Patent Application
20160125538
The present invention relates generally to automated electrical financial management and more particularly to portfolio selection.
A financial portfolio is a set of financial assets or securities (ex: stocks, bonds, etc.). At its most basic level, it is specified by the level of the portfolio owner's investment in each asset. Financial portfolio owners typically try to optimize financial indicators based on their preferences. Key preferences include liquidity and expected financial return on investment balanced with risk over some period of time. Portfolio owners typically seek a diverse portfolio spanning different types of investments, sectors of activity and geographies, since this might hedge the risks involved. The portfolio owner may have specific requirements, for instance, they may wish to include or exclude certain types of financial assets based on their geographies or industries. Generally, the overall objective is to maximize the return on investment (ROI) over some time period, while trying to manage risk, liquidity and the afore-mentioned preferences.
Embodiments of the present invention disclose a method, computer program product, and system for generating financial portfolios, the method included categorizing, by a computer, financial assets in a database of financial portfolios into asset categories based on their characteristics, clustering, by the computer, the financial portfolios of the database into a plurality of portfolio clusters based on the asset categories, each portfolio cluster includes financial portfolios having similar asset allocations in similar asset categories, identifying, by the computer, a target portfolio cluster from the plurality of portfolio clusters based on pre-defined financial metrics, and generating, by the computer, novel combinations of assets within the boundaries of the target portfolio cluster, the novel combinations of assets have similar asset allocations in similar asset categories and similar financial metrics as the target portfolio cluster.
The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
Financial portfolios (hereinafter “portfolios”) and targets evolve over time, depending on investment goal and horizon, or changes in financial markets. There are many possible financial assets (hereinafter “assets”) and combinations of assets that a portfolio owner could consider. Due to the sheer quantity, a portfolio owner may therefore not have the necessary knowledge nor the capability to select assets among the many potential investments. How can a portfolio owner generate a creative set or grouping of assets combinations (that may go well together) to choose from? How can a portfolio owner find an asset combination that is aligned with their financial objectives, such as maximizing expected return, and satisfy custom constraints on investment categories, such as, risk and liquidity?
Embodiments of the present invention use a novel portfolio generation program to create financial portfolios that meet the specified user-defined requirements by using a database of existing portfolios. The portfolio generation program will recommend a novel portfolio that is creative, for example, a portfolio that might be novel while simultaneously satisfying the owners preferences and constraints regarding financial KPIs (ex: risk-adjusted reward). The value of novelty is that it may expose new and creative ways to achieve desired financial goals. In its most basic form, the portfolio generation program may first cluster similar combinations of assets from a database of existing portfolios. Next, the program identifies a portfolio category or cluster which best represents the desired investment strategy of a user. Finally, the program will generate and select a creative a new portfolio, based on the cluster.
Referring now to
The network 106 may include wired connections, wireless connections, fiber optic connections, or some combination thereof. In general, the network 106 can be any combination of connections and protocols that will support communications between the client computer 102 and the server computer 104. The network 106 may include various types of networks, such as, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, a telecommunication network, a wireless network, a public switched network and/or a satellite network.
In various embodiments, the client computer 102 and/or the server computer 104 may be, for example, a laptop computer, tablet computer, netbook computer, personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smart phone, a mobile device, or any programmable electronic device capable of communicating with the server computer 104 via the network 106. As described below with reference to
In an embodiment, the system 100 may include any number of client computers 102 and/or server computers 104; however only one of each is shown for illustrative purposes only. It may be appreciated that
In an embodiment, the portfolio generation program 116 may run on the server computer 104. The portfolio generation program 116 may be used to generate a novel portfolio of financial assets, or novel financial portfolio, corresponding with individualized investment constraints or financial metrics. For example, a user may access the portfolio generation program 116 running on the server computer 104 via the client computer 102 and the network 106. The user may use the client computer 102 to input or provide the portfolio generation program 116 with the investment constraints, and the portfolio generation program 116 will generate and provide the user, via the client computer 102, with a novel portfolio matched to the inputted investment constraints. The portfolio generation program 116 and associated method is described and explained in further detail below with reference to
Referring now to
The portfolio database may then be processed to identify unique portfolios having consistent or steady asset allocation over time. The unique portfolios identified during processing of the portfolio database may then be compiled to generate a portfolio knowledge base. In an embodiment, the portfolio knowledge base may be a modified version of the portfolio database. In another embodiment, the portfolio knowledge base may be another database separate and apart from the portfolio database. During processing of the portfolio database, an individual portfolio may be split and identified as two or more unique portfolios when the asset distribution within the portfolio changes above a certain threshold, for example, 1%. By splitting the portfolios as described above, each unique portfolio may be defined by a more uniform and constant asset composition. Additionally, portfolios with a lifespan shorter than a predetermined threshold, for example 1 year, may be discarded or ignored during processing, and thus omitted from the portfolio knowledge base. The portfolio knowledge base may include all of the unique portfolios identified during processing.
