ERN: Time-Series Models (Multiple) (Topic)最新文献

{"title":"Markov Switching Artificial Neural Networks and Volatility Modeling with an Application to a Turkish Stock Index","authors":"M. Bildirici, Ozgur Omer Ersin","doi":"10.2139/ssrn.2118917","DOIUrl":"https://doi.org/10.2139/ssrn.2118917","url":null,"abstract":"The study analyzes the family of regime switching GARCH neural network models, which allow the generalization of MS type RS-GARCH models to MS-GARCH-NN models by incorparating with neural network architectures with different dynamics and forecasting capabilities both in addition to the family of GARCH models. In addition to the Gray (1996) RS-GARCH model which allows for within regime heteroskedasticity with markov switching of Hamilton (1989), the models analyzed in the study allow regime switching modeled with GARCH-NN specifications developed by Donaldson and Kamstra (1996) and further investigated by Bildirici and Ersin (2009). In addition to regime swiching type nonlinearity, proposed models incorporate different neural network architectures based on Multi Layer Perceptron (MLP), and Hybrid MLP models. Obtained models are MS-GARCH-MLP and MS-GARCH-Hybrid MLP. Above mentioned models are further extended to account for fractional integration (FI) in GARCH specification to obtain MS-FIGARCH-MLP and MS-FIGARCH-Hybrid MLP. By allowing asymmetric power transformation as modeled in APGARCH model, models are augmented to obtain MS-APGARCH-RBF and MS-FIGARCH-Hybrid MLP. Models are evaluated with MAE, MSE and RMSE criteria and equal forecast accuracy is tested with modified Diebold-Mariano tests. Among the models analyzed, though models which allow fractional integration and asymmetric power transformation perform better in modeling the daily returns in IMKB100 stock index, hybrid MLP and time lag recurrent architectures such as MS-FIAPGARCH-HybridMLP provide significant forecast and modeling performance. Overall, results suggest models with markov switching and neural network methodologies in modeling volatility in forecasting future returns in an emerging market stock index.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114772805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Way Capital Flows and Global Imbalances: A Neoclassical Approach","authors":"Y. Wen, Pengfei Wang, Zhiwei Xu","doi":"10.2139/ssrn.2088429","DOIUrl":"https://doi.org/10.2139/ssrn.2088429","url":null,"abstract":"Financial capital and fixed capital tend to flow in opposite directions between poor and rich countries. Why? What are the implications of such two-way capital flows for global trade imbalances and welfare in the long run? This paper introduces frictions into a standard two- country neoclassical growth model to explain the pattern of two-way capital flows between emerging economies (such as China) and the developed world (such as the United States). We show how underdeveloped credit markets in China can lead to abnormally high rate of returns to fixed capital but excessively low rate of returns to financial capital relative to the U.S., hence driving out household savings (financial capital) on the one hand while simultaneously attracting foreign direct investment (FDI) on the other. When calibrated to match China’s high marginal product of capital and low real interest rate, the model is able to account for the observed rising trends of China’s financial capital outflows and FDI inflows as well as its massive trade imbalances. Despite double heterogeneity in households and firms and a less than 100% capital depreciation rate, our two-country model is analytically tractable with closed form solutions at the micro level, which permits exact aggregation by the law of large numbers, so the general equilibrium of the model can be solved by standard log-linearization or higher order perturbation methods without the need of using numerical computation methods. Our model yield, among other things, three implications that stand in sharp contrast with the existing literature: (i) Global trade imbalances between emerging economies and the developed world are sustainable even in the steady state. (ii) There exists an immiserization effect of FDI --- namely, FDI is beneficial for the sourcing country but harmful to the recipient country under financial frictions. (iii) Our quantitative results cast doubts on the conventional wisdom that the \"saving glut\" of emerging economies is responsible for the low world interest rate.>","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117201272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A One-Step Test for the Presence of Multiple Cointegrating Vectors","authors":"M. Asali","doi":"10.2139/ssrn.2034253","DOIUrl":"https://doi.org/10.2139/ssrn.2034253","url":null,"abstract":"Based on the Johansen's approach for cointegration tests, we offer critical values to test for the existence and rank of cointegration between first-order integrated variables. In this single-step procedure, the cointegrating rank is equal to the number of instances in which the test statistics are less than the respective proposed critical values.