U.S. patent application number 10/950751 was filed with the patent office on 2005-12-08 for method for tracking and predicting the price of a mutual fund prior to the close of the market.
Invention is credited to Vaudrie, Jeffrey D..
Application Number | 20050273413 10/950751 |
Document ID | / |
Family ID | 35450192 |
Filed Date | 2005-12-08 |
United States Patent
Application |
20050273413 |
Kind Code |
A1 |
Vaudrie, Jeffrey D. |
December 8, 2005 |
Method for tracking and predicting the price of a mutual fund prior
to the close of the market
Abstract
The present invention is a method for predicting mutual fund
prices. The method of the present invention involves tracking the
correlation of a mutual fund to an index, utilizing algorithms to
determine the optimum numbers of days to average the correlation
over and then predicting the price of the mutual fund prior to the
close of the market based on the movement of the index. A typical
prior art system monitors the price movement of a mutual fund and
sounds an alarm when a tolerance is breached, but since mutual
funds prices are only calculated at the end of each trading day one
would not be able to take action until the close of the following
day. The result could be increased losses and/or lost gains. To
prevent this, the present invention discloses a system that can
predict, based on the changes in the related index, where that
mutual fund will close at the end of the day and action can be
taken before the market closes. The method of the present invention
enables a user to make buy and sell decisions based on current data
more accurately and helps overcome the time-delay typical in buying
and selling mutual funds. The method uses quality assurance methods
to auto correct itself and can also be incorporated into automated
portfolio management systems known in the art.
Inventors: |
Vaudrie, Jeffrey D.;
(Johnson City, TN) |
Correspondence
Address: |
WHITE-WELKER & WELKER, LLC
P.O. BOX 199
CLEAR SPRING
MD
21722-0199
US
|
Family ID: |
35450192 |
Appl. No.: |
10/950751 |
Filed: |
September 27, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10950751 |
Sep 27, 2004 |
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10859859 |
Jun 3, 2004 |
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Current U.S.
Class: |
705/36R |
Current CPC
Class: |
G06Q 40/04 20130101;
G06Q 40/00 20130101; G06Q 40/06 20130101; G06Q 40/12 20131203 |
Class at
Publication: |
705/036 |
International
Class: |
G06F 017/60 |
Claims
1. A method for predicting mutual fund prices for use in an
automated portfolio monitoring system wherein; a mathematical
algorithm is used to determine and monitor the correlation between
a mutual fund and an assigned index; said algorithm determines the
optimum numbers of days to average the correlation over and then
predicts the price of the mutual fund prior to the close of the
market based on the movement of said index said algorithm predicts
where said mutual fund will close with respect to price, at the end
of the trading day; quality assurance methods are used by said
algorithm to auto correct itself; based on the changes in said
index and where said mutual fund will close at the end of the
trading day, action can be taken before the market closes.
2. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 1 comprising a first
process wherein; a first step where a specific mutual fund is
associated with a relevant market index for which real-time pricing
information is available; a second step of calculating a first
correlation ratio wherein: said first correlation ratio equals the
associated index closing price of a first day divided by the mutual
fund closing price of a first day a third step of repeating said
second step for multiple days resulting in correlation ratio (1 . .
. n); a fourth step in which the average of n days correlation
ratios is calculated as follows: (CR(1)+CR(2) . . . +CR(n) )/n); a
fifth step in which the standard deviation of n days correlation
ratios is similarly calculated resulting in two data points: n day
moving average and n day standard deviation.
3. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 2 comprising a
second process wherein; a first step wherein the process of claim 2
is repeated for multiple days resulting in a meaningful number of n
day moving averages and n day standard deviations; a second step
that determines which of the standard deviations from step one is
lowest.
4. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 2 wherein said
second step defaults to initially five days worth of data resulting
in a five-day average and five-day standard deviation.
5. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 4 wherein the
average and standard deviations of said firsts data set is
calculated resulting in a five-day average and five-day standard
deviation.
6. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 3 further comprising
a second process wherein; said first, second, and third steps are
repeated for every day between a period days between a first
selected date and a second selected date; and a determination of
which day the standard deviation is smallest is made with said day
becoming the default day.
7. The method for predicting mutual find prices for use in an
automated portfolio monitoring system of claim 6 wherein said
first, second, and third steps are repeated for every day between
days five and day seventy-five.
8. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claims 3 and 6 further
comprising a third process wherein, on a daily basis, the system
uses said default number of days to complete said first process
that provides the correlation factor and standard deviation to use
all day.
9. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claims 3 and 6 further
comprising a fourth process wherein daily quality control is
accomplished by using the last two or more days of data points for
the actual mutual fund closing price and predicted mutual fund
closing price and following a predetermined mathematical
algorithm.
10. The method for predicting mutual fund prices for use in an
automated portfolio monitoring system of claim 10 wherein quality
control is accomplished by using the last eight days worth of data
points for the actual mutual fund closing price and predicted
mutual fund closing price and following a predetermined
mathematical algorithm.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] Not Applicable
[0002] This application is a continuation of U.S. patent
application Ser. No. 10/859,859, entitled "Real-Time Client
Portfolio Management System", filed on Jun. 3, 2004.
