scholarly journals Relationships between Copper Futures Markets from the Perspective of Jump Diffusion

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2268
Author(s):  
Xue Jin ◽  
Shiwei Zhou ◽  
Kedong Yin ◽  
Mingzhen Li
Keyword(s):  
New York ◽  
Futures Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Correlation Effect ◽  
Futures Contracts ◽  
Causality Test ◽  
Significance Level ◽  
Equilibrium Relationship ◽  
Integration Test

This paper analyzes the price correlation effect between domestic and foreign copper futures contracts. The VAR-BEKK-GARCH (1,1) spillover effect model and the BN-S class non-parametric model based on the jumping perspective are used. The co-integration test shows a long-term equilibrium relationship between the three copper futures markets, and the Granger causality test shows that copper futures contracts have significant two-way spillover effects between different periods in Shanghai for New York copper and unidirectional mean spillover effects for London copper. The BEKK model shows significant bidirectional fluctuation spillover effects between the futures contracts of the Shanghai, London, and New York copper markets before the stock market crash. After the crash, Shanghai and New York copper have significant one-way fluctuation spillover effects on London copper futures contracts. There are jumps within a single market, and the number of joint jumps between markets increases with the significance level.

scholarly journals Effect of Weather on Cryptocurrency Index: Evidences From Coinbase Index

2019 ◽  
Vol 10 (4) ◽  
pp. 108
Author(s):  
Chinnadurai Kathiravan ◽  
Murugesan Selvam ◽  
Balasundram Maniam ◽  
Sankaran Venkateswar ◽  
J. Gayathri ◽  
...  
Keyword(s):  
New York ◽  
Investment Decision ◽  
Efficient Market Hypothesis ◽  
Weather Factors ◽  
Causality Test ◽  
Federal Reserve Bank ◽  
Long Run ◽  
Integration Test ◽  
The Usa ◽  
Dynamic Relationships

This study proposes to investigate the dynamic relationships between the three weather factors (temperature, humidity, and wind speed) in New York City of USA and Coinbase Index from Federal Reserve Bank of St. Louis, in the USA. Statistical tools like Descriptive Statistics, Unit Root, Granger Causality Test and Johansen Co-Integration test were employed. This study clearly found that the temperature influenced the investors’ mood and their investment decision in respect of Cryptocurrency index (Coinbase Index) and also found that there was long run equilibrium between the sample variables during the study period. The results of study provided strong evidence against the Efficient Market Hypothesis (EMH).

Volatility Spillover between the KOSPI 200 Spot and Futures Markets Using the VECM-DCC-GARCH Model

2011 ◽  
Vol 19 (3) ◽  
pp. 233-249
Author(s):  
Sang Hoon Kang ◽  
Seong-Min Yoon
Keyword(s):  
Information Flow ◽  
Futures Markets ◽  
Price Discovery ◽  
Spillover Effects ◽  
Spot Market ◽  
Futures Market ◽  
Market Volatility ◽  
Futures Contracts ◽  
Volatility Spillover ◽  
Asymmetric Volatility

This paper investigates the price discovery, volatility spillover, and asymmetric volatility spillover effects between the KOSPI 200 market and its futures contracts market. The investigation was performed using the VECM-DCC-GARCH approach. In the case of returns, we found a significant unidirectional information flow from the futures market to the spot market; this implies that the KOSPI 200 futures market plays an important role on the price discovery in the spot market. In addition, we found a strong bi-directional casualty involving the volatility interaction between the spot and futures markets; this implies that market volatility originating in the spot market will influence the volatility of the futures market and vice versa. We also found strong asymmetric volatility spillover effects between the two markets.

Shared Prosperity (or Lack Thereof) in the Sharing Economy

2022 ◽  
Author(s):  
Mohammed Alyakoob ◽  
Mohammad S. Rahman
Keyword(s):  
New York ◽  
Employment Growth ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Sharing Economy ◽  
Economic Benefits ◽  
Percentage Point Increase ◽  
Point Increase ◽  
Job Growth ◽  
The Impact

This paper examines the potential economic spillover effects of a home sharing platform—Airbnb—on the growth of a complimentary local service—restaurants. By circumventing traditional land-use regulations and providing access to underutilized inventory, Airbnb attracts visitors to outlets that are not traditional tourist destinations. Although visitors generally bring significant spending power, it is unclear whether visitors use Airbnb only primarily for lodging and thus do not contribute to the adjacent economy. To evaluate this, we focus on the impact of Airbnb on restaurant employment growth across locales in New York City (NYC). Specifically, we focus on areas in NYC that did not attract a significant tourist volume prior to the emergence of a home-sharing service. Our results indicate a salient and economically significant positive spillover effect on restaurant job growth in an average NYC locality. A one-percentage-point increase in the intensity of Airbnb activity (Airbnb reviews per household) leads to approximately 1.7% restaurant employment growth. Since home-sharing visitors are lodging in areas that are not accustomed to tourists, we also investigate the demographic and market-structure-related heterogeneity of our results. Notably, restaurants in areas with a relatively high number of White residents disproportionately benefit from the economic spillover of Airbnb activity, whereas the impact in majority-Black areas is not statistically significant. Thus, policy makers must consider the heterogeneity in the potential economic benefits as they look to regulate home-sharing activities.

