PATENT BY THIMMAIAHBC

1. 1
FORM 2
THE PATENTS ACT, 1970
(39 OF 1970)
AND
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)
Title of Invention:
“MACHINE LEARNING APPROACHES IN STOCK MARKET PREDICTION AND
MUTUAL FUND PORTFOLIO MANAGEMENT”
NAME OF APPLICANT NATIONALITY ADDRESS
DR S KIRUBAKARAN INDIAN ASSOCIATE
PROFESSOR/CSE, CMR
COLLEGE OF
ENGINEERING AND
TECHNOLOGY,
KANDLAKOYA,
HYDERABAD 501 401
PROFESSOR SANTOSH RAM
PAGARE
INDIAN PROFESSOR, FACULTY OF
COMMERCE, K.J. SOMAIYA
COLLEGE OF ARTS,
COMMERCE AND SCIENCE,
KOPARGAON, 423601
DR.GANESH KONDAJI
CHAVHAN
INDIAN ASSOCIATE PROFESSOR,
K.J. SOMAIYA COLLEGE OF
ARTS, COMMERCE AND
SCIENCE, KOPARGAON,
423601
DR. PRAJNADIPTA DAS INDIAN FACULTY, COLLEGE OF IT
AND MANAGEMENT
EDUCATION,ZONE-B, PLOT
NO.4, MANCHESWAR IE RD,
SECTOR A,
BHUBANESWAR, ODISHA
751010
DR. HEMADIVYA
KANTAMANENI
INDIAN ASSOCIATE PROFESSOR,
DEPARTMENT OF MBA,
KONERU LAKSHMAIAH
EDUCATION FOUNDATION,
WADDESWARAM, ANDHRA
PRADESH,INDIA.
AMRITA BHATTACHARYA INDIAN NSHM KNOWLEDGE
CAMPUS, NSHM BUSINESS
SCHOOL, ASSISTANT
PROFESSOR, ARRAH VIA
SHIBTALA, MUCHIPARA,

2. 2
DURGAPUR 713212
V RANGANATHAM INDIAN SANSKRITHI SCHOOL OF
BUSINESS, PUTTAPARTHI
DR. SHAILENDRA
KASHINATH BANSODE
INDIAN ASSISTANT PROFESSOR,
K.J.SOMAIYA COLLEGE OF
ARTS, COMMERCE AND
SCIENCE,
KOPARGAON,423601
SUNITHA B K INDIAN HEAD OF THE
DEPARTMENT, CMS,JAIN (
DEEMED TO THE
UNIVERSITY)
BANGALORE,560040
DR . THIMMAIAH
BAYAVANDA CHINNAPPA
INDIAN PROFESSOR ,
DEPARTMENT OF
MANAGEMENT STUDIES ,
IVANE JAVANKISHI TBILISI
STATE UNIVERSITY OF
GEORGIA
ABHISHEK KUMAR YADAV INDIAN NEW REST HOUSE
COLONY, PRAYAG
STATION, PRAYAGRAJ,
211002
DHARINI RAJE SISODIA INDIAN ASSISTANT PROFESSOR /
MANAGEMENT, ARMY
INSTITUTE OF
MANAGEMENT &
TECHNOLOGY, GREATER
NOIDA UTTAR PRADESH
201310
The following specification describes the invention and the manner in which it is to be
performed.

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FIELD OF INVENTION
The present invention relates to the field of designing & implementing a framework of
machine learning in stock prediction. The invention also focuses on analyzing the portfolio
of mutual funds.
BACKGROUND OF INVENTION
[0001] Background description includes information that may be useful in
understanding the present invention. It is not an admission that any of the
information provided herein is prior art or relevant to the presently claimed
invention, or that any publication specifically or implicitly referenced is prior art.
[0002] A Stock Market, Equity Market or Share Market is the aggregation of buyers
and sellers of stocks, which represent ownership claims on business. Investment is
usually made with an investment strategy in mind. A stock exchange is an exchange
where stock brokers and traders can buy and sell shares (equity stock), bonds and
other securities.
[0003] A number of different types of mutual stock market analysis systems that are
known in the prior art. For example, the following patents are provided for their
supportive teachings and are all incorporated by reference.
[0004] Mutual Fund Portfolio Management Using LSTM Stock market prediction is
one of the most difficult computations due to the many internal as well as any number
and type of external factors. It is impossible to get the exact computation hence we
look for the method which gives the computation with less error. Different machine
learning methods are being applied for the computations which involve many
parameters. In this research work we choose Long Short-Term Memory (LSTM) for
the prediction as it is computationally suitable for these types of data analysis. After
doing the prediction of share price the work is extended to manage portfolio of the

