KR20050107144A - System for the optimization of corporate financial structure - Google Patents

Abstract

The present invention relates to an analysis system for optimizing a corporate debt structure, the method comprising: defining a financial target function of a company and establishing an analysis model according to the target function; Reflecting constraints such as corporate business environment, financial market environment and current debt structure; Creating various financial strategy scenarios and performing simulations under given conditions for each of these scenarios; Presenting the simulation results and finding an optimal scenario; Verifying the effect on the financial strategy; Characterized in that it comprises a.

According to the system for optimizing the debt structure of the company according to the present invention, the financial costs are greatly increased by integrating the exposure of the operating sector in the corporate management environment and the exchange rate and interest rate level, volatility, correlation, and future prospects of the financial market environment. In addition to savings, it also has the effect of enabling effective scientific financial strategies to eliminate unnecessary currency and interest rate risks. In addition, there is an effect of increasing the user's confidence in adopting a new financial strategy through various comparative analysis of the strategy derived from the analysis method for the corporate debt structure optimization and the current debt strategy of the present invention.

Description

System for the Optimization of Corporate Financial Structure

The present invention relates to an analysis system for optimizing a company's financial strategy, and in particular, the structure of interest rates by currency of debt, and exposes companies such as currency risk and interest rate risk in consideration of the company's business environment and external financial market environment. I would like to present an analytical method that systematically explores financial strategies that maximize the expected return of the business while minimizing the financial risks that have been made.

The main technologies that are related to the financial strategy of a conventional company can be roughly classified into a technique for measuring risk and a portfolio optimization technique. Among them, VaR (Value at Risk) and its application forms, such as Earnings at Risk (EaR) and Cash Flow at Risk (CFaR), are technologies that have been developed in the financial sector. The downside was to focus only on measuring and controlling the risks inherent in the strategy and not taking into account the expected returns from adopting the strategy.

On the other hand, Markowitz's portfolio theory is a representative technology that considers both risk and profit at the same time, but it has been widely applied in the asset management field of financial institutions, but it has not been applied to the corporate debt portfolio.

In the case of corporations, there was no case of applying Markowitz's portfolio theory. Unlike financial institutions, corporations are divided into business and financial sectors.The methodology for unifying the risk and profit factors of these two sectors and the specific model to apply them are It was difficult to develop. Therefore, effective analytical methods for optimizing a company's financial strategy have not yet been developed. As a result, companies have too much risk to reduce their financial costs or unnecessarily high financial costs to control their risks. .

An object of the present invention to solve the above problems is that, under the situation that the exchange rate and interest rates fluctuate randomly, the financial target of the company is adjusted when the financial strategy is adjusted by changing the composition of the debt currency and interest rate conditions. It provides an analytical system that analyzes how it is affected and explores financial strategies that optimize goals in terms of risk and returns.

Another object of the present invention is to present how the financial target function is explicitly changed when a company changes its analysis target to ordinary income, cash flow, financial cost, etc., and factors affecting the target function (variables). ) And an analytical model that specifically identifies the magnitude (sensitivity) of the impact.

It is still another object of the present invention to provide a verification method that identifies in advance how likely the financial strategy presented according to the above analysis method is to achieve the expected performance and confirms that such performance is performed afterwards. .

In order to achieve the above object, an analysis system for optimizing a company's debt structure according to the present invention includes: defining a financial goal function of a company and setting an analysis model according to the goal function, a business environment and a financial market environment of the company Reflecting constraints such as absence structure, creating various financial strategy scenarios and performing simulations under given conditions for each of these scenarios, presenting the simulation results and finding an optimal scenario and It characterized in that it comprises the step of performing the effect analysis.

Defining a financial target function of the company and setting an analysis model according to the target function may include setting an analysis target according to an analysis purpose, and setting a currency risk criterion, an interest rate risk criterion, and an analysis period.

It supports both cash flow and accounting profit and loss criteria and further expands to select specific target variables so that they can be selectively applied according to the purpose of analysis without pre-setting the targets of risk and profit of the financial target function of the company. It can be characterized by.

Exposures arising from financial activities in accordance with the analysis target set for the purpose of the analysis ( = Financial expenses at profit and loss, = Cash-based financial expenses) is characterized by setting a separate analysis criteria.

In setting the exchange risk standard, the increase or decrease of the principal repayment burden due to the exchange rate fluctuation is Is defined as (wherein = Exchange rate sensitivity of fixed rate liabilities, = Exchange rate sensitivity of floating rate liabilities, = share of fixed-rate liabilities of the i currency, = share of floating rate liabilities in the i currency, = rate of change of the exchange rate of the i currency, and = Total interest-bearing liabilities.) On an accounting basis, , Is = = 1, and in the case of cash flow basis, it becomes the ratio of the amount of repayment of the principal during the relevant period among the corresponding debts (fixed interest rate debt and variable rate debt), and can be set arbitrarily.

In setting interest rate risk criteria, a model for calculating interest rate exposure of nominal financial expenses is Is defined as (wherein = a variable that determines the cost of the fixed rate liabilities of the i currency, = variable that determines the cost of floating rate liabilities in the i currency.) , (Wherein = Interest rate sensitivity of fixed rate liabilities, = Interest rate sensitivity of floating rate liabilities = i's currency Long-term rate at time = i's currency Long-term rate at time = additional interest rate for the long-term rate of the i currency, = i's currency The level of short-term interest rates at that time, = i's currency The short-term interest rate level at the time point, and = the addition rate to the long-term rate of the i currency. and Is determined according to the financial environment of the company and can be set arbitrarily.

The interest rate sensitivity of the nominal financial expenses , (Wherein = Interest rate risk exposure weighted by expiration year.), It is possible to weight the interest rate risk for future coupons by changing parameters arbitrarily.

