scholarly journals A Note on Forecasting the Historical Realized Variance of Oil-Price Movements: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6775
Author(s):  
Rangan Gupta ◽  
Christian Pierdzioch ◽  
Wing-Keung Wong
Keyword(s):  
Real Time ◽  
Predictive Value ◽  
Oil Price ◽  
Realized Variance ◽  
Monthly Data ◽  
Significant Evidence ◽  
Out Of Sample ◽  
Price Movements

We examine the predictive value of gold-to-silver and gold-to-platinum price ratios, as proxies for global risks affecting the realized variance (RV) of oil-price movements, using monthly data over the longest available periods of 1915:01–2021:03 and 1968:01–2021:03, respectively. Using the two ratios, we find statistically significant evidence of in-sample predictability for increases in RV for both ratios. This finding also translates into statistically significant out-of-sample forecasting gains derived from these two ratios for RV. Given the importance of real-time forecasts of the volatility of oil-price movements, our results have important implications for investors and policymakers.

scholarly journals El Niño, La Niña, and the Forecastability of the Realized Variance of Heating Oil Price Movements

2021 ◽  
Vol 13 (14) ◽  
pp. 7987
Author(s):  
Mehmet Balcilar ◽  
Elie Bouri ◽  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
El Niño ◽  
Predictive Value ◽  
El Nino ◽  
Southern Oscillation ◽  
La Niña ◽  
Realized Variance ◽  
La Nina ◽  
Out Of Sample ◽  
Heating Oil ◽  
Price Movements

We use the heterogenous autoregressive (HAR) model to compute out-of-sample forecasts of the monthly realized variance (RV) of movements of the spot and futures price of heating oil. We extend the HAR–RV model to include the role of El Niño and La Niña episodes, as captured by the Equatorial Southern Oscillation Index (EQSOI). Using data from June 1986 to April 2021, we show evidence for several model configurations that both El Niño and La Niña phases contain information useful for forecasting subsequent to the realized variance of price movements beyond the predictive value already captured by the HAR–RV model. The predictive value of La Niña phases, however, seems to be somewhat stronger than the predictive value of El Niño phases. Our results have important implications for investors, as well as from the perspective of sustainable decisions involving the environment.

scholarly journals Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4173
Author(s):  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
Crude Oil ◽  
Predictive Value ◽  
Realized Variance ◽  
International Spillovers ◽  
Forecasting Models ◽  
West Texas ◽  
Out Of Sample ◽  
One Year ◽  
Lasso Estimator

We use a dataset for the group of G7 countries and China to study the out-of-sample predictive value of uncertainty and its international spillovers for the realized variance of crude oil (West Texas Intermediate and Brent) over the sample period from 1996Q1 to 2020Q4. Using the Lasso estimator, we found evidence that uncertainty and international spillovers had predictive value for the realized variance at intermediate (two quarters) and long (one year) forecasting horizons in several of the forecasting models that we studied. This result holds also for upside (good) and downside (bad) variance, and irrespective of whether we used a recursive or a rolling estimation window. Our results have important implications for investors and policymakers.

scholarly journals THE ROLE OF PALM OIL PRICE IN INDONESIA’S AGGREGATE DEMAND

2020 ◽  
Vol 23 (2) ◽  
pp. 161-178
Author(s):  
Susan Sunila Sharma
Keyword(s):  
Palm Oil ◽  
Government Spending ◽  
Aggregate Demand ◽  
Oil Price ◽  
Consumption Expenditure ◽  
Monthly Data ◽  
Real Gdp ◽  
Out Of Sample ◽  
Total Investment

This study examines the predictability of Indonesia’s aggregate demand using palm oil price. We conduct both in-sample and out-of-sample forecasting evaluations. These evaluations are based on time-series quarterly and monthly data frequencies and cover three different forecasting horizons. Overall, we find that palm oil price predicts real GDP, consumption expenditure, total investment, net spending from overseas, while predictability of government spending is sensitive to the use of forecasting approaches and horizons.

Uncertainty and Forecasts of U.S. Recessions

2019 ◽  
Vol 24 (4) ◽  
Author(s):  
Christian Pierdzioch ◽  
Rangan Gupta
Keyword(s):  
Predictive Value ◽  
Nonlinear Function ◽  
Boosted Regression Trees ◽  
Securities Markets ◽  
Forecast Horizon ◽  
Forecast Performance ◽  
Monthly Data ◽  
Receiver Operating Characteristic Curves ◽  
Out Of Sample ◽  
Dynamic Version

AbstractWe estimate Boosted Regression Trees (BRT) on a sample of monthly data that extends back to 1889 to recover the predictive value of disaggregated news-based uncertainty indexes for U.S recessions. We control for widely-studied standard predictors and use out-of-sample metrics to assess forecast performance. We find that war-related uncertainty is among the top five predictors of recessions at three different forecast horizons (3, 6, and 12 months). The predictive value of war-related uncertainty has fallen in the second half of the 20th century. Uncertainty regarding the state of securities markets has gained in relative importance. The probability of a recession is a nonlinear function of war-related and securities-markets uncertainty. Receiver-operating-characteristic curves show that uncertainty improves out-of-sample forecast performance at the longer forecast horizons. A dynamic version of the BRT approach sheds light on the importance of various lags of government-related uncertainty for recession forecasting at the long forecast horizon.

