Abstract:
A system and method for analyzing derivative securities includes a central processing unit, an input device, an output device, and a storage. The system includes input and output routines, a compiler, a sequencer, and a simulator. The input and output routines generate graphical user interfaces that allow the user to construct scenarios for simulation. A scenario includes a set of events that define changes to the value of the derivative security over time. The compiler parses an input scenario and converts it to a low-level executable object. The sequencer then uses the output of the compiler and other simulation code for a financial Monte Carlo simulation to produce programs executable by the CPU. The simulator is automatically invoked and runs the executable code using the CPU. The simulator utilizes the input and output routines to display the results on the display device. Also disclosed is a method for running the financial Monte Carlo simulation that comprises the steps of: inputting and constructing a scenario, compiling the scenario into executable code objects, sequencing the code objects with the simulation code, performing the simulation, and displaying the simulation results on the output device.

Description:
RELATED APPLICATIONS 
     This is a continuation of application Ser. No. 07/890,437 filed on May 28, 1992 now abandoned. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     This invention relates to a system and method for the rapid assessment of the fair market value and risk characteristics of complex financial securities without the need for knowledge of computer programming, sensitivity analysis, or statistical simulation techniques. 
     2. Description of the Prior Art 
     The present invention is directed toward an improved method for assessing the fair market value and risk characteristics of complex financial securities, a category of financial instruments that continues to broaden. Complex financial securities include, in particular, &#34;derivative products&#34; such as options and futures. Derivative securities fluctuate in value on the basis of the price of an underlying asset such as a precious metal, an agricultural product, or a company&#39;s common stock. The fair market value and risk characteristics of derivative securities depend on the value and price volatility of the underlying asset. 
     Banks, brokerages, and other major financial institutions generally apply simulation techniques to assess the fair market value and risk characteristics of derivative securities. Such techniques simulate changes in the prices of the underlying assets and other economic conditions over the life of the derivative security. Simulation techniques are employed because increasingly complex derivative securities provide various contingencies on various dates. The simulation assesses these contingencies in the context of asset price changes and economic conditions to determine an estimated payout. 
     One preferred simulation technique is the &#34;financial Monte Carlo&#34; simulation. Rather than require that all probabilities for economic contingencies be specified completely, a financial Monte Carlo simulation takes advantage of market information (within stated assumptions) and determines its own probability distribution. There are a variety of financial Monte Carlo techniques well known to those skilled in the analysis of derivative securities. Because of the complexity of financial Monte Carlo simulation, it commonly is implemented in a scientific programming language such as C or FORTRAN by staff programmers familiar with the technique, rather than by the securities traders who rely on the results. This requires that the trader communicate to the programmer the terms (contingencies, methods of calculating payoffs, underlying asset(s), and background assumptions) of the derivative security for coding into the financial Monte Carlo simulation program, as well as parameters for the behavior of the underlying asset, interest rates, and so forth. The programmer then typically codes and compiles the program, and executes the simulation. Finally, the programmer presents the resulting statistics to the trader in a numerical or graphical form which summarizes the fair market value and risk characteristics of the derivative security analyzed. 
     Unfortunately, this process often leads to breakdowns in communication between the trader (who is attempting to convey complex financial terms) and the research staff programmer (who is required to code the simulation), which result in errors in the simulation. As a result, the iterative process of re-coding, re-compiling, re-executing, and re-reporting frustrates a trader&#39;s ability to act quickly in response to market opportunities. 
     Consequently, there is a need for a system and method that allows the unsophisticated programmer or trader to perform their own analysis of the derivative securities by defining, creating and running a financial Monte Carlo simulation. 