In reflecting the constraints of the company's business environment, financial market environment, and current debt structure, the company's business environment constraints are based on the exchange exposure, capital expenditure currency exposure, and debt size of the operating sector in the financial environment. It is made by each estimation, and the financial market environment is characterized by reflecting the conditions common to companies such as exchange rate and interest rate, volatility and correlation of each financial variable and special conditions of individual companies.

In the financial market environment, it is possible to input and change the accessibility (financial possibility) and the credit spread in each market, which are special conditions for individual companies.

Generating the various financial strategy scenarios and performing the simulation under given conditions for each of these scenarios includes generating a strategy scenario by weighting a borrowing method according to the interest rate of each currency of the debt and the financial exposure of each scenario. Calculating a total exposure by calculating the total financial exposure and the business exposure; calculating an expected value and a variance for the total exposure; and storing the resultant value.

The scenario for debt composition is automatically generated by the system, and the upper and lower limits of the composition ratio (weighted values) of each variable are processed at regular intervals within the range, limiting the accessibility (financial possibility) to the financial market. It is characterized by making a condition.

In the step of calculating the financial exposure of each scenario, the effective financial cost is the sum of the nominal financial costs, the interest payment and the increase and decrease of the principal repayment burden due to the exchange rate fluctuation, and the exposure recognition criteria are determined according to the criteria defined in the model. do.

By reflecting the short-term outlook of each financial variable in the simulation process, it is possible to effectively grasp the effect of short-term changes in exchange rates and interest rates on the simulation results.

The effect analysis on the financial strategy may include comparing the strategy, pre-verification and performance analysis to analyze the effect of the strategy generated by applying the analysis method for optimizing the debt structure. .

In the strategy comparison analysis, if any strategy is to be adopted as a target strategy, the strategy may be compared with an existing strategy or any other strategy used as a comparison criterion to calculate a probability of achieving superior results.

The pre-verification is characterized in that if a certain strategy that can be classified as an effective strategy according to the simulation result is adopted at a certain point in time in the past, the probability that the strategy is superior to the existing strategy is calculated. .

When the performance analysis actually adopts a specific strategy classified as an effective strategy according to the simulation, the difference between the post-performance of the strategy and the originally estimated value is the actual realization value of the target function and the expected realization value when the target strategy is adopted. Deviations from financial activities expressed in terms of differences, the effect of strategy changes expressed as the difference between the expected realization value when the target strategy is adopted and the expected realization value when the existing strategy is adopted, the expected realization value when the existing strategy is adopted, In case of adopting the existing strategy, it is decomposed by the influence of market change expressed by the difference of expected value estimated at the time of strategy establishment.

Hereinafter, the features and operation principles of the present invention will be described in more detail.

Financial variables that determine a company's risk (volatility) and revenue (corporate value or accounting profit) are exchange rates and interest rates. When exchange rates and interest rates are given to the market, the factors that determine a company's risks and profits are the exposure of the operating sector, the exposure of the financial sector and the exposure of interest rates. Again, the factors that determine currency exposure and interest rate exposure in the financial sector are the currency composition of debt and the composition of interest rate conditions. Here, the exposure of the operating sector is exogenous given depending on the nature of the business in which the company operates, while the exposure and interest rate exposure of the financial sector can be changed according to the company's strategic decision. Thus, companies can control risks and returns by using the currency composition of debt and the composition of interest rate conditions as a policy variable, and further explore financial strategies that optimize risks and returns.

In the present invention, for example, the currency to be analyzed is set in won (KRW), dollar (USD), yen (JPY), and euro (EUR), and one short- and long-term base rate is set for each currency. When we correlate with a certain volatility, we create a number of scenarios with different currency-specific rate condition configurations and analyze the risks and returns of each of these scenarios. Here, the limitation of the currency to be analyzed is for convenience of system implementation and does not limit the invention.

First, in setting up an analysis model, an analysis target setting, a currency risk criterion, an interest rate risk criterion, and an analysis period are set according to an analysis purpose.

In setting the analysis target, the present invention supports both cash flow basis or accounting profit and loss basis so that the user can selectively apply according to the analysis purpose without prior confirmation, and furthermore, the user can select a specific target variable. do. In other words, the analysis target can be extended by processing the main account subjects constituting the income statement as a parameter and the analysis subject as a combination of the account subjects.

Next, the criteria for determining the extent of exchange risk and interest rate risk, that is, setting the recognition criteria for risk exposure, can be divided into cash and accounting standards, which are consistent with the applicable criteria according to the variables to be analyzed. There is no limit on the combination of analytical targets and exposure recognition methods.

When the analysis targets are classified into three categories: ordinary income, cash flow, and financial cost, the standard exposure recognition methods are shown in Table 1.

Target function Business port Financial Port Sum Ordinary profit Cash flow Financial costs -

(From the above, = Operating profit, = Operating cash flow, = Capital expenditure, = Financial cost and profit or loss = Financial cost in cash)

The difference between cash flows and operating profits generated from operating activities in Table 1 is generally an established accounting device and therefore does not require a separate explanation. However, exposures from financial activities Wow The analysis criteria should be determined separately, which is a major feature of the present invention.

Exposures from these financial activities are currency exposures and interest rate exposures. If this is expressed as an equation, Equation 1 is obtained.

) = Payment interest + additional principal

Here, the key to the exchange exposure analysis method is whether to include converted exposure. If the analysis targets cash flows and the exposure is recognized on a cash basis, then the gain or loss on long-term foreign currency liabilities should be recognized as the risk at the time of actual principal repayment. On the other hand, if the analysis targets recurring profits and exposure is recognized on an accounting basis, the gain or loss is recognized as a risk for the current year. As a compromise, the subject of the analysis is cash flows, but the gain or loss on valuation is the same as the actual occurrence at the time of valuation. In the present invention, both factors are reflected so that the user can consider the model decision. In summary, the additional principal redemption equation can be expressed as Equation 2.

