RoWDI: rolling window detection of sleep intrusions in the awake brain using fMRI

2021 ◽  
Author(s):  
Govinda Raj Poudel ◽  
Stephanie Hawes ◽  
Carrie R. H. Innes ◽  
Nicholas Parsons ◽  
Sean P.A. Drummond ◽  
...  
Keyword(s):  
Rolling Window

Economic Institutions and Growth Nexus: The Role of Governance and Democratic Institutions—Evidence from Time Varying Parameters’ (TVPs) Models

2016 ◽  
Vol 55 (4I-II) ◽  
pp. 675-688
Author(s):  
Ghulam Murtaza ◽  
Muhammad Zahir Faridi
Keyword(s):  
Structural Changes ◽  
Jel Classification ◽  
Economic Institutions ◽  
Time Varying ◽  
Democratic Institutions ◽  
Main Hypothesis ◽  
Dynamic Relationship ◽  
Rolling Window

The present study has investigated the channels through which the linkage between economic institutions and growth is gauged, by addressing the main hypothesis of the study that whether quality of governance and democratic institutions set a stage for economic institutions to promote the long-term growth process in Pakistan. To test the hypothesis empirically, our study models the dynamic relationship between growth and economic institutions in a time varying framework in order to capture institutional developments and structural changes occurred in the economy of Pakistan over the years. Study articulates that, along with some customary specifics, the quality of government and democracy are the substantial factors that affect institutional quality and ultimately cause to promote growth in Pakistan. JEL Classification: O40; P16; C14; H10 Keywords: Economic Institutions, Growth, Governance and Democracy, Rolling Window Two-stage Least Squares, Pakistan

scholarly journals Time-Varying Convergences of Environmental Footprint Levels between European Countries

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1813
Author(s):  
Durmuş Çağrı Yıldırım ◽  
Seda Yıldırım ◽  
Seyfettin Erdoğan ◽  
Işıl Demirtaş ◽  
Gualter Couto ◽  
...  
Keyword(s):  
Ecological Footprint ◽  
Unit Root Test ◽  
Data Availability ◽  
European Countries ◽  
Time Varying ◽  
Cross Sectional ◽  
Ecological Footprints ◽  
Window Method ◽  
International Policies ◽  
Rolling Window

This study proposes the time-varying nonlinear panel unit root test to investigate the convergence of ecological foot prints between the EU and candidate countries. Sixteen European countries (such as Albania, Austria, Belgium, Denmark, France, Germany, Greece, Italy, Luxembourg, Netherlands, Poland, Portugal, Romania, Spain, Sweden and Turkey) and analysis periods are selected according to data availability. This study proposes a cross-sectional Panel KSS with Fourier to test the convergence of the ecological footprints. Then, we combine this methodology with the rolling window method to take into account the time-varying stationarity of series. This study evaluated sub-components of ecological footprints separately and provided more comprehensive findings for the ecological footprint. According to empirical findings, this study proves that convergence or divergence does not show continuity over time. On the other side, this study points out the presence of divergence draws attention when considering the properties of the sub-components in general. As a result, this study shows that international policies by EU countries are generally accepted as successful to reduce ecological footprint, but these are not sufficient as expected. In this point, it is suggested to keep national policies to support international policies in the long term.

Excess Volatility in Bitcoin: Extreme Value Volatility Estimation

2021 ◽  
pp. 227797522098768
Author(s):  
Parthajit Kayal ◽  
G. Balasubramanian
Keyword(s):  
Investment Decisions ◽  
Extreme Value ◽  
Time Varying ◽  
Price Changes ◽  
Volatility Estimation ◽  
Policy Choices ◽  
Rolling Window ◽  
Excess Volatility ◽  
High Volatility ◽  
Over Time

This article investigates the excess volatility in Bitcoin prices using an unbiased extreme value volatility estimator. We capture the time-varying nature of the excess volatility using bootstrap, multi-horizon, sub-sampling and rolling-window approaches. We observe that Bitcoin price changes are almost efficient. Although Bitcoin prices exhibit high volatility and show signs of excess volatility for a few periods, it is decreasing over time. After controlling for the outliers, we also notice that the Bitcoin market shows signs of increasing maturity. Overall, Bitcoin prices show a sign of increasing efficiency with decreasing volatility. Our findings have implications for investors making investment decisions and for regulators making policy choices.

scholarly journals Long Run Returns Predictability and Volatility with Moving Averages

Risks ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 105 ◽  
Author(s):  
Chia-Lin Chang ◽  
Jukka Ilomäki ◽  
Hannu Laurila ◽  
Michael McAleer
Keyword(s):  
Financial Performance ◽  
Stock Returns ◽  
Moving Average ◽  
Long Run ◽  
Returns Predictability ◽  
Rolling Window ◽  
Risk Free Rate ◽  
Data Frequency ◽  
Predictability Of Returns ◽  
Free Rate