[0003] This application cross-references U.S. patent application
Ser. No. 10/919,426, entitled "Improved Stop-Loss System Enabling a
Plurality of Investment Protection Levels", filed on Aug. 16,
2004.
[0004] This application cross-references U.S. patent application
Ser. No. 10/925,305, entitled "Stop-Loss and Trailing Stop-Loss
System Utilizing a Dynamic Price Adjusting Feature", filed on Aug.
24, 2004.
[0005] This application cross-references U.S. patent application
Ser. No. 10/924,299, entitled "Method for Monitoring Cash Reserves
and Determining Potential Investments for Purchase While Managing
Individual or Multiple Investment Portfolios", filed on Aug. 23,
2004
FEDERALLY SPONSORED RESEARCH
[0006] Not Applicable
SEQUENCE LISTING OR PROGRAM
[0007] Not Applicable
TECHNICAL FIELD OF THE INVENTION
[0008] The present invention relates generally to a method of
predicting the closing price of a mutual fund. The present
invention relates more specifically to a method for predicting the
closing value of a mutual fund through the use of an algorithm that
tracks the correlation of a mutual fund with respect to an index
which can predict, based on the changes in the related index, where
that mutual fund will close at the end of the day and action can be
taken before the market closes.
BACKGROUND OF THE INVENTION
[0009] There are numerous software packages monitored as portfolio
management systems available. Mainly, these systems focus on the
accounting functions necessary to track transactions within an
account, keep the accounts in balance and allow for the reporting
of gains and losses. Some systems include additional features such
as contact management, financial planning calculations and
rudimentary security analysis. Some allow for model portfolios to
be created and then applied to an account with reports that will
show the difference between the two. These systems may include the
ability to have the system generate the transactions necessary to
convert the actual holdings to the model portfolio, but all of
those systems assume the conversion happens at the same point in
time. They do not allow for the gradual transition from the actual
portfolio to the model portfolio over time based on a set of
pre-determined factors.
[0010] Some existing systems (especially those with financial
planning functions) include portfolio return estimates, but they
rely on long-term historical returns for each of the underlying
investment classes. They do not allow estimates and resulting
portfolio management decisions to be based on an advisor's
short-term, forward-looking estimates of market performance. The
result is that historical returns can be far greater than those
expected in the short-term and can overstate the estimated
return.
[0011] No systems are available to the inventor's knowledge that
allow for the automating of the investment purchase and sale
process according to predetermined criteria that can vary from
client to client. No systems are available to the inventor's
knowledge that would monitor every investment in every client's
account and compare those predetermined levels against real-time
pricing data and signal an alert when that criteria is
breached.
[0012] There are a few systems available that aid an advisor in
making buy and sell decisions for an individual security based on
technical indicators, but these systems do not provide a
comprehensive portfolio management system that extends those
decisions to numerous clients while allowing different settings for
each client. The result is that the advisor would make a decision
on the security as a whole and then process a buy or sell across
all accounts holding that security. This process does not take into
account the specific circumstances in each account, including when
it was purchased and whether or not there is a gain or loss.
[0013] To the inventor's knowledge, none of the existing systems
available provide for the ability to assign an action level to each
investment in an account and then alert the advisor when that
action level was reached. For instance, suppose a client invested
$100k in security X but said that if security X lost $7,257 that
the advisor should sell it. In these situations the advisor would
need to manually enter a stop-loss order at the associated share
price. Existing systems do not provide this capability, especially
for numerous action levels on each investment in every client's
account. The result is that advisors are not able to provide a
sophisticated level of service and monitoring of a client's
accounts. This can result in additional losses to the client.
[0014] Additionally, none of the existing portfolio management
systems monitor securities in real-time to determine the
appropriate buy point based on technical analysis. This increases
the possibility of an advisor buying a security at the wrong
time.
[0015] There are not any systems that allow an advisor to predict
where a mutual fund will close on any given day and thus be able to
make the buy/sell decision prior to that day's market close. This
results in there being a 1-day lag between when the decision was
made and when the transaction could be processed. In rapidly
changing environments, this can result in additional losses or lost
gains to the client.
[0016] Numerous systems exist in the prior art for determining when
to sell a real investment. Most of these pertain to short term
investing and/or day trading. The most basic incarnation of this
system is a stop loss order. These are orders placed with a broker
when an investment is bought. These systems have varying features,
but most buyers place a fixed share price threshold that will
trigger an investment to be sold. This threshold is always a single
amount, not a plurality of amounts with variable liquidation
percentages. Some systems are even automated through a computer
program to track the price of an investment and make the selling
trade when a dynamic share price threshold is broken by the
downward movement in an investment's price. This system is commonly
referred to as trailing stop loss.
