Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares

Contributing to the budding literature on how emotional and sentimental actions impact the performance of financial markets, this study examines the predictability of energy futures prices with investors’ sentiments. In particular, we examine which of the three (neutral, bear and bull) investors’ sentiments offer accurate forecast information on four energy futures prices. Using the predictability test proposed by Westerlund and Narayan (2015), we discover that all the forms of investors’ sentiments are significant predictors of the movements in energy futures prices. However, the bear sentiments outshine other variants in the forecast of crude oil futures prices, while the bull sentiments provide the most accurate forecast information for the remaining energy futures prices, namely heating oil, gasoline and natural gas. We also find this evidence consistent even when asymmetries are considered in the predictability models. Among other implications of these findings, investors in energy futures and portfolio managers are expected to consider often emotional perceptions in their portfolio constructions and the predictability of future gains.     

基于Morlet小波时频互相关的股指期货价格发现效率研究

本文采用Morlet小波时频互相关分析方法,从"时域"和"频域"两个维度检验了我国以及国际主要市场股指期货和现货价格序列的动态关联性,研究了股指期货价格发现效率的问题。研究表明,沪深300指数和股指期货在低频长周期范围内,呈现长时间高度相关、协同波动的特征;在高频短周期范围内,两者整体仍然具有协同波动特征,但时常出现短暂紊乱的情况,即期货与现货的交错引导现象。我国股指期货市场的价格发现效率较美国、英国成熟市场仍有较大差距,但强于日本。     

Evidence of information transmission across currency futures markets using frequency domain tests

In this article, I examine the returns and volatility spillovers in the currency futures market incorporating the recently developed frequency domain tests. Such analysis allows differentiating between permanent (long-run) and transitory (short-run) linkages among the currency futures markets by investigating the causality dynamics at low and high frequencies respectively. I detect significant informational linkages between USD, EUR, GBP and JPY futures contracts in the Indian currency futures market. Evidence of innovations from USD futures market to other markets is the most significant for returns spillover and for volatility spillover, EUR is found to be the most significant compared to other currency futures contracts. The results would have implications for the market participants and policymakers.     

Bivariate garch estimation of the optimal commodity futures Hedge

Six different commodities are examined using daily data over two futures contract periods. Cash and futures prices for all six commodities are found to be well described as martingales with near-integrated GARCH innovations. Bivariate GARCH models of cash and futures prices are estimated for the same six commodities. The optimal hedge ratio (OHR) is then calculated as a ratio of the conditional covariance between cash and futures to the conditional variance of futures. The estimated OHRs reveal that the standard assumption of a time-invariant OHR is inappropriate. For each commodity the estimated OHR path appears non-stationary, which has important implications for hedging strategies.     

Forecasting oil futures market volatility in a financialized world: Why speculative activities matter

We analyze the relation between volatility and speculative activities in the crude oil futures market and provide short-term forecasts accordingly. By incorporating trading volume and opening interest (speculative ratio) into the volatility dynamics, we document the subtle interaction between the two measures of which the volatility-averse behavior of speculative activities plays a considerable role in the market. Moreover, by accounting for structural changes, we find significant evidence that this behavior currently becomes weaker than in the past, which implies the oil futures market is less informative and/or less risk-averse in recent time period. Our forecasts based on these features perform very well under the predictive preferences that are consistent with the volatility-averse behavior in the oil futures market. We provide discussions and policy inferences.     

Predicting crude oil prices: Replication of the empirical results in “What do we learn from the price of crude oil?”

In addition to their theoretical analysis of the joint determination of oil futures prices and oil spot prices, Alquist and Kilian (Journal of Applied Econometrics, 2010, 25(4), 539–573) compare the out‐of‐sample accuracy of the random walk forecast with that of forecasts based on oil futures prices and other predictors. The results of my replication exercise are very similar to the original forecast accuracy results, but the relative accuracy of the random walk forecast and the futures‐based forecast changes when the sample is extended to August 2016, consistent with the results of several other recent studies by Kilian and co‐authors.     

