Economic significance of commodity return forecasts from the fractionally cointegrated VAR model

Dolatabadi, Sepideh; Narayan, Paresh Kumar; Nielsen, Morten Ørregaard; Xu, Ke

doi:10.1002/fut.21866

Cited by 53 publications

(42 citation statements)

References 45 publications

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“…Pandey and Vipul (2017) established long-run relationship between underlying and the futures prices of eight commodities and concluded that price efficiency originates from futures price, while information content in each commodity is different. Dolatabadi et al (2018) examine the long-run relationship between 17 commodities for the period from 1983 to 2012. The study establishes a long-run relationship among the commodities but do not examine the existence of structural break within the period of the study.…”

Section: Introductionmentioning

confidence: 99%

Long-term relationship of crude palm oil commodity pricing under structural break

Salami

Haron

2018

JCMS

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Purpose-The purpose of this paper is to examine the pricing efficiency of the Malaysian crude palm oil (CPO) market before and after the structural break. This study uses the daily closing price of CPO and CPO futures (CPO-F) for the period ranging from June 2009 to August 2016 while taking structural breaks into account. Design/methodology/approach-In this study, symmetric and asymmetric long-run relationship model are employed, such as the Johansen cointegration, VECM, TAR and M-TAR models, to examine the impact of structural breaks on the pricing efficiency of the Malaysian CPO market. Findings-This finding establish that Malaysian CPO price is efficient before and after the structural break. The consistent efficiency of the Malaysian CPO market supports the trading of the CPO-F in Globex and the use of Malaysian CPO pricing as the reference price. This study establishes that a structural break in the Malaysian CPO price series does not affect the pricing efficiency of the market. Research limitations/implications-This study shows that using Malaysian CPO price as a reference price is sustainable even in the event of a structural break. Therefore, market participants in the Malaysian CPO market have less to worry about the CPO price as it supports the weak form of efficiency. Price deviation in the short run may not lead to arbitrage profit as transaction cost may not be covered. Practical implications-This study implies that if there is distortion in the price due to shocks, both manufacturers and producers need to hedge their positions in the futures market (subject to their positions in the underlying market). By entering into the futures market, pricing is locked in advance; hence, price risk is eliminated. Such a distortion could also affect the efficiency of the CPO price, therefore this study also addresses the issue of efficiency of the local CPO market. Originality/value-Previous studies on Malaysian CPO pricing efficiency did not take the effect of structural break into consideration, making it difficult for these studies to show consistency in the efficiency of the Malaysian CPO market.

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Section: Introductionmentioning

confidence: 99%

Long-term relationship of crude palm oil commodity pricing under structural break

Salami

Haron

2018

JCMS

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“…In what follows, we employ the permanent‐transitory (PT) decomposition of Gonzalo and Granger (1995) to identify the common permanent component of each pair of variances. To facilitate the PT decomposition, we follow Dolatabadi, Narayan, Nielsen, and Xu (2018) by constructing a fully specified framework which accommodates long‐run and short‐run effects in a system containing fractionally cointegrated variables. Such a framework is afforded by the fractionally cointegrated vector autoregressive (FCVAR) model of Johansen (2008) and Johansen and Nielsen (2012) as follows

Δ^{d} (X_{t} - μ) = α β' Δ^{d - b} L_{b} (X_{t} - μ) + {falsefalse}_{\sum}^{c = 1} Γ_{c} Δ^{d} L_{b}^{c} (X_{t} - μ) + ε_{t}

where

X_{t}

denotes the pair of variances under analysis,

Δ^{d}

and

L_{b}

, respectively represent the fractional difference operator and the fractional lag operator.…”

Section: Resultsmentioning

confidence: 99%

Return predictability of variance differences: A fractionally cointegrated approach