[0017] These systems fail to adequately protect long-term
investors. Both work in the context of actual dollars that prevents
the stop loss from changing proportionally with the investment as
it grows in value. Take this example. A standard stop loss order is
placed with the purchase of an investment. The investment was
purchased at $100 per share. The stop loss was placed at $95 per
share. The investment then grows to $150 per share. The stop loss
would still be at $95 per share leaving the investor a potential
loss of $65 per share before the stop loss would be activated. That
system allows for too much potential loss. A trailing stop loss
would perform better. Instead of a stop loss of $95 per share in
the previous example the investor utilizes a trailing stop loss of
$5 per share. That means that when the investment is priced a $150
per share the stop loss trigger would be $145 per share. When
originally placed the stop loss was 5% of the price per share. When
the investment reaches $150 per share the stop loss of $5 per share
will only be 3.33% of the price per share. The shrinking difference
as a percentage would become undesirable to an investor who wants
to allow the investment room to grow.
[0018] An improved system would be dynamic, that is, changing with
an investments high price per share. It would have a plurality of
triggers and a plurality of liquidation percentages. It would also
be proportional, that being a percentage of an investments price
per share. The system would utilize time sliced data on an
investments price from a communication medium such as the Internet
and automatically adjust the plurality of triggers in real-time.
The system would automatically sell an investment when conditions
are met or trigger an alert for manual intervention.
[0019] All known stop loss systems in the prior art sell 100% of an
investment when a stop loss is triggered. This is well adapted to
short term investors but is not optimal for long-term investors.
Long-term investors are willing to accept a greater price
fluctuation for an investment. There are also possibly negative tax
implications for selling 100% of any investment. An improved system
would allow for plurality of stop losses with a plurality of
liquidation percentages. However no stop loss system such as this
exists to help better control the selling of investments.
SUMMARY OF THE INVENTION
[0020] When clients choose to work with an advisor, they typically
want that advisor to monitor their investments, make them grow and
take action to protect their money. This is particularly true for
clients who are retired. A portfolio management system allows them
to participate in the growth of the market but actively protects
their principal and locks in their profits should the market go
sour.
[0021] A portfolio management system is a sophisticated means of
automating the management of client's investment portfolios. A
portfolio management system may be comprised of several distinct
modules in a variety of configurations. The overall system provides
for the use of financial planning and time value of money
calculations to determine the growth rate needed for a client. The
client can then decide that they want a higher or lower rate. The
client's target growth rate (TGR) is then used to develop a target
asset allocation designed to achieve the client's TGR. To
accomplish this end, the Portfolio Management System of the present
invention uses the real-time management of multiple client
portfolios with alerts when any individual security performs
outside of pre-set tolerances. The Portfolio Management System also
has the ability to automate the buy and sell decision processes
base on a pre-defined strategy. This results in the ability to
transition from an actual client portfolio to a recommended
portfolio based on market events over time.
[0022] A buy and/or sell risk tolerance is assigned at the
security, account and/or client level. The system then continuously
monitors any existing investments, the balances of the accounts,
and the variance between the actual and target portfolios and
generates buy or sell alerts based on market movements. The P
portfolio management system creates a system that sets a plurality
of static floor levels with variable liquidation percentages.
[0023] Additionally, the present invention may create a system that
sets a plurality of dynamic proportional stop loss settings that
may have variable liquidation percentages. The combination of these
creates a preferred embodiment of the present invention that is
effective at protecting an investor's principle and allowing it to
grow.
[0024] The portfolio management system utilized by the present
invention has three novel attributes. The first is a floor system
of a plurality of triggers and a plurality of liquidation
percentages that provide a static protection from an investment's
drop in value. This is called The Principle Protector.sup.SM. The
second is a dynamic proportional relationship between the price per
share of a real investment and that investments stop loss trigger.
The third is the setting of a plurality of trailing stop losses for
an investment and having a variable percentage of the investment's
value set to be sold when each stop loss is triggered. These last
two attributes are part of The Profit Protector.sup.SM.
[0025] The present invention takes an investment and applies a
series of triggers that define how an investment will be
liquidated. These series of triggers are complex. The need for
accurate pricing data, and the ability of the system to
automatically sell percentages of and or complete investments
necessitate a computing deviation that can communicate over the
Internet or other similar communication medium. A set of
instructions for the computing deviation required may vary in both
length and content. A person skilled in the art will recognize that
this system can be applied not only at the individual investment
level but also at other levels such as class, sector, account, and
client level.
BRIEF DESCRIPTION OF THE DRAWINGS
[0026] FIG. 1 is a schematic diagram that illustrates a typical
portfolio management system known in the prior art;
[0027] FIG. 2 is a flow chart illustrating the Expected Growth Rate
system of the present invention;
[0028] FIG. 3 is a flow chart illustrating the creating of a client
account and corresponding Actual Portfolio and Target
Portfolio;
[0029] FIG. 4a is a flow chart illustrating the security monitoring
of the present invention and allocation of excess cash after a
sale;
[0030] FIG. 4b is a screen shot of the a typical client buy
list;
[0031] FIG. 5 is a flow chart illustrating the process of the
Mutual Fund Prediction Module;
[0032] FIG. 6 is a flow chart illustrating the floor system that
consists of a plurality of triggers and a plurality of liquidation
percentages that provide static protection from a real investment's
drop in value;
[0033] FIG. 7 is a table illustration two possible variations on
utilizing a plurality of variable trigger levels to minimize
investment losses;
[0034] FIG. 8 is a flow chart illustrating the stop loss sales as a
percentage of real investment holdings variable with a plurality of
stop losses for a real investment.