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mutual fund. The framework has been designed in such a way so that the portfolio
manager can choose any number of business sectors as well as any number of shares
belong to this sector. This research work henceforth applicable for computing
individual share price as well as managing a diversified portfolio.
[0005] A mutual fund is a professionally managed investment fund that pools
money from many investors to purchase securities. Mutual funds are regulated by
governmental bodies and are required to publish information including performance,
fees charged and securities held. The proposed invention focuses on analyzing the
positive and negative aspects of both the stock market and mutual fund portfolio’s.
[0006] Above information is presented as background information only to assist
with an understanding of the present disclosure. No determination has been made,
no assertion is made, and as to whether any of the above might be applicable as prior
art with regard to the present invention.
[0007] In the view of the foregoing disadvantages inherent in the known types of
stock market analysis now present in the prior art, the present invention provides an
improved system. As such, the general purpose of the present invention, which will
be described subsequently in greater detail, is to provide a new and improved
machine learning based techniques to analyze the mutual fund portfolios along with
stock market analysis that has all the advantages of the prior art and none of the
disadvantages.
SUMMARY OF INVENTION
[0008] In the view of the foregoing disadvantages inherent in the known types of
mutual fund transaction analysis systems now present in the prior art, the present
invention provides an improved one. As such, the general purpose of the present
invention, which will be described subsequently in greater detail, is to provide a new

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and improved machine learning based approach to analyze the interrelationship
between stock market and mutual fund which has all the advantages of the prior art
and none of the disadvantages.
[0009] The Main objective of the proposed invention is to design & implement a
framework of machine learning to analyze the interrelationships with stock market
and mutual funds. The invention also aims at understanding the pros and cons of
both the stock market and mutual funds portfolio.
[0010] Yet another important aspect of the proposed invention is to design &
implement a framework of machine learning to analyze the data sets of stock market
and mutual fund. The investments, returns and the risks involved are studied and
analyzed. The proposed invention focuses on providing a resultant database which
includes the positive and negative traits of both stock market and mutual funds.
[0011] In this respect, before explaining at least one embodiment of the invention in
detail, it is to be understood that the invention is not limited in its application to the
details of construction and to the arrangements of the components set forth in the
following description or illustrated in the various ways. Also, it is to be understood
that the phraseology and terminology employed herein are for the purpose of
description and should not be regarded as limiting.
[0012] These together with other objects of the invention, along with the various
features of novelty which characterize the invention, are pointed out with
particularity in the disclosure. For a better understanding of the invention, its
operating advantages and the specific objects attained by its uses, reference should
be had to the accompanying drawings and descriptive matter in which there are
illustrated preferred embodiments of the invention.

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BREIF DESCRIPTION OF DRAWINGS
[0013] The invention will be better understood and objects other than those set forth
above will become apparent when consideration is given to the following detailed
description thereof. Such description makes reference to the annexed drawings
wherein:
Figure 1 illustrates the block diagram of machine Learning Approaches in Stock
Market Prediction and Mutual Fund Portfolio Management, according to the
embodiment herein.
DETAILED DESCRIPTION OF INVENTION
[0014] In the following detailed description, reference is made to the accompanying
drawings which form a part hereof, and in which is shown by way of illustration
specific 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, and it is to be understood that the embodiments may be combined, or that
other embodiments may be utilized and that structural and logical changes may be
made without departing from the spirit and 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 by the appended claims and their
equivalents.
[0015] While the present invention is described herein by way of example using
several embodiments and illustrative drawings, those skilled in the art will recognize
that the invention is neither intended to be limited to the embodiments of drawing or
drawings described, nor intended to represent the scale of the various components.
Further, some components that may form a part of the invention may not be
illustrated in certain figures, for ease of illustration, and such omissions do not limit

