scholarly journals Selecting a Model for Forecasting

Econometrics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 26
Author(s):  
Jennifer L. Castle ◽  
Jurgen A. Doornik ◽  
David F. Hendry
Keyword(s):  
Structural Breaks ◽  
Simulation Experiment ◽  
Structural Break ◽  
Static Model ◽  
Forecast Period ◽  
Forecast Performance ◽  
Significance Level ◽  
Forecasting Models ◽  
Theoretical Results

We investigate forecasting in models that condition on variables for which future values are unknown. We consider the role of the significance level because it guides the binary decisions whether to include or exclude variables. The analysis is extended by allowing for a structural break, either in the first forecast period or just before. Theoretical results are derived for a three-variable static model, but generalized to include dynamics and many more variables in the simulation experiment. The results show that the trade-off for selecting variables in forecasting models in a stationary world, namely that variables should be retained if their noncentralities exceed unity, still applies in settings with structural breaks. This provides support for model selection at looser than conventional settings, albeit with many additional features explaining the forecast performance, and with the caveat that retaining irrelevant variables that are subject to location shifts can worsen forecast performance.

Clustering-Triggered Efficient Room Temperature Phosphorescence from Nonconventional Luminophores

2019 ◽  
Author(s):  
Shuyuan Zheng ◽  
Taiping Hu ◽  
Xin Bin ◽  
Yunzhong Wang ◽  
Yuanping Yi ◽  
...  
Keyword(s):  
Room Temperature ◽  
High Efficiency ◽  
Spin Orbit Coupling ◽  
Design Rationale ◽  
Emission Mechanism ◽  
Room Temperature Phosphorescence ◽  
Electronic Interactions ◽  
Energy Gaps ◽  
Theoretical Results

Pure organic room temperature phosphorescence (RTP) and luminescence from nonconventional luminophores have gained increasing attention. However, it remains challenging to achieve efficient RTP from unorthodox luminophores, on account of the unsophisticated understanding of the emission mechanism. Here we propose a strategy to realize efficient RTP in nonconventional luminophores through incorporation of lone pairs together with clustering and effective electronic interactions. The former promotes spin-orbit coupling and boost the consequent intersystem crossing, whereas the latter narrows energy gaps and stabilizes the triplets, thus synergistically affording remarkable RTP. Experimental and theoretical results of urea and its derivatives verify the design rationale. Remarkably, RTP from thiourea solids with unprecedentedly high efficiency of up to 24.5% is obtained. Further control experiments testify the crucial role of through-space delocalization on the emission. These results would spur the future fabrication of nonconventional phosphors, and moreover should advance understanding of the underlying emission mechanism.<br>

scholarly journals The epigenetic etiology of cardiovascular disease in a longitudinal Swedish twin study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Xueying Qin ◽  
Ida K. Karlsson ◽  
Yunzhang Wang ◽  
Xia Li ◽  
Nancy Pedersen ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Cvd Risk ◽  
Significance Level ◽  
Latent Trajectory ◽  
Lagged Effects ◽  
The Cross ◽  
Level 2 ◽  
Cardiometabolic Traits

Abstract Background Studies on DNA methylation have the potential to discover mechanisms of cardiovascular disease (CVD) risk. However, the role of DNA methylation in CVD etiology remains unclear. Results We performed an epigenome-wide association study (EWAS) on CVD in a longitudinal sample of Swedish twins (535 individuals). We selected CpGs reaching the Bonferroni-corrected significance level (2 $$\times$$ ×  10–7) or the top-ranked 20 CpGs with the lowest P values if they did not reach this significance level in EWAS analysis associated with non-stroke CVD, overall stroke, and ischemic stroke, respectively. We further applied a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to evaluate the cross-lagged effect between DNA methylation of these CpGs and cardiometabolic traits (blood lipids, blood pressure, and body mass index). Furthermore, mediation analysis was performed to evaluate whether the cross-lagged effects had causal impacts on CVD. In the EWAS models, none of the CpGs we selected reached the Bonferroni-corrected significance level. The ALT-SR model showed that DNA methylation levels were more likely to predict the subsequent level of cardiometabolic traits rather than the other way around (numbers of significant cross-lagged paths of methylation → trait/trait → methylation were 84/4, 45/6, 66/1 for the identified three CpG sets, respectively). Finally, we demonstrated significant indirect effects from DNA methylation on CVD mediated by cardiometabolic traits. Conclusions We present evidence for a directional association from DNA methylation on cardiometabolic traits and CVD, rather than the opposite, highlighting the role of epigenetics in CVD development.

