Price volatility, hedging and variable risk premium in the crude oil market

OPEC Review ◽  
2006 ◽  
Vol 30 (2) ◽  
pp. 55-70 ◽  
Author(s):  
Ahmad R. Jalali-Naini ◽  
Maryam Kazemi Manesh
Keyword(s):  
Crude Oil ◽  
Risk Premium ◽  
Price Volatility ◽  
Oil Market

Oil Price Volatility, Exchange Rate Movements and Stock Market Reaction: The Nigerian Experience (1985-2017)

2018 ◽  
Vol 3 (1) ◽  
pp. 12-25
Author(s):  
Onyemachi Maxwell Ogbulu
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Price Volatility ◽  
Market Prices ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Exchange Rate Movements ◽  
Dollar Price ◽  
Pass Through

Given the observed volatility in crude oil prices in the international oil market and the role which oil and gas play in the Nigerian economy, this paper is an attempt to investigate the impact of crude oil prices and foreign exchange rate movements on stock market prices in Nigeria. In addition, the paper examined whether there is any volatility pass-through between the dollar price of Nigerian crude oil, foreign exchange rate of the Naira and stock market prices respectively. Data employed for the study are monthly values of the Nigerian Stock Exchange (NSE) All-Share Index (ASI), Dollar price of Nigerian Crude Oil (DPO) and the Official Exchange Rate of the Naira to the US Dollar (FXR) from January, 1985 to August, 2017. The methodology adopted for the study include the ADF unit root tests, Johansen co-integration tests, the ECM technique, Granger causality tests, variance decomposition as well as the GARCH(1,1) to model the volatility relationships among the variables. Findings reveal that there is one long-run dynamic co-integrating relationship among the variables ASI, DPO and FXR while the ECM results indicate that Crude oil price (DPO) significantly impact on Stock market prices. The Granger causality test reports a bi-directional causality relationship between ASI and DPO and a unidirectional causality running from FXR to ASI. The ARCH-GARCH volatility analysis demonstrates vividly that stock market prices in the NSE exhibit ARCH effect with a significant and positive first order ARCH term. The GARCH term is also positive and significant indicating that previous month’s stock market price volatility significantly influences current stock market volatility in the NSE. In addition, findings show that the volatility of dollar price of Nigerian oil (DPO) in the world oil market is significantly transmitted to the volatility of stock market prices in Nigeria.  The pass-through effect of the volatility of exchange rate (FXR) to the volatility of stock market prices is also positive and significant. These findings offer significant informational signal to policy makers, portfolio managers/advisors and the investing public in achieving optimal asset and portfolio profile.

The Financialization of Storable Commodities

2020 ◽  
Author(s):  
Steven D. Baker
Keyword(s):  
Risk Premium ◽  
Price Level ◽  
Dynamic Equilibrium ◽  
Price Volatility ◽  
Risk Premia ◽  
Spot Price ◽  
Oil Market ◽  
Long Run ◽  
The Mean ◽  
And Storage

I solve a dynamic equilibrium model of commodity spot and futures prices, incorporating an active futures market, heterogeneous risk-averse participants, and storage. When calibrated to data from the crude oil market, the model implies that financialization reduces the futures risk premium and increases correlation between futures open interest and the spot price level. However, there is no long-run increase in the mean spot price, and speculative storage generally attenuates financialization’s effect on spot price volatility. Therefore, financialization’s effect on spot price dynamics through storage arbitrage is likely modest, even if futures positions and risk premia are substantially altered. This paper was accepted by Gustavo Manso, finance.

Modeling and forecasting oil price risk: the role of implied volatility index

2017 ◽  
Vol 44 (6) ◽  
pp. 1003-1016 ◽  
Author(s):  
Anupam Dutta
Keyword(s):  
Crude Oil ◽  
Information Content ◽  
Price Volatility ◽  
Oil Price ◽  
Base Line ◽  
Content Type ◽  
Oil Market ◽  
Oil Price Volatility ◽  
Volatility Index ◽  
The Us

Purpose While numerous empirical studies have tried to model and forecast the oil price volatility over the years, such attempts using the crude oil volatility index (OVX) rarely exist. In order to conceal this void, the purpose of this paper is to investigate whether including OVX in the realized volatility (RV) models improve the accuracy of predictions. Design/methodology/approach At the empirical stage, the authors employ several measures to frame the RV of crude oil futures returns. In particular, the authors use three different range-based RV estimators recommended by Parkinson (1980), Rogers and Satchell (1991) and Alizadeh et al. (2002), respectively. Findings The findings reveal that the information content of crude OVX helps to provide more accurate volatility predictions in comparison to the base-line RV model which contains only historical oil volatilities. Besides, the forecast encompassing test further suggests that the modified RV model (when OVX is introduced in the base-line RV model) forecast encompasses the conventional RV forecast in majority of the cases. Practical implications Since forecasting oil price volatility plays a vital role in portfolio optimization, derivatives pricing, optimum asset allocation decisions and risk management, the findings of this study thus carry important implications for energy economists, investors and policymakers. Originality/value This paper adds to the existing literature, since it is one of the initial studies to explore whether OVX is informative about the realized variance of the US oil market returns. The findings recommend that the information content of oil implied volatilities should be taken into account when modeling the US oil market volatility. In addition, range-based measures should be utilized while estimating the RV.

