Simulation model for the financing strategies of a leasing company.
It is often the case that payment sources or tools can be combined in a financing strategy that would lead to a minimum financing cost. Such an approach is recommended when the most advantageous financing tool doesn't fully cover the needs for financing. We will go on by outlining a simulation model of financing strategies for equipment purchases by a leasing company.
1.1 Formulating the problem
Elaborate the financing strategy based on a weighted average capital cost minimum for a purchase transaction of one or several products by a leasing company under the following conditions:
--Products are homogeneous and are purchased simultaneously;
--Products are non-homogeneous and are purchased simultaneously;
--Products are purchased on different dates.
The financing strategy entails awareness of the following information:
--Possible financing sources;
--The access conditions, namely:
* The access time-frame (the period of time since the moment the source was called on till the time the financing fund is assigned);
* The source threshold (the minimum and maximum amounts outlining the limits of source access);
* The accessing costs for a certain source;
* The value of products to be financed;
* The financing period (deadline).
Moreover, access to the respective financing source is conditioned by the business and credit worthiness of the economic actor, namely:
--It should not have outstanding debts to the budget;
--It should undertake a profitable activity;
--It should not have debt arrears or outstanding loans or interests rates, losses or be bankrupt;
--It should be able to refund the credit at deadline and to pay interest;
--It should submit collaterals and insurance.
In order to access a bank credit, it should also submit one of the following collaterals:
--Collateral/mortgage for owned or purchased goods;
--Assignment of debts on cash-ins from other sales contracts (letters of credit);
--Assignment of debts on cash-ins from the insurance policy on the suretyship bond;
--Assignment of debts on cash-ins from the insurance policy of the respective good; Or one of the following secondary bank guarantees:
--Letter of bank guarantee;
--Bills of exchange and promissory notes;
--Collateral for real estates.
Input above-mentioned entry data based on which the proposed simulation algorithm will identify financing sources, which can be called upon according to the access conditions. Thus the algorithm will compare access time-frames for every individual source with the financing deadline imposed by the client. Such comparisons rule out sources with a too high access time-frame. If, for instance, the deadline for which the leasing company wants to obtain financing is of ten days, sources with significantly higher access time-frames cannot be considered.
In the case of accessible sources, the thresholds for every source shall be compared against the value to be financed (the required investment). Should a source or several sources separately comply with the required investment, the unitary cost for every source shall be then computed, and the minimum-cost source will be selected, with the financing to be wholly covered by that source. If no source evinces a threshold that exceeds the required investment, combinations of sources will be taken into account in order to compute the weighted average cost of the sources (Boobyer, 2003).
From a mathematical point of view, this algorithm can be assimilated in a generic form by the following system of equations (Andreica et al., 2003):
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (1)
Where: x1 ... xn--represent the amounts to enter financing from sources 1 ... n;
c1 ... cn--unit costs of sources 1 ... n;
q1 ... qn--minimum values for which sources can be accessed;
Q1 ... Qn--maximum sources thresholds
2. ALGORITHM DESCRIPTION
The algorithm was integrated in the IT product LEASYM made in the Visual Basic.Net programming environment, representing a program product for assisting leasing company managers in adopting financing strategies for investment products requested by clients. The program simulates the selection of attracted financing sources and of self-financing, its ultimate goal being to minimize the financing cost (if sources can wholly support the transaction financing) or the weighted average cost (in the case when source participate up to different extents in covering the required investment).
The product analyzes the main financing sources, among the ones most often used in the real-life environment (Marks et al., (2) (0) (0) (5) ) namely:
Self-financing entails capitalizing on the profits and depreciation funds of the respective economic actor.
Purchased products can be homogeneous or non-homogeneous (in this case, we need to know how many distinctive products are required for delivery and, for every individual type, the number ad value of each product). This information is the foundation for computing the initial required financing that the importer must have.
2.1 Stages in the algorithm for financing cost minimization Stage 1: Introducing initial data
--client (beneficiary) data: number of products, value per product (based on which the initial required financing shall be determined), the down payment to the importer and the desired deadline for product delivery. The amount to be provided by the client as down payment will diminish the importer's required financing
--specific data for leasing companies: the thresholds they can reach through various attracted financing sources, the euro-lei exchange rate (needed in the case of foreign credit financing), the time frames within which the company gains access to the respective financing sources, as well as the self-financing threshold the company has and that can be used to finance the transaction.
