In-Depth: Practical Statistical Analysis for the Energy & Power Markets
This course adds a third day to the popular Energy Statistical Analysis seminar to allow the time needed for a more in-depth discussion and explanation of many important topics. Additionally, this three-day course is designed as a hand-on workshop. Not only will you learn about practical energy statistical techniques and tools, but you will practice building statistical models in a workshop format.
Learn why companies continue to be exposed to significant energy and electricity related price risk, and how risk and value are properly quantified. Energy and electricity companies worldwide depend on accurate information about the risks and opportunities facing day to day decisions. Statistical analysis is frequently misapplied and many companies find that "a little bit of knowledge is a dangerous thing."
This comprehensive three-day program is designed to provide a solid understanding of key statistical and analytic tools used in the energy and electric power markets. Through a combination of lecture and hands-on exercises that you will complete using your own laptop, participants will learn and practice key energy applications of statistical modeling. Be armed with the tools and methods needed to properly analyze and measure data to reduce risk and increase earnings for your organization.
A laptop is required with any version of EXCEL.
Upcoming start dates
- Self-paced Online
Who should attend?
Who Should Attend
Among those who will benefit from this seminar include energy and electric power executives; attorneys; government regulators; traders & trading support staff; marketing, sales, purchasing & risk management personnel; accountants & auditors; plant operators; engineers; and corporate planners.
Types of companies that typically attend this program include energy producers and marketers; utilities; banks & financial houses; industrial companies; accounting, consulting & law firms; municipal utilities; government regulators and electric generators.
Prerequisites and Advance Preparation
This fundamental level group live seminar has no prerequisites. No advance preparation is required before the seminar.
- The Basics of Deterministic vs. Probabilistic Thinking for Energy Applications
- Basics of data science - Information from Data
- Descriptive Statistics, Means, Standard Deviations, Distribution Shapes
- Frequency Distributions and Confidence Intervals
- Implications of the Empirical Rule, Transformations and Probability
- Fundamental Modeling Tools and Simulation
- Exercise: Setting up a Monte Carlo Simulation to Evaluate Project Value and Risk
- Application: Calculating Value at Risk (VaR)
- The Linear Method and
- The Quadratic Method
- Historic Simulation Method
- Monte Carlo Method
- Exercise: Calculating VaR Using Three Different Methods
- Application: Hedging Energy Exposure
- Understanding the "Greeks"
- How and when to Hedge
- Delta Hedging
- Dynamic Hedging
- Gamma Hedging
- Application: Component Risk Analysis
- Payoff Diagrams
- Portfolio VaR Diagram
- CAPM, RAROC and the Sharp Ratio
- Calculating Load Following Supply Risk
- Layered Hedging using Statistical Triggers
- Exercise: Customer Migration Model Estimating Migration out of Standard Offer Service
- Exercise: Measuring Load Following Supply Risk
- Exercise: Measuring Intermittent Renewable Supply Risk
- Correlation and Regression Analysis for Maintaining the Competitive Edge
- Univariate and Multivariate Analysis
- Hypotheses Testing
- Testing for Equal Means and Variances
- Control Charts
- The Energy Forecasting Toolbox
- Historical Trend Analysis
- Univariate Time Series
- Multivariate Time Series
- Econometric Models
- Bayesian Estimation
- End-Use Models
- Engineering or Process Models
- Network Models
- Game Theory
- Case Study: Statistical Reports that Everyone Can Understand
- Case Study: Benchmarking to Industry Standards- GTS Steel vs. KCPL
- Exercise: Building Regressions and Forecasting, PDF's, CDF's and Payoff Diagrams
- Exercise: Calculating Hedge Ratios, Constructing an Energy Hedge and a Weather Hedge
- Exercise: Using Forecasts in Monte Carlo Simulation to Calculate Risk Premium
- Introduction to Real Options Analysis
- Details of Option Model Implementation
- Real Options and Net Present Value (NPV) Analysis
- Estimating Volatility and Uncertainty In Historical Prices
- Black-Scholes, Binomial Trees, and GARCH Models
- Geometric Brownian Motion and Mean Reversion
- Application: Minimizing Price Risk through Operational Design Flexibility
- Application: Real Option Value of Demand Response and the Smart Grid
- Exercise: Calculating Volatility
- Exercise: Simulating Prices using GBM and Mean Reversion Monte Carlo Models
- Exercise: Valuing Combustion Turbines using Real Options
- Exercise: Valuing Gas Storage using Real Options
Course delivery details
This course can be delivered as a three day CPE approved classroom seminar or as an online self-paced course (no CPE).
You can also contact PGS Energy Training about their group training options if you would like to bring this course on-site for your employees
Contact this provider
PGS Energy Training
PGS Energy Training (PGS) is a leading provider of quality seminars for the electric power and energy industries. Established in 1990, PGS offers on-site training programs, open-registration classroom seminars, live online seminars, and private education sessions for senior executives....