     SUMMARY OF THE INVENTION 
     The present invention overcomes the limitations of this a prior art by creating an integrated system and method for a user unsophisticated in computer programming or simulation techniques to rapidly execute financial Monte Carlo simulations on complex financial securities without use of intermediaries. The integrated system for analyzing derivative securities preferably comprises a central processing unit, an input device, an output device, mass storage and memory means. The memory means preferably includes input and output routines, compiling means, sequencing means, and simulation means. The input and output routines of the present invention produce an interactive data input means for specifying the terms of derivative securities and parameters. The compiling means and sequencing means are used to create low-level executable code objects embodying the algebraic operations specified (or implied) by these terms and determine the sequence of execution within the simulator. The simulation means calculates the desired results, and the input and output routines are utilized to display the results on the display device. These features of the invention make it useful for other purposes, including: designing new financial instruments, evaluating complex patterns of cash flow and contingencies, auditing financial valuations produced by other systems, and &#34;benchmarking&#34; in-house analytic models which are used for the valuation of derivative securities. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block schematic diagram of a preferred embodiment of the system of the present invention; 
     FIG. 2 is a flow chart illustrating operation of the preferred method of the present invention; 
     FIGS. 3A, 3B, and 3C are a detailed flow chart illustrating the operation of the preferred method of the present invention; 
     FIGS. 4A and 4B are graphic representations of the display device showing preferred embodiments of the graphic interface for defining and starting a simulation; and 
     FIG. 5 is a graphic representation of the display device showing a preferred embodiment of the output of the simulation. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENT 
     Referring now to FIG. 1, a preferred embodiment of the system of the present invention is shown. The preferred system comprises a central processing unit (CPU) 10, an input device 12, a display device 14, an addressable memory means 16 and mass storage 18. The CPU 10 is coupled to and controls the display device 14 to produce a variety of images in response to inputs supplied to the CPU 10 by user manipulation of the input device 12. The CPU 10 is also coupled to other sources of information such as mass storage 18 and addressable memory 16 in a conventional architecture. In an exemplary embodiment, the CPU 10 may be a microprocessor from the &#39;X86 family produced by Intel™ or the 68000 family produced by Motorola™. 
     The input device 12 is a conventional type as known in the art. The input device 12 is preferably a keyboard with a &#34;mouse&#34; type controller. For example, the input device 12 may include a mouse or track ball. A pointer or mouse cursor is produced on the display device 14 to represent the position of the mouse and corresponding movement. By moving the mouse, a user 32 can point to and manipulate different objects shown on the display device 14. 
     The display device 14 is also a conventional type known in the art. The display device 14 is preferably a raster-type display used with the CPU 10 in a conventional manner to produce images of characters generated from codes such as ASCII in text mode. The CPU 10 may also create images on the display device 14 in other conventional ways such as producing an image from a group of dots or pixels in graphics mode as in the Windows™ operating system produced by Microsoft™. The display device 14 also operates in a conventional manner with the input device 12 to produce a cursor on the display device 14 that indicates the location where data will be input or the object on the display device 14 that will be manipulated. 
     The addressable memory 16 is a conventional type and preferably includes Random Access Memory (RAM) and Read Only Memory (ROM). The addressable memory 16 further comprises processing routines, programs and data for interactive display control 20. For example, the memory 16 includes input device interrupt routines and drivers. The memory 16 also includes routines for transferring data from the CPU 10 to the display device 14 and for presentation of the data on the display device 14. The memory 16 further includes an operating system and other programs 30 as conventional in the art. 
     More particularly, the memory means 16 of the present invention further comprises routines and means that allow the unsophisticated user to create and run financial Monte Carlo analysis. The memory 16 includes input and output routines 24, compiling means 26 and sequencing means 28, and simulation means 22. These routines and means are advantageously integrated by the present invention into system for performing financial Monte Carlo simulations on derivative securities that only requires the user input the terms for the derivative security, and its contextual market information. Thus, a user who is sophisticated in terms of financial knowledge while unsophisticated in computing or scientific knowledge is able the use the system of the present invention to run financial Monte Carlo simulations. The system of the present invention also provides improvements in performance that significantly reduce the time required to run a financial Monte Carlo simulation. 
