Abstract:
Various embodiments of the present invention are directed to systems and methods for algorithmic trading strategies and/or systems and methods for use in executing an order directed to a security traded in a market. More particularly, one embodiment of the present invention relates to a method implemented by a programmed computer system for use in executing an order directed to a security traded in a market, comprising: calculating a plurality of expected market impacts associated with execution of the order over a plurality of different time periods; calculating a plurality of expected price risks associated with execution of the order over the plurality of different time periods; calculating a plurality of expected total costs associated with execution of the order over the plurality of different time periods, wherein the plurality of expected total costs are calculated using the plurality of expected market impacts and the plurality of expected price risks; and trading the security via execution of the order over a time period at which the expected total cost is optimal (e.g., minimized).

Description:
RELATED APPLICATIONS 
     This application claims the benefit of U.S. Provisional Application Ser. No. 60/577,771, filed Jun. 7, 2004. 
    
    
     FIELD OF THE INVENTION 
     Various embodiments of the present invention are directed to systems and methods for algorithmic trading strategies and/or systems and methods for use in executing an order directed to a security traded in a market. 
     More particularly, one embodiment of the present invention relates to a method implemented by a programmed computer system for use in executing an order directed to a security traded in a market, comprising: calculating a plurality of expected market impacts associated with execution of the order over a plurality of different time periods; calculating a plurality of expected price risks associated with execution of the order over the plurality of different time periods; calculating a plurality of expected total costs associated with execution of the order over the plurality of different time periods, wherein the plurality of expected total costs are calculated using the plurality of expected market impacts and the plurality of expected price risks; and trading the security via execution of the order over a time period at which the expected total cost is optimal (e.g., minimized). 
     BACKGROUND OF THE INVENTION 
     Various stock trading and order execution mechanisms have been proposed. Examples include the mechanisms described in the following patent documents. 
     United States Patent Application 2005/0075965 relates to a securities market and market maker activity tracking system and method. More particularly, this application relates to a method, system and computer program to monitor securities market activity to seek out imbalances in market activity that could lead to a price change in a particular security. Level 1 and/or level 2 data is analyzed to track the activity of market makers and to derive indicators of momentary upward or downward price pressure. The indicators associated with each selected security can be displayed to a user. 
     United States Patent Application 2004/0148242 relates to a method and system for intelligent automated security trading via the Internet. More particularly, this application relates to a method and system for intelligent automated security trading via the Internet, which provides an Automated Trading Service Center (ATSC), offering a Home Page Service and managing at least one Virtual Fund Manager (VFM) system. The ATSC is a wireless e-commerce service center providing automated trading services to investors anytime anywhere. By accessing the HPS, the investor can interact with ATSC to develop a custom investment strategy based personal VFM system to automatically trade electronic trading based securities. The VFM is a real time running program incorporated by four engines: the Quote Processing Engine, the Decision Making Engine, the Order Execution Engine, and the Order Processing Engine. Under commands of ATSC server, the VFM can periodically retrieve quotation from the security exchange, monitor the market fluctuation by performing intensive calculations to detect the desired Buy/Sell timing as predetermined by investor&#39;s proprietary investment strategy algorithms, and ultimately execute the transaction automatically. 
     United States Patent Application 2004/0024690 relates to a volume limitation method and system for a real-time computerized stock trading system. More particularly, as provided for in this application a system controls the volume of trading for an individual investor for a given stock and protects against market domination in real-time computerized stock trading systems. These stock trading systems may provide trading environments that do not have sufficient liquidity and may thus be susceptible to market domination due to large trade orders placed typically by large institutions or users with great resources. The system determines a volume limit and rejects or flags new trade orders that make a user&#39;s total trading volume for a certain stock exceed the determined volume limit. 
     United States Patent Application 2003/0101128 relates to a state tracking system for a basket trading system. More particularly, this application relates to a tracking system that includes an order tracking database that stores the status of orders as they are processed within a distributed order fulfillment system that has a number of order execution systems that fill all or part of each order. Each order goes through a number of different transaction stages and the result of each stage is reported as an event to the database. The events are transmitted as messages using an output queue in the order execution system and an event message queue in an event tracking service. The tracking service updates the database when events appear in the event queue. The message processing system operates independently of order processing allowing order processing to continue while the tracking service updates the database. The messages include the components of an asset record of a core system database. The status of any order within the distributed system can be obtained from the database. The system also includes execution confirmation and error tracking with corresponding centralization of this information. 
     United States Patent Application 2002/0184237 relates to methods and apparatus for compiling, processing and disseminating equity transaction data. More particularly, this application provides a system for distributing data describing trading activity occurring on a plurality of different Electronic Communications Networks (ECNs), each of which receives buy and sell orders from stock traders and each of which performs equity sales transactions based on the received orders. Live data fed from each ECN describing pending buy and sell orders and executed transactions on each exchange are reformatted into standard form and aggregated to create, update and maintain consolidated trading data that is stored in a database. In response to one or more request specifications received from a remotely located user, the system extracts and processes selected portions of the consolidated data to produce response data returned to the requestor. This requested data may include streaming ticker tape and stock status data describing the status of all or a selected subset of stocks being actively traded on the multiple ECNs; an index value representative of the current selling price of a predetermined group of securities being traded on the multiple ECNs, depth-of-book data describing the current best pending offers to buy and sell one or more selected securities, and news stories concerning the securities being traded, including artificially generated natural language text news which is automatically produced by items of consolidated ECN data that satisfies predetermined conditions which define “newsworthy” events. 
     United States Patent Application 2002/0152153 relates to a securities trading system, computer system, buy/sell order placement method, buy/sell order processing method, and program. More particularly, this application provides a securities trading system including a customer&#39;s PC  30  connected to the Internet  10 , a securities company&#39;s site  20  which is connected to the Internet  10  and processes securities trading orders from the customer&#39;s PC  30 , and an exchange&#39;s computer  50  connected to the securities company&#39;s site  20  via a leased line  40 , wherein the securities company&#39;s site  20  provides information of a group order entry screen for entering an order covering multiple issues and their respective limit prices specified as a group, to the customer&#39;s PC  30 , and after displaying the group order entry screen information provided by the securities company&#39;s site  20  in a browser  31 , the customer&#39;s PC  30  outputs a group order covering a group of issues for which respective limit prices are specified, through the Internet  10 . 
     United States Patent Application 2002/0138401 relates to a method and system for automatic execution of a securities transaction. More particularly, as provided for in this application a securities transaction, such as a buy or sell order is transmitted to a securities exchange with an indicator requesting automatic execution. In one embodiment, the securities transaction has a limit price and if the limit price is equal to or better than the current quote for the security on the exchange, the transaction is automatically executed without exposing the transaction to the auction market crowd on the exchange floor for possible price improvement. In another embodiment, the securities transaction is a market order, and if otherwise eligible, the transaction is automatically executed without exposing the transaction to auction market crowd on the exchange floor for possible price improvement. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a chart in connection with a first embodiment of the present invention; 
         FIG. 2  shows a chart in connection with another embodiment of the present invention; and 
         FIG. 3  shows a chart in connection with another embodiment of the present invention. 
     