In other words, the increase or decrease of the principal repayment burden due to exchange rate fluctuations corresponds to the exchange rate sensitivity ( , ), Multiply all of them, and change the rate of exchange rate ( ) Is multiplied by Foreign currency liabilities by interest rate terms are converted into total borrowings ( ) Composition ratio of the debt to , ) Is multiplied by

Next, corporate interest rate risk is likely to increase the debt burden of interest payments as interest rates rise. In general, firms see variable-rate liabilities at risk of interest rates, but even fixed-rate liabilities are exposed to interest rate risks. Therefore, the interest payment is expressed as Equation 3 below.

In other words, the interest paid is the amount of the debt, , ), Then multiply each and add them up. And the amount of debt for each currency's interest rate condition is total debt ( ) Composition ratio of the debt to , ) Is multiplied by However, the interest payment burden on future coupons is not realized in the current period, but should be considered as a current risk. For example, if interest rates rise, hedging the risk of floating rate liabilities through derivatives trading will allow the firm to preempt future financial costs. Thus, future cash flows, either on a cash flow basis or in accounting profit or loss, do not directly affect the performance of the current year, but form part of the interest rate risk.

According to the present invention, the interest exposure can be directly set to a user's definition of how much the risk of future financial cost fluctuation due to the interest rate changes, or the current exposure can be weighted to interest rate exposure targets in the future. To be recognized. In summary, variables that determine the cost rates of fixed-rate liabilities and floating-rate liabilities ( , ) Can be expressed as Equation 4 below.

,

In the present invention, as described above, , You can directly assign the value of, , (Wherein = Interest rate risk exposure weighted by maturity year).

Another factor to determine in the analytical model is the analysis period to be applied to the long-term model. Since this may vary depending on the characteristics of the company, the present invention allows the user to designate it. In general, the model to be applied requires a long-term model that strategically optimizes the debt structure of the company from a long-term perspective, and a short-term model that maintains the long-term strategy but reflects the short-term prospects of exchange rates and interest rates.

When the analysis target, currency risk standard, interest rate risk standard, and analysis period are set in the analysis model, in order to define values and conditions of variables to be performed according to the analysis conditions, the company's own financial environment and financial Examine the market environment and current debt structure to set the values and conditions of the variables.

First, in the financial environment determined by the management constraints of a company, it defines how much the operating term of the target function is affected by the financial variables. Scale estimation is included. In addition to the exchange rate, the financial variables affecting the business performance of a company may include interest rates and raw material prices. However, the present invention excludes the influence of interest rates and raw material prices for the convenience of system implementation, and does not limit the invention.

The exchange exposure in the operating segment is an estimate of the yearly amount and currency composition of the main items of the income statement showing the company's operating activities over the analysis period specified in the model. Capital expenditures and currency exposures also estimate the company's annual capital expenditure and currency composition for the analysis period specified in the model. For the simulation, we estimate the amount of interest-bearing liabilities by year during the analysis period. At this time, the currency composition of debt is a policy variable for optimization and cannot be determined in advance, so only the total amount is estimated without currency classification.

Next, in the financial market environment, it can be divided into general conditions common to all companies and conditions specific to individual companies. The latter may include accessibility and credit spreads to each financial market, and most other factors are general conditions. The present invention includes a function of processing a general condition to reflect both kinds of conditions and a function of reflecting the situation of an individual company.

As a general condition, a correlation coefficient between the exchange rate, the short-term and the short-term base rate, volatility, and variables is required for each currency to be analyzed. In the present invention, volatility and correlation are estimated using source time series data. The details of the estimation method are known to anyone who has a knowledge of statistics and are not explained separately.

In a financial market environment, credit spreads are determined by the creditworthiness and market access of each company, so strictly speaking, they belong to the financial environment but are closely related to the financial environment analysis function. Spreads allow users to enter and change on-screen at any time, because any company has variable credit ratings and spreads are variable for companies with the same creditworthiness, depending on financial market conditions.

The next thing to look at is the current debt structure. The current debt structure refers to the composition ratio of each debt's displayed currency and the fixed / floating interest rate ratio, which are the basis for comparison with the strategy scenario in the simulation process described later. In this case, if the debt is not a simple bond but a structured bond, and if there is a derivatives transaction, these transactions are financially decomposed to calculate the composition ratio based on the sensitivity to the actual exchange rate.

Once the analytical model is established and all conditions and values are established, various financial strategy scenarios are created to find the optimal debt structure and the results are simulated under the given conditions for each of these scenarios.

The strategy scenario is to use the borrowing method according to the interest rate of each currency as a variable and weight each variable. The variables in the present invention are the fixed rate of won, the floating rate of dollar, the fixed rate of dollar, the variable rate of dollar rate, The ratio of yen fixed rate, yen floating rate, euro rate fixed rate, euro rate floating rate are eight.

The strategy scenario allows the system to automatically generate the interval between the weights of the scenarios (for example, 1%, 2%, 5%, etc.) with an upper limit and a lower limit on the composition ratio (weight) of each variable. At this time, the upper limit and the lower limit are set by the user, but reflect the predefined accessibility (financial possibility) to the financial market as a constraint. The weight of each variable is generally positive (ie 0-100%), but in some cases negative values are allowed.

Table 2 shows an example of a scenario generated when the upper weight limit of each variable is 100%, the lower limit is 0%, and the composition ratio interval is 5%.

Fixed Won Korean Won USD fixed USD change JPY fixed JPY change EUR fixed EUR change Scenario 1 100% 0% 0% 0% 0% 0% 0% 0% Scenario 2 95% 5% 0% 0% 0% 0% 0% 0% Scenario 3 95% 0% 5% 0% 0% 0% 0% 0% ... Scenario n 45% 15% 5% 5% 5% 15% 5% 5% ....