     The input and output routines 24 are used along with the operating system 30 to create a unique graphical user interface (GUI) on the display device 14. The GUI is designed to prompt the user 32 to input any number of scenarios upon which a simulation is to be run. The user 32 is prompted by an interactive display control means 20 to specify the terms of the security to simulate. This specification of terms is known as the &#34;Scenario.&#34; The input and output routines 24 produce a worksheet of five columns and several rows, and direct the placement of certain information in each column through the use of headings at the top of each column. The unique 5-part event field displayed and used by the present invention is particularly advantageous because it provides a means for the user 32 to specify all the terms of the derivative security and also improve execution speed of the system. Means are provided to make visible a portion of the available rows at any given time through the use of a scrollable window. Each row is termed an &#34;event,&#34; since it represents information which is concurrent in simulation time, even though it is evaluated (left to right) in real time. 
     FIG. 4A shows the display device 14 with the GUI for inputting a Scenario producing using the input and output routines 24. The first column labeled &#34;TIME&#34; 40 is for inputting a date (or formula for determining a date, down to the minute on a particular date) on which the corresponding event occurs, to be evaluated by the simulation means 22. The event usually involves a possible payment to the holder of the derivative security, but may also represent any point in simulated time where calculation or simulated activities are required. The second column labeled &#34;GENCALC&#34; 42 is for inputting the formulae, if any, necessary to determine the values accessed by concurrent or future events. The third column labeled &#34;PAYCON&#34; 44 is to input any payoff contingencies, expressed as a variable evaluated as a Boolean value. The fourth column labeled &#34;Payoff&#34; 46 contains a formula to be evaluated by the simulation means 22 in the event that the payoff contingency is found to occur, representing the amount of the payoff of the derivative product. The fifth column labeled &#34;ABSCON&#34; 48 is to contain the absorption contingency (the formula for determining whether the simulation is to terminate), expressed as a variable evaluated as a Boolean value. Termination of the simulation of a derivative security is known as absorption. 
     Each row in the Scenario preferably comprises information relating to one &#34;Event.&#34; An Event is a point in time at which a potentially significant scheduled occurrence takes place. Any occurrence which is known to the trader, such as the payment of a dividend on the underlying asset, or the evaluation of a contingency, and which might affect the value of the derivative security can be scheduled as an Event. Events must be listed in order of the simulated time of their occurrence. 
     The formulae and variables used to set forth the terms of the derivative security are expressed in a simple language capable of being transformed by the compiling/sequencing means. In the preferred embodiment, this language is known as the DerivaTool Expression Language (DEL). 
     FIG. 4B illustrates an example scenario for a particular derivative security with two events. The security is a call option (a right to purchase) on gold in three months at an exercise (or &#34;strike&#34;) price of $350 (per ounce). The trader would like to know the probable return on this security, three months from now, to determine its fair market value today. Since the call option will not be exercised if the market price of gold on the exercise date is less than $350, the return might be zero. The call option will be exercised if the market price of gold exceeds $350 on the exercise date, and the return on the security will be the difference between the market and exercise prices. The estimated market price on the exercise date, &#34;xprice()&#34;, is determined by financial Monte Carlo simulation. The potential payoff is represented by the formula &#34;max(0, xprice()-350)&#34; in the fourth column 46 of the row labeled Event 2. In columns three 44 and five 48 of FIG. 4B, the contingencies are forced to true because the payoff is certain and there are no subsequent events to be evaluated. 
     This security, however, has an earlier payoff contingency (Event 1) designed to protect the seller of the call option from a dramatic increase in the price of gold. If the market price of gold has risen by more than ten dollars ($10) in the first month after purchase, the seller will pay the holder of the call option twice the increase in market price greater than ten dollars ($10). In other words, if xprice() is greater than $360, the payoff is twice the difference, and the seller&#39;s obligations are extinguished. However, if xprice() is less than or equal to $360, there is no payoff and the security behaves as an ordinary call option. The formula for the relevant difference in price is the familiar one &#34;max(0, xprice()-360)&#34;. To simplify the Scenario, a variable can be assigned this value. In FIG. 4B, the equation &#34;y:=max(0, xprice()-360)&#34; has been placed in the second column 42. If y is zero, there is no payoff; if y exceeds zero, the contingency is satisfied and a payoff must be calculated. In FIG. 4B, this relationship is represented by the Boolean operator z being assigned the value &#34;(y&gt;0)&#34; in column two, and by placing z in the payoff contingency column 44 and the termination contingency column 48. The payoff formula is simply twice the price difference, or &#34;2 * y&#34;, and is placed in the fourth column 46 of FIG. 4B. 