For example, portfolio A of the portfolio database may be processed by the portfolio generation program 116. Portfolio A began or was created on January 2010 with an asset allocation of 50% IBM assets and 50% American Express assets. On January 2011 portfolio A's asset allocation switched to 100% IBM. Therefore, after processing, portfolio A would be classified into two unique portfolios, portfolio B and portfolio C, due to the change in the investment distribution in January 2011. Portfolio B would include an asset allocation of 50% IBM assets and 50% American Express assets, and portfolio C would include an asset allocation of 100% IBM assets.
The portfolio knowledge base may further contain characteristic information for each unique portfolio as well as for individual assets of the unique portfolios. For each unique portfolio the portfolio knowledge base may include information such as start date, end date, start value, end value, and asset composition. For individual assets the portfolio knowledge base may include information such as risk assessment, returns assessment, asset type, sector of activity, and geography.
Referring now to
With specific reference to
Next, category values may be assigned to each asset category of each unique portfolio. The assignment of category values may be based on the asset allocation of a particular category of assets within a unique portfolio. The asset allocation may be measured in terms of a percentage and may be used to assign a corresponding category value from a predetermined range of values. For example, a higher asset allocation percentage may correspond with a higher category value and a lower asset allocation percentage may correspond with a lower category value. In an embodiment, the category value may be equal to the percentage of a portfolio that belongs to a given asset category. In other words, the category values may be represented as a percentage. It should be noted that the ten portfolios in
For example, with continued reference to
Next, with specific reference to
In an embodiment, clustering algorithms such as k-means clustering may be used to cluster the unique portfolios. For example, select a number of clusters K so that K is at least 5-10 times greater than the number of financial assets, and the number of portfolios in the database is at least 5-10 greater than K.
For example, the post-clusterization chart of
It should be noted that the number of portfolios and asset categories depicted in the figures are limited for illustration purposes only. Furthermore, the range and scale of category values is limited for illustration purposes only and a different scale with different graduations may be used for improved granularity and/or accuracy.
With continued reference to
Referring now to
In an embodiment, the portfolio generation program 116 may receive the financial metrics from a sample portfolio provided by the user. Alternatively, the portfolio generation program 116 may receive the financial metrics as user inputs. In an embodiment, more specifically, an owner or user may input the financial metrics into the client computer 102, and the portfolio generation program 116 running on the server computer 104 may receive the same from the client computer 102 via the communication network 106.
For example, the financial metrics may include but are not limited to, expected return and value-at-risk (VaR). Next, a set of portfolio clusters satisfying the desired financial metrics are selected by comparing and matching the sample portfolio and/or user provided metrics to the portfolio clusters in the portfolio knowledge base (step 504). The set of portfolio clusters may include one or more portfolio clusters that satisfy the preferred financial metrics of the user.
In an embodiment, the portfolio generation program 116 may use mathematical optimization or multi-objective optimization to compute the pareto optimal set of financial portfolio clusters or efficient frontier set of portfolio clusters based on the desired financial metrics. In the present embodiment, the efficient frontier may be a set of optimal portfolios that offers the highest expected return for a defined level of risk or the lowest risk for a given level of expected return in which the financial metrics define the risk and/or expected return. In general, portfolios that lie below the efficient frontier are sub-optimal, because they do not provide enough return for the level of risk. Additionally, portfolios that lie to the right of the efficient frontier are also sub-optimal, because they have a higher level of risk for the defined rate of return.
