, the necessity of imposing constraints in the spirit of the block-recursive structure noted by Koch and Koch (1991) in the DAG analysis of VAR innovations is proposed and discussed thoroughly in this study. Second, innovation accounting analysis is more thoroughly explored in the study. Innovation accounting tools (i.e., impulse response analysis and forecast error variance Decomposition) have been commonly used to summarize the dynamic pattern of price transmission among international financial markets. The importance of the factorization of innovations (i.e., VAR residuals) in yielding sound inference has been well acknowledged theoretically by Bernanke (1986), Sims (1986), and Swanson and Granger (1997). The application of the DAG technique, as discussed in Swanson and Granger (1997) and explained in the next section, is further key to innovation accounting analysis. In this study, the instantaneous price transmission pattern between market innovations (as identified by the DAG analysis) provides a data-determined solution to the basic problem of orthogonalization of residuals from the ECM and thus is critical to impulse response analysis or forecast error variance Decompositions. Swanson and Granger (1997) argue that compared to the Choleski Decomposition, the DAG-based structural Decomposition is sensible but not subjective, because it allows for the properties exhibited by the data. Although several recent studies, such as those by Bessler and Yang (2003), Bessler et al. (2003), Haigh and Bessler (forthcoming), and Yang (2003), have used the DAG-based structural Decomposition in a similar setting, the study is the first attempt responding to the suggestion by Swanson and Granger (1997, 364) of investigating the empirical implications of the DAG-based contemporaneous causal modeling. …

  • The International Price Transmission in Stock Index Futures Markets
    SSRN Electronic Journal, 2003
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    This study explores dynamic price relationships among nine major stock index futures markets, combining an error correction model with directed acyclic graph (DAG) analysis. DAG-based innovation accounting results show that the Japanese market is isolated from other major stock index futures markets. The U.S. and the UK appear to share leadership roles in stock index futures markets. The UK and German markets rather than the US exert significant influences on most European markets, which indicates a pattern of regional integration in Europe. Innovation accounting results based on widely used Choleski Decomposition are found to be seriously misleading.

  • The International Price Transmission in Stock Index Futures Markets
    1
    Co-Authors: Jian Yang, David A. Bessler
    Abstract:

    This study explores dynamic price relationships among nine major stock index futures markets, combining an error-correction model with directed acyclic graph (DAG) analysis. DAG-based innovation accounting results show that the Japanese market is isolated from other major stock index futures markets. The United States and the United Kingdom appear to share leadership roles in stock index futures markets. The UK and German markets rather than the U.S. exert significant influences on most European markets, which indicates a pattern of regional integration in Europe. Innovation accounting results based on widely used Choleski Decomposition are found to be seriously misleading. (JEL G15, C32) Copyright 2004, Oxford University Press.