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Journal articles on the topic 'Exponential smooth transition autoregressive model'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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1

Buncic, Daniel. "Identification and Estimation Issues in Exponential Smooth Transition Autoregressive Models." Oxford Bulletin of Economics and Statistics 81, no. 3 (2018): 667–85. http://dx.doi.org/10.1111/obes.12264.

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2

Baharumshah, Ahmad Zubaidi, and Venus Khim-Sen Liew. "Forecasting Performance of Exponential Smooth Transition Autoregressive Exchange Rate Models." Open Economies Review 17, no. 2 (2006): 235–51. http://dx.doi.org/10.1007/s11079-006-6812-7.

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3

Yoon, Gawon. "Do real exchange rates really follow threshold autoregressive or exponential smooth transition autoregressive models?" Economic Modelling 27, no. 2 (2010): 605–12. http://dx.doi.org/10.1016/j.econmod.2009.11.015.

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4

Shintani, Mototsugu. "THE INF-TTEST FOR A UNIT ROOT AGAINST ASYMMETRIC EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE MODELS." Japanese Economic Review 64, no. 1 (2013): 3–15. http://dx.doi.org/10.1111/jere.12005.

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5

He, Qi-zhi. "Empirical Research on Repo Rates Based on Exponenti- al Smooth Transition Autoregressive Model." Journal of Service Science and Management 01, no. 01 (2008): 77–82. http://dx.doi.org/10.4236/jssm.2008.11007.

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6

Odelia, Maria, Di Asih I. Maruddani, and Hasbi Yasin. "PERAMALAN HARGA SAHAM DENGAN METODE LOGISTIC SMOOTH TRANSITION AUTOREGRESSIVE (LSTAR) (Studi Kasus pada Harga Saham Mingguan PT. Bank Mandiri Tbk Periode 03 Januari 2011 sampai 24 Desember 2018)." Jurnal Gaussian 9, no. 4 (2020): 391–401. http://dx.doi.org/10.14710/j.gauss.v9i4.29403.

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Series such as financial and economic data do not always form a linear model, so a nonlinear model is needed. One of the popular nonlinear models is the Smooth Transition Autoregressive (STAR). STAR has two possible suitable transition function such as logistic and exponential that need to be test to find the appropriate transition function. The purpose of writing this thesis is to determine the LSTAR model, then use the model to predict the stock price of PT Bank Mandiri. This study uses the data of the weekly stock price of PT Bank Mandiri from the period of January 3, 2011 to December 24, 2

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7

Yoon, Gawon. "Nonlinear mean-reversion to purchasing power parity: exponential smooth transition autoregressive models and stochastic unit root processes." Applied Economics 42, no. 4 (2010): 489–96. http://dx.doi.org/10.1080/00036840701604552.

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8

Otero, Jesús, and Jeremy Smith. "Response Surface Models for OLS and GLS Detrending-based Unit-root Tests in Nonlinear ESTAR Models." Stata Journal: Promoting communications on statistics and Stata 17, no. 3 (2017): 704–22. http://dx.doi.org/10.1177/1536867x1701700310.

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In this article, we calculate response surface models for a large range of quantiles of the Kapetanios, Shin, and Snell (2003, Journal of Econometrics 112: 359–379) and Kapetanios and Shin (2008, Economics Letters 100: 377–380) tests for the null hypothesis of a unit root against the alternative—that the series of interest follows a globally stationary exponential smooth transition autoregressive process. The response surface models allow estimation of finite-sample critical values and approximate p-values for different combinations of the number of observations, T, and the lag order in the te

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9

Cagli, Efe Caglar, Dilvin Taskin, and Pınar Evrim Mandaci. "The short- and long-run efficiency of energy, precious metals, and base metals markets: Evidence from the exponential smooth transition autoregressive models." Energy Economics 84 (October 2019): 104540. http://dx.doi.org/10.1016/j.eneco.2019.104540.

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10

Gregoriou, Andros. "Modelling non-linear behaviour of block price deviations when trades are executed outside the bid-ask quotes." Journal of Economic Studies 44, no. 2 (2017): 206–13. http://dx.doi.org/10.1108/jes-03-2016-0050.

