View Of Busy Stock Traders Office

Source: ZE

A common challenge experienced by many market participants is the effort it takes to manage different contract lengths for the same commodity when building forward curves.

Forward curves, a series of sequential prices either for future delivery of an asset or expected future settlements of an index (Platts), trade on a daily, weekly, monthly, quarterly and annual basis as forward contracts. One of the methods to manage these varying contract periods is through the blending of individual forward curves into one single curve. However, working with all this data requires a lot of time and attention to detail. It can also be extremely difficult to automate.

A quicker solution is to work with our enterprise data management solution the ZEMA Suite, which allows you to create curves for each contract type (monthly, annual, quarterly), and derive prices from overlapping periods.


Figure 1: Overlapping monthly, quarterly and annual contract prices. Source: ZE. Graph created by ZEMA

ZEMA has a number of functions that can enable you to blend forward curves.

There are two main methods for calculating blended curves. The first is simply identifying the weights for each scenario that might arise with overlapping contracts. The second method is to use ZEMA’s formulas and functions to do customize blending. The example below shows how the weights can be manipulated to derive a single blended curve.

Blended: The intuitive and easier method is using the “Blended” functionality under a forward analysis tab in our data series manager. Creating blended curve in ZEMA is easy; the image below demonstrates the creation of blended curve in ZEMA:


Source: ZE.

Using the forward curve analysis tab to create blended curves eliminates steps to create a separate data series for single curves. Below is the logic for blended curve execution in ZEMA:


Source: ZE.

Each column in the Quote table above represents a combination of single curves availability. Numbers are % weights of single curves in the blended curve. The user can edit the weights.

There are also a number of formulaic methods that can be used to blend curves in ZEMA, ranging from:

1) Priority() which allows users to determine which contracts to prioritize over others,

2) FC_ARBITRAGE_FREE_BLENDING which blends forward curve taking out all arbitrage opportunities and

3) A combination of ZEMA’s date, business logic and conditional formulas that can be used to isolate and manipulate overlapping contracts to build a blended curve.

Priority: A ZEMA user can create a separate curve for each time granularity and then use PRIORITY () function for blending.

ZEMA Profile example using Priority function:

Data sources:

a) Monthly forward curve

b) Quarterly forward curve

c) Annual forward curve


d) PRIORITY (a,b,c)


Figure4: Priority blending Source: ZE. Graph created by ZEMA

FC_Arbitrage_Free_Blend: A ZEMA user can create separate curve for each time granularity and then use FC_Arbitrage_Free_Blend() function for blending. ZEMA profile example:

Suggested ZEMA profile:

Data Sources:

a) Monthly forward curve

b) Quarterly forward curve

c) Annual forward curve




The calculations of this FC_Arbitrage_Free_Blend function are based on no arbitrage conditions.


Figure5: Arbitrage free blending. Source: ZE. Graph created by ZEMA

Overlap calculations: This is a little more complex method but gives more flexibility to users, allowing them to employ their custom blending models using ZEMA formulas. A user can choose from a slew of formulas in ZEMA to blend forward curves including non-standardized types of contracts such as a balance of month contracts.

All of these methods will dynamically adapt with date ranges and allow for seamless transition as contracts change in the future.

To make financial data management easier and analysis intuitive use ZEMA’s Market Analyzer. Contact us to get a complete walkthrough on building and blending forward curves.