text: the present invention provides a predictive automated routing system for user trading of securities . the term “ trading ”, as used herein , includes the exchange of securities or commodities by bartering or by buying and selling for money or its equivalent , such as the buying , selling , crossing , selling long or selling short of a security . the term “ security ”, as used herein , includes any note , stock , treasury stock , bond , debenture , or certificate of interest or participation in any profit - sharing agreement or in any oil , gas , or other mineral royalty or lease , as well as any collateral - trust certificate , preorganization certificate or subscription , transferable share , investment contract , voting - trust certificate , certificate of deposit , or any other instrument commonly known as a “ security .” [ 0018 ] fig1 presents an embodiment of the present invention . a user 100 accesses or creates a best execution profile form 102 . as fig2 shows , the user 100 may be a private or individual investor 202 or may be a institutional investor 204 , a broker / dealer 206 , a broker / dealer trading desk 208 , or some other party interested in trading a security . referring back to fig1 the best execution profile form 102 may be an electronic form , such as a hypertext markup layer ( html ), secure hypertext markup layer ( shtml ) or extensible markup layer ( xml ) web page , that is displayed on an order screen 104 and which is located at an internet website or other networked location and which may be accessed via the internet , an intranet or other network using an entry device 106 , such as a computer , personal digital assistant ( pda ), kiosk or other personal or public device . further , the best execution profile form 102 may be an electronic form that is mailed electronically ( e - mail ) to and / or from the user 100 . alternatively , the best execution profile form 102 is a paper form that may be transmitted to and / or received from the user 100 via the postal service , courier service or facsimile . as a further alternative , the best execution profile form 102 may be provided by a voice mail system whereby a user 100 dials a telephone number and then provides verbal or keyed - in responses . the best execution profile 102 may be supplied to the user at the time that the user initiates an order to perform a trade or , alternatively , is supplied before any trades are ordered to permit the user to provide preferences for future trades . the best execution profile form 102 typically requests that the user 100 select one or more execution quality parameters for a particular trade , particular class of trades or for all trades . included are execution at / within best bid and offer ( bbo ) or national best bid and offer ( nbbo ), price improvement , speed of execution , liquidity enhancement , size improvement , performance above the national average price , custom measures , and other execution quality parameters . the selected execution quality parameters define a user profile that is used to select the market center where trades are to be routed . the user may also assign relative weights to one or more of the selected execution qualities that is also included in the user profile , such as by selecting a weight from a scale of one to ten , or from a scale having another range . for example , a price conscious user may assign , for all trades , a high raw weight value , such as 10 on a scale of 0 - 10 where 0 would indicate least importance to the user and 10 indicates greatest importance to the user , to the “ price improvement ” parameter and a low raw weight value or no raw weight value to the other parameters to indicate that the user considers the “ price improvement ” parameter to be the sole measure or the most important measure for determining where to route orders . alternatively , the user may assign a relatively high raw weight value , such as 9 or 10 , to the “ speed of execution ” parameter for volatile technology stock trades and may assign a higher raw weight value , such as 7 , to the “ liquidity enhancement ” parameter and a lower raw weight value , such as 3 , to the “ performance above national average ” parameter for blue - chip stock trades . as a further alternative the user may assign the same raw weight value to one or more of the parameters or to each of the selected parameters . the respective weightings are processed to derive a user &# 39 ; s particular “ execution quality profile matrix ” or “ best execution profile ”. fig3 illustrates an example of the processing of the user - selected statistical measures and the user - selected weights according to the invention . in the example , the user selects the execution speed , price improvement frequency and the liquidity enhancement frequency statistical measures . the user assigns a raw weight value of 9 to the execution speed statistical measure , a raw weight value of 6 to the price improvement frequency statistical measure , and a raw weight value of 2 to the liquidity enhancement frequency statistical measure . the user - defined raw weights are then processed to obtain relative weight values , namely the raw weight values of 9 , 6 and 2 are combined to obtain a combined raw weight value of 17 . each of the user - defined raw weight values are then divided by the combined raw weight value to obtain respective relative weight values . thus , the relative weight value of the execution speed statistical measure is { fraction ( 9 / 17 )} or 52 . 9 %, the relative weight value of the price improvement frequency statistical measure is { fraction ( 6 / 17 )} or 35 . 3 %, and the relative weight value of the liquidity enhancement frequency statistical measure is { fraction ( 2 / 17 )} or 11 . 8 %. the relative weight values may be determined at the user &# 39 ; s device or at the location of the broker / dealer . thus , the best execution profile form 102 represents a profile of user predilections for the various execution qualities . the profile is then used to determine how a current trade or a future trade is to be routed . as fig4 shows , after or concurrent with completing the best execution profile form 102 , the user 100 transmits the best execution profile form 200 to a broker / dealer 300 in the manner described above . upon receipt of the completed best execution profile form 200 at the broker / dealer 300 , the user - supplied information contained in the best execution profile form 200 is entered manually or electronically into a storage medium of a computer 400 or similar device . the computer and / or the storage medium may be located at the broker / dealer &# 39 ; s office or may be located elsewhere and connected via a network to the broker / dealer . the computer 400 also communicates with a database 500 that is located either within the computer 400 or within a respective stand - alone unit . the database 500 stores respective statistical measures of the execution quality parameters for securities traded at one or more market centers that correspond to some or all of the execution quality parameters shown on the best execution