Journal Article |
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12 months |
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Last month |
3 months |
12 months |
Total |
A copula–multifractal volatility hedging model for CSI 300 index futures |
0 |
0 |
0 |
11 |
0 |
0 |
0 |
95 |
A nonparametric approach to test for predictability |
0 |
0 |
0 |
8 |
1 |
1 |
1 |
34 |
Abnormal temperature and the cross-section of stock returns in China |
0 |
0 |
2 |
2 |
0 |
1 |
9 |
9 |
Analysis of efficiency for Shenzhen stock market based on multifractal detrended fluctuation analysis |
0 |
0 |
3 |
80 |
0 |
0 |
4 |
298 |
Analysis of efficiency for Shenzhen stock market: Evidence from the source of multifractality |
0 |
0 |
0 |
22 |
1 |
1 |
2 |
153 |
Analysis of market efficiency for the Shanghai stock market over time |
0 |
0 |
1 |
25 |
1 |
1 |
4 |
113 |
Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis |
0 |
0 |
1 |
23 |
1 |
3 |
7 |
88 |
Analysis of the efficiency of the Shanghai stock market: A volatility perspective |
0 |
0 |
0 |
9 |
1 |
1 |
1 |
54 |
Are crude oil spot and futures prices cointegrated? Not always! |
0 |
0 |
1 |
40 |
0 |
0 |
3 |
172 |
Asymmetric spillover of geopolitical risk and oil price volatility: A global perspective |
0 |
0 |
2 |
5 |
0 |
1 |
6 |
11 |
Auto-correlated behavior of WTI crude oil volatilities: A multiscale perspective |
0 |
0 |
0 |
4 |
1 |
1 |
1 |
49 |
Can GARCH-class models capture long memory in WTI crude oil markets? |
0 |
0 |
0 |
57 |
1 |
1 |
2 |
212 |
Can commodity prices forecast exchange rates? |
0 |
0 |
2 |
30 |
0 |
0 |
4 |
106 |
Climate risk exposure and the cross-section of Chinese stock returns |
0 |
0 |
2 |
4 |
0 |
0 |
9 |
15 |
Cloud cover and expected oil returns |
0 |
0 |
2 |
2 |
2 |
2 |
5 |
6 |
Commodity price changes and the predictability of economic policy uncertainty |
0 |
0 |
1 |
49 |
1 |
2 |
3 |
193 |
Cross-correlations between Chinese A-share and B-share markets |
0 |
1 |
1 |
23 |
0 |
1 |
2 |
93 |
Cross-correlations between spot and futures markets of nonferrous metals |
0 |
0 |
0 |
12 |
0 |
0 |
3 |
46 |
Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging |
0 |
1 |
2 |
24 |
0 |
1 |
8 |
131 |
Crude oil futures and the short-term price predictability of petroleum products |
1 |
1 |
4 |
4 |
1 |
1 |
8 |
8 |
Detrended fluctuation analysis on spot and futures markets of West Texas Intermediate crude oil |
0 |
0 |
0 |
12 |
0 |
2 |
2 |
88 |
Disentangling the determinants of real oil prices |
0 |
0 |
1 |
26 |
0 |
2 |
4 |
107 |
Dynamic portfolio allocation with time-varying jump risk |
0 |
0 |
1 |
23 |
0 |
1 |
3 |
75 |
Economic-environmental equilibrium-based bi-level dispatch strategy towards integrated electricity and natural gas systems |
0 |
0 |
0 |
7 |
0 |
0 |
1 |
18 |
Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis |
0 |
0 |
0 |
23 |
0 |
1 |
4 |
97 |
Energy prices and exchange rates of the U.S. dollar: Further evidence from linear and nonlinear causality analysis |
0 |
0 |
6 |
97 |
0 |
2 |
11 |
304 |
Exploiting the sentiments: A simple approach for improving cross hedging effectiveness |
0 |
0 |
1 |
1 |
0 |
1 |
4 |
4 |
Extreme risk spillovers between crude oil prices and the U.S. exchange rate: Evidence from oil-exporting and oil-importing countries |
0 |
0 |
0 |
13 |
0 |
0 |
2 |
41 |
Eye in outer space: satellite imageries of container ports can predict world stock returns |
1 |
1 |
18 |
23 |
2 |
4 |
54 |
69 |
Forecasting Bitcoin volatility: A new insight from the threshold regression model |
0 |
1 |
3 |
17 |
1 |
3 |
6 |
33 |
Forecasting U.S. real GDP using oil prices: A time-varying parameter MIDAS model |
0 |
0 |
1 |
31 |
1 |
3 |
8 |
190 |
Forecasting US stock market volatility: How to use international volatility information |
0 |
0 |
1 |
6 |
0 |
0 |
1 |
25 |
Forecasting aggregate market volatility: The role of good and bad uncertainties |