     The Scenario also includes background information on the underlying asset and the market. The user 32 is presented with means (a menu bar from which to pull down menus and representations of buttons on the display screen that can be pressed by clicking the left mouse button when the mouse cursor is positioned over the displayed button) to input this information, as well as control information for the simulation, such as the number of iterations of price calculations the financial Monte Carlo engine should perform. The user is prompted for historical asset price information through a two-column representation of a worksheet in which the user can place dates and corresponding prices. The most recent date entered is significant because it becomes the &#34;base date&#34; substituted in DEL expressions using the constant &#34;basedate()&#34;. 
     The user 32 is prompted for market data, including projected interest rates, the yield term structure or forward price term structure of the underlying asset, and the volatility of the underlying asset, as derived by the user from available financial information. The user 32 also has the option to &#34;perturb&#34; the foregoing rates, that is, to have random fluctuations introduced during the simulation process, according to user-defined parameters. 
     The compiling means 26 is used to parse the data input by user 32 using the input and output routines 24. The compiling means 26 extracts any algebraic codes input and converts the codes by them compiling into low-level executable objects. In the preferred embodiment, DEL expressions are parsed and reduced to tokenized form. Each token provides (a) context for further parsing, and/or (b) is connected to low-level machine language subroutines which perform computation and variable assignment. In particular, each DEL intrinsic function is associated with a token which involves such a low-level subroutine, enhancing the speed of subsequent execution of the simulation means 22. 
     The sequencing means 28 uses the signals output by the compiling means 26 to produce executable programs that can be run by the CPU 10. In particular, the sequencing means 28 integrates the code for performing the financial Monte Carlo simulation along with the specific parameters output by the compiling means 26 into an executable program for each event. The sequencing means 28 also arranges the data input by events for financial Monte Carlo simulation. For example, when several events are input by the user 32, the sequencing means 28 of the preferred embodiment assembles the tokens produced by the compiling means 26 into a sequence which is left to right over the five portions 40, 42, 44, 46 and 48, and then repeats for each event, top to bottom in the Scenario. 
     After the sequencing means 28 produces executable code, the simulation means 22 automatically runs the executable code using the CPU 10. The simulation means 22 also includes data files that are used during execution of the financial Monte Carlo simulation. The simulation means 22 executes the code and stores the results in memory 16 or in mass storage 18. The information can then be utilized by the input and output routines 24 to convey the results to the user 32. 
     Referring now to FIG. 2, an overview of the method of the present invention is shown. The unique configuration of memory 16 provided by the present invention and the use of the operating sequences described above are directed toward an integrated method that evaluates the value of derivative securities given only the contract terms and market data. The method begins in step 50 by prompting the user for the contract terms. As has been described, the contract terms are input by specifying a Scenario with one or more events through manipulation of the input device 14. The user 32 produces five signals representing the five fields/terms that are required in each event of a Scenario describing a derivative security. Next, in step 52, the contract terms, in particular the algebraic operations in the GENCALC 42 column, are compiled into executable code objects. The code objects produced by the compiling step 52 are used along with simulation code for performing a financial Monte Carlo simulation in step 54. In step 54, the code objects are sequenced with the simulation code to produce a program that is executable by the CPU 10. In step 56, the simulation means 22 executes the sequenced code and stores the results in a predefined location in memory 16. The results are then output 58 for review by the user 32. The present invention is particularly advantageous because it allows traders to evaluate the value of securities with nominal turn around time, and with a high level of accuracy. The problems of miscommunication of the prior art that introduce significant error are eliminated with the present invention that allows the trader to run a financial Monte Carlo simulation simply by specifying the terms of the contract and market context. 
     Referring now to FIGS. 3A-3C, a detailed description of the preferred embodiment of the method of the present invention for performing financial Monte Carlo analysis is shown. The method begins in step 60 by monitoring the use of the input device 12 for construction of a Scenario. After the user 32 has built the Scenario, the user 32 issues commands to store the information in mass storage 18. 