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126878103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pitfalls in Backtesting Historical Simulation VAR Models","authors":"J. Escanciano, Pei Pei","doi":"10.2139/ssrn.2026537","DOIUrl":"https://doi.org/10.2139/ssrn.2026537","url":null,"abstract":"Historical Simulation (HS) and its variant, the Filtered Historical Simulation (FHS), are the most popular Value-at-Risk forecast methods at commercial banks. These forecast methods are traditionally evaluated by means of the unconditional backtest. This paper formally shows that the unconditional backtest is always inconsistent for backtesting HS and FHS models, with a power function that can be even smaller than the nominal level in large samples. Our findings have fundamental implications in the determination of market risk capital requirements, and also explain Monte Carlo and empirical findings in previous studies. We also propose a data-driven weighted backtest with good power properties to evaluate HS and FHS forecasts. A Monte Carlo study and an empirical application with three US stocks confirm our theoretical findings. The empirical application shows that multiplication factors computed under the current regulatory framework are downward biased, as they inherit the inconsistency of the unconditional backtest.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126934774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Natural Sciences Doctoral Attainment by Foreign Students at U.S. Universities","authors":"Robert V. Hamilton, C. McNeely, W. D. Perry","doi":"10.2139/ssrn.1999816","DOIUrl":"https://doi.org/10.2139/ssrn.1999816","url":null,"abstract":"The nearly sixty thousand foreign students who attained natural sciences doctorates at United States (U.S.) universities from 1980 to 2005 are conceptualized and analyzed as a case of highly-skilled migration. Multivariate regression analyses of tendencies for foreign students from over 147 countries and regions to attain doctorates in the natural sciences at U.S. universities indicated a two time-period model corresponding to Cold War and post-Cold War eras. Highly-skilled migration patterns for the purposes of natural sciences doctoral education at U.S. universities appear to have become depoliticized with the end of the Cold War, with U.S. universities acting as de facto recruiters of a globally diverse and talented population of foreign doctoral students for the U.S. scientific workforce. These results also suggest the need for an expanded longitudinal study of this phenomenon, addressing policy implications and measuring global science and technology doctoral education migration networks in light of changing political, social, and economic conditions across countries and regions.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132432529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GMM Estimation with Noncausal Instruments Under Rational Expectations","authors":"Matthijs Lof","doi":"10.2139/ssrn.1975775","DOIUrl":"https://doi.org/10.2139/ssrn.1975775","url":null,"abstract":"There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the GMM estimator is inconsistent, when the instruments are lags of noncausal variables. This paper argues that this inconsistency depends on distributional assumptions, that do not always hold. In particular under rational expectations, the GMM estimator is found to be consistent. This result is derived in a linear context and illustrated by simulation of a nonlinear asset pricing model.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131852522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Interrelationship Between Military Expenditure and External Debt: Patterns of Causation in Northern Africa Countries","authors":"Andreas G. Georgantopoulos, Anastasios Tsamis","doi":"10.22610/JEBS.V3I4.279","DOIUrl":"https://doi.org/10.22610/JEBS.V3I4.279","url":null,"abstract":"It is supported by academics and scholars that defense expenditure can significantly affect a country’s economic growth and in some cases it influences external debt having implications in various macroeconomic indicators. However, relevant empirical studies have produced contradictory evidence while the literature in this field remains relatively poor. In this spirit, this survey investigates the causal links between military expenditure and external debt for four emerging Northern Africa countries (i.e. Egypt, Tunisia, Algeria and Morocco) during the period 1988-2009. Empirical findings on the long-term relationship between the tested variables are based on cointegration test. The Granger Causality test results using Vector Auto Regression (VAR) estimates and the Error Correction Model imply that there is no dynamic causal link between military expenditure and external debt for Tunisia, Algeria and Morocco. On the other hand regarding Egypt, results imply that a strong unidirectional causality exists running from defense expenditure to external debt. Collectively, empirical calculations show that military burden do not have any significant impact on most Northern Africa countries. The only exception is the case of Egypt; empirical results show that military expenditure robustly affect the country’s external debt. These are the only findings provided from this study that validate the hypothesis that military burden may be important in determining the evolution of debt in developing countries.