Volatility returns with vengeance: Financial markets vs. commodities

To assess how financial markets and commodities are inter-related, this paper introduces a ‘volatility surprise’ component into the asymmetric DCC with one exogenous variable (ADCCX) framework. We develop an econometric model in which returns and volatility allow to influence pairs of assets, and derive several case studies linking commodities to stocks, bonds and currencies from 1983 to 2013. The innovative feature of our model is that these volatility spillovers are modeled consistently within the correlation dynamics of the ADCCX. We find evidence that return and volatility spillovers do exist between commodity and financial markets and that in turn, their relative impact on each other is very substantial.     

Small fish in big ponds: Connections of green finance assets to commodity and sectoral stock markets

We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some ‘big pond’ markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some ‘big pond’ markets, e.g., commodities, while others negatively affect the connectedness.     

Risk–Return Profiles of Islamic Equities and Commodity Portfolios in Different Market Conditions

Motivated by the recent phenomenal growth in Islamic finance and the financialization of commodities, this study makes an initial attempt to investigate the risk–return profiles of optimized portfolios combining (a) Islamic equities with commodities and (b) conventional equities with commodities during the crises and noncrises periods. The findings tend to indicate that Islamic equity–commodity portfolios provide relatively higher diversification benefits than the conventional equity–commodity portfolios during the 1997 Asian Financial Crisis triggered by the financial sector compared to the 2008 global financial crisis triggered by the real housing sector. The findings further suggest that except for a few cases, commodities in general and gold in particular improve diversification benefits.     

Testing the Prebisch–Singer hypothesis since 1650: Evidence from panel techniques that allow for multiple breaks

In this paper, we re-examine two important aspects of the dynamics of relative primary commodity prices, namely the secular trend and the short run volatility. To do so, we employ 25 series, some of them starting as far back as 1650 and powerful panel data stationarity tests that allow for endogenous multiple structural breaks. Results show that all the series are stationary after allowing for endogenous multiple breaks. Test results on the Prebisch–Singer hypothesis, which states that relative commodity prices follow a downward secular trend, are mixed but with a majority of series showing negative trends. We also make a first attempt at identifying the potential drivers of the structural breaks. We end by investigating the dynamics of the volatility of the 25 relative primary commodity prices also allowing for endogenous multiple breaks. We describe the often time-varying volatility in commodity prices and show that it has increased in recent years.     

Dynamic spillovers between commodity and currency markets

In this study, we examine the dynamic link between returns and volatility of commodities and currency markets. Based on weekly data over the period from January 6, 1987 to July 22, 2014, we find the following empirical regularities. First, our results suggest that the information contents of gold, silver, platinum, and the CHF/USD and GBP/USD exchange rates can help improve forecast accuracy of returns and volatilities of palladium, crude oil and the EUR/CHF and GBP/USD exchange rates. Second, gold (CHF/USD) is the dominant commodity (currency) transmitter of return and volatility spillovers to the remaining assets in our model. Third, the analysis of dynamic spillovers shows time- and event-specific patterns. For instance, the dynamic spillover effects originating in gold and silver (platinum) returns and volatility intensified (degraded) in the period marked by the global financial crisis. After the global financial crisis, the net transmitting role of gold and silver (platinum) returns shocks weakened (strengthened), while the net transmitting role of gold, silver and platinum volatility shocks remained relatively high. Overall, our findings reveal that, while the static analysis clearly classifies the aforementioned variables into net transmitters and net receivers, the dynamic analysis denotes episodes wherein the role of transmitters and receivers of return (volatility) spillovers can be interrupted or even reversed. Hence, even if certain commonalities prevail in each identified category of commodities, such commonalities are time- and event-dependent.     

Multivariate FIAPARCH modelling of financial markets with dynamic correlations in times of crisis

This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.     

Volatility spillovers between oil prices and the stock market under structural breaks

This paper employs univariate and bivariate GARCH models to examine the volatility of oil prices and US stock market prices incorporating structural breaks using daily data from July 1, 1996 to June 30, 2013. We endogenously detect structural breaks using an iterated algorithm and incorporate this information in GARCH models to correctly estimate the volatility dynamics. We find no volatility spillover between oil prices and US stock market when structural breaks in variance are ignored in the model. However, after accounting for structural breaks in the model, we find strong volatility spillover between the two markets. We compute optimal portfolio weights and dynamic risk minimizing hedge ratios to highlight the significance of our empirical results which underscores the serious consequences of ignoring these structural breaks. Our findings are consistent with the notion of cross-market hedging and sharing of common information by financial market participants in these markets.     

