Hickory Farm Case Study

1624 Words7 Pages
1. Risk Modeling A study conducted by King’s College London said that, risk modeling is about modeling and quantification of risk. For the financial industry, the cases of credit-risk quantifying potential losses due, such as to bankruptcy of debtors or market-risks quantifying potential losses due to negative fluctuations of a portfolio's market value are of particular relevance. Operational risk, quantifying potential losses incurred due to failing processes is a relevant issue for any form of organization. Besides, according to Curtis, risk model is a mathematical representation of a system, commonly incorporating probability distributions. Models use relevant historical data as well as “expert elicitation” from people versed in the topic…show more content…
Recognizing this issue, Hickory Farms streamlined itself, reduce their number of products from 2,500 to 300 with more modern visuals, descriptions, and other features, including less packaging and more recycled content. The company also overhauled their website, making it easier to shop online. All of this streamlining resulted in a price reduction of 13% that Hickory Farms was able to pass on to their customers. Brand strategist Jennifer Woodbery believes that this was a smart move, making the most of Hickory Farms' trusted name and image with an effective rebranding of offerings. (Online…show more content…
Although, the basic statistical properties of financial data during stable periods remain (almost) the same as during crisis is the basic assumption in most statistical risk modelling. The functional form of risk models normally is not updated frequently and model parameters get updated slowly, as a result, risk models do not work well in crisis. Statistical properties of data during crisis is different that statistical properties in normal times. Risk modelling affects the distribution of risk however risk is not separate stochastic variable assumed by most risk models. If a lot of market participants need to execute the same trading strategies during crisis, they will change the distributional properties of risk considerably. Therefore, the distribution of risk is different during crisis than in other periods, and risk modelling is not only useless but may disturb the crisis, and lead to large price swings and lack of liquidity.(Danielsson, J.
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