     In step 61, the compiling means 26 is actuated, either by selecting an option from a menu with the keyboard and/or mouse, or by clicking a representation of a button on the display screen. In step 61, the CPU 10 parses the parameter passed by the GUI including the name of the data file, the number of iterations to run and cumulation flags. The method continues to step 62 where the file containing the Scenario is retrieved from mass storage 18. Then, in step 63, the additional background information such as simulation control, market and perturbation and asset price information is read from the Scenario file. In step 64, the event information is read from the Scenario file. The compiling means 26 compiles all the information retrieved and read in steps 62-64 into low-level executable code objects. In particular, the variables, operators and formulae are transformed from text to low-level executable objects by an integral compiler. In the preferred embodiment, a low-level object is created for each variable, function name, algebraic operator etc. Each object preferably comprises (1) an external multi-byte symbol; (2) a unique one byte token; and (3) a machine-language subroutine. The symbol token association employs standard symbol table and lexical analysis techniques. The token subroutine association enables the subsequent employment of the simulation mean 22 to execute the associated subroutines of tokens as they are encountered. 
     In step 66, the low-level objects are sequenced for execution according to the order of events in the Scenario. The code objects are preferably sequenced in order from left to right and from top to bottom as specified in the GUI when the Scenario was constructed. Importantly, the five-part fields 42-48 of an event are employed to sequence the tokens which are produced by the compilation/lexical analysis step 65. Simulated time remains constant during all parts of an event, but the sequencing within the event is controlled by the order of appearance (left to right) in the fields 42-48 displayed to the user 32. The sequencing means 28 then passes program control to the simulation means in step 67. 
     In step 68, the simulation means 22 begins execution of the sequenced code produced by the sequencing means 28. The simulation means 22 directs the CPU 10 to advance to the code for the first or next event in step 68. For the event being executed, the method first determines the point in simulated time at which the first event takes place in step 69. In step 70, the simulation means 22 applies the financial Monte Carlo process to determine the prices of the underlying assets, and other economic conditions affecting the value of the derivative security and the event contingency at that point in simulated time. The simulation means 22 proceeds to step 71, and calculates variables set forth as general formulae in the GENCALC field and stores the values for the variables. In step 72, the simulation means 22 performs the specified calculation necessary to evaluate the payoff contingency and tests whether the contingency is satisfied. If the contingency is not satisfied, then the method proceeds directly to step 74. However, if the contingency is satisfied, the simulation means 22 proceeds to step 73, makes the calculated payoff, and then continues to step 74. In step 74, the preferred method tests whether the termination or absorption contingency is satisfied. If the absorption contingency is not satisfied, the simulation means 22 returns to step 68 to advance to the next event, and repeats the cycle until absorption occurs. When the absorption contingency is satisfied, the simulation is terminated. 
     Upon termination of the simulation, the simulation means 22 writes the results of the simulation to the mass storage means 18 in step 77 and passes program control to the interactive display control means 20 in step 78, the input and output routines 24 are then used to notify the user 32 that the simulation has run to completion. In step 79, the user 32 can then view the simulation results using the input and output routines 24. The input and output routines 24 include menus and representations of buttons for the user to view the results of the simulation, as a table of numbers and as a chart. An exemplary embodiment of the display device 14 showing simulation results is illustrated in FIG. 5. 
     It should be understood that in the preferred embodiment, the Scenario-building and results-viewing functions are separated from the calculation engine containing the compiling means 26, sequencing means 28 and the simulation means 22. By making the calculation engine a separate executable program, it can be invoked through the GUI interface, but run as a separate task, thread, or process (depending on the capabilities of the operating software), enabling the user to continue building alternative scenarios or to perform other, entirely separate, input-intensive work. This separation also makes possible the unattended execution of multiple simulations through execution of a &#34;batch&#34; file during off hours. Having described the present invention with reference to specific embodiments, the above description is intended to illustrate the operation of the preferred embodiments and is not meant to limit the scope of the invention. The scope of the invention is to be delimited only by the following claims. From the above discussion, many variations will be apparent to one skilled in the art that would yet be encompassed by the true spirit and scope of the present invention. ##SPC1##