Allocation Rate – Definition

Cite this article as:"Allocation Rate – Definition," in The Business Professor, updated February 23, 2020, last accessed October 23, 2020,


Allocation Rate Definition

The allocation rate is the normal overhead for a production unit or other operation calculations. It reflects a proportion of the cash or capital spent by an investor on a final investment. In other words, an allocation rate can be defined as the amount of investment in a net sum of any fees arising out of the investment transaction.

It can also be defined as the amount of money left to invest after expenses are withdrawn when payments are transferred to a fund (for example a pension fund). The distribution rate would be 98% if, for example, the fees were 2%.

A Little More on What is Allocation Rate

The allocation rate is usually applied in the transition of cost into a cost object, which may be necessary to ensure a complete cost application to the inventory under one of the accounting frameworks. As part of the internal accounting process, an allocation rate can also be used to ensure the overhead costs are implemented in a business. The allocation rate is a percentage figure, which enables an investor to calculate the total investment capital. The measurement can be used for investment determination by means of an automatic investment plan and the calculation of the fees charged an investor for investing in a company or product.

Analyzing Product Allocation Rates

While buying and selling mutual funds, investors that use full-service brokerage service usually incur sales loads. The schedules on sales loads that can be frontend, backend or trailing are determined and divulged in a fund prospectus by mutual funds companies. Usually, the amount of sales loads invested in a product will be reduced by the total amount. An investor can use the following equation to determine the allocation rate of the capital actually invested in a product:

(Total Investment – Fees Paid) / Total Investment

The allocation rate percentage estimate allows an investor to understand better how his capital is used and how much he currently invested in a company, on which the overall assets invested and potential gains in the capital would be focused.

Looking at an example of a parent company that allocates its corporate overhead to its subsidiaries on the basis of their income. The total corporate overhead for companies is $1 million, and all of the subsidiary’s sales generated a total of $100 million. The rate of allocation should amount to $0.01 million per million of revenue given these levels of activity. Hence, if a subsidiary generates revenue of $20 million, the allocation limit requires that $200,000 be allocated to that subsidiary. The higher the fees paid by the company’s subsidiaries, the lower the overall allocation rate for the company’s subsidiaries.

Allocation Rates for Automated Investment

In general, an allocation rate refers to a percentage of the income that an investor chooses to allocate in an automatic investment plan for specific investments. Employee benefits program is an example of allocation rates for automated investments. The employer must adjust the allocation amount for the employee up to a certain level in many employee benefit programs. Another example is the personal pension plan created by most investors by choosing to use – an individual retirement account (IRA). Wrap accounts also give investors another option for making automatic investments at a fixed allocation rate through both brokerage firms and robo advisors.

Reference for “Allocation Rate”…/how-to-calculate-overhead-allocation……/the-single-rate-cost-allocation-method-in-cost-accountin… › Accounting Dictionary

Academics research on “Allocation Rate”

Subgradient methods in network resource allocation: Rate analysis, Nedic, A., & Ozdaglar, A. (2008, March). Subgradient methods in network resource allocation: Rate analysis. In 2008 42nd Annual Conference on Information Sciences and Systems (pp. 1189-1194). IEEE. We consider dual subgradient methods for solving (nonsmooth) convex constrained optimization problems. Our focus is on generating approximate primal solutions with performance guarantees and providing convergence rate analysis. We propose and analyze methods that use averaging schemes to generate approximate primal optimal solutions. We provide estimates on the convergence rate of the generated primal solutions in terms of both the amount of feasibility violation and bounds on the primal function values. The feasibility violation and primal value estimates are given per iteration, thus providing practical stopping criteria. We provide a numerical example that illustrate the performance of the subgradient methods with averaging in a network resource allocation problem.

Dynamic asset allocation in a mean-variance framework, Bajeux-Besnainou, I., & Portait, R. (1998). Dynamic asset allocation in a mean-variance framework. Management Science, 44(11-part-2), S79-S95. The aim of this article is to analyze the portfolio strategies that are mean-variance efficient when continuous rebalancing is allowed between the current date (0) and the horizon (T). Under very general assumptions, when a zero-coupon bond of maturity T exists, the dynamic efficient frontier is a straight line, the slope of which is explicitly characterized. Every dynamic mean-variance efficient strategy can be viewed as buy and hold combinations of two funds: the zero-coupon bond of maturity T and a continuously rebalanced portfolio. An appropriate dynamic strategy defining the latter is explicitly derived for two particular price processes and comparisons of the Efficient Frontiers (Static versus Dynamic) are provided in these cases.

Exchange-Rate Volatility, International Trade, and Resource Allocation: A Perspective on Recent Research, Willett, T. D. (1986). Exchange-Rate Volatility, International Trade, and Resource Allocation: A Perspective on Recent Research. Journal of International Money and Finance, 5, S101-S112. Recent research on the effects of exchange-rate volatility is discussed and Directions for future research are explored. The need to pay more attention to the effects of diversification and firms’ characteristic is emphasized. It is suggested that while international risk has risen substantially since floating, the differential between international and domestic risk may not. This could help explain the failure of international trade to fall drastically and suggests that exchange rate volatility has been more a reflection than an independent cause of underlying instability.

Financial market liberalisation in LDCs: the incidence of risk allocation effects of interest rate increases, Willett, T. D. (1986). Exchange-Rate Volatility, International Trade, and Resource Allocation: A Perspective on Recent Research. Journal of International Money and Finance, 5, S101-S112. ’High’ deposit interest rates are central to the financial liberalisation argument. The article investigates the relatively neglected issue of who must pay. Two issues are stressed. If loan charges increase the incidence falls on (typically), highly geared businesses and overall financial saving may not rise as claimed. Second, although loan charges need not increase (and enhanced credit availability may compensate borrowers if they do), the financial risks of banks increase. These risks are pertinent to monetary policy and may force actions contrary to the liberalisation approach. Institutional developments to foster the supply of risk‐bearing capital are emphasised in conclusion.

Capital allocation and delegation of decision-making authority within firms, Graham, J. R., Harvey, C. R., & Puri, M. (2015). Capital allocation and delegation of decision-making authority within firms. Journal of Financial Economics, 115(3), 449-470. We use a unique data set that contains information on more than 1,000 Chief Executive Officers (CEOs) and Chief Financial Officers (CFOs) around the world to investigate the degree to which executives delegate financial decisions and the circumstances that drive variation in delegation. Delegation does not appear to be monolithic; instead, our results show that it varies across corporate policies and also varies with the personal characteristics of the CEO. We find that CEOs delegate financial decisions for which they need the most input, when they are overloaded, and when they are distracted by recent acquisitions. CEOs delegate less when they are knowledgeable (long-tenured or with a finance background). Capital is allocated based on “gut feel” and the personal reputation of the manager running a given division. Finally, corporate politics and corporate socialism affect capital allocation in European and Asian firms.

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