The Experts below are selected from a list of 16158 Experts worldwide ranked by ideXlab platform
Rasmus T Varneskov - One of the best experts on this subject based on the ideXlab platform.
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consistent inference for predictive regressions in persistent economic systems
Journal of Econometrics, 2020Co-Authors: Torben G Andersen, Rasmus T VarneskovAbstract:Abstract This paper studies standard predictive regressions in economic systems governed by persistent vector autoregressive dynamics for the state variables. In particular, all – or a subset – of the variables may be fractionally integrated, which induces a spurious regression problem. We propose a new inference and testing procedure – the Local speCtruM (LCM) approach – for joint significance of the regressors, that is robust against the variables having different integration orders and remains valid regardless of whether predictors are significant and, if they are, whether they induce cointegration. Specifically, the LCM procedure is based on fractional filtering and band spectrum regression using a suitably selected set of frequency ordinates. Contrary to existing procedures, we establish a uniform Gaussian limit theory and a standard χ 2 -distributed test statistic. Using the LCM inference and testing techniques, we explore predictive regressions for the Realized Return variation. Standard least squares inference indicates that popular financial and macroeconomic variables convey valuable information about future Return volatility. In contrast, we find no significant evidence using our robust LCM procedure. If anything, our tests support a reverse chain of causality, with rising financial volatility predating adverse innovations to key macroeconomic variables. Simulations are employed to illustrate the relevance of the theoretical arguments for finite-sample inference.
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consistent inference for predictive regressions in persistent var economies
CREATES Research Papers, 2018Co-Authors: Torben G Andersen, Rasmus T VarneskovAbstract:This paper studies the properties of standard predictive regressions in model economies, characterized through persistent vector autoregressive dynamics for the state variables and the associated series of interest. In particular, we consider a setting where all, or a subset, of the variables may be fractionally integrated, and note that this induces a spurious regression problem. We then propose a new inference and testing procedure - the local spectrum (LCM) approach - for the joint significance of the regressors, which is robust against the variables having different integration orders. The LCM procedure is based on (semi-)parametric fractional-filtering and band spectrum regression using a suitably selected set of frequency ordinates. We establish the asymptotic properties and explain how they differ from and extend existing procedures. Using these new inference and testing techniques, we explore the implications of assuming VAR dynamics in predictive regressions for the Realized Return variation. Standard least squares predictive regressions indicate that popular financial and macroeconomic variables carry valuable information about Return volatility. In contrast, we find no significant evidence using our robust LCM procedure, indicating that prior conclusions may be premature. In fact, if anything, our results suggest the reverse causality, i.e., rising volatility predates adverse innovations to key macroeconomic variables. Simulations are employed to illustrate the relevance of the theoretical arguments for finite-sample inference.
Torben G Andersen - One of the best experts on this subject based on the ideXlab platform.
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consistent inference for predictive regressions in persistent economic systems
Journal of Econometrics, 2020Co-Authors: Torben G Andersen, Rasmus T VarneskovAbstract:Abstract This paper studies standard predictive regressions in economic systems governed by persistent vector autoregressive dynamics for the state variables. In particular, all – or a subset – of the variables may be fractionally integrated, which induces a spurious regression problem. We propose a new inference and testing procedure – the Local speCtruM (LCM) approach – for joint significance of the regressors, that is robust against the variables having different integration orders and remains valid regardless of whether predictors are significant and, if they are, whether they induce cointegration. Specifically, the LCM procedure is based on fractional filtering and band spectrum regression using a suitably selected set of frequency ordinates. Contrary to existing procedures, we establish a uniform Gaussian limit theory and a standard χ 2 -distributed test statistic. Using the LCM inference and testing techniques, we explore predictive regressions for the Realized Return variation. Standard least squares inference indicates that popular financial and macroeconomic variables convey valuable information about future Return volatility. In contrast, we find no significant evidence using our robust LCM procedure. If anything, our tests support a reverse chain of causality, with rising financial volatility predating adverse innovations to key macroeconomic variables. Simulations are employed to illustrate the relevance of the theoretical arguments for finite-sample inference.
