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Options as Silver Bullets: Valuation of Term Loans, Inventory Management, Emissions Trading and Insurance Risk Mitigation using Option Theory
- Source :
- Annals of Operations Research, (2022), S.I.: Business Analytics and Operations Research, 001-041
- Publication Year :
- 2016
-
Abstract
- Models to price long term loans in the securities lending business are developed. These longer horizon deals can be viewed as contracts with optionality embedded in them. This insight leads to the usage of established methods from derivatives theory to price such contracts. Numerical simulations are used to demonstrate the practical applicability of these models. The techniques advanced here can lead to greater synergies between the management of derivative and delta-one trading desks, perhaps even being able to combine certain aspects of the day to day operations of these seemingly disparate entities. These models are part of one of the least explored, yet profit laden, areas of modern investment management. A heuristic is developed to mitigate any loss of information, which might set in when parameters are estimated first and then the valuations are performed, by directly calculating valuations using the historical time series. This approach to valuations can lead to reduced models errors, robust estimation systems, greater financial stability and economic strength. An illustration is provided regarding how the methodologies developed here could be useful for inventory management, emissions trading and insurance risk mitigation. All these techniques could have applications for dealing with other financial instruments, non-financial commodities and many forms of uncertainty.
- Subjects :
- Quantitative Finance - Pricing of Securities
Economics - General Economics
Quantitative Finance - Portfolio Management
Quantitative Finance - Trading and Market Microstructure
91G20 Derivative securities, 90B05 Inventory, 60G25 Prediction theory, 91B76 Environmental economics, 68U35 Computing methodologies for information systems
Subjects
Details
- Database :
- arXiv
- Journal :
- Annals of Operations Research, (2022), S.I.: Business Analytics and Operations Research, 001-041
- Publication Type :
- Report
- Accession number :
- edsarx.1609.01274
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/s10479-022-04610-w