    
    
     Among those benefits and improvements that have been disclosed, other objects and advantages of this invention will become apparent from the following description taken in conjunction with the accompanying figures. The figures constitute a part of this specification and include illustrative embodiments of the present invention and illustrate various objects and features thereof. 
     DETAILED DESCRIPTION OF THE INVENTION 
     Detailed embodiments of the present invention are disclosed herein; however, it is to be understood that the disclosed embodiments are merely illustrative of the invention that may be embodied in various forms. In addition, each of the examples given in connection with the various embodiments of the invention are intended to be illustrative, and not restrictive. Further, the figures are not necessarily to scale, some features may be exaggerated to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention. 
     Referring now to  FIG. 1 , a first embodiment of the present invention (hereinafter sometimes referred to as the “expected impact and market risk” embodiment) will be described. 
     More particularly, this expected impact and market risk embodiment may utilize an algorithm designed to help the user make a quantitative decision regarding execution strategy by optimally balancing expected market impact and market risk (see  FIG. 1 ). In this regard, the impact cost estimates may be generated by various trading cost models. In one example (which example is intended to be illustrative and not restrictive), the cost models may generate cost estimates by taking into account key stock and/or order characteristics, such as (but not limited to): order size; expected volume and spreads over execution horizon; market capitalization; listing venue (e.g., exchange); volatility; and price level. The algorithm may use these costs estimates along with the risk of the stock (e.g., price risk over time) and the user&#39;s risk aversion to generate an optimal trading strategy. This strategy may be dynamically adjusted to adapt to changing market dynamics and to deviations from historic patterns. 
     In another example (which example is intended to be illustrative and not restrictive), relevant trading parameters such as (but not limited to): volatility; spread; market cap; volume; and the user&#39;s risk aversion (e.g., measure of perceived strength of alpha/immediacy of execution) may be used by the algorithm to develop the trading strategy. 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may have an “aggressive” component and a “defensive” component, which work in tandem to execute the order. The “defensive” component may work the order with volume trying to maximize spread capture, while the “aggressive” component may look for pockets of liquidity at favorable price points (e.g., depending on the risk aversion selected by the user). 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may utilize the following:
         Size Restriction: No limit (the larger the size, the greater the variability of actual cost relative to benchmark cost estimate).   Minimum Duration: 10 minutes   Optional Parameters: Start time, End time, Price limit, Risk aversion level.       