After generating the strategic scenarios, the financial exposure recognition criteria are determined and the exposure is calculated according to the criteria defined in the model for each scenario. When calculating the financial exposure, the effective financial cost (EIC) is expressed as Equation 5 because it is the sum of the nominal financial expenses, the interest payments and the increase and decrease of the principal repayment burden due to exchange rate fluctuations.

Where the interest rate of liabilities by interest rate , ) Is the interest rate sensitivity ( , ), Which is used to calculate interest rate sensitivity and the increase or decrease in principal repayment burden ( , ) Are all determined by the business environment of the company and the nature of the objective function to be analyzed and are stored as system parameters when defining the model.

Looking at the financial exposure calculation model, when we first define a model that calculates currency exposure, , The value of depends on which criterion the model adopts. Based on accounting profit or loss = = 1, and on the basis of cash flows, it will be the ratio of the amount of the repayment of the principal during that period of the respective debt (fixed rate liabilities and floating rate liabilities).

When you define a model that calculates interest rate exposure, , (Wherein = Interest rate sensitivity of fixed rate liabilities, = Interest rate sensitivity of floating rate liabilities, = i's currency Long-term rate at time = i's currency Long-term rate at time = additional interest rate for the long-term rate of the i currency, = i's currency The level of short-term interest rates at that time, = i's currency The short-term interest rate level at the time point, and = the additive interest rate for the long term interest rate of the i th currency). , (Wherein = Interest rate risk exposure weighted by maturity year), allowing the user to arbitrarily change parameters to adjust interest rate risk exposure, ie the sensitivity of the interest rate in the financial term.

The above financial exposure recognition criteria are set when defining the model, and the system stores them as parameters and applies them accordingly when calculating the exposure.

Next, the sum of the calculated financial and business exposures is calculated. Total exposure is the sum of the operating and financial terms of each target function.

Based on ordinary profit, the operating term may be expressed as shown in Equation 6.

Ordinary profit ( ) Is not affected by external financial variables ( ) And exchange rates are affected. At this time, the part affected by the exchange rate is currency exposure per currency ( ) In the future, Multiply by)

On the other hand, the operating term is expressed as shown in Equation 7 based on the cash flow.

By definition, cash flows are defined as operating cash flows ( In capital expenditures ( ), Each of which is not affected by external financial variables ( ) And exchange rates. Again, the part affected by the exchange rate is the currency exposure per currency ( ) In the future, Multiply by)

The expected value and standard deviation of each scenario are calculated according to the exposure of the target function defined in the analysis model. The calculation method can be applied analytically or Monte Carlo simulation, and the result is a point on the plane. The horizontal coordinates of the points represent the risks (standard deviations) of each strategy, and the vertical coordinates represent the revenues (expected values) of each strategy.

First, the analytical method calculates the expected value and standard deviation of the target function directly assuming that random variables such as interest rate and exchange rate, which make up the target function, have a normal distribution. At this time, the expected value of the target function is expressed as a function of the expected value of the random variable such as interest rate and exchange rate, and the standard deviation of the target function is expressed as a function of standard deviation and correlation of the random variable such as interest rate and exchange rate. Calculation of expected values and standard deviations is based on general calculation methods and will not be explained in detail because anyone with statistical knowledge can know it.

Monte Carlo simulation measures the value of the target function by assigning random values to each of them to have a normal distribution, while maintaining a predefined correlation with the random variables, such as interest rates and exchange rates, that make up the target function. Calculate the expected value and standard deviation by performing statistical processing of the result. Again, calculations follow the usual method and are not explained in detail because anyone with statistical knowledge can know them.

On the other hand, in the present invention, it is possible to reflect the short-term outlook of the exchange rate, interest rates in the simulation process. For example, after 12 months, exchange rates will rise by 3% and interest rates will drop by 0.5% point. The exchange rate reflects the short-term outlook As interest rates , (In the above, , , Are forecasts for changes in exchange rates, long-term rates, and short-term rates, respectively.) The expected value of the target function reflects the expected value of each financial variable and the standard deviation remains unchanged.

The expected value and standard deviation of the target function are calculated for all the generated hypothetical strategy scenarios and the results are represented as a set of points on the same screen. The current debt portfolio is also expressed as a point on the plane by calculating the expected value and standard deviation of the target function. All points on the plane above the current debt portfolio would be valid for the current strategy. Employers can adopt the company's strategy as the one that most closely matches the company's policy direction, taking into consideration the company's risk tolerance, financial stability, and management goals.

However, even if the strategy recommended in the analytical system for optimizing the debt structure of the firm is adopted, it is not necessarily seen as a superior strategy afterwards. When comparing current and optimal strategies, even those that are superior in terms of risk and expected return mean that they are probabilistic, so individual results may be reversed. However, such a result does not deny the validity of the present invention. Therefore, in order to prove that the analytical method of the present invention is effective, a separate verification is required, and the present invention includes the following three analytical methods.

First, users can be more confident in adopting a new strategy if they can analyze in advance how likely (or probable) the target strategy to achieve is superior to the current strategy. Therefore, the two strategies need to be directly compared and analyzed. In the present invention, it is more generalized to compare any two strategies, and finds the probability that the comparison strategy is superior to the reference strategy. This analysis can be expressed as Equation 8, and like the strategy simulation, the value can be obtained in advance through analytic method or Monte Carlo simulation.

