Microsoft technology licensing, llc (20240127368). NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION simplified abstract
Contents
- 1 NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION
Organization Name
microsoft technology licensing, llc
Inventor(s)
Firas Hamze of Vancouver CA (US)
NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127368 titled 'NON-PARAMETRIC METHODS OF RESOURCE ALLOCATION
Simplified Explanation
The abstract presents a methodology for optimizing a value at risk associated with an allocation of objects with variable performance and loss characteristics, using nonparametric estimates of the portfolio loss density and an efficient approach to computing the value at risk gradient.
- Explanation of the patent/innovation:
- Methodology for optimizing value at risk associated with object allocation - Utilizes nonparametric estimates of portfolio loss density - Efficient approach for computing value at risk gradient - Allows inclusion of constraints on the strategy - Solves optimization problem using techniques like sequential quadratic programming
Potential Applications
The technology can be applied in various fields such as finance, risk management, and investment strategies.
Problems Solved
- Optimizing value at risk associated with object allocation - Dealing with variable performance and loss characteristics - Efficient computation of value at risk gradient
Benefits
- Improved risk management - Enhanced decision-making in investment strategies - Increased efficiency in optimizing value at risk
Potential Commercial Applications
- Financial institutions - Investment firms - Risk management companies
Possible Prior Art
There may be prior art related to optimization techniques for value at risk in finance and risk management industries.
What are the limitations of the methodology proposed in the patent application?
The abstract does not mention any potential limitations of the methodology proposed. It would be important to understand any constraints or drawbacks of the approach before implementing it in real-world scenarios.
How does the methodology compare to existing techniques for optimizing value at risk in investment strategies?
The abstract does not provide a comparison with existing techniques for optimizing value at risk in investment strategies. It would be beneficial to know how this methodology differs from or improves upon current practices in the field.
Original Abstract Submitted
a general methodology is presented for optimizing a value at risk (var) associated with an allocation of objects (i.e., a strategy) having variable performance and loss characteristics. for purposes of illustration, investment strategies prescribing a portfolio of items from a set of candidates with unknown and generally correlated joint losses are discussed. the framework is based on approximating the var using nonparametric estimates of the portfolio loss density and, using mathematical insights, an efficient approach to computing the var gradient with respect to the strategy. the approach also allows inclusion of constraints on the strategy (e.g. a maximum fraction per item) and allows the var optimization problem to be solved using optimization techniques such as sequential quadratic programming.
