Introducing Cycle Analysis and Monte Carlo Simulations
Joaquin Narro and Monica Caamano
Introduction
The Energy Supply and Demand Conundrum
A Brief History of Energy Markets
Systematic Trading in Energy Markets
The Trading Edge
Defining Trading Expectations
Exploring Technical Modelling in Idiosyncratic Energy Markets
Exploring Fundamental Modelling
Introducing Cycle Analysis and Monte Carlo Simulations
Data: Boundaries and Assumptions
Estimating Model Lifetime
Optimising Performance and Risk
Pitfalls in Systematic Model Development
Model Production
Portfolio Construction
Incorporating Human Behaviour
References
In this chapter, we show how a systematic model can be built by unearthing inefficiencies using cycle analysis, blending in Monte Carlo methods, to simulate the expected values of a trading strategy we wish to systematise. Duality exists when there is confirmation of two different regimes, and it is often evidenced by the display of heavy-tailed price behaviour at times, followed by periods of sustained lower volatility (Karakatsani and Bunn, 2010; Bessec and Bouabdallah, 2005). Quantitatively, heavy-tailed behaviour is associated with a price distribution that displays a higher probability of significantly higher (or lower) results when these are compared to a normal distribution.
In the following sections, we will describe a specific example involving short-term German electricity prices introducing the necessary market background and mathematical concepts as we go along. We will illustrate the process with an example concerning the duality of volatility regimes in short-term electricity markets against a backdrop of growing integration of renewables generation.
UNDERSTANDING THE ELECTRICITY MARKET BACKGROUND
We should clearly differentiate between spot and forward
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