(From the above, = Objective function of the comparison strategy, = Objective function of the reference strategy)

Secondly, when the effective strategy is adopted according to the analysis of the present invention, it is a forward testing that confirms the probability that the result is superior before executing the strategy. Pre-validation is retrospective at the time of analysis, for example, a year before the financial market environment and the corporate environment, subject to the same analysis, adopting the target strategy, and then the actual actual implementation of the actual financial market's strategy. It is compared with the actual value of the strategy. In this case, in order to avoid arbitrarily selecting the target strategy, the present invention is a method of obtaining a probability that the effective strategy is superior to the actual strategy by comparing only the strategy that is found to be the effective strategy as a result of the strategy simulation applied in the past to the actual actual value. Take it.

Finally, it is necessary to analyze whether the results of the strategy are actually adopted and then meet the expectations. Performance analysis is the adoption of an effective strategy in accordance with the present invention at the present time, and then identifying at a future point what will result in a future point in time, for example one year. In other words, it is judged whether the result is superior to the case of maintaining the existing strategy. In this case, since the adopted strategy cannot be applied 100% as it is, the present invention uses the actual value as the primary comparison target, but the estimation result when the adopted strategy is applied as the secondary comparison target. The performance is then analyzed against the original expected value. That is, the difference between the actual performance and the originally expected performance is decomposed as shown in Equation 9 below.

(From above = Actual value of the target function, = Expected realization of adopting a target strategy, = Expected realization value of adopting existing strategy, and = If the existing strategy is adopted, it is the estimated value at the time of strategy establishment.)

Hereinafter, a preferred embodiment of an analysis system for optimizing a company's debt structure according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a flowchart illustrating an analysis system for optimizing a debt structure of an enterprise of the present invention.

The analysis system for optimizing a company's debt structure includes the steps of defining a company's financial target function and setting an analytical model according to the target function (S1) and constraints such as the business environment, the financial market environment, and the current debt structure. (S2), generating various financial strategy scenarios and performing a simulation under given conditions for each of these scenarios (S3), expressing the simulation results and finding an optimal scenario (S4) and the And verifying the effect of the financial strategy (S5).

Looking at the process of defining the financial target function of the company of Figure 1 and setting the analysis model according to the target function (S1) with reference to Figure 2, the exposure exposure according to which analysis target to set the optimization of the debt structure Recognition criteria are different. If the analysis target is set for recurring profit (a1), the operating port is set for operating profit and the exchange exposure recognition standard is set for profit or loss. If we set another analysis target as financial expense (a2), we set the operating term to zero and set the exchange exposure recognition standard to profit and loss. On the other hand, when the analysis target is set to cash flow (a3), the operating port is set as cash flow and the exchange exposure recognition standard is set as cash basis. Once the currency exposure is set according to the analysis goal, interest rate exposure recognition criteria are set to input sensitivity or yearly weights to calculate interest rate risk exposure. The analysis period of the analysis model is entered for long-term optimization. In short-term optimization, the analysis period is one year.

In addition to setting an analysis model according to the target function (S1) and reflecting constraints such as a business environment, a financial market environment, and a current debt structure (S2), the variables to be analyzed according to the analysis conditions are included. To define the values and conditions, the constraints arising from the business environment and financial market environment of the company should be reflected.

First, variables related to the business environment include currency exposure in the operating sector, current debt portfolio composition, future interest rate, and additional interest rate variables by currency interest rate conditions. Currency exposure in the operating segment is a decomposition of the currency composition of each item of the income statement (sales, cost of sales, cost of sales and general management costs), which can be automatically entered by receiving data from the financial management system. The composition of the current debt portfolio can be automatically entered by receiving data from the financial management system of the current debt portfolio of the company to be analyzed, that is, the composition of interest rates by currency. The amount of future liabilities can be automatically entered by receiving data from the management planning system on a gross basis. The additional interest rate by currency rate condition is the additional interest rate actually applied by the company to be analyzed in the financial market, and includes the procurement method that is not yet used by the target company.

Next, variables related to the financial market environment include financial time series data and forecast variables of financial variables. Financial time series data is a daily closing price of currency exchange rates and short- and long-term base rates, which can be automatically input by receiving data from a financial data providing system. Using the inputted financial data as primary data, the system estimates the variability of each variable and the correlation between the variables. On the other hand, if the forecast of the financial variable is to reflect the short-term outlook of the particular financial variable, input the forecast value, which is directly input by the user in the simulation process.

The process of generating the various financial strategy scenarios and performing the simulation under given conditions for each of these scenarios is shown in FIG. 3.

First, the strategy scenario is generated according to the constraints reflecting the financial market environment (S30), the financial exposure recognition criteria are determined according to the criteria defined in the analysis model, and the exposure is calculated (S31), and then the calculated financial exposure and The total exposure (S32) is calculated by summing the operating exposures, and the expected value and standard deviation of the target function defined in the analysis model are calculated (S33). The above processes (S31 to S33) are repeated for all the generated strategy scenarios.

The process of calculating the expected value and the standard deviation of the target function defined in the model (S33) is the flow chart of FIG. The analytical method may be applied to an analytic method (S40a) or Monte Carlo simulation (S40b) in order to calculate the risk and the profit for each strategy by reading the exposure value and the financial environment data of the strategy scenario (S40). When the analysis method is an analytic method S40a, the coefficients of the expected value term are calculated, the expected value is calculated, the coefficients of the variability term are calculated, and the standard deviation is calculated. On the other hand, when the analysis method is Monte Carlo simulation (S40b), a random scenario for a financial variable is generated, the target function is calculated for each scenario, and then the mean and standard deviation of the calculation result are calculated. The calculated value is stored (S41).

The above process is repeated for all the generated strategic scenarios (S34). The result is the expected value and standard deviation of the target function for each strategy scenario.

In the step S4 of expressing the simulation result and finding an optimal scenario, the strategy simulation result generated by the financial strategy scenario generation and the simulation S3 is represented by coordinates on the screen. The generated strategy is represented by a planar point with the expected value of the target function as the vertical coordinate and the standard deviation as the horizontal coordinate.