     Of note, the algorithm may provide guidance when the user is uncertain about the appropriate trading horizon. 
     Of further note, specific execution objectives may be achieved with the prudent use of risk aversion. For example:
         By selecting a low risk aversion, the user can maximize the spread capture and reduce market impact by working the execution over a longer horizon—but allows for greater price risk. Most effective for less volatile names and/or where the user has no short-term alpha, or for baskets which are dollar neutral.   By selecting a high risk aversion, the algorithm reduces price risk by providing speedier executions, but at the expense of possibly larger market impact. Most effective for volatile stocks and/or where user has a strong short-term alpha.       

     Referring now to  FIG. 2 , another embodiment of the present invention (hereinafter sometimes referred to as the “volume-weighted average price” (or “VWAP”) embodiment) will be described. 
     More particularly, this VWAP embodiment may utilize an algorithm designed to provide users with the ability to target an execution to a certain volume-weighted average price (see  FIG. 2 ). For example (which example is intended to be illustrative and not restrictive), the algorithm may take into account user-defined parameters as well as the security&#39;s historical trading profile to execute the order. In another example (which example is intended to be illustrative and not restrictive), the algorithm may analyze historical patterns in the stock&#39;s trading volumes to determine the optimal execution trajectory for each order. In another example (which example is intended to be illustrative and not restrictive), while the order is alive, users may have the ability to update and/or cancel their order (providing them with a high level of comfort and flexibility when using this order type). 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may utilize statistical theoretical values (this may help in maximizing the probability of spread capture within the given constraints). 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may have the ability to use short-term technical indicators to make appropriate adjustments to the originally determined trading trajectory. 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may allow the users to dynamically change their price limits and/or order size. 
     In another example (which example is intended to be illustrative and not restrictive), cancellations may be allowed at any time during the working cycle (this may provide the user with flexibility of operation and control-subject, for example, to NYSE, NASDAQ &amp; TSX regulatory requirements). 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may utilize the following:
         Duration: Minimum 5 minutes.   Optional Constraints:
           Start time (defaults to order entry time).   End time: (defaults to 16:00 EST).   Price limit   Volume limit: be no more than a certain percentage of the volume at any time during the execution.   
               