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Purpose The purpose of this paper is to test and model non-linearities in block price deviations when they are executed outside the bid-ask quotes. The author conducts an empirical analysis on 662,312 transactions that were traded outside the bid-ask quotes in 2014 on the London Stock Exchange. Design/methodology/approach The tests reject the linearity hypothesis and the paper shows that the exponential smooth transition autoregressive model is capable of capturing the non-linear behaviour of block price misalignments. Findings The findings imply that when the deviation of block prices from th

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11

Ekhosuehi, Nosa. "Interval Forecast for Smooth Transition Autoregressive Model." AFRREV STECH: An International Journal of Science and Technology 5, no. 1 (2016): 27. http://dx.doi.org/10.4314/stech.v5i1.3.

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12

Ubilava, David, and C. Gustav Helmers. "Forecasting ENSO with a smooth transition autoregressive model." Environmental Modelling & Software 40 (February 2013): 181–90. http://dx.doi.org/10.1016/j.envsoft.2012.09.008.

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13

Kresnawati, Gayuh, Budi Warsito, and Abdul Hoyyi. "PERAMALAN INDEKS HARGA SAHAM GABUNGAN DENGAN METODE LOGISTIC SMOOTH TRANSITION AUTOREGRESSIVE (LSTAR)." Jurnal Gaussian 7, no. 1 (2018): 84–95. http://dx.doi.org/10.14710/j.gauss.v7i1.26638.

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Smooth Transition Autoregressive (STAR) Model is one of time series model used in case of data that has nonlinear tendency. STAR is an expansion of Autoregressive (AR) Model and can be used if the nonlinear test is accepted. If the transition function G(st,γ,c) is logistic, the method used is Logistic Smooth Transition Autoregressive (LSTAR). Weekly IHSG data in period of 3 January 2010 until 24 December 2017 has nonlinier tend and logistic transition function so it can be modeled with LSTAR . The result of this research with significance level of 5% is the LSTAR(1,1) model. The forecast of IH

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14

CHEN, Hao, Fangxing LI, and Yurong WANG. "Wind power forecasting based on outlier smooth transition autoregressive GARCH model." Journal of Modern Power Systems and Clean Energy 6, no. 3 (2016): 532–39. http://dx.doi.org/10.1007/s40565-016-0226-3.

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15

Hubner, Stefan, and Pavel Čížek. "Quantile-based smooth transition value at risk estimation." Econometrics Journal 22, no. 3 (2019): 241–61. http://dx.doi.org/10.1093/ectj/utz009.

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Summary Value at risk models are concerned with the estimation of conditional quantiles of a time series. Formally, these quantities are a function of conditional volatility and the respective quantile of the innovation distribution. The former is often subject to asymmetric dynamic behaviour, e.g., with respect to past shocks. In this paper, we propose a model in which conditional quantiles follow a generalised autoregressive process governed by two parameter regimes with their weights determined by a smooth transition function. We develop a two-step estimation procedure based on a sieve esti

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16

Skalin, Joakim, and Timo Teräsvirta. "MODELING ASYMMETRIES AND MOVING EQUILIBRIA IN UNEMPLOYMENT RATES." Macroeconomic Dynamics 6, no. 2 (2002): 202–41. http://dx.doi.org/10.1017/s1365100502031024.

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The paper discusses a simple univariate nonlinear parametric time-series model for unemployment rates, focusing on the asymmetry observed in many OECD unemployment series. The model is based on a standard logistic smooth transition autoregressive model for the first difference of unemployment, but it also includes a lagged level term. This model allows for asymmetric behavior by permitting “local” nonstationarity in a globally stable model. Linearity tests are performed for a number of quarterly, seasonally unadjusted, unemployment series from OECD countries, and linearity is rejected for a nu

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17

Zhang, Xiaolei, and Zhen He. "Integrated statistical and engineering process control based on smooth transition autoregressive model." Transactions of Tianjin University 19, no. 2 (2013): 147–56. http://dx.doi.org/10.1007/s12209-013-1892-0.

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18

Livingston, Glen, and Darfiana Nur. "Bayesian inference for smooth transition autoregressive (STAR) model: A prior sensitivity analysis." Communications in Statistics - Simulation and Computation 46, no. 7 (2017): 5440–61. http://dx.doi.org/10.1080/03610918.2016.1161794.

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19

Amaral, Luiz Felipe, Reinaldo Castro Souza, and Maxwell Stevenson. "A smooth transition periodic autoregressive (STPAR) model for short-term load forecasting." International Journal of Forecasting 24, no. 4 (2008): 603–15. http://dx.doi.org/10.1016/j.ijforecast.2008.08.006.