The expected value and standard deviation of the current debt portfolio target function are also plotted. In FIG. 5, the set b of all points in the upper left direction than the current debt portfolio a becomes the effective strategy. The employer can select the point that most closely matches the company's policy direction and adopt the debt composition as the company's strategy.

In the above, the analysis system for optimizing the debt structure of the company of the present invention was applied. However, if the effect of adopting the strategy recommended in the analysis system for debt structure optimization cannot be analyzed, the user may not be confident in adopting the new strategy. Therefore, the step (S5) of analyzing the optimal strategy of the analysis system for optimizing the debt structure of the company of the present invention at various angles is further provided.

Effectiveness verification (S5) of the present invention is a strategy comparison analysis, prior verification, performance analysis.

The strategy comparison analysis is to directly compare the target strategy with the current strategy to calculate the probability that the target strategy will have superior results. Referring to the strategy comparison analysis process of FIG. 6, first, an analysis model is set (S60), a reference strategy and a comparison strategy are set (S61), and then a difference between the comparison strategy and the reference strategy is set as a target function (S62), Read the financial environment data (S63), calculate the target function value using the analytical method (S64a) or Monte Carlo simulation (S64b), calculate the probability that the value of the target function is greater than 0 and output it (S65). )do.

The forward test is carried out retrospectively at the time of analysis, for example, subjecting the financial market environment and the business environment of one year ago to the same analysis, adopting the target strategy, and then realizing the actual value of the actual financial market strategy. It is compared with the actual value of the existing strategy adopted by the company. Looking at the pre-validation process through FIG. 7, the analysis target is selected (S70), the volatility and correlation is estimated based on the market data at the baseline point of time (S71), and the sales exposure is based on the sales environment at the baseline point of view. Calculation (S72). Next, a strategy scenario is generated according to a given rule (S73), and a simulation is performed for each generated scenario (S74) to determine whether the strategy is an effective strategy (S75). Calculate the performance of (S76), compare the actual performance of the target time and the performance of the target strategy to calculate the probability that the target strategy is superior to the actual performance and outputs the result (S77).

Looking at the performance analysis process through Figure 8, first read the portfolio of the target strategy and the standard strategy of the past adopted (S80), read the actual value of the financial variables (S81), and then the target strategy and the past adopted After estimating the performance of the reference strategy (S82), the actual actual value of the target function and the estimated expected value of the existing strategy are read (S83), and the results are compared and analyzed (S84). In this case, it is due to the influence of market changes that differ from the estimated actual value of the existing strategy and the original expected value, and the difference between the estimated value of the target strategy and the estimated value of the existing strategy indicates the effect of the strategy change, and the difference between the actual actual value and the estimated value of the target strategy. Analyze with a deviation. The analysis result is output (S85).

By verifying the effectiveness of the strategy, the user can be confident when adopting the strategy recommended by the analysis system for optimizing the corporate debt structure.

Next, look at the effects and features of the analysis system for optimizing the debt structure of the present invention through the embodiment.

First, the environment for analysis is as follows. Company A is a leading domestic conglomerate, with a significant portion of both exports and imports. Company A's operating income, operating cash flow, and capital expenditure are shown in Table 3.

Total (Unit 100 million won) KRW US Dollar Japanese Yen Operating profit 4,952 -15,943 20,895 0 Operating cash flow 6,952 -13,943 20,895 0 Capital expenditure 2,000 400 1,600 0

The interest rates, exchange rate levels, and volatility of each currency in the current financial market are shown in Table 4.

Interest Rate / Exchange Rate Levels Volatility Won short-term interest rates 4.23% 0.6665% USD short-term interest rate 1.17% 0.8177% JPY Short Term Interest Rates 0.06% 0.1992% Won long-term interest rates 5.08% 1.3202% USD exchange rate 1190 8.2062% JPY exchange rate 10.85 7.4700%

Correlation is shown in Table 5.

Won Short-term USD short term JPY Short Term Won USD Exchange Rates JPY exchange rate Won short-term interest rates One 0.3724 0.2649 0.4954 0.2038 0.1500 USD short-term interest rate 0.3724 One 0.2682 0.0999 -0.0473 0.0952 JPY Short Term Interest Rates 0.2649 0.2682 One 0.0602 0.1227 0.1761 Won long-term interest rates 0.4954 0.0999 -0.0602 One 0.1356 -0.0243 USD exchange rate 0.2038 -0.0473 -0.1227 0.1356 One 0.3225 JPY exchange rate 0.1500 0.0952 0.1761 -0.0243 0.3225 One

On the other hand, Company A can borrow from the financial market under the conditions shown in Table 6 in addition to the standard interest rate. At present, it is difficult to borrow long-term foreign currency with a fixed rate, and it does not take into account EUR borrowing.

Base rate level Interest rate Applicable interest rate Won short-term interest rates 4.23% 1.20% 5.43% USD short-term interest rate 1.17% 1.50% 2.67% JPY Short Term Interest Rates 0.06% 1.50% 1.56% Won long-term interest rates 5.08% 2.50% 7.58%

At present, A's external borrowings amount to 5.55 trillion and the composition ratio by currency-rate is shown in Table 7.

Sum Won fixed rate Won Change Rate USD floating rate JPY floating rate 100% 34% 8% 58% 0%

If A's objective function is optimized for recurring profit, we estimate A's recurring profit.

(Assuming the interest rate sensitivity of fixed rate debt: 0.16667 (= 1/6) and the interest rate sensitivity of floating rate debt: 1)

If we maintain the debt portfolio's current composition ratio, we estimate the expected value and standard deviation of A's current recurring profits next year, with an expected value of W266.5bn and a standard deviation of 369.7 billion won.