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126269637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cointegrated VARMA Models and Forecasting US Interest Rates","authors":"Christian Kascha, Carsten Trenkler","doi":"10.2139/ssrn.1957103","DOIUrl":"https://doi.org/10.2139/ssrn.1957103","url":null,"abstract":"We bring together some recent advances in the literature on vector autoregressive moving-average models creating a relatively simple specification and estimation strategy for the cointegrated case. We show that in the cointegrated case with fixed initial values there exists a so-called final moving representation which is usually simpler but not as parsimonious than the usual Echelon form. Furthermore, we proof that our specification strategy is consistent also in the case of cointegrated series. In order to show the potential usefulness of the method, we apply it to US interest rates and find that it generates forecasts superior to methods which do not allow for moving-average terms.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121200276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk Estimation for GARCH Processes with Heavy-Tailed Innovations","authors":"S. Prohl, Georgi K. Mitov, S. Rachev, F. Fabozzi, Aaron Kim","doi":"10.2139/ssrn.3312569","DOIUrl":"https://doi.org/10.2139/ssrn.3312569","url":null,"abstract":"The standard measures of risk such as RiskMetrics compute the Value-at-Risk as the maximum probability of loss of an investment over a certain period of time given a chosen confidence level. There are non-parametric and parametric methods to compute VaR. A non-parametric approach simulates the probability of distribution of future returns. The unconditional parametric approach assumes that location and scale components of the returns are constant and reduces the VaR problem to computing the γ-quantile of the returns for a given nominal level γ. A conditional approach assumes non-constant location and scale components. A standard implementation of this approach involves the ARCH/GARCH models. However, the popularity of this approach for risk management is restricted due to risk of misspecification of a GARCH model and of distributions for its conditional innovations. In this paper we focus on investigation of the parametric conditional approach under these both problems.<br><br>The empirical limitation of the assumption of a Gaussian distributions of portfolio returns has been well documented in the empirical research conducted over the last more than twenty years. It has been shown in several studies that returns exhibit high kurtosis and skewness that are incompatible with the normality assumptions (see, Fama (1965), Blattberg and Gonedes (1974), Marinelli et.al (2006)). A number of studies have showed how dramatically differ the estimates of VaR obtained under wrong assumptions with respect to the underlying return process (see, Beder, 1995).<br><br>Some recently proposed risk measure frameworks deal with these futures of high-frequency financial data. One natural approach to overcome these inconsistencies is to adopt the model with heavy-tailed innovations (Frey and McNeil 2000, Marinelli et al. 2004, Hang Chan et al. (2007)....).<br>A GARCH model with generalized Pareto distribution for the innovations was considered in Frey and McNeil (2000). They proposed a two-step procedure to compute conditional VaR for GARCH model. Hang Chan et al. (2007) work under different assumption than of Pareto distributed innovations, they suppose the model with heavy-tailed innovations. They compute VaR within the non-parametric framework. However, this paper does not provide a backtesting results. Marinelli et al. (2004) assume that returns are heavy-tailed, e.g., follow a stable law and provide comparison of the approach based on assumption of Paretian stable returns with the approach based on assumption of Gaussian returns and on the Extreme Value Theory. However, this paper does not consider the parametric method for GARCH model with heavy-tailed innovations.<br><br>Our work is closely related to the last two papers. Our contribution consist of numerical study which compares a backtesting procedure of alternative scheme to compute VaR. We consider the estimates for VaR and Expected Shortfalls (CVaR).","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125144190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Contribution of US Bond Demand to the US Bond Yield Conundrum of 2004 to 2007: An Empirical Investigation","authors":"Thomas Goda, Photis Lysandrou, C. Stewart","doi":"10.2139/ssrn.2411474","DOIUrl":"https://doi.org/10.2139/ssrn.2411474","url":null,"abstract":"Although the federal funds rate started rising from mid-2004 US long term rates continued to fall. A likely contributory factor to this conundrum was the contemporaneous increase in US bond demand. Using ARDL-based models, which accommodate structural breaks, this paper estimates the impact of demand on US bond yields in the conundrum period. This impact is shown to have been everywhere significantly negative. The fact that our model fully explains the bond yield conundrum gives support to the hypothesis that the US CDO market was rapidly expanded before 2007 chiefly to absorb the overspill of global demand for safe assets.","PeriodicalId":191102,"journal":{"name":"ERN: Time-Series Models (Multiple) (Topic)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123844999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}