DETAILED DESCRIPTION OF THE INVENTION
[0035] In the following detailed description of the invention and
exemplary embodiments of the invention, reference is made to the
accompanying drawings (where like numbers represent like elements),
which form a part hereof, and in which is shown by way of
illustration specific exemplary embodiments in which the invention
may be practiced. These embodiments are described in sufficient
detail to enable those skilled in the art to practice the
invention, but other embodiments may be utilized and logical,
mechanical, electrical, and other changes may be made without
departing from the scope of the present invention. The following
detailed description is therefore, not to be taken in a limiting
sense, and the scope of the present invention is defined only by
the appended claims.
[0036] In the following description, numerous specific details are
set forth to provide a thorough understanding of the invention.
However, it is understood that the invention may be practiced
without these specific details. In other instances, well-known
portfolio management and techniques known to one of ordinary skill
in the art have not been shown in detail in order not to obscure
the invention.
[0037] A portfolio management system is a complete system that
allows for the real-time management of multiple client portfolios
by an investment advisor, broker or agent. Within the industry,
there are several software programs that facilitate the creation of
an asset allocation for an account, software that allows the use of
model portfolios and there may even be software that provides an
indication of when a stock should be bought or sold. In the prior
art nothing exists that combines all the elements necessary to
effectively manage a large number of custom-tailored client
portfolios on a real-time basis, checking to see if predetermined
tolerances have been breached and/or generating the appropriate
purchase and sale decisions at the individual client account
level.
[0038] A portfolio management system starts with a module (100)
that allows for the creation of portfolio templates (103 and 104)
that can then be used to create customized, individual portfolios
for multiple clients (101 and 102). For instance, a portfolio
template (103) can be created for equities that breaks down the
percentage of each dollar allocated to it that should be invested
in large cap value (105), large cap blend (106), etc. (various
classes of investments). For each class, individual securities (107
and 108) can be selected and allocation percentages assigned to
them. This is standard in the industry and familiar within the art.
The system of the present invention allows for the creation of an
unlimited number of portfolio templates.
[0039] One unique aspect of the allocation system of the present
invention is the use of an Expected Growth Rate (200) (also
referred to as EGR). At the beginning of each year (or any
predetermined anniversary date), a prediction (201) of the expected
growth rate for the various markets such as real estate (202),
bonds(203), equities (204) is made. Then further break downs of the
EGR (200) for classes such as large cap (205), mid cap (206), small
cap (207), etc) and even assignments of an EGR (200) to individual
securities (208) are created.
[0040] The use of the EGR allows the user to verify that an
allocation designed for an individual client will allow them to
reach a specific Annual Return on Investment (ROI). The use of the
EGR also allows for comparison of the EGR of an existing investment
(their Actual Portfolio) to the EGR of a Target Portfolio.
[0041] There are no other systems that employ an EGR approach based
on a current prediction of market return in the prior art.
Traditional allocation systems are based on long-term historical
terms. The can be a significant difference expected results. For
example, most analysts are predicting that the S&P 500 will
grow about 8% in 2004. This is considerably lower than the
long-term historical return of 10-11%. The use of an EGR in the
current invention allows the user to better adjust portfolio
allocations for current economic conditions.
[0042] Now referring to FIG. 3 a new client account (301) is set up
in step 302 by creating a Target Portfolio (305) and assigning
either one of a variety of predetermined templates (303) or
percentage allocations (304). Once the client account (301) and
Target Portfolio (305) are set up, an Actual Portfolio (311) is
established for each client account (301). Additionally, a Sell
Risk Tolerance (306) and a Buy Risk Tolerance (307) are assigned to
each allocation (304) within both the Target Portfolio (305) and
Actual Portfolio (311) of the client account (301). In step 308 the
system looks at each individual security (309) in the underlying
Target Portfolio (310) and computes the amount that should be
invested in each individual security (309), computes the EGR for
each individual security (309), and computes the EGR for the Target
Portfolio (305). This can then easily be compared to the EGR of the
Actual Portfolio (312) and the ROI desired (313). The EGR
automatically adjusts based on changes in the settings related to
the client, account or allocation buy and/or sell risk tolerance
levels.
[0043] Now referring to FIG. 4, instead of automatically selling
the securities in the Actual Portfolio (311) and buying the
securities in the Target Portfolio (310) (like other systems known
in the prior art), the Portfolio Management System (400) of the
present invention utilizes a two component principal protector
system (401) and a profit protector system (402) to determine when
a security should be liquidated.
[0044] These systems are designed to monitor (403) each security in
each client account throughout the day and to trigger a sell alert
when they breach a tolerance threshold (404). Thus, securities in
the Actual Portfolio (311) are kept (405) until the system
determines it is time for them to be sold (406). Securities can be
sold manually based on data non-related to share price movements or
at the user's discretion. When a security in the Actual Portfolio
(312) is sold, the proceeds are moved into an interest-bearing cash
account or a money market mutual fund (407). The Portfolio
Management System actively monitors the level of cash in each
account (408). When the level of cash exceeds the percentage of the
account that is allocated to cash, the system recognizes that there
is excess cash available (409). Once there is excess cash available
within an account, the PMS compares the Target Portfolio to the
Actual Portfolio to determine the specific securities and the
amount of each that should be purchased (410).