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the embodiments outlined in any way. It should be understood that the drawings and
detailed description thereto are not intended to limit the invention to the particular
form disclosed, but on the contrary, the invention covers all modification/s,
equivalents and alternatives falling within the spirit and scope of the present
invention as defined by the appended claims. The headings are used for
organizational purposes only and are not meant to limit the scope of the description
or the claims. As used throughout this description, the word "may" be used in a
permissive sense (i.e., meaning having the potential to), rather than the mandatory
sense (i.e., meaning must). Further, the words "a" or "a" mean "at least one” and the
word “plurality” means one or more, unless otherwise mentioned. Furthermore, the
terminology and phraseology used herein is solely used for descriptive purposes and
should not be construed as limiting in scope. Language such as "including,"
"comprising," "having," "containing," or "involving," and variations thereof, is
intended to be broad and encompass the subject matter listed thereafter, equivalents,
and any additional subject matter not recited, and is not intended to exclude any
other additives, components, integers or steps. Likewise, the term "comprising" is
considered synonymous with the terms "including" or "containing" for applicable
legal purposes. Any discussion of documents, acts, materials, devices, articles and
the like are included in the specification solely for the purpose of providing a
context for the present invention.
[0016] In this disclosure, whenever an element or a group of elements is preceded
with the transitional phrase "comprising", it is understood that we also contemplate
the same element or group of elements with transitional phrases "consisting
essentially of, "consisting", "selected from the group consisting of”, "including", or
"is" preceding the recitation of the element or group of elements and vice versa.

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[0017] The stock markets as well as the mutual fund industry are associated with
each other in a sense that performance of one affects the performance of other.
Whenever the stock indices fluctuate, the Indian mutual fund industry faces a great
haste by the investors as they feel insecure for their money invested in the funds.
Mutual fund invests in the stocks and shares are traded in exchange and thus when
stock crashes, mutual funds will also crash.
[0018] Mutual funds are good investment for investors looking to diversify their
portfolios. The proposed invention focuses on implementing algorithms of ML to
analyze the database of stock market as well as mutual funds. The invention aims at
identifying the advantages, disadvantages and interconnection between portfolios of
mutual funds and stock market.
[0019] Reference will now be made in detail to the exemplary embodiment of the
present disclosure. Before describing the detailed embodiments that are in
accordance with the present disclosure, it should be observed that the embodiment
resides primarily in combinations arrangement of the system according to an
embodiment herein and as exemplified in FIG. 1
[0020] Figure 1 illustrates the block diagram of machine Learning Approaches in
Stock Market Prediction and Mutual Fund Portfolio Management 100. The proposed
system 100 includes a Database of share market investment 101 and mutual fund
investment 102. These data are segregated in to direct investments 103a, risk
analysis and returns 103c of share market data 101. The mutual fund Database 102
contains classified data sets depicted as 104a for indirect investments, profits 104b
and professional handling aspects 104c. These data are analyzed by machine
learning units 105a for 101 and 105b for 102. The results of 105a and 105b are used
by prediction unit 106. The resultant database 107 will contain results that will give

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positive and negative insights of both stock market and mutual fund portfolio.
[0021] In the following description, for the purpose of explanation, numerous
specific details are set forth in order to provide a thorough understanding of the
arrangement of the system according to an embodiment herein. It will be apparent,
however, to one skilled in the art that the present embodiment can be practiced
without these specific details. In other instances, structures are shown in block
diagram form only in order to avoid obscuring the present invention.
Gowthami S
Patent Agent
INPA 3797
On behalf of applicant
Digitally Signed
Date: 27/5/2022

10. 10
WE CLAIM
1. Machine learning approaches in stock market prediction and mutual fund portfolio
management comprises of
Machine learning unit;
Mutual fund investment and
Predictive unit.
2. Machine learning approaches in stock market prediction and mutual fund portfolio
management, according to claim 1, includes a machine learning unit, wherein the
machine learning unit will analyse the data sets of stock market and mutual funds.
3. Machine learning approaches in stock market prediction and mutual fund portfolio
management, according to claim 1, includes a mutual fund investment, wherein the
mutual fund investment unit will predict and suggest the profitable investments.
4. Machine learning approaches in stock market prediction and mutual fund portfolio
management, according to claim 1, includes a prediction unit, wherein the predictive
unit will predict the mutual fund portfolios along with profit and loss.
Gowthami S
Patent Agent
INPA 3797
On behalf of applicant
Digitally Signed
Date: 27/5/2022

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ABSTRACT
MACHINE LEARNING APPROACHES IN STOCK MARKET PREDICTION AND
MUTUAL FUND PORTFOLIO MANAGEMENT
Machine learning approaches in stock market prediction and mutual fund portfolio
management is the proposed invention. The invention aims at analysing the stock market
price by the algorithms of machine learning. The invention also focuses on understanding the
insights of mutual funds and their portfolio.
Gowthami S
Patent Agent
INPA 3797
On behalf of applicant
Digitally Signed
Date: 27/5/2022