Commodity Price Dynamics: A Structural Approach. Storage model for daily prices, focusing on higher moments of prices, covariation between prices of diff maturities, and implication of stochastic fundamental volatility, Electricity Price Model

Spreads between spot and futures prices as a measure of the return to storage, and to derive a “supply of storage” curve relating these spreads to the amount of commodity in store

Futures price = spot price + cost of carry inventory )cost of funds + warehousing fee + insurance) + convenience yield

commodity prices based on structural storage models

in this book I focus almost exclusively on the implications of storage models for high frequency– daily–prices, and use high frequency data to test these models

in this book I pay particular attention to the implications of storage models for higher moments of prices, covariation between prices of different maturities, the pricing of commodity options (including more exotic options), and the empirical behavior of stocks

I introduce a new feature into the fundamental shocks in the storage model. Specifically, I examine the implications of stochastic fundamental volatility

electricity.  2 approach dominates the electricity spot and forward market. first, jump diffusion-type processes for electricity prices. second, spot price of electricity depends on fundamental demand factors (e.g., weather, or “load”) and cost factors (e.g., fuel prices); specify stochastic processes for these fundamental factors; and then use standard derivatives pricing methods to solve for the prices of electricity forward contracts and options.

extensive use of numerical methods, with only a few close form solutions

How much does the price fluctuate over time, and what factors contribute to these fluctuations?

Electricity Price Model

- The model assumes that prices are determined by the intersection of a supply curve (that fluctuates randomly due to changes in fuel prices) and a (randomly fluctuating) demand curve

- In this approach, power prices in the physical measure are a function of two state variables.

- The first state variable is a demand variable, load. Load is the amount of electricity consumed. Since load depends heavily on temperature, it is also possible to use temperature as a state variable.

- Analysis of the dynamics of load from many markets reveals that this variable is very well behaved. Load is seasonal, with peaks in the summer and winter for most US power markets. Moreover, load for each of the various regions is nearly homoskedastic and there is little evidence of jumps in load. Finally, load exhibits strong mean reversion; random deviations of load from its seasonally-varying mean tend to reverse fairly rapidly

Valuing Daily Strike and Monthly Strike Options