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consistent inference for predictive regressions in persistent var economies
CREATES Research Papers, 2018Co-Authors: Torben G Andersen, Rasmus T VarneskovAbstract:This paper studies the properties of standard predictive regressions in model economies, characterized through persistent vector autoregressive dynamics for the state variables and the associated series of interest. In particular, we consider a setting where all, or a subset, of the variables may be fractionally integrated, and note that this induces a spurious regression problem. We then propose a new inference and testing procedure - the local spectrum (LCM) approach - for the joint significance of the regressors, which is robust against the variables having different integration orders. The LCM procedure is based on (semi-)parametric fractional-filtering and band spectrum regression using a suitably selected set of frequency ordinates. We establish the asymptotic properties and explain how they differ from and extend existing procedures. Using these new inference and testing techniques, we explore the implications of assuming VAR dynamics in predictive regressions for the Realized Return variation. Standard least squares predictive regressions indicate that popular financial and macroeconomic variables carry valuable information about Return volatility. In contrast, we find no significant evidence using our robust LCM procedure, indicating that prior conclusions may be premature. In fact, if anything, our results suggest the reverse causality, i.e., rising volatility predates adverse innovations to key macroeconomic variables. Simulations are employed to illustrate the relevance of the theoretical arguments for finite-sample inference.
Gordon M Bodnar - One of the best experts on this subject based on the ideXlab platform.
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crossing the lines the conditional relation between exchange rate exposure and stock Returns in emerging and developed markets
Journal of International Money and Finance, 2012Co-Authors: Sohnke M Bartram, Gordon M BodnarAbstract:This paper examines the importance of exchange rate exposure in the Return generating process for a large sample of non-financial firms from 37 countries. We argue that the effect of exchange rate exposure on stock Returns is conditional and show evidence of a significant Return impact to firm-level currency exposures when conditioning on the exchange rate change. We further show that the Realized Return to exposure is directly related to the size and sign of the exchange rate change, suggesting fluctuations in exchange rates as a source of time-variation in currency Return premia. For the entire sample the Return impact ranges from 1.2 to 3.3% per unit of currency exposure, and it is larger for firms in emerging markets compared to developed markets. Overall, the results indicate that foreign exchange rate exposure estimates are economically meaningful, despite the fact that individual time-series results are noisy and many exposures are not statistically significant, and that exchange rate exposure plays an important role in generating cross-sectional Return variation. Moreover, we show that the relation between exchange rate exposure and stock Returns is more consistent with a cash flow effect than a discount rate effect.
Sohnke M Bartram - One of the best experts on this subject based on the ideXlab platform.
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crossing the lines the conditional relation between exchange rate exposure and stock Returns in emerging and developed markets
Journal of International Money and Finance, 2012Co-Authors: Sohnke M Bartram, Gordon M BodnarAbstract:This paper examines the importance of exchange rate exposure in the Return generating process for a large sample of non-financial firms from 37 countries. We argue that the effect of exchange rate exposure on stock Returns is conditional and show evidence of a significant Return impact to firm-level currency exposures when conditioning on the exchange rate change. We further show that the Realized Return to exposure is directly related to the size and sign of the exchange rate change, suggesting fluctuations in exchange rates as a source of time-variation in currency Return premia. For the entire sample the Return impact ranges from 1.2 to 3.3% per unit of currency exposure, and it is larger for firms in emerging markets compared to developed markets. Overall, the results indicate that foreign exchange rate exposure estimates are economically meaningful, despite the fact that individual time-series results are noisy and many exposures are not statistically significant, and that exchange rate exposure plays an important role in generating cross-sectional Return variation. Moreover, we show that the relation between exchange rate exposure and stock Returns is more consistent with a cash flow effect than a discount rate effect.
željko Sevic - One of the best experts on this subject based on the ideXlab platform.
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testing the relation between beta and Returns in the athens stock exchange
Managerial Finance, 2010Co-Authors: Nikolaos G Theriou, Vassilios P Aggelidis, Dimitrios I Maditinos, željko SevicAbstract:Purpose - The purpose of this paper is to examine the relationship between beta and Returns in the Athens stock exchange (ASE), taking into account the difference between positive and negative market excess Returns' yields. Design/methodology/approach - The data were taken from DataStream database and the sample period consists of 12 years divided into four six-year periods such that the test periods do not overlap. Regression analysis is applied, using both the traditional (unconditional) test procedure and the conditional approach. Findings - The estimation of Return and beta without differentiating positive and negative market excess Returns produces a flat unconditional relationship between Return and beta. However, when using the conditional capital asset pricing model (CAPM) and cross-sectional regression analysis, the evidence tends to support the significant positive relationship in up market and a significant negative relationship in down market. Research limitations/implications - The small number of listed companies in the ASE led to the inclusion of the financial and insurance companies in the sample, and to the formation of a small number of portfolios. The same research methodology could be applied to individual stocks of the ASE and with the exclusion of all financial companies. Originality/value - The results tend to support the existence of a conditional CAPM relation between risk and Realized Return trade-off.