In the case of adopting a different strategy using the analysis system for optimizing the debt structure of the present invention, the expected value and the standard deviation of the ordinary profit are obtained and displayed as planar points with vertical and horizontal coordinates, respectively, as shown in FIG. 9. appear. In Figure 9, the horizontal axis represents the standard deviation of ordinary profit, and the vertical axis represents the expected value. As shown in FIG. 9, the current financial strategy is in a very disadvantageous position in terms of risk-return. In Fig. 9, the more favorable the strategy toward the upper left, the current financial strategy is that the risk is too large and the expected value is too small.

If so, see how much improvement can be achieved by adopting an alternative strategy. In FIG. 9, the coordinate of point A is (3512, 4165), which is a risk of 3512 billion and an expected value of 4165 billion. Compared to the current strategy, it can reduce the risk and increase the recurring profit expectation by 151.7 billion won. Compared to external borrowings, annual financial costs are reduced by 3%.

On the other hand, let's see how we can reduce the risk at the same expectation level. In FIG. 9, the coordinates of point B are (1430, 2698), and the expected value of ordinary profit is about the same level, but the risk is reduced to two fifths. Depending on the strategy chosen, it is possible to drastically reduce both risk and return. In Figure 9, the points in the upper left than the current financial strategy all represent such a strategy. In FIG. 9, the coordinates 2672 and 3676 of the point C can reduce the risk by 100 billion won or more, and increase the expected value by about 100 billion won. The system also shows what strategy each of these points represents. Point C, for example, represents a strategy with debt composition as shown in Table 8.

Sum Won fixed rate Won Change Rate USD floating rate JPY variable rate 100% 0% 25% 0% 75%

Now suppose that Company A expects the value of the dollar to fall and reflects it in their strategy. For example, assuming that the dollar exchange rate is raised to 30 won in six months, the total set of points is changed as shown in FIG.

Also, the point D shown in FIG. 10 is in a position similar to the point C of FIG. 9, but the strategy configuration is different as shown in Table 9 below. As the USD exchange rate is expected to fall, it may be advantageous to use USD as the currency.

Sum Won fixed rate Won Change Rate USD floating rate JPY floating rate 100% 0% 20% 20% 60%

Estimate A's financial costs under the same conditions. If the debt portfolio's current composition ratio is maintained, the expected value and standard deviation of A's financial expenses for next year will be W155.5bn and standard deviation (risk) of W244.1bn.

When different strategies are employed using the analysis system for optimizing the debt structure of the present invention, the expected values and standard deviations of financial costs are obtained, respectively, and are represented as planar points of vertical coordinates and horizontal coordinates. . As with the analysis of recurring profits, the current financial strategy is in a very unfavorable position. Again, as in recurring profit analysis, any effective strategy can be targeted and the portfolio composition tracked.

Assume the cash flow of Company A. (Assuming the sensitivity of foreign currency risk to currency exchange rate sensitivity of fixed rate foreign currency debt: 0.2 and foreign exchange rate sensitivity of floating rate foreign currency debt: 0.5.) If we look at the expected value and the standard deviation of A's cash flow next year, the expected value is W2648bn and the standard deviation (risk) is W241.4bn.

When different strategies are employed using this system, the expected values and standard deviations of cash flows are obtained, respectively, and are represented as points on a plane with vertical coordinates and horizontal coordinates. Even in this case, the current financial strategy is in a very unfavorable position and it can be seen that the cash flow can be greatly improved by changing the debt portfolio. Although the analysis is for one year of cash flows, similar conclusions can be drawn for many years of cash flows.

As described above, according to the analysis system for optimizing the debt structure of the company according to the present invention, the business environment of the company, that is, the exposure and financial market environment of the operating sector, that is, the exchange rate and interest rate level, volatility, correlation, future prospects This can be used to derive an effective financial strategy that not only significantly reduces financial costs but also eliminates unnecessary currency and interest rate risks. Therefore, as a result of conventional financial strategies that firms have established without a rigorous analysis, the financial costs are increased and the debt structure that is not compatible with the financial environment of the company is maintained. There is a dramatic effect on enabling strategic planning.

In addition, various comparisons between the strategies derived from the system for optimizing the debt structure of the company and the current debt strategy can increase the user's confidence in adopting a new strategy.

Although the present invention has been described in detail only with respect to the described embodiments, it will be apparent to those skilled in the art that various modifications and changes are possible within the technical scope of the present invention, and such modifications and modifications belong to the appended claims. .

1 is a flowchart of an analysis system for optimizing a debt structure of an enterprise of the present invention.

2 is a flow chart of an analytical model for finding an optimization of a company's debt structure.

3 is a flow chart of strategy scenario generation and simulation.

4 is a flowchart for calculating the expected value and standard deviation of the target function defined in the model.

5 is a result diagram showing expected values and standard deviations in coordinates on a plane.

6 is a flowchart of a strategy comparison analyzing the effects of the present invention.

7 is a pre-verification flow chart analyzing the effects of the present invention.

8 is a performance analysis flowchart for analyzing the effects of the present invention.

9 is an exemplary view based on recurring profits using an analysis for optimizing the debt structure of an enterprise of the present invention.

FIG. 10 is an exemplary view based on recurring profit in the case of reflecting a falling dollar.

11 is an exemplary view estimated on the basis of financial cost optimization using an analysis system for optimizing debt structure of a company of the present invention.

12 is an exemplary embodiment estimated based on cash flow optimization using an analysis system for optimizing a company's debt structure according to the present invention.

