Enron Mail

From:vladimir.gorny@enron.com
To:james.steffes@enron.com, karen.barbour@enron.com, scott.stoness@enron.com,scott.gahn@enron.com, harry.kingerski@enron.com
Subject:Curve Validation
Cc:ted.murphy@enron.com, david.gorte@enron.com, steven.kean@enron.com
Bcc:ted.murphy@enron.com, david.gorte@enron.com, steven.kean@enron.com
Date:Thu, 20 Apr 2000 06:27:00 -0700 (PDT)

Outlined below are some details of the existing curve validation process and
its application to the proposed validation of tariff curves.

Wholesale Curve Validation

The existing process incorporates validation of all wholesale curves and
includes monthly validations and random curve reviews. Every month, results
of the validation are summarized in a memo and distributed to the Senior
Management. Results of the random curve reviews are brought up to the
attention of Desk Heads responsible for the respective curves and Senior
Management as necessary.

Curve Assessment
Green:
- curve is reasonable
- small P&L impact from curve shift
Yellow:
- curve is illiquid
- medium-to-large position and P&L impact from curve shift
- some ability to validate prices from external sources
Red:
- curve mark is inaccurate (based on external data obtained)
- curve is illiquid: no ability to validate externally
- significant positions and P&L impact from curve shift

Curves that are inaccurately marked based on data obtained from external
sources are urged by the Senior Management to be corrected. In the cases
where external data is not available or clear, the Senior Management urges
the respective Desk Head not to increase an already large illiquid position
or to built in a risk premium by widening the respective bid/offer spread and
not to take on positions inside of that spread.

Selection Criteria
The criteria for monthly curve selection are the following:
P&L sensitivity
Largest positions
Staleness (curves have not been marked for a period of time)
Completeness (curves that have not been validated in a long time)

The main criteria for random curve validation is new deals.

Curve Validation Tools
Broker Quotes/Other external data
Graph Analysis (curve slope vs. a peer group, curve humps/sculpting vs. a
peer group, curve shift vs. position shift, etc.)
New Deal Analysis (comparison of curve marks and executed/quoted prices)
Boundary Analysis/V@R Simulations (comparison of curve to simulated curve
boundaries using Enron's V@R Engine)
SAVA Model Comparison (comparison of curves to model generated results)


Tariff Curve Validation

Scope/Timing:
ASAP - 20 curves with the largest positions related to deals pending review:
(Frito-Lay, Quaker Oats, Starwood) - to ensure timely and smooth approval of
these deals.
Next 30-days - 20 curves with the largest positions/P&L impact
Monthly/Quarterly - 20 curves selected based on criteria described above
Randomly - curves with significant positions/P&L impact, resulting from new
deals

Data Gathering:

This Month: Listing of 20 curves (related to deals in progress) and the
related support requested by EGA (to be provided by Scott Stoness)
On-going Basis: The process of obtaining data should be streamlined and the
curve validation process should be relatively painless:
- RAC should have access to the curve data (Minal Dalia is fully devoted
to EES and is currently residing on the EES floor)
- Curve assumptions should be documented (to be provided by Scott Stoness)

Execution/Reporting:

RAC, EGA and EES Risk Management Group work together on curve validation
utilizing available tools and work on developing new tools
Utilize the Wholesale Curve Assessment methodology (Green, Yellow, Red)
Generate a curve validation report (see template attached)
Provide feedback to the Desk Heads and distribute the Curve Validation Report
to Enron and EES Senior Management



Other Curves

Other curves related to EES business should be gradually incorporated into
the aforesaid process (ancillary services, congestion, DSM and labor related
curves) - let us set a timetable.

In conclusion, curve validation results should be evaluated in conjunction
with other risk analytics: stress testing of prices, volatilities and
correlations, Value-at-Risk/Capital-at-Risk analysis, performance measures,
capital allocation framework, etc.

Vlady.