[0045] Now referring to FIG. 4b which illustrates how the client
buy list (450) would appear to a broker through a typical computer
system, a security will not be added to a Target Buy List (411)
unless (A) the actual percentage invested at the Category level is
less than the percentage allocated to that Category in the Target
Portfolio (460) (B) the actual percentage invested at the Class
level is less than the percentage allocated to that Class in the
Target Portfolio (461); (C) the actual amount invested (451) in
that security is less than the amount allocated (452) to that
security in the Target Portfolio (462); (D) the amount to purchase
exceeds the minimum purchase amount required for that security
(463) (can be manually overridden); and (E) pre-purchase technical
indicators are met (464). This results in an account-level Target
Buy List (450).
[0046] The system then begins active real-time monitoring (412) of
each individual security on the account-level Target Buy Lists to
determine based on user-defined technical indicators the optimal
time it should be purchased. When that occurs, a Buy Alert (465) is
sounded and the purchases can be executed automatically or manually
by the user. Whenever a buy trigger threshold is triggered (413) a
new security is purchased (414), money added to existing
securities, etc, setting for the Principal Protector (401) and the
Profit Protector (402) are automatically applied based on system
defaults and continuously monitored. The PMS monitors the price
fluctuations of each security in the system in real time or can use
free delayed quotes from the Internet. The result is that it makes
real-time decisions on the purchase and sale decisions.
[0047] Mutual funds, though, can only be bought or sold at the end
of the day. A system that monitors the price movement of a mutual
fund and sounds an alarm when a tolerance is breached would not be
able to take action until the close of the following day. The
result is that there could be an additional day's loss before the
fund was sold. Likewise, if a buy signal were alerted based on that
day's closing price, the purchase could not be made until the
following day. The result could be increased losses and/or lost
gains to the client. To prevent this, the present invention
incorporates a unique Mutual Fund Predictive Module. The MFPM uses
a proprietary mathematical algorithm that determines and monitors
the correlation between any mutual fund and its assigned index.
Then the system can predict, based on the changes in the related
index, where that mutual fund will close at the end of the day and
action can be taken before the market closes.
[0048] Mutual funds are priced at 4 pm daily. Any orders entered
throughout the day receive the 4 pm price of the fund. The MFPM
tracks the correlation of a mutual fund to an index, utilizes
algorithms to determine the optimum numbers of days to average the
correlation over and then predicts the price of the mutual fund
prior to the close of the market based on the movement of the
index. The system uses quality assurance methods to auto correct
itself.
[0049] The inventor is not aware of any processes currently
available or known in the prior art that provide for the prediction
of where a mutual fund share price will close. Trading systems
exist in prior art that provide general buy and sell
recommendations for mutual funds.
[0050] The MFPM, in FIG. 5, starting with Process 1 (501), in Step
1 (502): default to initially 5 days worth of data consisting of an
Index Closing Price 1/MF Closing Price 1=Correlation Ratio 1 (CR1)
which is then repeated for CR2 through CR5 for each initial day's
worth of data. Next in Step 2 (503) the average and standard
deviation of Step 1's data set is calculated. The result is a 5-Day
Average and 5-Day Standard Deviation.
[0051] In Process 2 (505), Process 1 (501) is repeated for every
day between days 5 and 75 (506), then a determination of which day
the standard deviation is smallest is made with that day becoming
the default day, default correlation factor (average) and default
standard deviation (507).
[0052] On a Daily Basis, in process 3 (508) the MFPM uses the
default number of days to complete Process 1 (501) that provides
the correlation factor and standard deviation to use all day
(509).
[0053] In process 4 (510) Quality control on a daily basis (511) is
accomplished by using the last eight days of data points for actual
mutual fund closing price (ACP) and predicted mutual fund closing
price (PCP) and following the mathematical algorithm described in
Table 1.
1TABLE 1 MFMP Daily Quality Control Algorithms: 1 Using last 8 days
data points (dp(i)) for actual mutual fund closing price (ACP) and
predicted mutual fund closing price (PCP): a. If (PCP dp(i) >
ACP dp(i) and PCP dp(ii) > ACP dp(ii) . . . dp(viii)) OR If (PCP
dp(i) < ACP dp(i) and PCP dp(ii) < ACP dp(ii) . . . dp(viii))
then recalculate. b. If PCP dp(i) > 3 standard deviations away
from ACP dp(i) OR PCP dp(ii) > 3 standard deviations away from
ACP dp(ii) . . . dp(viii) then recalculate. 2. Using last 3 days
data points for ACP and PCP: If (PCP dp(i) > ACP dp(i) AND PCP
dp(ii) > ACP dp(ii) AND PCP dp(iii) > ACP dp(iii)) OR ((PCP
dp(i) < ACP dp(i) AND PCP dp(ii) < ACP dp(ii) and PCP dp(iii)
< ACP dp(iii)) AND (2 out of 3 (PCP dp(i . . . iii) > 2
standard deviations from ACP dp(i . . . iii))) then recalculate. 3.