0 |
0 |
0 |
6 |
1 |
1 |
3 |
24 |
Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index |
0 |
0 |
1 |
3 |
1 |
1 |
3 |
8 |
Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors |
0 |
1 |
1 |
1 |
0 |
2 |
4 |
4 |
Forecasting commodity prices out-of-sample: Can technical indicators help? |
1 |
2 |
8 |
62 |
1 |
2 |
12 |
202 |
Forecasting crude oil futures market returns: A principal component analysis combination approach |
1 |
1 |
2 |
5 |
3 |
4 |
11 |
23 |
Forecasting crude oil market returns: Enhanced moving average technical indicators |
0 |
0 |
1 |
10 |
0 |
0 |
1 |
17 |
Forecasting crude oil market volatility using variable selection and common factor |
0 |
1 |
2 |
12 |
1 |
2 |
4 |
24 |
Forecasting crude oil market volatility: A Markov switching multifractal volatility approach |
0 |
1 |
5 |
48 |
0 |
4 |
11 |
220 |
Forecasting crude oil market volatility: A comprehensive look at uncertainty variables |
1 |
2 |
5 |
5 |
1 |
2 |
6 |
6 |
Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility |
0 |
0 |
1 |
3 |
0 |
0 |
6 |
17 |
Forecasting crude oil market volatility: Further evidence using GARCH-class models |
0 |
0 |
7 |
196 |
0 |
0 |
12 |
565 |
Forecasting crude oil price returns: Can nonlinearity help? |
0 |
0 |
0 |
1 |
1 |
2 |
2 |
5 |
Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors? |
1 |
3 |
12 |
67 |
2 |
5 |
23 |
191 |
Forecasting crude oil prices: A reduced-rank approach |
0 |
0 |
1 |
1 |
2 |
2 |
7 |
9 |
Forecasting crude oil prices: A scaled PCA approach |
4 |
4 |
16 |
64 |
7 |
8 |
34 |
178 |
Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models? |
0 |
1 |
10 |
177 |
1 |
3 |
22 |
569 |
Forecasting excess stock returns with crude oil market data |
0 |
0 |
0 |
33 |
0 |
0 |
2 |
145 |
Forecasting oil futures returns with news |
0 |
0 |
0 |
0 |
0 |
0 |
6 |
6 |
Forecasting realized volatility in a changing world: A dynamic model averaging approach |
1 |
2 |
6 |
59 |
2 |
4 |
16 |
210 |
Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach |
0 |
0 |
1 |
4 |
0 |
5 |
9 |
24 |
Forecasting stock market realized volatility: the role of global terrorist attacks |
0 |
0 |
2 |
3 |
1 |
1 |
3 |
7 |
Forecasting stock market volatility: The sum of the parts is more than the whole |
3 |
4 |
13 |
17 |
5 |
6 |
26 |
37 |
Forecasting stock returns: A predictor-constrained approach |
0 |
0 |
1 |
10 |
0 |
2 |
7 |
51 |
Forecasting stock returns: A time-dependent weighted least squares approach |
2 |
2 |
11 |
44 |
2 |
2 |
22 |
134 |
Forecasting the Chinese stock market volatility: A regression approach with a t-distributed error |
0 |
0 |
1 |
5 |
0 |
1 |
3 |
12 |
Forecasting the equity premium using weighted regressions: Does the jump variation help? |
0 |
0 |
0 |
0 |
0 |
2 |
3 |
3 |
Forecasting the real prices of crude oil under economic and statistical constraints |
0 |
0 |
0 |
21 |
0 |
0 |
1 |
148 |
Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models |
0 |
0 |
2 |
28 |
0 |
0 |
5 |
113 |
Forecasting the real prices of crude oil using robust regression models with regularization constraints |
0 |
1 |
1 |
20 |
1 |
3 |
7 |
84 |
Forecasting the real prices of crude oil: A robust weighted least squares approach |
0 |
0 |
0 |
7 |
0 |
0 |
5 |
20 |
Forecasting the real prices of crude oil: What is the role of parameter instability? |
0 |
0 |
2 |
13 |
0 |
1 |
5 |
24 |
Forecasting the stock risk premium: A new statistical constraint |
0 |
0 |
1 |
2 |
1 |
1 |
4 |
6 |
Forecasting the volatility of crude oil basis: Univariate models versus multivariate models |
0 |
2 |
4 |
4 |
0 |
3 |
6 |
6 |
Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint |
0 |
1 |
4 |
4 |
0 |
1 |
6 |
7 |
Futures Hedging in CSI 300 Markets: A Comparison Between Minimum-Variance and Maximum-Utility Frameworks |
0 |
0 |
0 |
9 |
1 |
1 |
1 |
22 |
Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks |
0 |
0 |
0 |
6 |
0 |