--specific data for every financing source under analysis: fore foreign or domestic credit financing--credit period, interest rate, commissions incurred by the bank, as well as the type of return used, with constant annuities or equal return rates; in the case of bond issues, the following entry data are necessary--nominal bond value, coupon value, deadline, inflation rate and the commission to be paid to the intermediary.
Stage 2. Checking source eligibility (Checking access time frames for sources)
Access time frames for every individual source are compared against the delivery deadline set by the client. Those sources with access time frames that are below the delivery deadline can be deemed eligible sources, and thus the first filtering is performed (Limoncelli, 2005). The algorithm will henceforth operate on eligible sources.
Stage 3. Checking the possibility of supporting the transaction
If access time frames to the importer's financing sources are within the delivery deadline required by the client and if the amounts obtained from the respective sources allow for the transaction to be financed, this can be fully performed, through one, two or even several attracted sources (cost minimization being the goal) or through combinations of sources, by computing the weight for each of them in the required financing (the weighted average cost). If these conditions are not fulfilled the transaction shall be rejected.
Stage 4. Calculating source costs
During this stage unit costs are calculated for every eligible source that can partly or wholly finance the transaction under work: bond issue, domestic credit financing, foreign credit financing (in this case, the exchange rate should also be introduced, in order to make it possible to compare the cost of this financing with other costs), self-financing (the costs are calculated as an opportunity cost, for instance how much the importer would stand to gain if they deposited the money in the bank instead of covering the respective transaction), joint venture (the cost is again calculated as an opportunity cost, for instance how much the economic actor, associated to the importer, would stand to gain if it deposited the money in the bank instead of investing in the ongoing transaction) (Fabozzi, 2002).
Stage 5. Source hierarchy. Selecting the source / the combination of low-cost sources. Calculating the final minimum cost.
If the self-financing threshold allows for the full financing of the purchase, then this source shall be compared against the attracted accessible source, based on the minimum cost criterion. The self-financing cost is calculated as an opportunity cost--the earning turned in by the company by self-financing the client's investment project. This should amount to at least the one obtained by shareholders from other investments with a comparable risk liability.
The same calculation method is to be applied in the case of joint venture, the difference residing in the standpoint for the respective cost. To put it more clearly, for the associated economic actor, the cost of the invested amount will again be an opportunity cost--the earning obtained by the latter must be at least as high enough as the one obtained in case the associate invests in the respective project instead of other projects with a comparable risk liability.
In case the money obtained from all sources we have access to do not allow for a full financing of the transaction, for every individual case, check if the purchase can also be supported by self-financing resources. If it can, calculate the weight of every source in the required financing and, further on, the weighted average cost of the financing. If no, try supporting the purchase by associating with another economic actor interested in the respective transaction. If even this means cannot cover the purchase, then the transaction shall be rejected, either because of insufficient funds, or because of too high entailed costs.
In case at least one of the sources that the importer has access to can fully finance the transaction, with the other sources supplying lesser amounts than the required financing, the transaction will be undertaken through a combination of financing resources if the unit costs of partial sources are lesser than the cost of the integral source. These combinations are based on the ascending ranking of unitary costs for all possible financing sources.
If the source that can provide full financing for the transaction has the smallest unit cost, then it will make up the optimum financing means. If not, it can have a certain weight in making up the weighted average financing cost.
The simulation model presented above and the Leasym software based on it are some very important tools for the managers of the leasing companies, helping them to solve a very important issue in their activity: the financing strategy, which becomes more and more difficult to figure in the actual dynamic and unstable global financial market. We undertake to pursue further, extended research along this line in the future.
Andreica, M.;Andreica, C.; Mustea-Serban, I.; Mustea-Serban, R. (2003): The Financing Decision in Leasing, Cibernetica MC, ISBN 973-96916-0-9, Bucharest
Boobyer, C. (2003): Leasing and Asset Finance--Fourth Edition, Euromoney Books, ISBN 978-1855649859, London
Fabozzi, F.J. (2002): The Handbook of Financial Instruments, Wiley Finance, ISBN 978-0471220923, Hoboken, New Jersey
Limoncelli, T. (2005): Time Management for System Administrators, O'Reilly, ISBN 978-0596007836, Cambridge
Marks, K.H.; Robbins, L.E.; Fernandez, G.; Funkhouser, J.P. (2005): The Handbook of Financing Growth: Strategies and Capital Structure, Wiley Finance, ISBN 978-0471429579, Hoboken, New Jersey
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|Author:||Folcut, Ovidiu; Ciocirlan, Doinita; Serban, Razvan Mustea|
|Publication:||Annals of DAAAM & Proceedings|
|Date:||Jan 1, 2008|
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