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Forecasting the Prices of Crude Oil, Natural Gas and Refined Products Istanbul Duration: 1 Week/s

Course Information

  • Course Price
  • Location Istanbul Courses
  • Course Code FPCNRI
  • Course Date 15 Apr - 19 Apr 2024

Course Objectives

Due to the strategic nature of Crude oil in the global economy, governments, businesses, investors, financial institutions, regulators, and the public spend a lot of time to find out the direction of the Oil prices. Forecasting the exact direction of Oil prices has become a herculean task and hence, the lack of a widely accepted consensus on the best way to forecast Oil prices. This course will highlight most of the commonly used techniques in forecasting the prices of Crude Oil, Natural Gas and Refined Products. It is also expected that, aside from the standard techniques such as linear regression and econometrics, alternative methods such as structural models and computer-drive analytics will be explored.
The movement in global Oil price is influenced by so many variables and therefore the course will also explore the use of Technical Analysis (TA) as a technique that measures sentiment to predict the direction of Oil prices. Technical Analysis also known as charting is widely used by the financial market traders and is gradually gaining acceptability of the academicians due to its relationship with behavioural finance.

Who Should Attend?

Financial analysts, Government and regulatory officials with responsibility to energy sector,
Risk Managers, Energy traders, Consultants in the commodity sector, etc.

Course Overview

  • Measuring Anxiety/Uncertainty of Equity and Commodity Markets

  • The Crude-Oil Markets: Level and Slope of Crude-Oil Futures Markets; Impact of Economic, Financial and Geopolitical Events on Implied Instability in the Crude-Oil Market

  • Effect of Seasonality on Global Petroleum and Gas Markets

  • The Refining Spread and Retail Gasoline Prices

  • The Domestic Petroleum and Gas Market: The effect of seasonality

  • The Futures Contract

  • Financial Markets’ “Message from Markets”; Interpret bond-market moves in concurrence with those in equity markets.

  • Empirical Regularities of Global Fixed Income Markets

  • Understanding the fundamentals of bond valuation

  • Eurodollar Futures and Interest Rate Swaps

  • Duration and Convexity; Hedging interest rate exposure

  • Interest-Rate Volatility

  • Basic Statistical Concepts: Average and Volatility; Stationarity of time variables

  • Regression Analysis

  • Using Solver to Solve Constrained Optimization Problems

  • Fundamentals of Forwards and Futures Contracts: Definition, Payoff Diagram, Pricing by Arbitrage

  • Forward/Futures Prices and Forecast Prices

  • Commodity Swaps

  • The Key Difference between Real-Asset Valuation and Expected Value

  • Black-Scholes Formula

  • Option “Sensitivities” (the “Greeks”); Delta and Gamma

  • Real Options in Energy Markets: Power Plants as a Strip of Spark Spread Options; Oil Fields as the Valuation of an Extraction Option

  • Historical Volatility; The Term Structure of Volatility (TSOV)

  • Estimating Volatility from Market Prices of Options in Energy Markets

  • Characterizing the Volatility “Surface” Across Time and Strike

  • The “Market Price of Risk”: Estimating a Risk Premium in Finance and Applying it to Energy Prices.

  • How Can Use Regression Analysis to Fortify Our Understanding of Financial Markets’ Perspective on Forecast Prices?

  • Where Can We Observe Forecast Prices?

  • What is the Difference between Futures Prices and Forecast Prices?

  • What is the Capital Asset Pricing Model (CAPM) and How Can We Use it to Forecast Oil Prices?

  • Applying a Jump-Diffusion Model to Oil Futures Options

  • Using the Market Price of Risk to Implement Risk-Management from a Corporate Perspective

  • Categorizing derivative products: option collars, average options, spread options, swing options, weather derivatives, commodity-linked bonds; “Swing” Options; Weather Derivatives.

  • Structuring and valuing option collars

  • Technical Vs Fundamental Analysis

  • Technical Analysis Vs Random Walk Theory

  • Brief on Dow Theory

  • Trend and Trendlines, Volumes, Supports and Resistance Levels

  • Chart Patterns

  • Technical Indicators such as Moving Averages, RSI, Stochastics,

  • Fibonacci Retracement


    • Learning Goals:

    Upon completion of this course, the participants will to:
  • Use financial models to analyse and forecast energy prices; extrapolate forward prices beyond the liquidity tenor.

  • Understand the risk of and return from futures and options contracts on energy commodities.

  • Manage and optimise their organisations’ energy risk exposure.

  • Estimate expected returns and calculate volatility in energy prices.

  • Obtain a comprehensive knowledge of the financial-economics techniques used to forecast prices.

  • Apply option valuation techniques to the energy markets.

  • Utilise real options theory to value energy assets; use information from futures/option prices to make optimal production decisions: Optimal timing for extraction, optimal rate at which to extract oil (gas) from a field; value oil fields, pipelines and storage facilities, power plants.


    • Training Methodology:

    This course will be presented through a combination of following methods:
  • Clear presentation of notes with the requisite supportive analytics

  • Detailed presentation of the relevant empirical regularities/stylized facts of the energy markets

  • Presentation of several case studies designed to exemplify the application of risk-management and valuation principles.

  • Interspersed in the lectures are relevant problem-sets, designed to afford participants with the opportunity to apply the principles conveyed and see their implementation.

  • Dissemination to and sharing with participants critical spreadsheets that will permit them to address issues within the course, as well as utilise these concepts once they have completed the course.

  • Valuation and role of futures contracts and swap agreements

  • Mean forecasts to make better business decisions.

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