Optimal time-varying tail risk network with a rolling window approach

2021 ◽  
pp. 126127
Author(s):  
Xingmin Zhang ◽  
Shuai Zhang
Keyword(s):  
Optimal Time ◽  
Time Varying ◽  
Tail Risk ◽  
Rolling Window ◽  
Window Approach

Financial Integration in Asia: A Systemic View on Currency Markets

2020 ◽  
Vol 19 (2) ◽  
pp. 41-58
Author(s):  
Dayong Zhang ◽  
Wanli Zhao ◽  
Fei Wu ◽  
Qiang Ji
Keyword(s):  
Financial Integration ◽  
Time Varying ◽  
Currency Markets ◽  
Vector Autoregressive ◽  
Republic Of China ◽  
Rolling Window ◽  
Causality Tests ◽  
The Republic ◽  
Window Approach ◽  
Systemic View

Using a systemic approach, this study investigates the time-varying linkages among currency markets of Japan, the People's Republic of China, the Republic of Korea, and the five core ASEAN economies to understand financial integration in Asia. We first construct a vector autoregressive model and use the Diebold and Yilmaz ( 2014 ) approach to quantitatively identify the connectedness within the system, accompanied by a rolling-window approach to allow for time-varying dynamics and pairwise Granger causality tests to check the robustness of our main results. We find that though systemic interconnectedness varies over time, the Singapore dollar is constantly a top net contributor, explaining most of the variation in East Asian currency markets.

Time-varying spillovers among first-tier housing markets in China

Urban Studies ◽  
2019 ◽  
Vol 57 (4) ◽  
pp. 844-864 ◽  
Author(s):  
Chien-Fu Chen ◽  
Shu-hen Chiang
Keyword(s):  
National Level ◽  
Housing Price ◽  
Housing Markets ◽  
Control Policy ◽  
Sufficient Evidence ◽  
Time Varying ◽  
Ripple Effects ◽  
Chinese Characteristics ◽  
Rolling Window ◽  
Window Approach

Numerous efforts have over the last few years been devoted to studying spillovers (ripple effects) among cities as a means of evaluating overheated housing markets. What seems to be lacking, however, is the application of a rolling-window approach to further explore time-varying spillovers in a timely manner in order to look more closely at a housing market with Chinese characteristics; for example, a market with rapidly increasing prices and a sequence of policy recommendations. By focusing on total, directional and net spillovers, and using 2000–2017 monthly housing price data across six Chinese cities, this study’s results indicate that time-varying spillovers provide a better understanding of the interactions among first-tier cities. It is interesting to note that, following the downside risk faced by the economy in 2014, the spillovers among cities have been abruptly transformed into those exhibiting bilateral co-movements based on high total spillovers and low net spillovers, and these results are also confirmed by the frequency dynamics of spillovers. Based on the above, there is sufficient evidence to conclude that the housing frenzies in China, which have become a national-level issue, deserve a more explicit macro-control policy in relation to real estate assets.

scholarly journals Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying Vector Autoregressions

2018 ◽  
Vol 53 (3) ◽  
pp. 1371-1390 ◽  
Author(s):  
Marco Valerio Geraci ◽  
Jean-Yves Gnabo
Keyword(s):  
Dynamic Network ◽  
Spillover Effects ◽  
Time Varying ◽  
Vector Autoregressions ◽  
Crisis Events ◽  
Time Varying Parameter ◽  
Rolling Window ◽  
The 2008 Financial Crisis ◽  
Window Approach

We propose a market-based framework that exploits time-varying parameter vector autoregressions to estimate the dynamic network of financial spillover effects. We apply it to financials in the Standard & Poor’s 500 index and estimate interconnectedness at the sectoral and institutional levels. At the sectoral level, we uncover two main events in terms of interconnectedness: the Long-Term Capital Management crisis and the 2008 financial crisis. After these crisis events, we find a gradual decrease in interconnectedness, not observable using the classical rolling-window approach. At the institutional level, our framework delivers more stable interconnectedness rankings than other comparable market-based measures.

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 Dynamic Optimization of a Subcritical Steam Power Plant under Time-Varying Power Load

2018 ◽  
Author(s):  
Chen Chen ◽  
George M. Bollas
Keyword(s):  
Power Plant ◽  
Dynamic Optimization ◽  
Electricity Market ◽  
Optimization Problems ◽  
Optimal Time ◽  
Time Varying ◽  
Power Demand ◽  
Test Bed ◽  
Simulation And Optimization ◽  
Power Load

The increasing variability in power plant load, in response to a wildly uncertain electricity market and the need to to mitigate CO2 emissions, lead power plant operators to explore advanced options for efficiency optimization. Model-based, system-scale dynamic simulation and optimization are useful tools in this effort, and the subject of the work presented here. In prior work, a dynamic model validated against steady-state data from a 605 MW subcritical power plant was presented. This power plant model is used as a test-bed for dynamic simulations, in which the coal load is regulated to satisfy a varying power demand. Plant-level control regulates plant load to match an anticipated trajectory of the power demand. The efficiency of the power plant operating at varying load is optimized through a supervisory control architecture that performs set point optimization on the regulatory controllers. Dynamic optimization problems are formulated to search for optimal time-varying input trajectories that satisfy operability and safety constraints during the transition between plant states. An improvement in time-averaged efficiency of up to 1.8% points is shown feasible with corresponding savings in coal consumption of 184.8 tons/day and carbon footprint decrease of 0.035 kg/kWh.

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.

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