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20

Huang, Alex YiHou, and Wen-Cheng Hu. "Regime switching dynamics in credit default swaps: Evidence from smooth transition autoregressive model." Physica A: Statistical Mechanics and its Applications 391, no. 4 (2012): 1497–508. http://dx.doi.org/10.1016/j.physa.2011.08.008.

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21

CHEN, Hao, Fangxing LI, and Yurong WANG. "Erratum to: Wind power forecasting based on outlier smooth transition autoregressive GARCH model." Journal of Modern Power Systems and Clean Energy 7, no. 6 (2017): 1749. http://dx.doi.org/10.1007/s40565-016-0250-3.

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22

McAleer, Michael, and Marcelo C. Medeiros. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries." Journal of Econometrics 147, no. 1 (2008): 104–19. http://dx.doi.org/10.1016/j.jeconom.2008.09.032.

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23

Lei, Jieqi, Xuyuan Wang, Yiming Zhang, Lian Zhu, and Lin Zhang. "Policy and Law Assessment of COVID-19 Based on Smooth Transition Autoregressive Model." Complexity 2021 (January 18, 2021): 1–13. http://dx.doi.org/10.1155/2021/6659117.

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As of the end of October 2020, the cumulative number of confirmed cases of COVID-19 has exceeded 45 million and the cumulative number of deaths has exceeded 1.1 million all over the world. Faced with the fatal pandemic, countries around the world have taken various prevention and control measures. One of the important issues in epidemic prevention and control is the assessment of the prevention and control effectiveness. Changes in the time series of daily new confirmed cases can reflect the impact of policies in certain regions. In this paper, a smooth transition autoregressive (STAR) model i

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24

Lukicheva, I. A., and A. L. Kulikov. "Multi-model power system state estimation based on linear transition models." Vestnik IGEU, no. 1 (February 28, 2021): 31–40. http://dx.doi.org/10.17588/2072-2672.2021.1.031-040.

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Power system state estimation is one of the most important functions of power system control centers. In recent years, the complexity of power system state estimation has significantly increased due to the growing number of distributed, including renewable energy sources, electric vehicles, the demand response technologies, and the increased risk of cyber-attacks. Under these conditions, state estimation methods, which consider information about the time-correlation of the power system states have a great potential. The correlation is described by a transition model. The well-known state estim

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25

Hsu, Kuang-Chung, and Hui-Chu Chiang. "Nonlinear effects of monetary policy on stock returns in a smooth transition autoregressive model." Quarterly Review of Economics and Finance 51, no. 4 (2011): 339–49. http://dx.doi.org/10.1016/j.qref.2011.08.003.

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26

Silvennoinen, A., and T. Terasvirta. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model." Journal of Financial Econometrics 7, no. 4 (2009): 373–411. http://dx.doi.org/10.1093/jjfinec/nbp013.

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27

Umer, Usman M., Tuba Sevil, and Güven Sevil. "Forecasting performance of smooth transition autoregressive (STAR) model on travel and leisure stock index." Journal of Finance and Data Science 4, no. 2 (2018): 90–100. http://dx.doi.org/10.1016/j.jfds.2017.11.006.

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28

Umer, Usman M., Tuba Sevil, and Güven Sevil. "Forecasting performance of smooth transition autoregressive (STAR) model on travel and leisure stock index." Journal of Finance and Data Science 5, no. 1 (2019): 12–21. http://dx.doi.org/10.1016/j.jfds.2018.02.004.

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29

Adedokun, Adebayo, Philip Akanni Olomola, and James Temitope Dada. "Does non-linearity in exchange rate hold in Nigeria evidence from smooth transition autoregressive model." International Journal of Monetary Economics and Finance 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijmef.2020.10034068.

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30

Dada, James Temitope, Philip Akanni Olomola, and Adebayo Adedokun. "Does non-linearity in exchange rate hold in Nigeria evidence from smooth transition autoregressive model." International Journal of Monetary Economics and Finance 14, no. 2 (2021): 152. http://dx.doi.org/10.1504/ijmef.2021.114024.

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31

McMillan, David G. "Bubbles in the dividend–price ratio? Evidence from an asymmetric exponential smooth-transition model." Journal of Banking & Finance 31, no. 3 (2007): 787–804. http://dx.doi.org/10.1016/j.jbankfin.2006.02.006.

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32

Huang, Ying, Carl R. Chen, and Maximo Camacho. "Determinants of Japanese Yen interest rate swap spreads: Evidence from a smooth transition vector autoregressive model." Journal of Futures Markets 28, no. 1 (2007): 82–107. http://dx.doi.org/10.1002/fut.20281.