1 |
4 |
45 |
Geopolitical risk trends and crude oil price predictability |
0 |
0 |
5 |
28 |
1 |
1 |
18 |
75 |
Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility |
0 |
0 |
3 |
5 |
0 |
0 |
6 |
13 |
Good oil volatility, bad oil volatility, and stock return predictability |
0 |
1 |
2 |
6 |
2 |
4 |
12 |
26 |
Good volatility, bad volatility, and time series return predictability |
0 |
2 |
5 |
10 |
1 |
3 |
7 |
18 |
Hedging crude oil using refined product: A regime switching asymmetric DCC approach |
0 |
0 |
1 |
21 |
0 |
0 |
5 |
103 |
Hedging pressure momentum and the predictability of oil futures returns |
1 |
2 |
6 |
12 |
2 |
3 |
12 |
25 |
Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy? |
0 |
0 |
5 |
81 |
0 |
0 |
11 |
213 |
Heterogeneous beliefs and aggregate market volatility revisited: New evidence from China |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
18 |
How does corporate investment react to oil prices changes? Evidence from China |
0 |
1 |
2 |
20 |
0 |
2 |
10 |
61 |
Improving volatility prediction and option valuation using VIX information: A volatility spillover GARCH model |
0 |
0 |
4 |
28 |
3 |
3 |
11 |
60 |
Industry equi-correlation: A powerful predictor of stock returns |
0 |
0 |
1 |
24 |
1 |
2 |
9 |
65 |
Information connectedness of international crude oil futures: Evidence from SC, WTI, and Brent |
0 |
0 |
0 |
3 |
1 |
1 |
3 |
23 |
Information transmission between gold and financial assets: Mean, volatility, or risk spillovers? |
0 |
0 |
1 |
6 |
0 |
0 |
1 |
26 |
Intraday return predictability in China’s crude oil futures market: New evidence from a unique trading mechanism |
0 |
0 |
0 |
6 |
0 |
1 |
5 |
32 |
Investor attention and oil market volatility: Does economic policy uncertainty matter? |
0 |
0 |
1 |
11 |
0 |
0 |
3 |
46 |
Is WTI crude oil market becoming weakly efficient over time?: New evidence from multiscale analysis based on detrended fluctuation analysis |
0 |
0 |
1 |
59 |
0 |
1 |
5 |
206 |
It's not that important: The negligible effect of oil market uncertainty |
0 |
0 |
1 |
6 |
0 |
0 |
2 |
47 |
Limited attention of individual investors and stock performance: Evidence from the ChiNext market |
0 |
0 |
2 |
19 |
0 |
0 |
3 |
73 |
Long memory in energy futures markets: Further evidence |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
95 |
Macroeconomic fundamentals, jump dynamics and expected volatility |
0 |
0 |
1 |
5 |
1 |
1 |
4 |
23 |
Macroeconomic uncertainty and expected shortfall (and value at risk): a new dynamic semiparametric model |
0 |
1 |
2 |
8 |
0 |
2 |
7 |
24 |
Macroeconomic uncertainty, speculation, and energy futures returns: Evidence from a quantile regression |
0 |
0 |
0 |
11 |
1 |
1 |
4 |
24 |
Managerial ability and idiosyncratic volatility |
1 |
1 |
2 |
5 |
1 |
1 |
5 |
24 |
Modeling and forecasting stock return volatility using the HARGARCH model with VIX information |
1 |
1 |
5 |
5 |
2 |
4 |
11 |
11 |
Modelling and forecasting crude oil price volatility with climate policy uncertainty |
0 |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
Momentum of return predictability |
0 |
0 |
0 |
52 |
0 |
0 |
2 |
213 |
Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis |
0 |
0 |
0 |
11 |
0 |
0 |
3 |
83 |
Multifractal characterization of energy stocks in China: A multifractal detrended fluctuation analysis |
0 |
0 |
0 |
10 |
0 |
2 |
2 |
45 |
Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets |
0 |
0 |
0 |
5 |
0 |
0 |
2 |
36 |
Multifractal detrending moving average analysis on the US Dollar exchange rates |
0 |
0 |
0 |
17 |
0 |
0 |
0 |
90 |
Not all geopolitical shocks are alike: Identifying price dynamics in the crude oil market under tensions |
0 |
0 |
0 |
3 |
2 |
4 |
9 |
20 |
Oil and the short-term predictability of stock return volatility |
0 |
0 |
2 |
30 |
0 |
1 |
5 |
127 |
Oil implied volatility and expected stock returns along the worldwide supply chain |