Using last 5 days data points for ACP and PCP: If (PCP dp(i) <
ACP dp(i) AND PCP dp(ii) < ACP dp(ii) . . . dp(v)) OR (PCP dp(i)
> ACP dp(i) AND PCP dp(ii) > ACP dp(ii) . . . dp(v)) AND 4 of
the 5 (PCP dp(i) > 1 standard deviation from ACP dp(i) . . .
dp(v) then recalculate.
[0054] The result is a complete Portfolio Management System that
automates the management of client accounts. The Portfolio
Management System actively monitors the Actual Portfolio and alerts
when part or all of a security should be sold. Then Portfolio
Management System determines, based on the Target Portfolio, which
securities should be purchased (and amounts) and alerts the advisor
at the appropriate time to make that purchase. Thus an advisor can
provide a level of real-time portfolio management for numerous
client accounts that currently does not exist in the marketplace
today. Moreover, the system will modify the underlying decisions
based on the progress an account and client have made toward their
Desired ROI. The Portfolio Management System dynamically adjusts
based on the actual results of the account compared to the target
results (411) at the security, class, category, account and/or
client levels.
[0055] The sell trigger module of the Portfolio Management System
of the present invention incorporates the principle protector
system (401) and a profit protection system (402). The purpose of
the principle protector is to meet investors' demands that advisor
take action to protect their money if an investment they made
begins to lose value. Investors also expect their advisor to take
action and lock in profits on a security if an investment increases
in value but then begins to lose value. The profit protection
system enables the price of an investment to fluctuate but if the
investment reaches a threshold loss, a sale will occur increasing
the potential for profit.
[0056] The Principal Protector is an electronic monitoring system
that monitors the protector levels of every investment for every
account for every client in real-time and alerts the advisor when a
tolerance is breached and action should be taken. Additionally, the
system allows for a multitude of stop-loss levels to be set for
each security and a liquidation percentage assigned to each. This
allows for the gradual reduction of investment in a security should
it decline in value while allowing the partial participation in
growth should the security begin to appreciate.
[0057] Now referring to FIG. 6, the first step in the series is to
create a plurality of floor values (601, 602, and 603) with a
variable liquidation percentage (604, 605, and 606) corresponding
to each floor value (601, 602, and 603). A floor value is defined
here as a price per share below the original purchase price (607)
per share. This is an example, in which the invention could consist
of a plurality of floor values with variable liquidation
percentages. The floor values are static, i.e. they do not change
as the value of the investment changes.
[0058] If a client invests $100k in Investment A and it starts to
lose value at some point they would want it sold and the money
moved to cash where it wouldn't fluctuate and could then be put to
better use. The level at which the sale should occur will vary
based on the clients risk tolerance. If an advisor has numerous
accounts, it is close to impossible to watch every investment and
to keep track of every clients stop loss level on each one.
Additionally, the risk of selling an investment when it goes down
is that, should the investment begin to go back up, you are not
able to participate in future growth. Therefore, selling 100% when
the investment drops to $95,000 eliminates the possibility of
participating in future profits.
[0059] For instance, let's assume that using the example
illustrated in FIG. 7 where Client #1 (701) and Client #2 (702)
have their respective Principle Protector settings (703, 704, and
705) on an investment as illustrated. The portfolio management
system of the present invention would monitor the real-time price
of the investment and if the value of Client #1's investment
dropped to $97k (706) it would alert the advisor to sell 15% of his
position (707). If the value continued to fall to $95k (708), the
system would alert the advisor again to sell 50% of the remainder
of Client #1's position (709), and if the valued fell to 93% (710)
the system would alert the advisor again to sell 100% (711) or the
remaining holding of the security. An unlimited number of Principal
Protector levels can be used, but the best mode of the principle
protector system of the present invention utilizes three. Note that
the Principal Protector settings do not fluctuate with the share
price of the security. They remain static, but are adjusted for
additions and withdrawals to an account.
[0060] Investors also expect their advisor to take action and lock
in profits on a security if it begins to lose value. It is not
uncommon to buy a security, have it increase in value only to drop
back to where it started or less. The security should be given
enough room to fluctuate so that it can grow, but should be sold
and the gains locked-in if it breaks below its normal tolerance.
Again, each client would need to be able to have his or her own
tolerance level.
[0061] The problem is that an advisor does not have the ability to
efficiently monitor these levels for numerous clients. The advisor
can place a stop loss order. Unfortunately the stop loss order is
static so if the price of the stock moves up the stop loss order
would have to be canceled and another one entered in, etc, etc.
This would have to happen on every security of every client. It
would be physically impossible. As a result, clients can quickly
see their profits go down the drain because the advisor failed to
take action.
[0062] The Profit Protector module provides an advisor with this
flexibility and then some. In its most basic sense, the Profit
Protector allows there to be a trailing stop loss (trailing means
it follows behind the share price as it goes up--but it can't go
down--without user intervention) set for each investment of each
account of each client. The system then monitors the price
movements of the security in real time and will automatically
increase the trigger price of the trailing stop loss (even
fractions of a cent) as the share price increases. During the real
time monitoring, the system is also checking to see if the trailing
stop loss trigger level has been breached. If it has, the system
can automatically execute the sell transaction or the advisor can
be alerted to take action manually so that the profits can be
locked in.