scholarly journals Investigating the Behavior of Iran's Light Crude Oil Price in Short Term

2016 ◽  
Vol 10 (3) ◽  
pp. 45
Author(s):  
Seyed Abdollah Razavi ◽  
Mostafa Salimifar ◽  
Seyed Mahdi Mostafavi ◽  
Mortaza Baky Haskuee
Keyword(s):  
Crude Oil ◽  
Price Volatility ◽  
Oil Prices ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Light Crude Oil ◽  
Oil Market ◽  
Oil Price Volatility

<p class="zhengwen">Investigate the causes of changing the oil price and modeling for predicting its volatility has always been one of the most important fields of Iran's economic literature study due to its position in Iran's economy. On the other hand, oil price volatility lead to the difficulty in the development programs. Empirical studies show that oil prices volatility are caused the structural bottlenecks (trade balance bottleneck, budget bottlenecks, etc.) in Iran's economic.<strong></strong></p>Understanding the mechanism of oil prices formation can reduce the risk of oil price volatility and its negative impacts on Iran's economy. With the development of oil bourse and oil futures market, oil market changed the crude oil price formation so that the cash flow between financial markets and oil market will deviant the crude oil price from its long term direction by changing in interest rate in short-term. In this paper, it is investigated the crude oil price deviation from its long-term direction with regard to the relationship between mentioned markets in short-term. For this purpose, Fisher price jump model and Frankel theory will be used for test by using daily time series data of 2005-13 about Iran's light crude oil in different areas (different markets), as well as multivariate GARCH technique method. Also, the results show that the pricing strategy is false signal in the use of Urals crude oil in the determining of crude oil price in the Mediterranean and North West Europe markets.

Contango in Cushing? - Evidence on Financial-Physical Interactions in the U.S. Crude Oil Market

2012 ◽  
Author(s):  
Louis H. Ederington ◽  
Chitru S. Fernando ◽  
Kateryna V. Holland ◽  
Thomas K. Lee
Keyword(s):  
Crude Oil ◽  
Oil Market ◽  
Physical Interactions ◽  
The U.S

scholarly journals COVID-19 pandemic and the crude oil market risk: hedging options with non-energy financial innovations

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Afees A. Salisu ◽  
Kingsley Obiora
Keyword(s):  
Crude Oil ◽  
Structural Breaks ◽  
Exchange Traded Funds ◽  
Modeling Framework ◽  
Risk Hedging ◽  
Financial Innovations ◽  
Oil Market ◽  
Price Series ◽  
Hedging Effectiveness ◽  
Multivariate Volatility

AbstractThis study examines the hedging effectiveness of financial innovations against crude oil investment risks, both before and during the COVID-19 pandemic. We focus on the non-energy exchange traded funds (ETFs) as proxies for financial innovations given the potential positive correlation between energy variants and crude oil proxies. We employ a multivariate volatility modeling framework that accounts for important statistical features of the non-energy ETFs and oil price series in the computation of optimal weights and optimal hedging ratios. Results show evidence of hedging effectiveness for the financial innovations against oil market risks, with higher hedging performance observed during the pandemic. Overall, we show that sectoral financial innovations provide resilient investment options. Therefore, we propose that including the ETFs in an investment portfolio containing oil could improve risk-adjusted returns, especially in similar financial crisis as witnessed during the pandemic. In essence, our results are useful for investors in the global oil market seeking to maximize risk-adjusted returns when making investment decisions. Moreover, by exploring the role of structural breaks in the multivariate volatility framework, our attempts at establishing robustness for the results reveal that ignoring the same may lead to wrong conclusions about the hedging effectiveness.

Multivariate Markov-switching score-driven models: an application to the global crude oil market

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Szabolcs Blazsek ◽  
Alvaro Escribano ◽  
Adrian Licht
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Local Level ◽  
Markov Switching ◽  
Impulse Response Functions ◽  
Common Trends ◽  
Vector Autoregressive ◽  
Oil Market ◽  
Long Run ◽  
Special Cases

Abstract A new class of multivariate nonlinear quasi-vector autoregressive (QVAR) models is introduced. It is a Markov switching score-driven model with stochastic seasonality for the multivariate t-distribution (MS-Seasonal-t-QVAR). As an extension, we allow for the possibility of having common-trends and nonlinear co-integration. Score-driven nonlinear updates of local level and seasonality are used, which are robust to outliers within each regime. We show that VAR integrated moving average (VARIMA) type filters are special cases of QVAR filters. Using exclusion, sign, and elasticity identification restrictions in MS-Seasonal-t-QVAR with common-trends, we provide short-run and long-run impulse response functions for the global crude oil market.

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