Allocation 3M 4+

Machine learning and data analysis are increasingly used in daily work to improve the quality of decision-making and work efficiency. Allocation3M uses three mathematical statistical models to calculate the resource allocation ratio of diversified project portfolios, which can help you analyze resource allocation problems in your work. Resources can be time, manpower, products, materials, budget, etc.

For example, you can allocate resources based on the demand for coffee beans in each region and seek the allocation rate that maximizes sales growth.
For example, you can allocate resources based on labor costs in each region and seek the allocation rate that minimizes cost volatility.
For example, you can allocate resources based on the price of raw materials in each region and seek the allocation rate with the same price volatility.

Mean-Variance Model:
This model uses the "expected growth rate" and "volatility" of the project to configure the optimal "allocation ratio”.
The core idea of the Mean-Variance model is that users can reduce portfolio volatility by holding a diversified portfolio of projects. Diversification may allow the same expected growth rate with reduced volatility.

Black-Litterman Model:
This model adds the user's prediction of the project growth rate to configure the optimal "allocation ratio”.
The "Black-Litterman" model is based on the "Mean-Variance" model by adding the user's opinion of the project growth rate to configure the optimal "allocation ratio”.

Risk-Parity Model:
This model requires that each project in the project portfolio be assigned the same volatility weight.
The purpose of both the Mean-Variance model and the Black-Litterman model is to optimize the expected growth rate, while the Risk-Parity model is to optimize the volatility.
The core idea of the "Risk-Parity" model is to require each project to maintain the same volatility contribution to the overall project portfolio. The "risk parity" strategy is to expect the project portfolio to maintain the effect of risk diversification in different environments.