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.
DAY
ONE:
The
Basics of Deterministic vs. Probabilistic Thinking for Energy Applications
·       Â
Basics of data science - Information
from Data
·       Â
Descriptive Statistics, Means,
Standard Deviations, Distribution
Shapes
·       Â
Frequency Distributions and Confidence
Intervals
·       Â
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)
·       Â
The Linear Method and
·       Â
The Quadratic Method
·       Â
Historic Simulation Method
·       Â
Monte Carlo Method
Exercise:
Calculating VaR Using Three Different Methods
Application:
Hedging Energy Exposure
·       Â
Understanding the "Greeks"
·       Â
How and when to Hedge
·       Â
Delta Hedging
·       Â
Dynamic Hedging
·       Â
Gamma Hedging
Application:
Component Risk Analysis
·       Â
Payoff Diagrams
·       Â
Portfolio VaR
Diagram
·       Â
CAPM, RAROC and the Sharp Ratio
·       Â
Calculating Load Following Supply
Risk
·       Â
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
·       Â
Univariate and Multivariate Analysis
·       Â
Hypotheses Testing
·       Â
Testing for Equal Means and
Variances
·       Â
Control Charts
DAY
TWO:
The
Energy Forecasting Toolbox
·       Â
Historical Trend Analysis
·       Â
Univariate Time Series
·       Â
Multivariate Time Series
·       Â
Econometric Models
·       Â
Bayesian Estimation
·       Â
End-Use Models
·       Â
Engineering or Process Models
·       Â
Optimization
·       Â
Network Models
·       Â
Simulation
·       Â
Game Theory
·       Â
Scenarios
·       Â
Surveys
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
DAY Three:
Introduction
to Real Options Analysis
·       Â
Details of Option Model
Implementation
·       Â
Real Options and Net Present Value
(NPV) Analysis
·       Â
Estimating Volatility and
Uncertainty In Historical Prices
·       Â
Black-Scholes, Binomial Trees, and
GARCH Models
·       Â
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 Â
Exercise: Valuing Combustion Turbines using Real Options
Exercise: Valuing Gas Storage using Real Options
This live group seminar is eligible for 18.0 CPE credits. Be aware that state boards of accountancy have final authority on the acceptance of individual courses for CPE credit. As of January 1, 2002, sponsored learning activities are measured by program length, with one 50-minute period equal to one CPE credit. One-half CPE credit increments (equal to 25 minutes) are permitted after the first credit has been earned in a given learning activity. You may want to verify that the state board from which your participants will be receiving credit accept one-half credits.
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.
This fundamental level group live seminar has no prerequisites. No advance preparation is required before the seminar.
PGS seminars are known for their clear explanations and in-depth content. Register for a PGS class today, and join the over 10,000 energy professionals who have already attended one of PGS's proven programs.