This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The important issue regarding the predictability of returns is assessed. It is found that performance improves, on average, when the rolling window is expanded and the data frequency is low. However, when the size of the rolling window reaches three years, the frequency loses its significance and all frequencies considered produce similar financial performance. Therefore, the results support stock returns predictability in the long run. The procedure takes account of the issues of variable persistence as we use only returns in the analysis. Therefore, we use the performance of MA rules as an instrument for testing returns predictability in financial stock markets.

scholarly journals EVALUATING MEASURES OF MARKET RISK IN CIRCUMSTANCES OF GLOBAL FINANCIAL CRISIS – EMPIRICAL EVIDENCE FROM FIVE COUNTRIES

2013 ◽  
Vol 1 ◽  
pp. 75-81
Author(s):  
Ivica Terzić ◽  
Marko Milojević
Keyword(s):  
Value At Risk ◽  
Global Financial Crisis ◽  
Market Risk ◽  
Var Models ◽  
Risk Models ◽  
Historical Simulation ◽  
Rolling Window ◽  
Independence Properties ◽  
Window Approach ◽  
Metrics Model

The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.

The Relationship Between R&D Expenditures and Economic Growth ın OECD Countries With Different Causality Tests

2020 ◽  
pp. 107-118
Author(s):  
Gökhan Karhan
Keyword(s):  
Economic Growth ◽  
Research And Development ◽  
Oecd Countries ◽  
Causality Test ◽  
Panel Causality ◽  
Rolling Window ◽  
Causality Tests ◽  
Mathematical Techniques ◽  
Rolling Windows ◽  
The Relationship

In this chapter, the relationship between research and development (R&D) expenditures and economic growth was investigated with both Emirmahmutoğlu and Köse Causality test and the Dimitrescu and Hurlin Panel Causality test based on Rolling Windows Regression for the selected 19 OECD member countries for the period 1996-2015. The results concluded that for all panel there is a causality from economic growth to R&D expenditures. In this study, the relationship between variables was investigated using different mathematical techniques like rolling windows. According to the results of the Dimitrescu and Hurlin Panel Causality Test based on Rolling Window Regression, which is applied differently from other studies in the literature, there was a causality from economic growth to R&D expenditures in 2010. In 2011, there was causality from R&D expenditures to economic growth for all panels.

DOES THE CAUSAL RELATIONSHIP BETWEEN THE TWIN DEFICITS VARY OVER TIME? EVIDENCE FROM A BOOTSTRAP ROLLING WINDOW APPROACH

2020 ◽  
pp. 1-23
Author(s):  
TIE-YING LIU ◽  
ZI-CHEN GU
Keyword(s):  
World War Ii ◽  
Causal Relationship ◽  
Structural Breaks ◽  
Negative Impact ◽  
Positive Impact ◽  
Trade Deficit ◽  
Fiscal Deficit ◽  
Rolling Window ◽  
Oil Crisis ◽  
Window Approach

This paper uses the bootstrap rolling window approach to analyze the dynamic causal relationship between the fiscal deficit and the trade deficit in the US from 1901 to 2018. We find the origination and termination of each causality period by considering the structural breaks. The results show that the fiscal deficit had a positive impact on the trade deficit from 1946 to 1956, from 1982 to 1998, in 2000 and from 2002 to 2008, which is in accord with the results of the Mundell–Fleming model, while it had a negative impact from 1937 to 1945. The trade deficit had a positive impact on the fiscal deficit from 1940 to 1942, from 1959 to 1975 and from 1981 to 1994, mainly due to the World War II, oil crisis and trade friction with Japan. It means that the fiscal policy of American federal government can affect the external imbalance.

scholarly journals Critical slowing down associated with critical transition and risk of collapse in crypto-currency

2020 ◽  
Vol 7 (3) ◽  
pp. 191450 ◽  
Author(s):  
Chengyi Tu ◽  
Paolo D'Odorico ◽  
Samir Suweis
Keyword(s):  
Standard Deviation ◽  
Mean Field ◽  
Window Size ◽  
High Variability ◽  
Critical Slowing Down ◽  
Critical Transition ◽  
Slowing Down ◽  
Rolling Window ◽  
Stochastic Transition ◽  
Crypto Currency

The year 2017 saw the rise and fall of the crypto-currency market, followed by high variability in the price of all crypto-currencies. In this work, we study the abrupt transition in crypto-currency residuals, which is associated with the critical transition (the phenomenon of critical slowing down) or the stochastic transition phenomena. We find that, regardless of the specific crypto-currency or rolling window size, the autocorrelation always fluctuates around a high value, while the standard deviation increases monotonically. Therefore, while the autocorrelation does not display the signals of critical slowing down, the standard deviation can be used to anticipate critical or stochastic transitions. In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, which could have served as the early warning signals of two major price collapses that have happened in the following periods. We finally propose a mean-field phenomenological model for the price of crypto-currency to show how the use of the standard deviation of the residuals is a better leading indicator of the collapse in price than the time-series' autocorrelation. Our findings represent a first step towards a better diagnostic of the risk of critical transition in the price and/or volume of crypto-currencies.

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