[0063] The use of a trailing stop loss is available in various
systems designed for use by day traders and is well known in the
prior art. Unfortunately, they are designed to liquidate 100% of a
security and do not allow the investor to participate in any growth
should the share price go back up. Just like the Principal
Protector module, the Profit Protector module employs the use of
multiple trailing stop loss levels with each having an associated
liquidation percentage. That way, a position can be gradually
liquidated if the security continues to decline in price. That
provides for the opportunity to profit on the portion that hasn't
yet been liquidated should the stock price go back up. Currently
the portfolio management system of the present invention utilizes
four Profit Protector levels.
[0064] Now referring to FIG. 8, Client 1 could set a trailing stop
loss at 3% with 25% liquidation (801), 4% with 50% liquidation
(802) and 5% with 100% liquidation. If the stock price were
initially $10.00 per share the triggers would be set at $9.70,
$9.60, and $9.50 respectively. If the stock went up to $10.01 per
share the triggers would automatically increase to $9.7097,
$9.6096, and $9.5095 respectively. Should the stock decline to
$9.7097, the system would automatically execute the transaction or
alert the advisor to sell 25% of the position. If the stock
continued to decline (not time dependent) to $9.6096 the system
would automatically execute the transaction or alert the advisor to
sell 50% of the remainder of the position.
[0065] If the stock price then started to increase in value and
went to $11 per share, the investors' remaining position would
participate in that growth. As the stock price rose above $9.6096
the system would automatically reset trigger #2. If it continued to
rise about $9.7097, the system would automatically reset trigger
#1. From that point, the triggers settings would all adjust up as
the share price increased. As part of the overall Portfolio
Management System, a buy order in the same security might be
triggered as each security increases in price so the effect can be
to reduce a position as the price falls and add to it as it starts
going back up.
[0066] In another embodiment of the Portfolio Management System of
the present invention a further enhancement on the stop-loss
trigger method, the Dynamic Adjusting Module allows a target growth
rate to be set at the security, class, category, account and client
level. Each of the tolerance settings of the Sell Trigger Module
are then dynamically reduced real-time according to pre-defined
criteria based on the performance of the security relative to the
before mentioned target growth rates at each of five different
levels. The result is that the greater a security performs the
greater the profits are protected and it is completely adjustable
based on the needs of the client.
[0067] The Dynamic Adjusting Module is a further enhancement on the
Sell Trigger Module (STM). The existing STM consists of only one
setting for each trigger value. Even though the STM allows for
multiple dynamically adjusting triggers, each trigger is based on a
percentage of the current price. The STM does not provide for the
percentage of the current price to be dynamically adjusted based on
performance criteria.
[0068] It would be an improvement on the STM to have the ability to
dynamically adjust the percentage values in real-time based on a
variety of performance-based criteria. This would allow the system
to automatically reduce the amount a security would have to decline
prior to a protective trigger breach based on predefined
performance criteria.
[0069] In other words, when a security has an 8% return, a client
might desire a protective level set at 4% so if the security
dropped half of the gain would be locked in. On the other hand, if
the security continued to increase in value, say it achieved a 12%
return, the client might desire the protective level to narrow to a
setting of 10%. Then, the protective level would trigger if the
security return were to decline by only 2%.
[0070] A system with this capability would allow an investor to
start with a wider protective setting initially to allow the
position in that security the greatest opportunity for growth,
while clamping down on the setting as the position had greater and
greater returns. It is logical that the relationship of the actual
performance to the expected performance could be one basis for such
adjustment, but other criteria could be used. For instance, instead
of performance-based criteria, time-based or volume-based criteria
could be used.
[0071] An additional improvement is the ability to dynamically
adjust that amount of a security that would be liquidated based on
performance-based criteria. This improvement would provide the
capability for a greater percentage to be liquidated as the
performance improved.
[0072] This improvement requires several additional data points.
The new data points for each Profit Protector and Principal
Protector Level are Trigger Price Wide (TPW), Trigger Price Narrow
(TPN), Trigger Price Current (TPC), Trigger Liquidation % Wide,
Trigger Liquidation % Narrow, and Trigger Liquidation % Current. So
if there were 7 Protector levels, there would be 21 different
settings. The Trigger Price settings use a share price whereas the
Liquidation % settings state the percentage of the remainder that
should be sold.
[0073] Additionally, there is a data point to determine when the
dynamic adjustments should start (DAS) and a data point to
determine when they should reach their narrowest setting or end
(DAE). On each calculation cycle, a current price for a security is
obtained and the Period-To-Date Performance Percentage (PP) is
calculated. Once the PP is calculated, the Trigger Price Current
setting is determined as follows:
2 If PP <= DAS Then TPC = TPW If PP > DAS and PP < DAE
Then TPC = TPW - ((PP - DAS/DAE - DAS) .times. (TPW - TPN) If PP
>= DAE then TPC = TPN
[0074] For instance, based on the actual performance of Security X
with these settings:
3 Trigger Price Wide (TPW) = 6% Trigger Price Narrow (TPN) = 3%
Dynamic Adjust Start (DAS) = 5% Dynamic Adjust End (DAE) = 9%
Period-To-Date Performance (PP) = 7%
[0075] At the beginning of the period, the Trigger Price Current
(TPC) would be set to 6 (meaning a 6% decline in Security X's price
before a sale was triggered). Real-time pricing info would be
monitored and the return for the investment in Security X since the
beginning of the period would be recalculated with each upward
price movement. So, if PP=7, then TPC would be 4.5 and Security X
would be liquidated at a 4.5% decline in price.
