ASSET BACKED TRADING
Table 1: State of Asset-Based Trading Support Analytics
Asset-Based Trading Support Analytics (ETRM + Spreadsheets)
Multiple spreadsheets individually developed and maintained
High model risk Manual workflow/ intensive
Disconnected and/or unsupported trading analytics function
Reliance on individual expertise. Personnel risk
Source: NQuantX, LLC
for statistical and mathematical computing (such as C++, R and Matlab) can enable analysts and traders to monitor the impact of alternative hedging strategies or perform sensitivity analysis to change in market conditions or evaluate operational events. Stand-alone spreadsheets play a critical role and
can provide quick answers not available through other systems, but their use also introduce other issues that need to be evaluated. For example, traders and analyst still spend a significant amount of their time maintaining and updating those spreadsheets. That process is highly prone to human error, and therefore introduces significant model risk for their firms. In addition, the more sophisticated spreadsheets
are not easily audited and often fall outside the control of the risk, IT and audit groups. For example, if a trader moves to a competitor, poorly documented and tested spreadsheets are likely to be abandoned, which results in a loss of know-how for the firm. Instead of relying on inflexible CTRM systems or
stand-alone spreadsheets, a better solution would be one that would allow traders and risk managers to continue using spreadsheets as their front- end tool, but with integrated data tools as well as analytic support engines running underneath and performing the intensive computation tasks. The right modular framework design would also increase the communication with other legacy systems.
NQuantX Global Commodity Workbench™ was designed to meet needs of firms with asset-based strategies such as valuation, hedging and risk
quantification by offering software solutions and advisory services. The end result is that traders can continue working with spreadsheets, but in a controlled environment and where it is easier and faster to deploy new solutions.
Footnotes 1. See
www.commodities-now.com for more information.
A flexible analytic engine for asset-based
strategies should allow for the segregation of analytic processes to enable modular design and increased scalability. For instance, the separation
The right modular framework design
would also increase the communication with other legacy systems systems
of instrument-level valuation analytics from the market scenario generation engine increases the ease of editing or adding new valuation or Monte Carlo routines in the future. •
Carlos Blanco is Co-Founder and Managing
Director of NQuantX, LLC, a financial engineering firm that develops customized software to design and implement hedging programs and trading strategies, as well as valuation and risk measurement of energy derivatives, long term contracts and physical assets. He also conducts several courses on energy derivatives hedging, pricing and risk management, as well as credit and counterparty risk management for the Oxford-Princeton Program. He is a lecturer on
risk management at the University of California, Berkeley.
E:
carlos@nquantx.com
Michael Pierce is Co-Founder and Director of Financial Engineering at NQuantX LLC. Some specific areas of development include energy forward curve calibration and modelling,
development of a hybrid electricity model used in Monte Carlo real asset valuation of generating assets and load serving agreements, correlation
matrix calibration and multi-regional temperature modelling for weather derivatives
www.
nquantx.com September 2011 81
NQuantX Asset-based Trading Solutions (Integrated analytics with Excel interface)
Excel interface to risk libraries
Tested and supported code and applications. Source control
Automated Workflow
Dedicated analytics group committed to continuous enhancements
Best of breed. Access to financial engineering support group
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