profile form 200 . the statistical data is dynamically derived from historical and current data concerning the securities traded at a particular market and may change with the availability of new statistical information . for example , the database may contain the following information : the price improvement measure for security 1 at market center 1 is value x . the price improvement measure for security 1 at market center 2 is value y . the price improvement measure for security 2 at market center 1 is value z . the price improvement measure for security 2 at market center 2 is value q . after the best execution profile form 200 information is stored in the computer 400 , the predictive automated routing of user trades may be carried out in real time by a processor located within the computer 400 as a function of the best execution statistics of one or more market centers . for example , a user 100 that previously supplied a best execution profile form may subsequently telephone the broker / dealer , electronically access the network site of the broker / dealer , or otherwise contact the broker / dealer 300 and request a purchase of 100 shares of motorola ™ stock . the broker / dealer 300 may then access the computer 400 , enter the user &# 39 ; s name and / or other identification , and enter the name and quantity of the security that is to be traded . alternatively , the user accesses the computer or other client device of the broker / dealer to perform these operations directly . the computer 400 then uses the user &# 39 ; s previously stored best execution profile containing the execution quality preferences , using the information stored from the best execution profile form , to select the market center where the trade is to be carried out . alternatively , the computer uses a profile of newly - supplied execution quality preferences provided concurrently with the current request , to select the market center where the trade is to be effected . referring back to fig1 a predictive automated routing system ( pars ) 110 contained within the computer routes a user requested trade 114 by first accessing a database 112 to read the statistical measures stored therein that correspond to the user - selected execution quality preferences . the predictive automated routing system ( pars ) 110 then analyzes the statistical measures for any and all market centers to determine the market center most likely to provide the best execution , as shown at 118 , namely the market centers having the highest likelihood of meeting the user - selected best execution profile 116 criteria . [ 0033 ] fig5 illustrates an example in which the user issues a “ buy ” order 402 to purchase of 300 shares of microsoft ™ stock . if the user &# 39 ; s stored best execution profile 510 indicates that price improvement is most heavily weighted , followed in weight by the speed of execution , the pars determines which market center has the highest likelihood of meeting the criteria in the user profile 510 for the order . referring back to fig1 once the market center 132 having the closest match to the user - defined best execution profile is determined , the order is automatically routed to that market center , as shown at 120 . [ 0035 ] fig6 illustrates an example of the operations carried out to determine the market center having the closest statistical match to the user &# 39 ; s best execution profile . column [ a ] represents the relative weight values of the user - defined statistical measures shown in fig3 . when an order is issued by the user , the pars obtains performance data corresponding to each of the user - defined statistical measures for each of market center 1 , market center 2 , . . . , market center n from the database , as shown in columns [ c ], [ f ], and [ l ]. the pars then averages the market center performance data of each of the user - defined statistical measures , as column [ b ] shows , and determines a relative strength of each of the user - defined statistical measures for each market center using the average values . when a lower performance data value is more desirable , the relative strength is determined by dividing the average value of the user - defined statistical measure by the performance data of the user - defined statistical measure for the market center . as an example , a lower execution speed statistical measure is more desirable than a higher value , and therefore the execution speed relative strength of a respective market center is determined by dividing the average execution speed of the market centers , shown in column [ b ], by the execution speed of the respective market center , shown in columns [ c ], [ f ], and [ l ], to obtain the relative strengths , shown in columns [ d ], [ g ] and [ j ]. alternatively , when a greater value is more desirable , the relative strength of a particular user - defined statistical measure is determined by dividing the performance data of the statistical measure for the respective market by the average value of the statistical measure . as an example , a higher price improvement frequency value is more desirable than a lower value and a higher liquidity enhancement frequency value is more desirable than a lower value so that the relative strength of the price improvement frequency and the liquidity enhancement frequency statistical measures of a particular market center are determined by dividing the corresponding performance data of the respective market center , shown in columns [ c ], [ f ] and [ l ] by the average value of the corresponding statistical measure for all of the market centers , shown in column [ b ]. the pars then determines weighted performances for each of the market centers by multiplying the user - defined relative weight values of the statistical measure for a respective market center , shown in column [ a ], by the relative strengths of the user - defined statistical measures for the respective market center , shown in columns [ d ], [ g ] and [ j ], to obtain the weighted performance values , shown in columns [ e ], [ h ] and [ k ]. thereafter , the pars combines the weighted performances of the user - defined statistical measures for each respective market center to obtain a market center score for the market center . then , the pars selects the market center having the highest market center score to carry out the requested transaction . alternatively , other methods may be used to determine the market center having the closest statistical match to the user - defined best execution profile . although the present invention has been described in relation to particular embodiments thereof , many other variations and modifications and other uses may become apparent to those skilled in the art . it is preferred , therefore , that the present invention be limited not by this specific disclosure herein , but only by the appended claims . the following claims are thus intended to cover all of the generic and specific features of the invention described herein , and all statements of the scope of the invention which , as a matter of language , might be said to fall therebetween .