Download or read book Forecasting the Price of Crude Oil with Multiple Predictors written by Hüseyin Kaya and published by . This book was released on 2017 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the price of crude oil, this paper aims to investigate the predictive content of a variety of variables including oil futures prices, exchange rates of particular countries and stock-market indexes. Out-of-sample forecasting results suggest that oil futures prices have marginal predictive power for the price of oil at a 1-month forecast horizon. However, they generally lose their forecasting power at higher forecast horizons. The results also suggest that exchange rates help predicting oil prices at higher forecast horizons. The paper also considers forecast averaging and variable selection methods, and fınds that forecast averaging significantly improves the forecasting performances.

Download or read book Crude Oil Price Prediction written by Yifeng Zhu and published by . This book was released on 2016 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we propose linear and nonparametric models to predict one month, three months, six months, one year, eighteen months and two years ahead crude oil price in out-of-sample background. Mainly, our forecast depends on three predictor variables, the change in crude oil inventories, its previous prices and product spread. By employing mean-squared prediction error (MSPE) and stochastic dominance (SD) tests, we find that the prediction result of our nonparametric models is significantly better than the random walk model, while the corresponding linear models' performance is better than the random walk model only for longer horizon forecasts (one to two years). In General, for the sample period from 1995.1 to 2015.4, the conclusion is that our model applying nonparametric estimation always outperforms all other models in different horizon forecasting. And for the nonparametric model including all three predictors, we document MSPE reduction as high as 62.6% and directional accuracy ratio as high as 77.5% at the two years horizon compared to the random walk model.

Download or read book Forecasting the Price of Crude Oil Via Convenience Yield Predictions written by Thomas Knetsch and published by . This book was released on 2016 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield which can be derived from the cost-of-carry relationship. In a recursive out-of-sample analysis, forecast accuracy at horizons within one year is checked by the root mean squared error as well as the mean error and the frequency of a correct direction-of-change prediction. For all criteria employed, the proposed forecasting tool outperforms the approach of using futures prices as direct predictors of future spot prices. Vis-à-vis the random-walk model, it does not significantly improve forecast accuracy but provides valuable statements on the direction of change.

Download or read book Forecasting Accuracy of Crude Oil Futures Prices written by Mr.Manmohan S. Kumar and published by International Monetary Fund. This book was released on 1991-10-01 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper undertakes an investigation into the efficiency of the crude oil futures market and the forecasting accuracy of futures prices. Efficiency of the market is analysed in terms of the expected excess returns to speculation in the futures market. Accuracy of futures prices is compared with that of forecasts using alternative techniques, including time series and econometric models, as well as judgemental forecasts. The paper also explores the predictive power of futures prices by comparing the forecasting accuracy of end-of-month prices with weekly and monthly averages, using a variety of different weighting schemes. Finally, the paper investigates whether the forecasts from using futures prices can be improved by incorporating information from other forecasting techniques.

Download or read book Price Forecasting Models for Crude Oil CL F Stock written by Ton Viet Ta and published by . This book was released on 2021-03-11 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: https: //www.dinhxa.com One-Week Free Trial (subject to change) Do you want to earn up to a 7723% annual return on your money by two trades per day on Crude Oil CL=F Stock? Reading this book is the only way to have a specific strategy. This book offers you a chance to trade CL=F Stock at predicted prices. Eight methods for buying and selling CL=F Stock at predicted low/high prices are introduced. These prices are very close to the lowest and highest prices of the stock in a day. All methods are explained in a very easy-to-understand way by using many examples, formulas, figures, and tables. The BIG DATA of the 5122 consecutive trading days (from August 23, 2000 to March 4, 2021) are utilized. The methods do not require any background on mathematics from readers. Furthermore, they are easy to use. Each takes you no more than 30 seconds for calculation to obtain a specific predicted price. The methods are not transient. They cannot be beaten by Mr. Market in several years, even until the stock doubles its current age. They are traits of Mr. Market. The reason is that the author uses the law of large numbers in the probability theory to construct them. In other words, you can use the methods in a long time without worrying about their change. The efficiency of the methods can be checked easily. Just compare the predicted prices with the actual price of the stock while referring to the probabilities of success which are shown clearly in the book (click the LOOK INSIDE button to read more information before buying this book). The book is very useful for Investors who have decided to buy the stock and keep it for a long time (as the strategy of Warren Buffett), or to sell the stock and pay attention to other stocks. The methods will help them to maximize profits for their decision. Day traders who buy and sell the stock many times in a day. Although each method is valid one time per day, the information from the methods will help the traders buy/sell the stock in the second time, third time or more in a day. Beginners to CL=F Stock. The book gives an insight about the behavior of the stock. They will surely gain their knowledge of CL=F Stock after reading the book. Everyone who wants to know about the U.S. stock market. https: //www.dinhxa.com includes a software (app) for stock price forecasting using the methods in this book. The software gives 114 predictions while this book gives 16. One-Week Free Trial (subject to change)

Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-08-23 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics

Download or read book Forecasting the Price of Crude Oil Via Convenience Yield Predictions written by Thomas A. Knetsch and published by . This book was released on 2006 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book World Market Price of Oil written by Adalat Muradov and published by Springer. This book was released on 2019-04-10 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops new econometric models to analyze and forecast the world market price of oil. The authors construct ARIMA and Trend models to forecast oil prices, taking into consideration outside factors such as political turmoil and solar activity on the price of oil. Incorporating historical and contemporary market trends, the authors are able to make medium and long-term forecasting results. In the first chapter, the authors perform a broad spectrum analysis of the theoretical and methodological challenges of oil price forecasting. In the second chapter, the authors build and test the econometric models needed for the forecasts. The final chapter of the text brings together the conclusions they reached through applying the models to their research. This book will be useful to students in economics, particularly those in upper-level courses on forecasting and econometrics as well as to politicians and policy makers in oil-producing countries, oil importing countries, and relevant international organizations.