scholarly journals Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4173
Author(s):  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
Crude Oil ◽  
Predictive Value ◽  
Realized Variance ◽  
International Spillovers ◽  
Forecasting Models ◽  
West Texas ◽  
Out Of Sample ◽  
One Year ◽  
Lasso Estimator

We use a dataset for the group of G7 countries and China to study the out-of-sample predictive value of uncertainty and its international spillovers for the realized variance of crude oil (West Texas Intermediate and Brent) over the sample period from 1996Q1 to 2020Q4. Using the Lasso estimator, we found evidence that uncertainty and international spillovers had predictive value for the realized variance at intermediate (two quarters) and long (one year) forecasting horizons in several of the forecasting models that we studied. This result holds also for upside (good) and downside (bad) variance, and irrespective of whether we used a recursive or a rolling estimation window. Our results have important implications for investors and policymakers.

Absence of the weekend effect and industry-style portfolios

2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman
Keyword(s):  
New York ◽  
Stock Market ◽  
Structural Breaks ◽  
Stock Exchange ◽  
Structural Break ◽  
Weekend Effect ◽  
Content Type ◽  
Market Portfolio ◽  
The Us ◽  
Using Data

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.

Testing Structural Break in the Relationship Between Exchange Rate and Macroeconomic Variables

2019 ◽  
Vol 23 (4) ◽  
pp. 442-453 ◽  
Author(s):  
Saidia Jeelani ◽  
Joity Tomar ◽  
Tapas Das ◽  
Seshanwita Das
Keyword(s):  
Exchange Rate ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Series Data ◽  
Ripple Effect ◽  
Macroeconomic Factors ◽  
Parameter Instability ◽  
Macroeconomic Variables ◽  
The Relationship

The article aims to study the relationship between those macroeconomic factors that the affect (INR/USD) exchange rate (ER). Time series data of 40 years on ER, GDP, inflation, interest rate (IR), FDI, money supply, trade balance (TB) and terms of trade (ToT) have been collected from the RBI website. The considered model has suggested that only inflation, TB and ToT have influenced the ER significantly during the study period. Other macroeconomic variables such as GDP, FDI and IR have not significantly influenced the ER during the study period. The model is robust and does not suffer from residual heteroscedasticity, autocorrelation and non-normality. Sometimes the relationship between ER and macroeconomic variables gets affected by major economic events. For example, the Southeast Asian crisis caused by currency depreciation in 1997 and sub-prime loan crisis of 2008 severely strained the national economies. Any global economic turmoil will affect different economic variables through ripple effect and this, in turn, will affect the ER of different economies differently. The article has also diagnosed whether there is any structural break or not in the model by applying Chow’s Breakpoint Test and have obtained multiple breaks between 2003 and 2009. The existence of structural breaks during 2003–2009 is explained by the fact that volume of crude oil imported by India is high and oil price rise led to a deficit in the TB alarmingly, which caused a structural break or parameter instability.

scholarly journals Regulation of the normalized rate of driven magnetic reconnection through shocked flux pileup

2021 ◽  
Vol 87 (3) ◽  
Author(s):  
Joseph Olson ◽  
Jan Egedal ◽  
Michael Clark ◽  
Douglass A. Endrizzi ◽  
Samuel Greess ◽  
...  
Keyword(s):  
Magnetic Reconnection ◽  
System Size ◽  
Force Balance ◽  
Absolute Rate ◽  
Reconnection Rate ◽  
Supersonic Plasma ◽  
Reconnection Layer ◽  
Inflow Conditions ◽  
Theoretical Results

Magnetic reconnection is explored on the Terrestrial Reconnection Experiment (TREX) for asymmetric inflow conditions and in a configuration where the absolute rate of reconnection is set by an external drive. Magnetic pileup enhances the upstream magnetic field of the high-density inflow, leading to an increased upstream Alfvén speed and helping to lower the normalized reconnection rate to values expected from theoretical consideration. In addition, a shock interface between the far upstream supersonic plasma inflow and the region of magnetic flux pileup is observed, important to the overall force balance of the system, thereby demonstrating the role of shock formation for configurations including a supersonically driven inflow. Despite the specialized geometry where a strong reconnection drive is applied from only one side of the reconnection layer, previous numerical and theoretical results remain robust and are shown to accurately predict the normalized rate of reconnection for the range of system sizes considered. This experimental rate of reconnection is dependent on system size, reaching values as high as 0.8 at the smallest normalized system size applied.

A revisit of the unemployment rate, interest rate, GDP growth and Inflation of Pakistan: Whether Structural break or unit root?