※ Explanation of code for main part of drawing

a: value of current financial strategy b: scope of effective strategy

Claims (17)

Defining a financial target function of the enterprise and setting up an analytical model according to the target function; Reflecting constraints such as the business environment, the financial market environment, and the current absence structure of the company; Creating various financial strategy scenarios and performing simulations under given conditions for each of these scenarios; Presenting the simulation results and finding an optimal scenario; And, Performing an effect analysis on the financial strategy; Analysis system for optimizing the debt structure of the enterprise comprising a. The method of claim 1, Defining the financial target function of the company and setting up an analysis model according to the target function, An analysis system for optimizing the debt structure of the enterprise, characterized in that the analysis target is set according to the analysis purpose, and the currency risk standard, interest rate risk standard, and analysis period are set. The method of claim 2, Supports both cash flow and accounting profit and loss criteria to expand and select specific target variables so that they can be selectively applied according to the purpose of the analysis, without pre-setting the risk and profit targets of the firm's financial target function. And an analysis system for optimizing the debt structure of the enterprise. The method of claim 2, Exposures arising from financial activities in accordance with the analysis target set for the purpose of the analysis ( = Financial expenses at profit and loss, = Cash-based financial expenses) is an analysis system for optimizing the debt structure of the enterprise, characterized in that a separate analysis criteria. The method of claim 2, In setting the exchange risk standard, the increase or decrease of the principal repayment burden due to the exchange rate fluctuation is Is defined as (wherein = Exchange rate sensitivity of fixed rate liabilities, = Exchange rate sensitivity of floating rate liabilities, = share of fixed-rate liabilities of the i currency, = share of debt from the floating rate of the i currency, = exchange rate fluctuation of the i currency, = Total interest-bearing liabilities.) On accounting basis , , Is = = 1, and in the case of the cash flow basis, the debt structure of the enterprise, characterized in that it is the ratio of the amount of repayment of the principal during the period among the corresponding debts (fixed rate liabilities and variable rate liabilities) Analytical system for optimization. The method of claim 2, In setting interest rate risk criteria, a model for calculating interest rate exposure of nominal financial expenses is Is defined as (wherein = a variable that determines the cost of the fixed rate liabilities of the i currency, = variable that determines the cost of floating rate liabilities in the i currency.) , (Wherein = Interest rate sensitivity of fixed rate liabilities, = Interest rate sensitivity of floating rate liabilities = i's currency Long-term rate at time = i's currency Long-term rate at time = additional interest rate for the long-term rate of the i currency, = i's currency The level of short-term interest rates at that time, = i's currency The short-term interest rate level at the time point, and = the addition rate to the long-term rate of the i currency. and The analysis system for optimizing the debt structure of the enterprise, characterized in that it is determined according to the financial environment of the company and can be arbitrarily set. The method of claim 6, The interest rate sensitivity of the nominal financial expenses , (Wherein = Interest rate risk exposure weighted by the maturity year.), Wherein the interest rate risk for future coupons can be weighted by arbitrarily changing parameters. The method of claim 1, At the stage of reflecting the constraints of the business environment, financial market environment and current debt structure, The business environment constraints of a company consist of estimates of exchange exposure, capital expenditure exchange exposure, and debt size of the operating sector in the financial environment.In the financial market environment, exchange rate and interest rate level, volatility and correlation of each financial variable An analysis system for optimizing the debt structure of the company, characterized in that it can reflect the conditions commonly applied to the company, such as relationships and special conditions of the individual company. The method of claim 8, In the financial market environment, an analysis system for optimizing the debt structure of the enterprise, characterized in that it is possible to input and change the accessibility (financial possibility) and the credit spread in each market, which are special conditions for individual companies. The method of claim 1, Creating the various financial strategy scenarios and performing the simulation under given conditions for each of these scenarios, Generating a strategy scenario by assigning a weight to a borrowing method according to interest rates of debts; Calculating financial exposures of each scenario; Calculating a total exposure by adding the financial exposure and the business exposure; Calculating an expected value and a variance for the total exposure; And Storing the result value; Analysis system for optimizing the debt structure of the enterprise, characterized in that consisting of. The method of claim 10, The scenario for debt composition is automatically generated by the system, and the upper and lower limits of the composition ratio (weighted values) of each variable are processed at regular intervals within the range, limiting the accessibility (financial possibility) to the financial market. Analysis system for the debt structure optimization of the enterprise, characterized in that the condition. The method of claim 10, In the step of calculating the financial exposure of each scenario, the effective financial cost is the sum of the nominal financial costs, the interest payment and the increase and decrease of the principal repayment burden due to the exchange rate fluctuation, and the exposure recognition criteria are determined according to the criteria defined in the model. Analysis system for optimizing the debt structure of the enterprise. The method of claim 10, The analysis system for optimizing the debt structure, characterized in that by reflecting the short-term outlook of each financial variable in the simulation process, it is possible to effectively grasp the impact of short-term changes in the exchange rate, interest rates on the simulation results. The method of claim 1, Analyzing the effect of the financial strategy, And comparing the strategy, pre-verification, and performance analysis to analyze the effect of the strategy generated by applying the analysis method for optimizing the debt structure. The method of claim 14, In the strategy comparison analysis, if any strategy is to be adopted as a target strategy, the debt is characterized by calculating the probability of showing superior results compared to the existing strategy or any other strategy based on the comparison criteria. Analytical system for structural optimization. The method of claim 14, When the pre-verification assumes that a certain strategy that can be classified as an effective strategy according to the simulation result at a certain point in time in the past, the probability that the strategy showed superiority to the existing strategy is calculated. An analysis system for optimizing the debt structure. The method of claim 14, In the performance analysis, when a particular strategy classified as an effective strategy is actually adopted according to the simulation, the difference between the post-performance of the strategy and the originally estimated value is Deviations from financial activities expressed as the difference between the actual realized value of the target function and the expected realized value when the target strategy is adopted; The impact of a strategy change expressed as the difference between the expected realization of adopting a target strategy and the expected realization of adopting an existing strategy, The analysis system for optimizing the debt structure, characterized in that it is decomposed by the effect of market changes expressed by the difference between the expected realization value when the existing strategy is adopted and the expected value estimated at the time of strategy establishment.