Dissecting hedge funds' strategies

This paper dissects the dynamics of the hedge fund industry with four financial markets, including the equity market, commodities, currencies, and debt market by employing a large number of assets from these markets. We employ four main representative hedge fund strategy indices, and a cap-weighted global index to estimate an asymmetric dynamic conditional correlation (ADCC) GJR-GARCH model using daily data from April 2003 to May 2021. We break down the performance, riskiness, investing style, volatility, dynamic correlations, and shock transmissions of each hedge fund strategy thoroughly. Further, the impact of commodity futures basis on hedge funds' return is analyzed. Comparing the dynamic correlations during the 2008 global financial crisis (GFC) with COVID-19 pandemic reveals changing patterns in hedge funds' investing styles. There are strong and pervasive shock spillovers from hedge fund industry to other financial markets, especially to futures commodities. An increase in the futures basis of several commodities drives up hedge funds' performance. While hedge fund industry underperforms compared to equity market and commodities, the risk-reward measures show that hedge funds are superior to other markets, and safer than the bond market.     

Soft commodities and the global financial crisis: Implications for the economy,resources and institutions

Over the past decade, soft commodities have been subjected to increasing speculative price fluctuations. Following the 2008 financial crisis, most studies have highlighted causal relationships between price volatility, derivative and future markets for underlying financial assets as well as agricultural and mineral commodities. This article investigates the multifaceted effects of unrestrained financialization of the resources and goods markets and its implications for agricultural markets and soft commodities for purposes other than direct human consumption. We place a particular emphasis on the process of commodification of food and non-food crops and their use as green source of liquid fuels (i.e. soy, sugar cane, palm oil, jatropha, and canola). It is argued that speculation in financial markets has led to spillover effects across commodity and resource markets. More importantly, speculation and price volatility in the commodity markets has had a direct bearing on the resource markets and organization and appropriation of common-pool resources. The article sheds further light on the causal relationship between derivative markets, hedging techniques, financial yields and price volatility and spillover effects in the market for food and soft commodities.     

Industry characteristics and financial risk contagion

This article proposes a new measure of tail risk spillover: the conditional coexceedance (CCX), defined as the number of joint occurrences of extreme negative returns in an industry, conditional on an extreme negative return in the financial sector. The empirical application provides evidence of significant volatility and tail risk spillovers from the financial sector to many real sectors in the U.S. economy from 2001 to 2011. These spillovers increase in crisis periods. The CCX in a given sector is positively related to its amount of debt financing and negatively related to its valuation and investment. Therefore, real economy sectors—which require relatively high debt financing and whose value and investment activity are relatively lower—are prime candidates for stock price volatility and depreciation in the wake of a financial sector crisis. Evidence also suggests that the higher the industry’s degree of competition, the stronger the tail risk spillover from the financial sector.     

An analysis of commodity markets: What gain for investors?

In this paper we study whether the commodity futures market predicts the commodity spot market. Using historical daily data on four commodities—oil, gold, platinum, and silver—we find that they do. We then show how investors can use this information on the futures market to devise trading strategies and make profits. In particular, dynamic trading strategies based on a mean–variance investor framework produce somewhat different results compared with those based on technical trading rules. Dynamic trading strategies suggest that all commodities are profitable and profits are dependent on structural breaks. The most recent global financial crisis marked a period in which commodity profits were the weakest.     

Volatility spillovers across NFTs news attention and financial markets

The aim of this study is to investigate the volatility spillover connectedness between NFTs attention and financial markets. This paper firstly proposes a new direct proxy for the public’s attention in the NFT market: the non-fungible tokens attention index (NFTsAI), based on 590m news stories from the LexisNexis News & Business database and applies the historical decomposition to assess the historical variations of the NFTsAI. Then the empirical analysis is performed via a TVP-VAR volatility spillover connectedness model. The empirical results show that NFTsAI indicates NFT markets are dominated by cryptocurrency, DeFi, equity, bond, commodity, F.X. and gold markets. And NFT markets are volatility spillover receivers. In addition, NFT assets could impede financial contagion and have significant diversification benefits. Employing a panel pooled OLS regression model as a supplementary analysis and a GARCH-MIDAS model as a robustness test. This study reveals that NFTsAI has sufficient power to explain the return of NFT assets from a fixed effect perspective, and NFTsAI contains useful forecasting information for both short and long-term volatility of NFT markets, separately. The new NFTsAI and the empirical findings contain useful insights for risk-averse investors, portfolio managers, institutional investors, academics and financial policy regulators.     

Financialization in commodity markets: A passing trend or the new normal?

In this paper, we show that large inflows into commodity investments, a recent phenomenon known as financialization, has changed the behavior and dependence structure between commodities and the general stock market. The common perception is that the increase in comovements is the result of distressed investors selling both assets during the 2007–2009 financial crisis. We show that financial distress alone cannot explain the size and persistence of comovements. Instead, we argue that commodities have become an investment style for institutional investors. Given that institutional investors continue to target funds into commodities, we predict spillovers between commodities and the stock market to remain high in the future.     