0 |
0 |
0 |
4 |
0 |
2 |
7 |
16 |
Oil information uncertainty and aggregate market returns: A natural experiment based on satellite data |
0 |
0 |
1 |
1 |
0 |
0 |
5 |
5 |
Oil price increases and the predictability of equity premium |
0 |
3 |
4 |
29 |
0 |
4 |
10 |
115 |
Oil price shocks and Chinese economy revisited: New evidence from SVAR model with sign restrictions |
0 |
0 |
6 |
42 |
0 |
3 |
14 |
138 |
Oil price shocks and U.S. dollar exchange rates |
0 |
0 |
2 |
90 |
1 |
2 |
7 |
227 |
Oil price shocks and agricultural commodity prices |
0 |
0 |
2 |
176 |
1 |
3 |
13 |
519 |
Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries |
0 |
2 |
24 |
428 |
6 |
11 |
72 |
1,187 |
Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model |
0 |
0 |
4 |
92 |
0 |
2 |
15 |
290 |
Oil volatility risk and stock market volatility predictability: Evidence from G7 countries |
0 |
0 |
0 |
20 |
0 |
0 |
0 |
107 |
Out‐of‐sample volatility prediction: Rolling window, expanding window, or both? |
2 |
2 |
9 |
9 |
2 |
3 |
16 |
16 |
Portfolios with return and volatility prediction for the energy stock market |
0 |
0 |
2 |
9 |
1 |
2 |
8 |
22 |
Predictability of crude oil prices: An investor perspective |
0 |
0 |
0 |
7 |
0 |
0 |
7 |
84 |
Realized bipower variation, jump components, and option valuation |
0 |
0 |
0 |
9 |
0 |
0 |
2 |
31 |
Realized skewness and the short-term predictability for aggregate stock market volatility |
1 |
3 |
14 |
31 |
2 |
4 |
19 |
62 |
Revisiting the multifractality in stock returns and its modeling implications |
0 |
0 |
0 |
8 |
0 |
1 |
2 |
36 |
Risk spillovers between oil and stock markets: A VAR for VaR analysis |
0 |
0 |
5 |
27 |
3 |
3 |
12 |
122 |
Shrinking return forecasts |
0 |
1 |
1 |
3 |
0 |
2 |
3 |
7 |
Solving the Forecast Combination Puzzle Using Double Shrinkages |
0 |
0 |
0 |
0 |
0 |
1 |
3 |
3 |
The asymmetric effects of oil price changes on China’s exports: New evidence from a nonlinear autoregressive distributed lag model |
0 |
0 |
1 |
7 |
0 |
1 |
4 |
24 |
The dynamic spillover between carbon and energy markets: New evidence |
1 |
2 |
5 |
30 |
2 |
6 |
14 |
98 |
The effects of oil shocks on export duration of China |
0 |
0 |
0 |
5 |
0 |
0 |
0 |
38 |
The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns |
0 |
0 |
1 |
1 |
0 |
0 |
5 |
5 |
The predictability of iron ore futures prices: A product‐material lead–lag effect |
1 |
3 |
7 |
14 |
1 |
3 |
14 |
23 |
The predictive effect of risk aversion on oil returns under different market conditions |
0 |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach |
1 |
1 |
1 |
5 |
2 |
3 |
4 |
60 |
Time‐Varying Parameter Realized Volatility Models |
0 |
0 |
0 |
15 |
0 |
0 |
1 |
117 |
To jump or not to jump: momentum of jumps in crude oil price volatility prediction |
0 |
0 |
0 |
4 |
0 |
0 |
4 |
19 |
Uncertainty and the predictability of stock returns |
1 |
1 |
2 |
7 |
1 |
2 |
6 |
17 |
Understanding the multifractality in portfolio excess returns |
0 |
1 |
2 |
9 |
0 |
3 |
4 |
31 |
Volatility linkages between stock and commodity markets revisited: Industry perspective and portfolio implications |
0 |
0 |
0 |
8 |
0 |
1 |
6 |
22 |
Volatility spillover from the US to international stock markets: A heterogeneous volatility spillover GARCH model |
0 |
1 |
1 |
12 |
0 |
4 |
6 |
45 |
Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective |
0 |
0 |
1 |
29 |
2 |
3 |
8 |
139 |
What can we learn from the history of gasoline crack spreads?: Long memory, structural breaks and modeling implications |
0 |
0 |
2 |
22 |
1 |
1 |
8 |
133 |
What can we learn from the return predictability over the business cycle? |
0 |
0 |
1 |
8 |
1 |
1 |
4 |
22 |
What the investors need to know about forecasting oil futures return volatility |
0 |
0 |
0 |
11 |
0 |
0 |
2 |
86 |
Total Journal Articles |
26 |
62 |
327 |
3,362 |
93 |
217 |
972 |
11,917 |