Price Discovery and Volatility Transmission in Currency Spot and Futures Markets in India: An Empirical Analysis

2017 ◽  
Vol 20 (4) ◽  
pp. 931-945 ◽  
Author(s):  
P. Sakthivel ◽  
Krishna Reddy Chittedi ◽  
Daniel Sakyi
Keyword(s):  
Causal Relationship ◽  
Futures Markets ◽  
Price Discovery ◽  
Spot Price ◽  
Futures Prices ◽  
Causality Test ◽  
United States Dollar ◽  
Indian Rupee ◽  
Volatility Transmission ◽  
Integration Test

This article investigates the price discovery and volatility transmission between currency spot and futures markets in India. Daily closing currency spot and futures prices of United States dollar/Indian Rupee (USD/INR), Japanese Yen/Indian Rupee (JPY/INR), Great Britain Pound/Indian Rupee (GBP/INR) and Euro/Indian Rupee (EUR/INR) from 1 March 2010 to 20 January 2015 were used. Both long-and short-run relationship as well as volatility transmission was investigated by the use of Engle Granger co-integration test, error correction mechanism, causality test and the bivariate GARCH model. The co-integration results proved that there is a long-run relationship between currency spot and futures prices. The study finds that there is a unidirectional causal relationship from currency spot to futures prices of JPY/INR, GBP/INR and EUR/INR. Further, results conclude the bidirectional causal relationship between USD/INR currency spot and futures prices. The result further shows that the spot market adjusts to new information faster than futures market suggesting that spot price leads the futures price and contributes largely to price discovery. Finally, the results show that there is unidirectional volatility transmission from currency spot to futures prices of JPY/INR, GBP/INR and EUR/INR and bidirectional spillover between currency spot and futures prices of USD/INR. Based on the findings, relevant policy recommendations are made.

scholarly journals Market integration of selected cotton markets in Haryana

2019 ◽  
Vol 38 (4) ◽  
Author(s):  
V. Mahesh ◽  
R.K. Grover ◽  
R.S. Geetha
Keyword(s):  
Granger Causality ◽  
Market Integration ◽  
Granger Causality Test ◽  
Causality Test ◽  
Domestic Markets ◽  
Price Series ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Integration Test ◽  
Adf Test

The present study aimed to paper the co-integration among the selected cotton markets in Haryana. The monthly data on prices of cotton were collected for the period from 2005-06 to 2016-17. The advanced econometric tools like ADF test, Johansen co-integration test and Granger Causality test were used to study market integration. The price series of commodity namely cotton in selected markets showed the consequences of unit root and were stationary at first difference. The long run equilibrium relationship among the selected markets indicated that these were integrated with each other. This implies that prices in domestic markets of Haryana move together in response to changes in the demand and supply and cost of a product. Granger Causality test resulted Dabwali market as lead cotton market because it influenced the prices of most of selected cotton markets.

Energizing Finance: The Energy Crisis, Oil Futures, and Neoliberal Narratives

2019 ◽  
Vol 21 (1) ◽  
pp. 2-37
Author(s):  
CALEB WELLUM
Keyword(s):  
United States ◽  
New York ◽  
Futures Markets ◽  
The United States ◽  
Futures Contracts ◽  
Energy Crisis ◽  
Futures Trading ◽  
Oil Futures ◽  
Viable Solution ◽  
The U.S

This article examines the origins and development of oil futures trading in the United States to demonstrate the important role that energy concerns played in the financialization of the U.S. economy in the 1970s and 1980s. The article contextualizes the emergence of oil futures contracts by narrating the longer history of U.S. futures markets and financialization. It also explores the halting development of oil futures contracts, and analyzes the three kinds of legitimating narratives that accompanied oil futures trading: reason, the primacy of price, and power. As a whole, the article argues that energy crisis discourse contributed significantly to the financialization of the U.S. economy by framing futures markets as the only viable solution to the energy crisis. The much-celebrated oil futures contracts on the New York Mercantile Exchange supported and marked the emergent power of financial thinking as the United States entered a neoliberal era.

Commodity Residential House Price Volatility Spillover Effects of Study — To Zhengzhou City Circle as an Example

2013 ◽  
Vol 838-841 ◽  
pp. 2981-2984
Author(s):  
Feng Lan ◽  
Rui Rui Zhang
Keyword(s):  
Housing Prices ◽  
House Price ◽  
Spillover Effect ◽  
Price Volatility ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Causality Test ◽  
Obvious Effect ◽  
Residential House ◽  
House Price Volatility

With the overall urban scale and the constant improvement of the level of economic development and regional urban cluster gradually formed, the interactive relationship between urban residential market is increasingly significant.Based on building the VAR model, this paper using Johansen cointegration relationship test, Granger causality test based on VEC model and variance decomposition method of the nine cities of zhengzhou city circle commodity residential house price volatility spillover effect carries on the empirical analysis, the results showed that: each city commodity housing prices keep long-term stable equilibrium relationship between, and has obvious effect, the interaction of zhengzhou and luoyang to other urban commodity residential house price fluctuation has significant guiding role.