黄金期货价格与我国黄金采选业股票价格关系的实证研究——以山东黄金股票价格为例

本文通过对我国黄金期货价格和相关股票价格之间关系的研究,试图把握其内在规律,为相关行业、企业、市场参与者和市场监管部门提供有价值的市场信息,从而可以正确认识我国目前黄金期货市场的价格发现功能,以及股票市场的运行效率。     

Dynamic spillover and connectedness between oil futures and European bonds

This paper examines the spillovers and connectedness between crude oil futures and European bond markets (EBMs) having different maturities. We also analyze the hedging effectiveness of crude oil futures-bond portfolios in tranquil and turbulent periods. Using the spillovers index of Diebold and Yilmaz (2012, 2014), we show evidence of time-varying spillovers between markets under investigations, which varies between 65% and 83%. Moreover, three-month, six-month, one-year, three-year and thirty-year bonds and crude oil futures are net receivers of risk from other markets, whereas the remaining bonds are net contributors of risk to the other markets. Crude oil futures receive more risk from long-term than short-term bonds. Moreover, the magnitude of risk transmission is low for the pre-crisis and economic recovery periods. Crude oil futures market contributes significantly to the risk of other markets during the oil crisis and Brexit period. A portfolio risk analysis shows that that most investments should be in oil rather than bonds (except the short-term bonds). The hedge ratio is sensitive to market conditions, where the cost of hedging increases during GFC and ESDC period. Finally, a crude oil futures-bond portfolio offers the best hedging effectiveness during the COVID-19 pandemic period.     

Excess co-movement of agricultural futures prices: Perspective from contagious investor sentiment

This study investigates the excess co-movement of agricultural futures prices from a new perspective of contagious investor sentiment. This study shows that contagious investor sentiment is a key determinant of excess co-movement of agricultural futures prices, by using contagious investor sentiment among different agricultural futures. Further, this study decomposes contagious investor sentiment into expected and unexpected contagious investor sentiment. Results show that both of them can positively affect excess co-movement of agricultural futures prices. More interestingly, expected contagious investor sentiment outperforms unexpected contagious investor sentiment in soybean 1 future, soymeal future, and strong wheat future. In general, the results of this study can provide strong support for the significant roles of contagious investor sentiment in asset pricing applications.     

OPEC news and predictability of oil futures returns and volatility: Evidence from a nonparametric causality-in-quantiles approach

This paper provides a novel perspective to the predictive ability of OPEC meeting dates and production announcements for (Brent Crude and West Texas Intermediate) oil futures market returns and GARCH-based volatility using a nonparametric quantile-based methodology. We show a nonlinear relationship between oil futures returns and OPEC-based predictors; hence, linear Granger causality tests are misspecified and the linear model results of non-predictability are unreliable. When the quantile-causality test is implemented, we observe that the impact of OPEC variables is restricted to Brent Crude futures only (with no effect observed for the WTI market). Specifically, OPEC production announcements, and meeting dates predict only lower quantiles of the conditional distribution of Brent futures market returns. While, predictability of volatility covers the majority of the quantile distribution, barring extreme ends.     

Pricing of Forward and Futures Contracts

There has long been substantial interest in understanding the relative pricing of forward and futures contracts. This has led to the development of two standard theories of forward and futures pricing, namely, the Cost-of-Carry and the Risk Premium (or Unbiased Expectations) hypotheses. These studies have modelled the relationship between spot and forward/futures prices either through a no-arbitrage condition or a general equilibrium setting. Relatively few studies in this area have considered the impact of stochastic trends in the data. With the emergence of non-stationarity and cointegration in recent years, more sophisticated models of futures/forward prices have been specified. This paper surveys the significant contributions made to the literature on the pricing of forward/futures contracts, and examines recent empirical studies pertaining to the estimation and testing of univariate and systems models of futures pricing.     

Cross‐hedging and forward‐contract pricing of electricity in the Pacific Northwest

This paper develops a linear regression model for using actively traded NYMEX natural gas futures as a cross‐hedge against electricity spot‐price risk in the Pacific Northwest and for pricing the forward contracts in the presence of temperature and hydro risks. Our approach comports with reality and provides power purchasers with an effective instrument through which they can hedge their electricity bets through natural gas futures. It also demonstrates the sharp month‐to‐month variations in the natural gas futures' optimal hedge ratios and hedge effectiveness. Finally, it finds significant risk premiums in the Pacific Northwest forward prices, supporting the hypothesis that forward‐contract buyers are relatively more risk‐averse than sellers. Copyright © 2011 John Wiley & Sons, Ltd.     