2021 ◽  
Vol 3 (2) ◽  
pp. 80-92
Author(s):  
Sara Muhammadullah ◽  
Amena Urooj ◽  
Faridoon Khan
Keyword(s):  
Interest Rate ◽  
Unemployment Rate ◽  
Unit Root ◽  
Structural Breaks ◽  
Inflation Rate ◽  
Structural Break ◽  
Unit Root Test ◽  
Unit Root Tests ◽  
Gdp Growth ◽  
Macroeconomic Indicators

The study investigates the query of structural break or unit root considering four macroeconomic indicators; unemployment rate, interest rate, GDP growth, and inflation rate of Pakistan. The previous studies create ambiguity regarding the stationarity and non-stationarity of these variables. We employ Zivot & Andrews (1992) unit root test and Step Indicator Saturation (SIS) method for multiple break detection in mean. GDP growth and inflation rate are stationary at level whereas unit root tests fail to reject the null hypothesis of the unemployment rate and interest rate at level. However, Zivot and Andrew unit root test with a single endogenous break indicates that the unemployment rate and interest rate are stationary at level with a single endogenous break. On the other hand, the SIS method reveals that the series are stationary with multiple structural breaks. It is inferred that it is inappropriate to take the first difference of the unemployment rate and interest rate to attain stationarity. The results of this study confirmed that there exist multiple breaks in the macroeconomic variables considered in the context of Pakistan.

scholarly journals Impact of Stakeholders on Implementation of Strategic Plans in Tanzania’s Public Sector

2017 ◽  
Vol 7 (4) ◽  
pp. 294
Author(s):  
Venance Shillingi Salum ◽  
Roselyn. W. Gakure ◽  
Romanus Othiambo
Keyword(s):  
Public Sector ◽  
Random Sampling ◽  
Implementation Process ◽  
Simple Random Sampling ◽  
Significance Level ◽  
Target Populations ◽  
Strategic Plans ◽  
Executive Agencies ◽  
The Impact

The study investigated the impact of stakeholders on implementation of strategic plans in Tanzania’s public sector. Organisations fail not due to bad formulation of strategies, but the execution of strategies is vital to their failure or demise; and hence implementation process remains a challenge towards achieving organisation objectives. The main objective of the study was to investigate the impact of stakeholders on implementation of Strategic Plans in public sector. Seven (7) executive agencies which made 26% of all 27 executive agencies in Tanzania were randomly drawn using simple random sampling. Then, stratified random sampling was used to obtain a sample size of one hundred eighty-eight (188) respondents which was 30% of the target populations (632 employees) in the headquarters of sampled executive agencies. The study found that there was weak positive relationship (R = 0.236) between role of stakeholders and execution of strategic plans; although was statistically significant at alpha = 0.000. Also,  = 0.056 at significance level of 0.05 indicated that, 5.6% of the total variations in implementation of strategic plans is influenced by stakeholders and 94.4% is contributed by other factors which were not considered in this study. The study concluded that stakeholders do influence implementation of strategic plans in public sector. In line with findings, the study recommended that management in public sector should pay more attention on stakeholders if they have to benefit from, otherwise may negatively influence implementation process of strategic plans in public sector.

scholarly journals Mathematical Development and Evaluation of Forecasting Models for Accuracy of Inflation in Developing Countries: A Case of Vietnam

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Nhu-Ty Nguyen ◽  
Thanh-Tuyen Tran
Keyword(s):  
Raw Materials ◽  
Arima Model ◽  
Consumer Price Index ◽  
Forecast Accuracy ◽  
Complex Problem ◽  
Forecast Performance ◽  
Forecasting Models ◽  
Out Of Sample ◽  
Forecasting Inflation ◽  
Using Data

Inflation is a key element of a national economy, and it is also a prominent and important issue influencing the whole economy in terms of marketing. This is a complex problem requiring a large investment of time and wisdom to attain positive results. Thus, appropriate tools for forecasting inflation variables are crucial significant for policy making. In this study, both clarified value calculation and use of a genetic algorithm to find the optimal parameters are adopted simultaneously to construct improved models: ARIMA, GM(1,1), Verhulst, DGM(1,1), and DGM(2,1) by using data of Vietnamese inflation output from January 2005 to November 2013. The MAPE, MSE, RMSE, and MAD are four criteria with which the various forecasting models results are compared. Moreover, to see whether differences exist, Friedman and Wilcoxon tests are applied. Both in-sample and out-of-sample forecast performance results show that the ARIMA model has highly accurate forecasting in Raw Materials Price (RMP) and Gold Price (GP), whereas, the calculated results of GM(1,1) and DGM(1,1) are suitable to forecast Consumer Price Index (CPI). Therefore, the ARIMA, GM(1,1), and DGM(1,1) can handle the forecast accuracy of the issue, and they are suitable in modeling and forecasting of inflation in the case of Vietnam.

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