Download or read book The Role of Speculation in Oil Markets written by Bassam Fattouh and published by . This book was released on 2012 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Blending Ensemble Learning Model for Crude Oil Price Prediction written by Mahmudul Hasan and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given that the price of crude oil is driven by a number of factors with varying frequency, it is difficult to accurately capture its behavior, which in turn leads to challenges in forecasting. Moreover, different mechanisms of fluctuations have been observed at different time series periods. To efficiently capture these diverse fluctuation profiles, we propose to combine heterogenous predictors for predicting the crude oil price. Specifically, a forecasting model is developed using blended ensemble learning is developed that combines various machine learning methods, including linear regression, k-nearest neighbor regression, regression trees, support vector regression, and ridge regression. Brent and WTI crude oil data at various time series frequencies are used to validate the proposed blending ensemble learning approach. To show the effectiveness of the proposed model, its performance is compared with existing individual and ensemble learning methods used for crude oil price prediction, such as lasso regression, bagging lasso regression, boosting, random forest, and support vector regression. We show that our proposed blending ensemble learning model dominates the existing forecasting models in terms of forecasting errors. The proposed model exhibits a good prediction performance for both short- and long-term forecasting horizons, which is beneficial to stakeholders and related industries that depend on this energy source.

Download or read book Forecasting the Nominal Brent Oil Price with VARs One Model Fits All written by Benjamin Beckers and published by International Monetary Fund. This book was released on 2015-11-25 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: We carry out an ex post assessment of popular models used to forecast oil prices and propose a host of alternative VAR models based on traditional global macroeconomic and oil market aggregates. While the exact specification of VAR models for nominal oil price prediction is still open to debate, the bias and underprediction in futures and random walk forecasts are larger across all horizons in relation to a large set of VAR specifications. The VAR forecasts generally have the smallest average forecast errors and the highest accuracy, with most specifications outperforming futures and random walk forecasts for horizons up to two years. This calls for caution in reliance on futures or the random walk for forecasting, particularly for near term predictions. Despite the overall strength of VAR models, we highlight some performance instability, with small alterations in specifications, subsamples or lag lengths providing widely different forecasts at times. Combining futures, random walk and VAR models for forecasting have merit for medium term horizons.

Download or read book The Distributional Implications of the Impact of Fuel Price Increases on Inflation written by Mr. Kangni R Kpodar and published by International Monetary Fund. This book was released on 2021-11-12 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates the response of consumer price inflation to changes in domestic fuel prices, looking at the different categories of the overall consumer price index (CPI). We then combine household survey data with the CPI components to construct a CPI index for the poorest and richest income quintiles with the view to assess the distributional impact of the pass-through. To undertake this analysis, the paper provides an update to the Global Monthly Retail Fuel Price Database, expanding the product coverage to premium and regular fuels, the time dimension to December 2020, and the sample to 190 countries. Three key findings stand out. First, the response of inflation to gasoline price shocks is smaller, but more persistent and broad-based in developing economies than in advanced economies. Second, we show that past studies using crude oil prices instead of retail fuel prices to estimate the pass-through to inflation significantly underestimate it. Third, while the purchasing power of all households declines as fuel prices increase, the distributional impact is progressive. But the progressivity phases out within 6 months after the shock in advanced economies, whereas it persists beyond a year in developing countries.

Download or read book Time Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space

Download or read book The Price of Oil written by Roberto F. Aguilera and published by Cambridge University Press. This book was released on 2016 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains why oil prices rose so spectacularly in the past and examines how they will be suppressed in the future.

Download or read book Forecasting the Price of Oil written by Daniel Moetteli and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this analysis, Brent and WTI front month futures returns are predicted using Dynamic Model Averaging (DMA) and Dynamic Model Selection (DMS). These recently proposed econometric methods employ time-varying parameters but also allow for the entire forecasting model to change over time. The out-of-sample forecasting performance is examined using a real-time data set with vintages from August 1997 to July 2014, each containing data extending back to January 1989. The data set consists of 15 predictor variables, a combination of global oil market variables and financial market data, to capture market sentiments. The results show that the proposed framework is not suitable in predicting crude oil futures. Using mean squared forecasting errors (MSFE), the random walk benchmark can be outperformed only for the one-month-ahead prediction when forecasting Brent front month futures. Reporting the posterior inclusion probability for the variables into the forecasting model, it can be shown that the relevant set of predictors varies over time.

Download or read book Non linear and Non stationary Time Series Analysis written by Maurice Bertram Priestley and published by . This book was released on 1988 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: