Merrill Lynch Improves Liquidity Risk Management for Revolving Credit Lines
| Autor: | Russ Labe, Wenyue Hsu, Tom Duffy, Lihua Yang, Bonnie Liao, Manos Hatzakis, Xiangdong (Sheldon) Luo, Je Oh, Adeesh Setya |
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| Rok vydání: | 2005 |
| Předmět: | |
| Zdroj: | Interfaces. 35:353-369 |
| ISSN: | 1526-551X 0092-2102 |
| DOI: | 10.1287/inte.1050.0157 |
| Popis: | Merrill Lynch Bank USA has a multibillion dollar portfolio of revolving credit-line commitments with over 100 institutions. These credit lines give corporations access to a specified amount of cash for short-term funding needs. A key risk associated with credit lines is liquidity risk, or the risk that the bank will need to provide significant assets to the borrowers on short notice. We developed a Monte Carlo simulation to analyze liquidity risk of a revolving credit portfolio. The model incorporates a mix of OR/MS techniques, including a Markov transition process, expert-system rules, and correlated random variables to capture the impact of industry correlations among the borrowers. Results from the model enabled the bank to free up about $4 billion of liquidity. Over the 21 months since the bank implemented the model, the portfolio has expanded by 60 percent to over $13 billion. The model has become part of the bank’s tool kit for managing liquidity risk and continues to be used every month. |
| Databáze: | OpenAIRE |
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