The firm planned to build a marketplace for energy derivative products whose values were very sensitive to the correlation between heating oil, gasoline, and crude oil prices. In response to the client's request, Prescio Consulting undertook an exhaustive analysis of these energy market correlations. Prescio Consulting utilized advanced econometric methods to estimate time varying correlations that depend on prevailing market conditions (such as the spread between gasoline and crude oil prices). Prescio Consulting also developed an algorithm to forecast the relevant correlations over any time horizon. The client has implemented this methodology in its new energy trading operations.
The utility recognized that pricing approaches which applied in financial markets (and some other commodity markets) were inappropriate for electricity due to the unique characteristics of this product. Prescio Consulting proposed and implemented a novel valuation and risk measurement approach that addressed the utility's concerns about traditional pricing approaches. The Prescio Consulting approach (described in our Electricity page on this website) exploits the transparency of the fundamentals in the power market and explicitly models the effects of the non-storability of power, the seasonality of demand, and the non-linearity of power prices. Prescio Consulting used this model to create a customized derivatives pricing software for the client.
The utility wanted to develop a new load profiling model and application software in order to aggregate the present and future customers into finer load profile classes. Load profiling classifies a customer into a given group according to certain key characteristics. The finer the aggregation within a group, the higher the accuracy of the load profiles. The primary purpose of a finer aggregation is to attempt to reduce the biases resulting from assigning a class load shape to a subgroup of customers whose shape may be different from the class shape.
Prescio Consulting designed a Load profiling model to statistically attempt to segment different classes of customers into finer sub-classes with homogenous and functional characteristics This was done to minimize misclassification errors. Additionally Prescio Consulting fully incorporated weather patterns and economic indicators, as well as time characteristics into the profile curve models to make them dynamic and realistically driven by these key factors. The load model was also designed to forecast monthly average usage per profile class. These monthly aggregates could then be distributed over hours in each forecasted month, factoring in expected weather conditions, time of day characteristics, and economic activity trends.
A customer-switching model was developed to calculate switching impacts on the number of customers in each profile class. The switching model was used to generate the dynamics of the population over time within each profile class. Customized application software was then designed and developed to be seamlessly incorporated within the existing hardware and software architecture of the utility. The model was coded in C with a VB interface and Oracle 8i database.
A model was built that could analyze a given consumer portfolio, be able to filter customized portfolios given an original portfolio for different loan variable scenarios, and value the different portfolios and report the portfolio results. Additionally, the model was designed to be able to compare the values of portfolios created under different loan variable scenarios. The application software developed for the model included capabilities for analysts to perform ad-hoc statistical analysis on the portfolio data as well.
The project required an in-depth analysis of the data flow from various data storage systems, data flow within the software, reporting, model assumptions, and logical and coding errors in the software. Prescio Consulting was to perform the work within a specific period of time so that the client could meet an important deadline. After completion of the initial project, the engagement was extended to include several additional projects. The client requested further work on incorporating major changes and additions to the model and the software to address several loan history idiosyncrasies due specifically to the clients' operational systems.
The initial project and the extensions were performed and implemented in record time and exceeded the clients' expectations.
Prescio Consulting was requested to conceptualize the model and develop an application that could be applied by different levels of staff and management. The client requested that the model and the application be built in a way that allowed for maximum flexibility in data storage formats, operating systems, and reporting platforms. In addition, the client requested that the model be based on a conceptual platform similar to the Value at Risk concept for ease of decision making.
The project called for thorough analysis of the client's portfolio of products and data. Modification of the client's data was required to extract relevant information required by the Average Loss Rate analysis and Markov forecasting model. This information included determining data for variables such as Outstanding, Commitments, Chargeoffs, Recovery, and LTVR among others. Prescio developed the application to extract the data in the format required by the Migration Model. Prescio proceeded to exceed the client's expectations by both implementing the application software and training the client's personnel in record time.
The client's personnel recommended to senior management that Prescio Consulting address some of the Bank's other Risk Measurement and Management issues as well as its quantitative and business process issues.
The project requires thorough understanding of the clients business, including the client's portfolio of products, current risk management methodologies, business processes, systems, data architecture and data flow. This intimate knowledge of the client is necessary in order to apply the Basel II Accord's recommendations to the client's unique conditions.
The project is current and an update will be provided as the project is completed.
The project required complete understanding of the banking loan process and different scenarios for different loan types. Although being a completely new project for Prescio, we at Prescio took it as a challenge and worked around the clock to understand a loan process. We were able to deliver to the client a thorough detail on the loan disbursement process