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33

Wai, Seuk, Mohd Tahir Ismail ., and Siok Kun Sek . "A Study of Intercept Adjusted Markov Switching Vector Autoregressive Model in Economic Time Series Data." Information Management and Business Review 5, no. 8 (2013): 379–84. http://dx.doi.org/10.22610/imbr.v5i8.1065.

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Commodity price always related to the movement of stock market index. However real economic time series data always exhibit nonlinear properties such as structural change, jumps or break in the series through time. Therefore, linear time series models are no longer suitable and Markov Switching Vector Autoregressive models which able to study the asymmetry and regime switching behavior of the data are used in the study. Intercept adjusted Markov Switching Vector Autoregressive (MSI-VAR) model is discuss and applied in the study to capture the smooth transition of the stock index changes from r

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34

McMillan, David G. "Non-linear cointegration and adjustment: an asymmetric exponential smooth-transition model for US interest rates." Empirical Economics 35, no. 3 (2008): 591–606. http://dx.doi.org/10.1007/s00181-007-0180-z.

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35

Xaba, Diteboho, Ntebogang Dinah Moroke, Johnson Arkaah, and Charlemagne Pooe. "A Comparative Study Of Stock Price Forecasting Using Nonlinear Models." Risk Governance and Control: Financial Markets and Institutions 7, no. 2 (2017): 7–17. http://dx.doi.org/10.22495/rgcv7i2art1.

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This study compared the in-sample forecasting accuracy of three forecasting nonlinear models namely: the Smooth Transition Regression (STR) model, the Threshold Autoregressive (TAR) model and the Markov-switching Autoregressive (MS-AR) model. Nonlinearity tests were used to confirm the validity of the assumptions of the study. The study used model selection criteria, SBC to select the optimal lag order and for the selection of appropriate models. The Mean Square Error (MSE), Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) served as the error measures in evaluating the forecasting a

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36

Babangida, Jamilu S., and Asad-Ul I. Khan. "Effect of Monetary Policy on the Nigerian Stock Market: A Smooth Transition Autoregressive Approach." Central Bank of Nigeria Journal of Applied Statistics 12, No. 1 (2021): 1–21. http://dx.doi.org/10.33429/cjas.12121.1/6.

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This paper examines the nonlinear effect of monetary policy decisions on the performance of the Nigerian Stock Exchange market, by employing the Smooth Transition Autoregressive (STAR) model on monthly data from 2013 M4 to 2019 M12 for All Share Index and monetary policy instrument. This study considers the two regimes characterizing the stock market, which are the lower regime (the bear market) and the upper regime (the bull market). The results show evidence of nonlinear effect of monetary policy on the stock exchange market. Monetary policy rate, money supply, lagged monetary policy rate an

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37

Li, Wenying, Yunhan Li, and Jeffrey H. Dorfman. "Dynamically Changing Cattle Market Linkages with Supply-Side-Controlled Transitions." Journal of Agricultural and Applied Economics 51, no. 3 (2019): 472–84. http://dx.doi.org/10.1017/aae.2019.14.

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AbstractCattle are costly to transport, which could lead to segmented regional cattle markets. The cointegration of cattle prices over regions has been of research interest for decades. This article investigates price cointegration between regional cattle markets in the United States and proposes a simple procedure for incorporating a flexible transition function into an economic indicator–controlled smooth transition autoregressive (ECON-STAR) model to evaluate market dynamics. The empirical results show that these markets have been highly integrated when excess supply exists, but when cattle

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38

Lopez, GREKOU Gahié. "Hypothesis of Twin Deficits in Cote d’Ivoire: The Nonlinear Effect Analysis with a Smooth Transition Autoregression Model (STAR)." Applied Economics and Finance 8, no. 1 (2020): 59. http://dx.doi.org/10.11114/aef.v8i1.5108.

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This paper tests the hypothesis of double deficit in Côte d'Ivoire in non-linear aid framework, using an autoregressive smooth transition model (STAR). The main results validate the hypothesis of double deficit in Côte d' Ivoire. The effect of current balance on budget balance is greater than budget balance on current balance. Moreover, the rapid effects of current account instability on fiscal balance reveal the lack of expectation by economic agents that leads to current account deterioration compared to the deterioration of budget balance. Thus, economic policies aimed at influencing the ef

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39

LIEW, VENUS KHIM-SEN, AHMAD ZUBAIDI BAHARUMSHAH, and KIAN-PING LIM. "ON SINGAPORE DOLLAR–U.S. DOLLAR AND PURCHASING POWER PARITY." Singapore Economic Review 49, no. 01 (2004): 71–84. http://dx.doi.org/10.1142/s0217590804000809.