[0076] The same method is used to determine all of the appropriate
current settings for both the price triggers and the liquidation
percentages.
[0077] Multiple levels of criteria can be used to dynamically
adjust the settings in real-time. This provides precise control
over the overall function of the system. For instance, the PMS of
said invention adjusts trigger settings according to the following
schedule:
[0078] 1) An individual security's triggers would be adjusted based
on the PP of a security relative to that security's EGR
[0079] 2) The triggers of all the securities in a Class of
securities would be adjusted based on the PP of the Class relative
to the Class EGR
[0080] 3) The triggers of all of the securities in each Class of a
Category would be adjusted based on the PP of the Category relative
to the Category EGR.
[0081] 4) The triggers of all the securities in an Account would be
adjusted based on the PP of the Account relative to the Account
EGR.
[0082] 5) The triggers of all the securities of a Client would be
adjusted based on the PP of the Client relative to the Client
EGR.
[0083] The result is that the greater a Security, Class, Category,
Account or Client performs the greater the profits are protected.
It is completely adjustable based on the needs of the client.
Without this levels-based logic, the return of one level could be
eroded by the poor performance of investments in the other
levels.
[0084] Once the DAM adjusts the current settings, the current price
would be compared to the various Protector levels to determine if
one has been breached. If so, the appropriate transaction would be
automatically executed or the user alerted for manual decision. The
user should be able to define the Performance Period. For instance,
the PMS of said invention utilizes the calendar years as its
Performance Period. Others may want to use Quarterly, Semi-Annual
or multi-year time periods.
[0085] For the DAM to function properly, adjustments need to be
made when transitioning from Performance Period #1 to Performance
Period #2. These adjustments are:
[0086] 1) In the STM, the Principal Protector settings are based on
the net amount invested in a security. The Principal Protector
protects that investment by automatically selling all or a portion
should the value decline to the pre-determined static level. In
order for the PP1 returns to be protected in PP2, the Net Invested
value should be increased to the current end of period value if the
current end of period value is greater than the beginning of period
value (Net Invested value). Then, the Principal Protector settings
would be based on this greater amount and provide static protection
for those gains.
[0087] 2) At the beginning of a new period, the Current trigger
settings should be reset to equal the Wide settings.
[0088] 3) If there are any period performance to date values
stored, they should be set to zero at the beginning of the
period.
[0089] It is common in the art to utilize moving averages in
deciding when to purchase a security and this typically is a manual
process. The Portfolio Management System of the present invention
defines a target portfolio for a client that details the securities
and respective percentages that should be invested in each. The
Portfolio Management System of the present invention may
incorporate a Buy Trigger Module that continually compares the
target portfolio to the client's actual portfolio to determine when
there is excess cash available to invest. On a daily basis when
there is excess cash available, the system generates a list of
securities and amounts for that account that day that should be
purchased based on the differences between the actual and target
portfolios. The price movements of each security on a buy list are
then continuously monitored, the moving averages tracked and the
user alerted when there is a crossover and trend for that specific
security. The system then presents the user with a list of accounts
that have cash available and the amounts that need to be invested
in that security wherein the user can then execute the trades.
Alternatively, trades could be executed automatically.
[0090] At the PMS level, the BTM monitors every security in every
client account real-time to determine if the purchase criteria have
been met. Included in the BTM is the ability to use different
moving average levels to represent different client Buy Risk
Tolerances. The present system uses 3 Buy Risk Tolerance settings.
The settings for the 3 moving averages can be different for each
security in the system. For instance, Security A could use 10, 25,
and 50-day moving averages whereas Security B could use 7, 18, and
23-day moving averages.
[0091] In yet another embodiment the Portfolio Management System of
the present invention may incorporate a Real-time Portfolio
Monitoring System. Within the industry it is necessary for a
financial advisor to manually look at the holdings in a clients
account to determine if action should be taken. The result is that
a client's portfolio is not actively monitored. The Real-time
Portfolio Monitoring System utilizes a data feed or other security
pricing methods to continuously monitor the performance of every
investment in every clients account and automatically executes
transactions or alerts the user if any investment fails to perform
within its tolerances.
[0092] Therefore, the foregoing is considered as illustrative only
of the principles of the present invention. Further, since numerous
modifications and changes will readily occur to those skilled in
the art, it is not desired to limit the invention to the exact
construction and operation shown and described, and accordingly,
all suitable modifications and equivalents may be resorted to,
falling within the scope of the invention. Thus, the scope of the
invention should be determined by the appended claims and their
legal equivalents, rather than by the examples given.
* * * * *