Regime-switching measure of systemic financial stress

In this paper, I propose an approach to measuring systemic financial stress. In particular, abrupt and large changes in the volatility of financial variables that represent the dynamics of the US financial sector are modeled with a joint regime-switching process, distinguishing “low” and “high” volatility regimes. I find that the joint “high” volatility regime for the TED spread, return on the NYSE index, and capital-weighted CDS spread for large banks is closely related to periods of financial stress. This result suggests that the probability of the joint high volatility regime of these financial variables can be considered as a measure of systemic financial stress.     

基于贝叶斯MSSV-ST金融波动模型的股市特征及机制转移性研究

针对有偏厚尾金融随机波动模型难以刻画参数的动态时变性及结构突变的问题,设置偏态参数服从 Markov 转换过程,采用贝叶斯方法,构建带机制转移的有偏厚尾金融随机波动模型,考量股市不同波动状态间的机制转移性,捕捉股市间多重波动特性。通过设置先验分布,实现模型的贝叶斯推断,设计相应的马尔科夫链蒙特卡洛算法进行估计,并利用上证指数进行实证。结果表明：模型不仅刻画了股市的尖峰厚尾、杠杆效应等特性,发现收益率条件分布的偏度参数具有动态时变性,股市波动呈现出显著的机制转移特性,而且证实了若模型考虑波动的不同阶段性状态后,将降低持续性参数向上偏倚幅度的结论。     

本次经济危机主要大宗商品期货价格波动性研究

本文在分析本次次债危机以来主要大宗商品价格变动情况的基础上,建立了ARMA和E-GARCH模型及ARMA和TARCH模型来描述本轮经济周期中石油、铜、铝、黄金、大豆和玉米等大宗商品的期货价格收益序列的波动性特征。自相关分析发现不同商品期货市场的有效性略有差异,原油和铜市场更为有效;ARMA和非对称GARCH模型表明,主要商品收益波动均具有积聚效应,原油和铝收益波动具有杠杆效应,坏消息对原油收益波动的冲击大于好消息,好消息对铝收益波动的冲击大于坏消息。     

Impact of speculation and economic uncertainty on commodity markets

We examine the interactions between commodity futures returns and five driving factors (financial speculation, exchange rate, stock market dynamics, implied volatility for the US equity market, and economic policy uncertainty). Nonlinear causality tests are implemented after controlling for cointegration and conditional heteroscedasticity in the data over the period May 1990 – April 2014. Our results show strong evidence of unidirectional linear causality from commodity returns to excess speculation for the majority of the considered commodities, in particular for agriculture commodities. This evidence casts doubt on the claim that speculation is driving food prices. We also find unidirectional linear causality from energy futures markets to exchange rates and strong evidence of nonlinear causal dependence between commodity futures returns, on the one hand, and stock market returns and implied volatility, on the other hand. Overall, the new evidence found in this paper can be utilized for policy and investment decision-making.     

Futures Trading Activity and Commodity Cash Price Volatility

Abstract:   This paper examines the lead‐lag relationship between futures trading activity (volume and open interest) and cash price volatility for major agricultural commodities. Granger causality tests and generalized forecast error variance decompositions show that an unexpected increase in futures trading volume unidirectionally causes an increase in cash price volatility for most commodities. Likewise, there is a weak causal feedback between open interest and cash price volatility. These findings are generally consistent with the destabilizing effect of futures trading on agricultural commodity markets.     

Estimating Volatility Persistence in Oil Prices Under Structural Breaks

Policy makers and financial market participants are interested in knowing how shocks affect the volatility of oil prices over time. We accurately compute the volatility persistence by incorporating endogenously determined structural breaks into a GARCH model. Contrary to previous findings, we find that oil shocks dissipate very quickly but have a strong initial impact. Understanding this behavior is not only important for derivative valuation and hedging decisions but for broader financial markets and the overall economy, for which there are significant consequences.     

Price dynamics in refined petroleum spot and futures markets

This article characterizes the spot and futures price dynamics of two important physical commodities, gasoline and heating oil. Using a non-linear error correction model with time-varying volatility, we demonstrate many new results. Specifically, the convergence of spot and futures prices is asymmetric, non-linear, and volatility inducing. Moreover, spreads between spot and futures prices explain virtually all spot return volatility innovations for these two commodities, and spot returns are more volatile when spot prices exceed futures prices than when the reverse is true. Furthermore, there are volatility spillovers from futures to spot markets (but not the reverse), futures volatility shocks are more persistent than spot volatility shocks, and the convergence of spot and futures prices is asymmetric and non-linear. These results have important implications. In particular, since the theory of storage implies that spreasd vary with fundamental supply and demand factors, the strong relation between spreads and volatility suggests that these fundamentals — rather than trading induced noise — are the primary determinants of spot price volatility. The volatility spillovers, differences in volatility persistence, and lead-lag relations are consistent with the view that the futures market is the primary locus of informed trading in refined petroleum product markets. Finally, our finding that error correction processes may be non-linear, asymmetric, and volatility inducing suggests that traditional approaches to the study of time series dynamics of variables that follow a common stochastic trend that ignore these complexities may be mis-specified.