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This study re-examines the validity of the relationship between the Singapore dollar–U.S. dollar exchange rate and relative prices using the latest econometric methodologies that account for non-linearity. Among others, this study finds Exponential Smooth Transition Autoregressive (ESTAR)-type non-linear mean-reverting adjustment process of the nominal Singapore dollar–U.S. dollar rate towards the consumer price index ratio. Unlike previous findings of a linear cointegration relationship between the nominal Singapore dollar–U.S. dollar exchange rate and consumer price index ratio, this study s

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40

Xiong, Weili, Lei Chen, Fei Liu, and Baoguo Xu. "Multiple Model Identification for a High Purity Distillation Column Process Based on EM Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/712682.

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Due to the strong nonlinearity and transition dynamics between different operating points of the high purity distillation column process, it is difficult to use a single model for modeling such a process. Therefore, the multiple model based approach is introduced for modeling the high purity distillation column plant under the framework of the expectation maximization (EM) algorithm. In this paper, autoregressive exogenous (ARX) models are adopted to construct the local models of this chemical process at different operating points, and the EM algorithm is used for identification of local model

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41

Güriş, Burak, and Gülşah Sedefoğlu. "UNEMPLOYMENT HYSTERESIS IN TURKEY: EVIDENCE FROM NONLINEAR UNIT ROOT TESTS WITH FOURIER FUNCTION." Metody Ilościowe w Badaniach Ekonomicznych 20, no. 3 (2019): 178–88. http://dx.doi.org/10.22630/mibe.2019.20.3.17.

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The purpose of the article is to give brief information about the development process of time series analysis and to test the validity of the unemployment hysteresis in Turkey for female and male graduates for the years from 1988 to 2013. For this purpose, Kapetanios et al. [2003], Sollis [2009] and Kruse [2011] nonlinear unit root tests are applied based on the smooth transition autoregressive (STAR) model. Besides, nonlinear unit root tests proposed by Christopoulos et al. [2010] and Guris [2018] are employed to model the structural breaks through Fourier approach and to model the nonlineari

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42

Li, Juan, Bo Jing, Hongde Dai, Zengjin Sheng, Xiaoxuan Jiao, and Xiaodong Liu. "A remaining useful life prediction method for airborne fuel pump after maintenance." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 15 (2019): 5660–73. http://dx.doi.org/10.1177/0954410019853995.

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Remaining useful life prediction is the core of condition-based maintenance under the technology framework of prognostic and health management. But the remaining useful life of airborne fuel pump after maintenance is difficult to predict because of the multi-stage noise and small data size. A new method is proposed to solve the remaining useful life prediction of repaired fuel pump. Firstly, an alternative smooth transition auto-regression model logistic smooth transition auto-regression or exponential smooth transition auto-regression is proposed to reduce the multi-stage noise. Secondly, ran

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43

Shah, Ismail, Hasnain Iftikhar, and Sajid Ali. "Modeling and Forecasting Medium-Term Electricity Consumption Using Component Estimation Technique." Forecasting 2, no. 2 (2020): 163–79. http://dx.doi.org/10.3390/forecast2020009.

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The increasing shortage of electricity in Pakistan disturbs almost all sectors of its economy. As, for accurate policy formulation, precise and efficient forecasts of electricity consumption are vital, this paper implements a forecasting procedure based on components estimation technique to forecast medium-term electricity consumption. To this end, the electricity consumption series is divided into two major components: deterministic and stochastic. For the estimation of deterministic component, we use parametric and nonparametric models. The stochastic component is modeled by using four diffe

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44

Jones, Paul M., and Walter Enders. "THE ASYMMETRIC EFFECTS OF UNCERTAINTY ON MACROECONOMIC ACTIVITY." Macroeconomic Dynamics 20, no. 5 (2016): 1219–46. http://dx.doi.org/10.1017/s1365100514000807.