Izzeldin

Yao

2020

Journal of Futures Markets

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This paper examines the fractional cointegration between downside (upside) components of realized and implied variances. A positive association is found between the strength of their cofractional relation and the return predictability of their differences. That association is established via the common longmemory component of the variances that are fractionally cointegrated, which represents the volatility-of-volatility factor that determines the variance premium. Our results indicate that market fears play a critical role not only in driving the long-run equilibrium relationship between implied-realized variances but also in understanding the return predictability. A simulation study further verifies these claims. K E Y W O R D S fractional cointegration, return predictability, variance risk premium J E L C L A S S I F I C A T I O N C14; C32; C51 | INTRODUCTIONNumerous empirical studies suggest that, unlike the variance, the variance risk premium (VRP) carries nontrivial predictive power for aggregate stock market returns over quarterly to annual horizons, where the degree of return predictability is greater than that afforded by more conventional predictors, see, Bollerslev, Tauchen, and Zhou (2009), Drechsler and Yaron (2010), Bollerslev, Marrone, Xu, and Zhou (2014), and Bali and Zhou (2016), among others. Those studies also provide strong evidence that much of the predictability implicit in the VRP may be attributed to its close relation with macroeconomic uncertainty and aggregate risk aversion.The VRP is formally defined as the wedge between option-implied and realized variances. It is measured as the difference between (the square of) the CBOE VIX index and the statistical expectation of the future return variation. In Bollerslev et al. (2009), Drechsler andYaron (2010) and Bollerslev, Sizova, and Tauchen (2012), the return predictability of the VRP is investigated using a self-contained general equilibrium model. This is in the spirit of the long-run risks (LRR) model pioneered by Bansal and Yaron (2004). Specifically, Bollerslev et al. (2009) andBollerslev et al. (2012) extend the LRR model by allowing the time-varying volatility-of-volatility (vol-of-vol) within the economy to be generated by its own stochastic process. They further show that the difference between the risk-neutral and the objective expectations of return variation isolates the vol-of-vol factor, which then serves as the sole source of the true VRP. The VRP, therefore, displays good predictive power for future returns in cases where the vol-of-vol plays a more dominant role in determining variation in the equity premium. A direct link between the VRP and the vol-of-vol is also demonstrated in a purely probabilistic model introduced by Barndorff-Nielsen and Veraart (2013). U D . The SJ and IVA are, respectively, measured as the difference between RV U and RV D and the difference between IV U and IV D . Using a semiparametric approach, we demonstrate the existence of a fractionally cointegrating relation in each pair of the semivariances...

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“…For its part, Eduardo Rossi and Santucci de Magistris (2013) applied this methodology to study the relationship between spot and futures markets, and Maggie E. C. Jones, Morten Ørregaard Nielsen, and Michał Ksawery Popiel (2014) checked the fractional long-run relationship between Canadian political support and macrovariables. Additionally, Sepideh Dolatabadi, Nielsen, and Ke Xu (2016) and Dolatabadi et al (2018) applied the FCVAR model for the analysis of price discovery in commodity markets, and more recently, Leandro Maciel (Forthcoming) modelled and forecasted daily high and low asset prices. Few studies in the literature have addressed the application of this methodology in the interest rates.…”

Section: Literature Reviewmentioning

confidence: 99%

The role of Eonia in the dynamics of short-term interbank rates

2020

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To signal monetary policies and market expectations, we apply a fractionally cointegrated vector autoregressive (FCVAR) model, aiming to analyse the expectations hypothesis of term structure (EHTS), persistence in the Euro OverNight Index Average (Eonia) spread and permanent-transitory decomposition using a novel approach. We use a monthly frequency sample for the 3month Euribor rate and Eonia rate, covering the period from January 1999 to February 2019. The results obtained confirm the EHTS and show evidence of a high persistence of the spread, which means that shocks may impede effectiveness in monetary policy and that the European Central Bank (ECB) loses control over interest rates. Additionally, according to permanent-transitory decomposition, we determine that the Eonia rate has a permanent component and thus dominates the common trend in the cointegration system. In sum, if the ECB wants to keep the interbank market interest rates under control, it must contemplate the evolution of the Eonia rate.

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Economic significance of commodity return forecasts from the fractionally cointegrated VAR model

Cited by 53 publications

References 45 publications

Long-term relationship of crude palm oil commodity pricing under structural break

Long-term relationship of crude palm oil commodity pricing under structural break

Return predictability of variance differences: A fractionally cointegrated approach

The role of Eonia in the dynamics of short-term interbank rates

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