铝期货市场的信息传递及其定价能力的比较研究——基于上海与伦敦铝期货市场的实证检验

借助现代计量经济分析方法,对上海期货交易所和伦敦金属交易所铝期货价格之间的联系以及两个市场在价格发现中的贡献份额进行了实证研究。研究结果表明:两个市场铝期货价格之间存在协整关系,期货价格之间相互影响、相互作用,一个市场的价格信息将对另外一个相关市场的价格波动产生影响;伦敦期铝市场在国际定价中处于主导地位,上海市场的定价能力次之。     

Toward efficiency in the crude-oil market

The ‘official’ (OPEC) prices of crude oil before the collapse in the oil market in the mid-1980s can be interpreted as contract prices and analysed on the basis of the theory of futures (or forward) markets. This paper uses the generalized method of moments estimation technique to test for efficiency in the relationship between the official prices and the ex-post spot prices at the time of delivery. Efficiency is rejected for the sample period 1978–1985 as a whole, but evidence is found of improvements over time. Further, the GMM Wald and Hansen tests, although asymptotically equivalent, are shown to differ greatly when applied to a small sample of monthly oil price data.     

Are VIX futures prices predictable? An empirical investigation

This paper investigates whether volatility futures prices per se can be forecasted by studying the fast-growing VIX futures market. To this end, alternative model specifications are employed. Point and interval out-of-sample forecasts are constructed and evaluated under various statistical metrics. Next, the economic significance of the forecasts obtained is also assessed by performing trading strategies. Only weak evidence of statistically predictable patterns in the evolution of volatility futures prices is found. No trading strategy yields economically significant profits. Hence, the hypothesis that the VIX volatility futures market is informationally efficient cannot be rejected.     

A novel text-based framework for forecasting agricultural futures using massive online news headlines

The agricultural futures prices are generally considered difficult to forecast because the causes of fluctuations are incredibly complicated. We propose a text-based forecasting framework, which can effectively identify and quantify factors affecting agricultural futures based on massive online news headlines. A comprehensive list of influential factors can be formed using a text mining method called topic modeling. A new sentiment-analysis-based way is designed to quantify the factors such as the weather and policies that are important yet difficult to quantify. The proposed framework is empirically tested at forecasting soybean futures prices in the Chinese market. Testing was based on 9715 online news headlines from July 19, 2012 to July 9, 2018. The results show that the identified influential factors and sentiment-based variables are effective, and the proposed framework performs significantly better in medium-term and long-term forecasting than the benchmark model.     

Crude oil price forecasting based on internet concern using an extreme learning machine

The growing internet concern (IC) over the crude oil market and related events influences market trading, thus creating further instability within the oil market itself. We propose a modeling framework for analyzing the effects of IC on the oil market and for predicting the price volatility of crude oil’s futures market. This novel approach decomposes the original time series into intrinsic modes at different time scales using bivariate empirical mode decomposition (BEMD). The relationship between the oil price volatility and IC at an individual frequency is investigated. By utilizing decomposed intrinsic modes as specified characteristics, we also construct extreme learning machine (ELM) models with variant forecasting schemes. The experimental results illustrate that ELM models that incorporate intrinsic modes and IC outperform the baseline ELM and other benchmarks at distinct horizons. Having the power to improve the accuracy of baseline models, internet searching is a practical way of quantifying investor attention, which can help to predict short-run price fluctuations in the oil market.     

Real‐time forecast combinations for the oil price

Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real‐time variables. Mindful of the importance of Brent crude oil as a global price benchmark, we extend consideration to the North Sea‐based measure and update the evaluation sample to 2017:12. We model the oil price futures curve using a factor‐based Nelson–Siegel specification estimated in real time to fill in missing values for oil price futures in the raw data. We find that the combined forecasts for Brent are as effective as for other oil price measures. The extended sample using the oil price measures adopted by Baumeister and Kilian yields similar results to those reported in their paper. Also, the futures‐based model improves forecast accuracy at longer horizons.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

Multi-scale interactions between economic policy uncertainty and oil prices in time-frequency domains

Dynamic interactions between policy uncertainty and economic activity, including oil prices, have attracted increasing amounts of scholarly interest, but few studies have considered the inherent feature that the entire market is composed of different stakeholders operating in different time horizons. To fill this gap and address this issue, this paper proposes a multi-scale correlation framework. Specifically, we use the wavelet coherence method and scale-by-scale linear Granger causality tests to explore the co-movement and causality of pairs of economic policy uncertainty indices of G7 countries, China, Brazil, and Russia and West Texas Intermediate (WTI) oil prices. Our results show that the interaction between economic policy uncertainty and oil prices in the short-term is weak but gradually strengthens towards the long-term, especially when significant historical political or financial events occurred. Moreover, a consistent conclusion is that the interaction is negative in the medium-term, while it is positive in the long-term. Further, Granger causality tests at different time-scales show that no Granger causality from economic policy uncertainty to oil prices exists in the short-term for all sample countries, except the US, while there is a strong unidirectional or bidirectional Granger causality for all researched countries in the medium- and the long-term.