After the set of portfolio clusters is chosen, any additional investment preferences may be considered and the set of portfolio clusters may be further narrowed, if at all (step 506). Optionally, additional investment preferences or constraints regarding specific assets, asset categories, etc. may also be provided by the user. For example, a user may prefer that predicted risk or predicted return should be below or above a certain threshold, respectively. For example, the user may also prefer that the target portfolio should belong to the same cluster as the user's current portfolio or a sample portfolio, or that some of the category values of a particular asset category for the target portfolio cluster must be within a certain range, for example 50-60% of assets in Asia. In other words, the set of portfolio clusters may shrink or be reduced after taking into consideration any additional investment preferences. If the user provides additional investment preferences, a sub-set of portfolio clusters satisfying the additional investment preferences may be selected from the set of portfolio clusters (step 508), from which one or more target portfolio clusters may be selected (step 510).
If the user does not provide any additional investment preferences, one or more target portfolio clusters may be selected from the set of portfolio clusters (step 510). The target portfolio cluster(s) may preferably have similar asset allocations in similar asset categories as the sample portfolio provided by the user. Furthermore, the target portfolio cluster(s) may preferably have similar investment constraints or financial metrics as the sample portfolio provided by the user. In an embodiment, for example, the portfolio generation program 116 may provide the client computer 102, and as such the user, with the set of portfolio clusters, or a subset of portfolio clusters, from which the user may choose a target portfolio cluster. It should be noted that the target portfolio cluster(s) may either be identified and chosen by the portfolio generation program 116 or identified by the portfolio generation program 116 and chosen by the user.
Referring now to
In the present example, the sample portfolio is most similar to cluster 1 and cluster 5 with respect to asset allocation as determined by comparing respective category values. Next, with respect to the financial metrics, the sample portfolio is most similar to cluster 1, both of which are classified as high risk high return. Therefore, cluster 1 may be chosen or selected as the target portfolio cluster due to it close match to the sample portfolio and satisfaction of the user provided financial metrics. Cluster 5 is classified as being high risk low return, and therefore, cluster 5 in the present example, would not likely be considered for the target portfolio cluster due to the mismatch between the financial metrics, specifically the low return. It should be noted that if the portfolio generation program 116 identifies more than one target cluster, it may instruct the user to select a single target portfolio cluster.
With continued reference to
With continued reference to
Referring now to
The computing device may include one or more processors 702, one or more computer-readable RAMs 704, one or more computer-readable ROMs 706, one or more computer readable storage media 708, device drivers 712, a read/write drive or interface 714, a network adapter or interface 716, all interconnected over a communications fabric 718. The communications fabric 718 may be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications and network processors, etc.), system memory, peripheral devices, and any other hardware components within a system.
One or more operating systems 710, and one or more application programs 711, for example, the portfolio generation program 116, are stored on the one or more of the computer readable storage media 708 for execution by one or more of the processors 702 via one or more of the respective RAMs 704 (which typically include cache memory). In the illustrated embodiment, each of the computer readable storage media 708 may be a magnetic disk storage device of an internal hard drive, CD-ROM, DVD, memory stick, magnetic tape, magnetic disk, optical disk, a semiconductor storage device such as RAM, ROM, EPROM, flash memory or any other computer-readable tangible storage device that can store a computer program and digital information.
The computing device may also include the R/W drive or interface 714 to read from and write to one or more portable computer readable storage media 726. Application programs 711 on the computing device may be stored on one or more of the portable computer readable storage media 726, read via the respective R/W drive or interface 714 and loaded into the respective computer readable storage media 708.
The computing device may also include the network adapter or interface 716, such as a TCP/IP adapter card or wireless communication adapter (such as a 4G wireless communication adapter using OFDMA technology). Application programs 711 on the computing device may be downloaded to the computing device from an external computer or external storage device via a network (for example, the Internet, a local area network or other wide area network or wireless network) and network adapter or interface 716. From the network adapter or interface 716, the programs may be loaded onto computer readable storage media 708. The network may comprise copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers.
The computing device may also include a display screen 720, a keyboard or keypad 722, and a computer mouse or touchpad 724. The device drivers 712 interface to the display screen 720 for imaging, to the keyboard or keypad 722, to the computer mouse or touchpad 724, and/or to the display screen 720 for pressure sensing of alphanumeric character entry and user selections. The device drivers 712, R/W drive or interface 714 and network adapter or interface 716 may include hardware and software (stored on computer readable storage media 708 and/or ROM 706).
The programs described herein are identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular program nomenclature herein is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature.
Based on the foregoing, a computer system, method, and computer program product have been disclosed. However, numerous modifications and substitutions can be made without deviating from the scope of the present invention. Therefore, the present invention has been disclosed by way of example and not limitation.