     In another example (which example is intended to be illustrative and not restrictive), the algorithm may be used for orders benchmarked to the VWAP since a primary objective of the algorithm may be to minimize deviation from VWAP. 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may be effective for sizeable orders that would have significant market impact if executed immediately. In this regard, the algorithm may permit the user to reduce market impact in a low-touch, yet customizable way by spreading orders out over time, trading most at those times of day when volumes have historically been greatest and scaling back during times where volumes have historically been light. 
     Of note, the performance relative to VWAP may depend on both price and volume volatility (e.g., the greater the volatility, the more likely the order is to deviate from the VWAP, both favorably and unfavorably). 
     Of further note, even though the algorithm may try to reduce market impact by working the order over time consistent with historical volume patterns, the order may have significant impact if the order is large relative to the stock&#39;s volume. The risk of market impact is greatest for less liquid stocks (i.e., those characterized by relatively low trading volume, high spreads, and/or low market capitalizations). In this regard, using price and volume constraints may allow the user to reduce market impact. However using these constraints actively may increase the probability that the order will not be completed by the end time. 
     Referring now to  FIG. 3 , another embodiment of the present invention (hereinafter sometimes referred to as the “participate” embodiment) will be described. 
     More particularly, this participate embodiment may utilize an algorithm designed to automate the process of achieving a certain percentage of the market volume. The algorithm may watch and react to real-time stock volume in the market, targeting the specified percentage of volume. The algorithm&#39;s ability to adjust its execution strategy to the available liquidity and the user&#39;s ability to decide certain parameters may help lead to an optimal outcome. 
     In one example (which example is intended to be illustrative and not restrictive), the algorithm may monitor market activity (e.g., essentially continuously) to gauge the liquidity in real-time as opposed to estimating it using historical data. This may help the algorithm to stay in-line with the desired level of participation. 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may attempt to capture spread by working multiple child orders simultaneously (e.g., with each child order priced at a different price level). 
     In another example (which example is intended to be illustrative and not restrictive), by using different volume limits, the user may have the option to control the aggressiveness of the execution. 
     In another example (which example is intended to be illustrative and not restrictive), the algorithm may provide the user with the flexibility to set the following optional parameters:
         Start time and Price limit   “Ignore Print” feature
           Absolute Print Size—will not respond to trades of a specified size (or larger).   Average Daily Volume %—will not respond to trades above the specified percentage of average daily volume.   
               

     Of note, the present invention may be applied when the user does not want his order to outsize the marketplace (depending on the participation rate and the order size, the order may not necessarily be completed). 
     Of further note, under the present invention the original order may be split into multiple “child orders”. In this regard, the algorithm may revise its trading strategy (e.g., in real-time) with regard to child order placement as child orders are executed and as market conditions change. In one example (which example is intended to be illustrative and not restrictive), some child orders may be sent to the primary market and some may be sent to other destinations (e.g., to access visible and hidden liquidity). See Table 1 below for examples of various destinations (of course, these examples are intended to be illustrative and not restrictive): 
     
       
         
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                 Listed Destinations 
                 OTC Destinations 
               
               
                   
               
             
             
               
                 New York Stock Exchange 
                 ArcaEx 
               
               
                 American Stock Exchange 
                 B-TRADE 
               
               
                 Toronto Stock Exchange 
                 Brut 
               
               
                 Arca Exchange 
                 INET 
               
               
                   
                 SuperMontage 
               
               
                   
               
             
          
         
       
     
     In another embodiment the algorithmic models may derive pricing and/or trading estimates based on historical volume patterns, real-time market data and/or parameters selected by the user. Of course, the ability of the algorithmic models to achieve the performance described herein can be impacted by significant changes in market conditions such as increased volatility, price dislocations, material market events or news or trading halts. In addition, systems or communications failures may impact the ability to access the markets and, consequently, the performance of the algorithmic models. Finally, factors such as order quantity, liquidity, spread size and the parameters selected by the user may impact the performance results. 
     Of note, the invention may, of course, be implemented using any appropriate computer hardware and/or computer software. In this regard, those of ordinary skill in the art are well versed in the type of computer hardware that may be used (e.g., a mainframe, a mini-computer, a personal computer (“PC”), a network (e.g., an intranet and/or the Internet)), the type of computer programming techniques that may be used (e.g., object oriented programming), and the type of computer programming languages that may be used (e.g., C++, Basic). The aforementioned examples are, of course, illustrative and not restrictive. 
     While a number of embodiments of the present invention have been described, it is understood that these embodiments are illustrative only, and not restrictive, and that many modifications may become apparent to those of ordinary skill in the art. For example, certain methods have been described herein as being “computer implemented”. In this regard, it is noted that while such methods can be implemented using a computer, the methods do not necessarily have to be implemented using a computer. Also, to the extent that such methods are implemented using a computer, not every step must necessarily be implemented using a computer. Further, the specific dates, time spans, rates, prices, values and the like described with reference to the various examples are, of course, illustrative and not restrictive. Further still, the invention may encompass a “structure,” a “transaction,” a “system” and/or a “method”. Further still, any actions or steps may be done periodically (wherein the term periodic could refer, for example, to daily, weekly, monthly, quarterly, semiannually, annually or at varying intervals). Further still, the various steps may be carried out in any desired order, one or more steps may be deleted and/or one or more steps may be added.