scholarly journals El Niño and forecastability of oil-price realized volatility

2021 ◽  
Vol 144 (3-4) ◽  
pp. 1173-1180
Author(s):  
Elie Bouri ◽  
Rangan Gupta ◽  
Christian Pierdzioch ◽  
Afees A. Salisu
Keyword(s):  
El Niño ◽  
Southern Oscillation Index ◽  
El Nino ◽  
Southern Oscillation ◽  
Realized Volatility ◽  
Oil Price ◽  
Out Of Sample ◽  
Asymmetric Loss Function ◽  
Standard Tests

AbstractWe forecast monthly realized volatility (RV) of the oil price based on an extended heterogenous autoregressive (HAR)-RV model that incorporates the role of the El Niño Southern Oscillation (ENSO), as captured by the Equatorial Southern Oscillation Index (EQSOI). Based on the period covering 1986 January to 2020 December and studying various rolling-estimation windows and forecast horizons, we find that the EQSOI has predictive value for oil-price RV particularly at forecast horizons from 2 to 4 years, and for rolling-estimation windows of length 4 to 6 years. We show that this result holds not only based on standard tests of out-of-sample predictability, but also under an asymmetric loss function.

HISTORICAL FORECASTING OF INTEREST RATE MEAN AND VOLATILITY OF THE UNITED STATES: IS THERE A ROLE OF UNCERTAINTY?

2021 ◽  
pp. 2050018
Author(s):  
HOSSEIN HASSANI ◽  
MOHAMMAD REZA YEGANEGI ◽  
RANGAN GUPTA
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Negative Impact ◽  
The United States ◽  
Policy Makers ◽  
Monthly Data ◽  
The Great Recession ◽  
The Us ◽  
Out Of Sample

Uncertainty is known to have negative impact on financial markets through its effects on investors’ decisions. In the wake of the “Great Recession”, quite a few recent studies have highlighted the role of uncertainty in predicting in-sample movements of interest rates. Since in-sample predictability does not guarantee out-of-sample forecasting gains, in this paper, we used historical daily and monthly data for the US to forecast mean and volatility of interest rate. The results show that changes in uncertainty measure movements fail to add any significant statistical gains to the forecast of interest rates for the US. In other words, policy makers in the US are not likely to improve their accuracy of future movements of the policy rate’s mean and volatility by incorporating information derived from changes in metrics of uncertainty.

scholarly journals Uncertainty, Spillovers, and Forecasts of the Realized Variance of Gold Returns

2021 ◽  
Vol 26 (3) ◽  
pp. 49
Author(s):  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
Forecast Accuracy ◽  
Systematic Effect ◽  
Derivative Securities ◽  
Realized Variance ◽  
International Spillovers ◽  
Out Of Sample ◽  
Related Derivative ◽  
Using Data ◽  
Lasso Estimator

Using data for the group of G7 countries and China for the sample period 1996Q1 to 2020Q4, we study the role of uncertainty and spillovers for the out-of-sample forecasting of the realized variance of gold returns and its upside (good) and downside (bad) counterparts. We go beyond earlier research in that we do not focus exclusively on U.S.-based measures of uncertainty, and in that we account for international spillovers of uncertainty. Our results, based on the Lasso estimator, show that, across the various model configurations that we study, uncertainty has a more systematic effect on out-of-sample forecast accuracy than spillovers. Our results have important implications for investors in terms of, for example, pricing of related derivative securities and the development of portfolio-allocation strategies.

scholarly journals Nexus of Gold Price-Exchange rate-interest rate-Oil Price: Lessons for Monetary Policy in Pakistan

2021 ◽  
pp. 1-16
Author(s):  
Zahid Iqbal ◽  
Muhammad Akbar ◽  
Warda Amjad
Keyword(s):  
Monetary Policy ◽  
Exchange Rate ◽  
Oil Prices ◽  
Gold Price ◽  
Oil Price ◽  
Policy Makers ◽  
Monthly Data ◽  
Short Run

This study aims to evaluate the links among gold price, oil price, exchange rate andinterest rate in Pakistan. All these channels are interconnected and have impact onmonetary policy of the country. Monthly data ranging from 1995-01 to 2016-12 is usedfor the analysis based on VAR Model. Exchange rate depreciations are responded bytight monetary policy actions, which seem to have a significant effect on exchange ratestabilization process and raise gold price. Changes in oil prices at global level stronglyaffect the nexus in Pakistan. Monetary policy managers are suggested to take changes ingold prices as indicators of short-run fluctuations in Pakistan economy. The studycontributes in two ways. Firstly, as a case study of Pakistan, it analyzes the role of goldmarket in response to changes in exchange rate and world oil prices. Secondly, the studylinks up monetary policy decisions to the nexus of gold price-oil price-exchange rate.Findings of the study may be useful for monetary policy makers, academia, and goldindustry alike.

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