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We estimate a number of macroeconomic variables as logistic smooth transition autoregressive (LSTAR) processes with uncertainty as the transition variable. The notion is that the effects of increases in uncertainty should not be symmetrical with the effects of decreases in uncertainty. Nonlinear estimation allows us to answer several interesting questions left unanswered by a linear model. For a number of important macroeconomic variables, we show that (i) a positive shock to uncertainty has a greater effect than a negative shock and (ii) the effect of the uncertainty shock is highly dependent

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45

Barboza, Gustavo, Laura Gavinelli, Valerien Pede, Alice Mazzucchelli, and Angelo Di Gregorio. "A contribution to the empirics of food price behavior: the case of rice price dynamics in Italy." British Food Journal 123, no. 1 (2020): 419–40. http://dx.doi.org/10.1108/bfj-12-2019-0937.

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PurposeThe purpose is to detect the nonlinearity wholesale rice price formation process in Italy in the 1995–2017 period.Design/methodology/approachA nonlinear smooth transition autoregressive (STAR)-type dynamics model is used.FindingsWholesale rice prices are significantly affected by variations in the international price of rice as well as variations in Arborio price.Research limitations/implicationsThe limitations include policy recommendations for the production and commercialization of rice in Italy.Practical implicationsUnderstanding rice pricing dynamics and nonlinearity behavior is pi

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46

Hale, Jacob, and Suzanna Long. "A Time Series Sustainability Assessment of a Partial Energy Portfolio Transition." Energies 14, no. 1 (2020): 141. http://dx.doi.org/10.3390/en14010141.

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Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainabili

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47

Rubino, Nicola. "IN- AND OUT-OF-SAMPLE PERFORMANCE OF NONLINEAR MODELS IN INTERNATIONAL PRICE DIFFERENTIAL FORECASTING IN A COMMODITY COUNTRY FRAMEWORK." EURASIAN JOURNAL OF ECONOMICS AND FINANCE 9, no. 2 (2021): 107–27. http://dx.doi.org/10.15604/ejef.2021.09.02.004.

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This paper presents an analysis of a group of small commodity-exporting countries' price differentials relative to the US dollar. Using unrestricted self-exciting threshold autoregressive models (SETAR), we evaluate the sixteen national Consumer Price Indexes (CPI) differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is estimated through calculation of mean absolute errors measures based on the monthly rolling window and recursive forecasts, and this estimation is extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive no

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48

Fonseca, Thais C. O., Vinicius S. Cerqueira, Helio S. Migon, and Christian A. C. Torres. "Evaluating the performance of degrees of freedom estimation in asymmetric GARCH models with t-student innovations." Brazilian Review of Econometrics 40, no. 2 (2021): 347–73. http://dx.doi.org/10.12660/bre.v40n22020.80292.

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This work investigates the effects of using the independent Jeffreys prior for the degrees of freedom parameter of a t-student model in the asymmetric generalised autoregressive conditional heteroskedasticity (GARCH) model. To capture asymmetry in the reaction to past shocks, smooth transition models are assumed for the variance. We adopt the fully Bayesian approach for inference, prediction and model selection We discuss problems related to the estimation of degrees of freedom in the Student-t model and propose a solution based on independent Jeffreys priors which correct problems in the like

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49

Bildirici, Melike, Nilgun Guler Bayazit, and Yasemen Ucan. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM." Energies 13, no. 11 (2020): 2980. http://dx.doi.org/10.3390/en13112980.

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Under the influence of the COVID-19 pandemic and the concurrent oil conflict between Russia and Saudi Arabia, oil prices have exhibited unusual and sudden changes. For this reason, the volatilities of the West Texas Intermediate (WTI), Brent and Dubai crude daily oil price data between 29 May 2006 and 31 March 2020 are analysed. Firstly, the presence of chaotic and nonlinear behaviour in the oil prices during the pandemic and the concurrent conflict is investigated by using the Shanon Entropy and Lyapunov exponent tests. The tests show that the oil prices exhibit chaotic behavior. Additionally

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Switzer, Lorne N., and Alan Picard. "The Cyclical Behaviour of the Small-Cap Premium: A Regime-Switching Approach." Journal of Business Accounting and Finance Perspectives 2, no. 1 (2020): 1. http://dx.doi.org/10.35995/jbafp2010006.

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Abstract:

While the average annual small-cap premia for the US and Canada are substantial over long horizons, there is considerable time variation of this premium within and across these countries. For the US, during expansions, the average annualized premium is a sizable 5.44%, while during recessions, there is a small-cap discount of 6.23%. The differentials are less pronounced in Canada. This paper investigates the hypothesis that the variation of the small-cap premium is related to macroeconomic and financial variables that can be captured by a nonlinear time series econometric model, i.e., the smoo

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