Systemic financial risk early warning of financial market in China using Attention-LSTM model

We propose an Attention-LSTM neural network model to study the systemic risk early warning of China. Based on text mining, the network public opinion index is constructed and used as a training set to be incorporated into the early warning model to test the early warning effect. The results show that: (i) the network public opinion is the non-linear Granger causality of systemic risk. (ii) The Attention-LSTM neural network has strong generalization ability. Early warning effects have been significantly improved. (iii) Compared with the BP neural network model, the SVR model and the ARIMA model, the LSTM neural network early warning model has a higher accuracy rate, and its average prediction accuracy for systemic risk indicators has been improved over short, medium and long terms. When the attention mechanism is included in the LSTM, the Attention-LSTM neural network model is even more accurate in all the cases.     

China feels the heat: negative impacts of high temperatures on China's rice sector

We analysed a county‐level data set of single‐season rice yield and daily weather outcomes in China to examine the effects of temperature on China's rice sector. We found that rice yield exhibited highly nonlinear responses to temperature changes: rice yield increased with temperature up to 28°C and decreased sharply with higher temperatures. Holding current growing seasons and regions constant, average rice yield in China is projected to decrease by 10–19 per cent by 2050 and 11–33 per cent by 2070 due to future warming under the global climate models HadGEM2‐ES and NorESM1‐M. These results imply that future warming poses a major challenge for Chinese rice farmers and that the effectiveness of adaptations will depend on how well they reduce the negative temperature impacts on rice yield because of very hot days.     

一种基于预测值量测转换的卡尔曼滤波跟踪算法

在雷达目标跟踪中，系统量测信息通常在球坐标系下获得。为了采用经典卡尔曼滤波算法实现有效目标跟踪，通常采用量测转换方法将非线性量测信息转换到直角坐标系中。针对传统量测转换方法基于量测值计算转换误差统计特性而导致的估计结果有偏问题，提出了一种基于预测值的量测转换方法，并将其与卡尔曼滤波算法相结合，获得了一种基于预测值量测转换的卡尔曼滤波跟踪算法。仿真结果表明，与现有的基于量测转换的卡尔曼滤波算法相比，该算法能在不提高运算量的情况下有效改善目标跟踪效果，跟踪精度提升约20%。     

Risk factors in Australian bond returns

This study examines the risk factors in Australian bond returns. The study quantifies bond liquidity and estimates a liquidity risk factor in the Australian setting. We develop a three‐factor asset pricing framework that uses term, default and liquidity risk factors to explain the variation of Australian bond returns. Our findings corroborate the US evidence on the pervasiveness of these risk factors faced by bond investors. The three‐factor model developed in this study has practical applications when calculating the cost of debt, evaluating the performance of an active bond fund manager and hedging underlying risk in a bond portfolio.     

The expectations hypothesis of the term structure of interest rates: The Brazilian case revisited

This article tests the Expectations Hypothesis (EH) using Brazilian monthly data for bond yields spanning the 2000–2017 sample period and ranging in maturity from 3 months to 5 years. Three tests are examined: the first is based on interest rates spread and the other two are based on the forward rates. On balance our results suggest rejection of the EH throughout the maturity spectrum examined, and are broadly consistent with previous findings that a linear combination of forward rates provides a statistically significant prediction of bond excess returns.     

构建农村剩余劳动力有序转移长效机制探讨

实现农村剩余劳动力合理有序转移,是建设现代农业、解决"三农"问题的重要途径。目前,由于多种因素的制约,农村剩余劳动力的转移速度趋缓,影响了农民收入的增加。因此,必须从战略层面,进行全方位多角度的分析和探讨,破解农村剩余劳动力转移的制约因素,拓宽转移渠道,形成一个协调有效的转移机制和政策体系,加快农村剩余劳动力转移。     

The untold story of commodity futures in China

We investigate the behavior of commodity futures risk premia in China. In the presence of retail-dominance and barriers-to-entry, the term structure and momentum premia remain persistent, whereas hedging pressure, skewness, volatility, and liquidity premia are distorted by time-varying margins and strict position limits. Furthermore, open interest, currency, and inflation premia are sensitive to institutional settings. The observed premia cannot be attributed to common risks, sentiment, transactions costs, or data-snooping, but are related to liquidity, anchoring, and regulation-induced limits-to-arbitrage. We highlight the distinctive features of Chinese futures markets and assess the challenges posed to theories of commodity risk premia.     

Inferring information from the S&P 500, CBOE VIX,and CBOE SKEW indices

This paper compares the information extracted from the S&P 500, CBOE VIX, and CBOE SKEW indices for the S&P 500 index option pricing. Based on our empirical analysis, VIX is a very informative index for option prices. Whether adding the SKEW or the VIX term structure can improve the option pricing performance depends on the model we choose. Roughly speaking, the VIX term structure is informative for some models, while the SKEW is very noisy and does not contain much important information for option prices. This paper also extends Zhang et al. (2017, J Futures Markets, 37, 211–237) into three typical affine models.     

Can commodity futures risk factors predict economic growth?

This paper examines whether commodity futures risk factors can predict future economic growth. We test risk factors capturing various spot or term premia and find that only three factors capturing term premia on the basis-momentum, basis, and change in slope are robust predictors for future economic growth, especially for long horizons. Our findings highlight the importance of the term premia, rather than the spot premia on which the literature has mainly focused. Moreover, we find that possible explanations for predictability of commodity factors—the intertemporal asset pricing model and information diffusion explanation—are all inconsistent with our empirical results.     

Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison

We use several U.S. and euro‐area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time‐varying uncertainty. We obtain survey‐consistent distributions of future inflation at any horizon, both in the U.S. and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the United States, while mild de‐anchoring occurred in the euro area. As of our sample end, both areas appear to be almost equally anchored.