Forecasting stock prices with commodity prices: New evidence from Feasible Quasi Generalized Least Squares (FQGLS) with non-linearities

The complexities in modern stock markets make it imperative to unravel the possible predictors of their future values. This paper thus provides insights into the predictability of stock prices of the BRICS countries with large dependence on commodities either for foreign exchange earnings or industrial while accounting for the role of asymmetries. Essentially, empirical evidence abound for the high volatility in world commodity markets, thus making us to determine if positive and negative changes in commodity prices predict stock prices differently. In addition, unlike the traditional forecast models, our choice of forecast models additionally addresses certain statistical features, including conditional heteroskedasticity, serial dependence, persistence and endogeneity, inherent in the predictors, which have the potential of causing estimation bias. In all, we find evidence in favour of the ability of commodity prices to predict stock prices of Brazil, Russia and South Africa. Also, both the in-sample and out-of-sample forecast performances of the predicted models support asymmetries in a number of commodity prices in each of these three countries. Our results are robust to different data samples and forecast horizons.     

Connectedness of commodity,exchange rate and categorical economic policy uncertainties — Evidence from China

This paper provides a fresh perspective to explore the network correlations among commodity, exchange rate, and categorical economic policy uncertainties (EPU) in China. We try to contribute to the literature by examining the spillover mechanism with a relatively novel connectedness network using the monthly data over the period between June 2006 and January 2021. Our results suggest that prior to the recession, China’s commodity price is subject to greater spillovers from the exchange rate than recessions. The domestic commodity prices are more sensitive to monetary policy uncertainty and fiscal policy uncertainty. The occurrence of COVID-19 revises the dominance in the system from monetary policy uncertainty and fiscal policy uncertainty to trade policy uncertainty.     

延迟退休、生育政策调整与中国经济增长

政府在放松生育政策的同时，配合退休政策的调整具有重要的现实意义。通过构建延迟退休和生育调整的理论模型发现：从劳动力增量看，延迟退休能够产生即期效应，而生育调整具有滞后效应，且两者导致的劳动力增量差距呈现先扩大后缩小的特点，节点在2031年；从社会总负担看，在实行延迟退休后，总抚养比迅速下降到一个低水平位置；从总产出看，同时实施延迟退休和放松生育政策，经济中潜在的福利损失最小；从产出增速看，放开生育的同时配合延迟退休，经济增速下降最慢；从人均产出看，放开生育的同时最好配合延迟退休，否则人均收入提升的效果不如政策不变时效果。     

Commodity prices and global economic activity

Commodity prices provide useful information about current and future global economic activity. First, we show that overall commodity prices indeed tend to comove with economic activity. Second, we try to extract the global demand factor(s) using many commodity prices. While commodity prices reflect both demand and supply factors, by relying on a wide variety of commodity prices, supply shocks can be filtered out as they tend to be commodity-specific idiosyncratic shocks except for widespread supply disruptions confined to a few historical periods. In this paper, we then show that factors extracted from commodity prices movement contain useful information to nowcast and forecast global GDP and industrial production.     

Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges.     

Co-movement between commodity and equity markets revisited—An application of the Thick Pen method

This paper analyses interdependence between the returns of specific energy and non-energy commodities and equities using (i) Thick Pen Measure of Association (TPMA) and (ii) Multi-Thickness Thick Pen Measure of Association (MTTPMA). We capture time-varying co-movement and co-movement across different time scales to analyse the short-term and long-term features of the time series using stationary data. Energy index futures show an increase in co-movement with equities since the start of the financialisation period. There are asymmetric effects in cross-scale co-movement between various commodities and equities. Weak co-movement between equity and specific commodity futures indicates diversification benefits for short-term and long-term investors.     

The risk spillover between China’s economic policy uncertainty and commodity markets: Evidence from frequency spillover and quantile connectedness approaches

Based on the frequency spillover method extended by Baruník and Křehlík (2018), we explore the risk spillover relationship between China’s economic policy uncertainty (CNEPU) and commodity futures in different frequency domains with daily settlement price data of 14 commodity futures in China. The results show that the risk spillover relationship between CNEPU and the commodity market mainly occurs in the short term. Quantile connectedness results show that economic policy uncertainty, which mainly plays the role of risk transmitter, is more closely related to the commodity market during the market boom and recession. Soybeans, soybean meal, and corn have shown high investment value in the process of market recovery, which is exposed to less risk spillover from policy uncertainty. Finally, the economic crisis with different characteristics will have specific impacts on asymmetric risk spillovers based on certain impact mechanisms.     

互联网金融影响了商业银行流动性创造吗?

选取2010-2019年中国98家商业银行年度数据就互联网金融对银行流动性创造的影响及其作用机制进行实证分析.研究发现:互联网金融通过分流银行存款及理财资金对银行盈利形成冲击,由此引发的"鲶鱼效应"会倒逼银行加大存贷期限错配来缓解盈利下降压力,从而促进银行流动性创造.相对于国有银行与城农商行,互联网金融对股份制银行流动性创造的促进力度更大.金融脱媒仅在P2P网络借贷对银行流动性创造的影响中承担着中介作用,但"第三方支付-金融脱媒-银行流动性创造"的传导渠道无效.银行业景气度提高会加剧互联网金融对流动性创造的促进作用,银行流动性创造存在顺周期倾向.     

Commodity financialization and funding liquidity in China

This study examines commodity financialization in China through commodity futures and stock market price co-movement, captured by a dynamic conditional correlation multivariate GARCH model (DCC-MGARCH). We find a dramatic increase in correlation after 2004; however, after 2010, the correlation decreases. We further investigate how funding liquidity affectes commodity financialization and find that its effect on the industrial sector is stronger than that on the agricultural sector, which reflects commodity financialization layering.     

Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes

This paper proposes a new network topology approach based on the STVAR model to identify asymmetric impacts of market conditions on multi-scale systemic risk spillovers of commodity markets. The results show that bearish market conditions enlarge low-frequency systemic risk spillovers in commodity markets, and bullish market conditions have more striking impacts on high-frequency systemic risk spillovers. Furthermore, the center of risk spillover networks varies across the market conditions and frequencies. Specifically, at the high-frequency level, sugar is the largest risk transmitter in bad regimes, and heating oil is in the center of the network in good regimes. At the intermediate frequency level, soybean becomes a more important risk transmitter in both regimes. In other cases, heating oil is the center of risk spillover networks.