Tax revenue and economic growth in developing country: an autoregressive distribution lags approach

2020 ◽  
Vol 7 (54) ◽  
pp. 205-217
Author(s):  
Mnaku Honest Maganya
Keyword(s):  
Economic Growth ◽  
Granger Causality ◽  
Testing Procedure ◽  
Gdp Growth ◽  
Bounds Testing ◽  
Causality Test ◽  
Significance Level ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
The Government

AbstractTanzania, like most other developing countries, faces numerous economic challenges in striving to achieve sustainable economic growth and development through taxation. In the literature, the debate on how effective taxes are as a tool for promoting economic growth and economic development remains inconclusive, as various research have reported mixed effects of tax on economic growth. This article investigates the effect of taxation on economic growth in Tanzania using the recently developed technique of autoregressive distributed lag model (ARDL) bounds testing procedure for the period from 1996 to 2019. Various preliminary tests were conducted including stationary tests as well as the pair-wise Granger causality test. According to the results obtained, domestic goods and services (TGS) taxes are positively related to GDP growth and are statistically significant at 1% level. Income taxes, on the other hand, were found to be negatively related to GDP growth and to be statistically significant at 5% level. The pair-wise Granger causality results indicated that there is bidirectional Granger causality between TGS and GDP growth at 1 % significance level. The government should aim at growing, nurturing and sustaining tax base to positively drive economic growth even further.

Effects of tourism development on economic growth: An empirical study of China based on both static and dynamic spatial Durbin models

2021 ◽  
pp. 135481662110211
Author(s):  
Honghong Liu ◽  
Ye Xiao ◽  
Bin Wang ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Spillover Effect ◽  
Tourism Development ◽  
Spillover Effects ◽  
Policy Implications ◽  
Long Term Effects ◽  
Spatial Spillover ◽  
Domestic Tourism ◽  
Inbound Tourism ◽  
Spatial Spillover Effect

This study applies the dynamic spatial Durbin model (SDM) to explore the direct and spillover effects of tourism development on economic growth from the perspective of domestic and inbound tourism. The results are compared with those from the static SDM. The results support the tourism-led-economic-growth hypothesis in China. Specifically, domestic tourism and inbound tourism play a significant role in stimulating local economic growth. However, the spatial spillover effect is limited to domestic tourism, and the spatial spillover effect of inbound tourism is not significant. Furthermore, the long-term effects are much greater than the short-term impact for both domestic and inbound tourism. Plausible explanations of these results are provided and policy implications are drawn.

scholarly journals Regional Disparity and Patients Mobility: Benefits and Spillover Effects of the Spatial Network Structure of the Health Services in China

2021 ◽  
Vol 18 (3) ◽  
pp. 1096
Author(s):  
Liping Fu ◽  
Kaibo Xu ◽  
Feng Liu ◽  
Lu Liang ◽  
Zhengmin Wang
Keyword(s):  
Health Economic ◽  
Health Services ◽  
Network Structure ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Health Economy ◽  
Spatial Network ◽  
Spatial Effects ◽  
Medical Resource ◽  
Medical Resources

Background: The distribution of medical resources in China is seriously imbalanced due to imbalanced economic development in the country; unbalanced distribution of medical resources makes patients try to seek better health services. Against this backdrop, this study aims to analyze the spatial network characteristics and spatial effects of China’s health economy, and then find evidence that affects patient mobility. Methods: Data for this study were drawn from the China Health Statistical Yearbooks and China Statistical Books. The gravitational value of China’s health spatial network was calculated to establish a network of gravitational relationships. The social network analysis method was used for centrality analysis and spillover effect analysis. Results: A gravity correlation matrix was constructed among provinces by calculating the gravitational value, indicating the spatial relationships of different provinces in the health economic network. Economically developed provinces, such as Shanghai and Jiangsu, are at the center of the health economic network (centrality degree = 93.333). These provinces also play a strong intermediary role in the network and have connections with other provinces. In the CONCOR analysis, 31 provinces are divided into four blocks. The spillover effect of the blocks indicates provinces with medical resource centers have beneficial effects, while provinces with insufficient resources have obvious spillover effects. Conclusion: There is a significant gap in the geographical distribution of medical resources, and the health economic spatial network structure needs to be improved. Most medical resources are concentrated in economically developed provinces, and these provinces’ positions in the health economic spatial network are becoming more centralized. By contrast, economically underdeveloped regions are at the edge of the network, causing patients to move to provinces with medical resource centers. There are health risks of the increasing pressure to seek medical treatment in developed provinces with abundant medical resources.

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