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Relative strength index for developing effective trading strategies in constructing optimal portfolio

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Abstract

Today’s investors’ dilemma is choosing the right stock for investment at right time. There are many technical analysis tools which help choose investors pick the right stock, of which RSI is one of the tools in understand whether stocks are overpriced or under priced. Despite its popularity and powerfulness, RSI has been very rarely used by Indian investors. One of the important reasons for it is lack of knowledge regarding how to use it. So, it is essential to show, how RSI can be used effectively to select shares and hence construct portfolio. Also, it is essential to check the effectiveness and validity of RSI in the context of Indian stock market. EPS and P/E ratio tend to reflect the profitability of a stock. It is also important to find which of the above better reflects the profitability of the organization so as to make better decisions regarding investment. In this case 20 stocks are chosen from NSE, 10 of which are based on highest P/E ratio and remaining 10 are based on highest EPS. Here, the portfolio consists of stocks both for short term investment and long term investment. For short term investment, we find 14 day RSI for all 20 scripts and for long term investment 56 day RSI is being found out for all the 20 scripts. RSI values are calculated for the time period 2011 January to 2013 December. Ten scripts that are chosen based on RSI from the 20 scripts are included in the portfolio. In order to find the validity of RSI in Indian stock markets, we evaluate the performance of short term investments by computing 14 day RSI for the chosen shot term investment stocks at a future point of time (March 2014), and the performance is evaluated by comparing it with the initial 14 day RSI. In this case most of the results proved positive, thus showing that RSI is valid in Indian stock markets. Also out of the 10 selected scripts six are the ones which have highest P/E ratio, this indicates that P/E ratio is a better indicator of profitability when compared to EPS.
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 19 (2017) pp. 8926-8936
© Research India Publications. http://www.ripublication.com
8926
Relative Strength Index for Developing Effective Trading Strategies in
Constructing Optimal Portfolio
Dr. Bhargavi. R
Associate Professor, School of Computer Science and Software Engineering,
VIT University, Chennai, Vandaloor Kelambakkam Road, Chennai, Tamilnadu, India.
Orcid Id: 0000-0001-8319-6851
Dr. Srinivas Gumparthi
Professor, SSN School of Management, Old Mahabalipuram Road, Kalavakkam,
Chennai, Tamilnadu, India.
Orcid Id: 0000-0003-0428-2765
Anith.R
Student, SSN School of Management, Old Mahabalipuram Road, Kalavakkam,
Chennai, Tamilnadu, India.
Abstract
Today’s investors’ dilemma is choosing the right stock for
investment at right time. There are many technical analysis
tools which help choose investors pick the right stock, of
which RSI is one of the tools in understand whether stocks are
overpriced or under priced. Despite its popularity and
powerfulness, RSI has been very rarely used by Indian
investors. One of the important reasons for it is lack of
knowledge regarding how to use it. So, it is essential to show,
how RSI can be used effectively to select shares and hence
construct portfolio. Also, it is essential to check the
effectiveness and validity of RSI in the context of Indian stock
market. EPS and P/E ratio tend to reflect the profitability of a
stock. It is also important to find which of the above better
reflects the profitability of the organization so as to make
better decisions regarding investment. In this case 20 stocks
are chosen from NSE, 10 of which are based on highest P/E
ratio and remaining 10 are based on highest EPS. Here, the
portfolio consists of stocks both for short term investment and
long term investment. For short term investment, we find 14
day RSI for all 20 scripts and for long term investment 56 day
RSI is being found out for all the 20 scripts. RSI values are
calculated for the time period 2011 January to 2013
December. Ten scripts that are chosen based on RSI from the
20 scripts are included in the portfolio.
In order to find the validity of RSI in Indian stock markets,
we evaluate the performance of short term investments by
computing 14 day RSI for the chosen shot term investment
stocks at a future point of time (March 2014), and the
performance is evaluated by comparing it with the initial 14
day RSI. In this case most of the results proved positive, thus
showing that RSI is valid in Indian stock markets. Also out of
the 10 selected scripts six are the ones which have highest P/E
ratio, this indicates that P/E ratio is a better indicator of
profitability when compared to EPS.
Keywords: RSI, Trading, Strategies innovation policy,
innovative capacity, innovation strategy, competitive
advantage, road transport enterprise, benchmarking.
INTRODUCTION
Relative Strength Index
Investment in stock market is common scenario for making
capital gains. One of the major concerns of today’s investors
is regarding choosing the right securities for investment,
because selection of inappropriate securities may lead to
losses being suffered by the investor. In order to reduce the
risk of incurring losses and increase the return many tools are
available, of which RSI is a powerful analytical tool which
will help the investor choose the right combination of
securities for their portfolio construction thus reducing the
risk and increasing the return. RSI is developed J. Welles
Wilder, the Relative Strength Index (RSI) is a momentum
oscillator that measures the speed and change of price
movements. RSI is an extremely popular momentum
indicator that has been featured in a number of articles,
interviews and books over the years. RSI oscillates between
zero and 100. Traditionally, and according to Wilder, RSI is
considered overbought when above 70 and oversold when
below 30. Signals can also be generated by looking for
divergences, failure swings and centerline crossovers. RSI can
also be used to identify the general trend.
Calculation
RSI = 100 100 / (1 + RS).
RS = Average Gain / Average Loss.
Average Gain = Sum of Gains over the past 14 periods / 14.
Average Loss = Sum of Losses over the past 14 periods / 14
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Here, RSI can be based on any number of periods, the default
number of periods suggested by Wilder is 14. For short and
medium term trading, the number of periods used will be low
when compared to that of long term trading. Generally 9 day
RSI and 14 day RSI are used for short and medium term
investments, whilst 56day RSI, 100 day RSI and 200day RSI
may be used for long term investment. In case of long term
investment the period under consideration will also be long.
For example, 56day RSI for a stock may be computed on two
year data of the stock and 200 day RSI for a stock may be
computed on eight year data. It is not necessary to use daily
data for the computation of RSI in case of long term
investments as it may involve lots of computations, instead
weekly or monthly data can be used for the computation of
RSI in long term.
Overbought and Oversold
If the RSI value of a stock goes beyond 70, it indicates that
the stock is being overbought and soon its prices would come
down. So, when the RSI value of a stock approaches 70, it is
best to sell it. The value of the stock may or may not decrease
immediately, but it will come down within a short period of
time. The following chart shows the price movement of Bosch
Limited by means of RSI.
From the above chart we can see that the RSI value has
crossed 70 by the first week of December itself, but it held its
upward trend for another two reaching 90, before it began its
downward trend. It is better to sell once RSI value reaches 70
itself, because one cannot be sure when the trend reverses.
If the RSI value of a stock goes below 30, it indicates that the
stock is being oversold and soon its prices would increase. So,
when the RSI value of a stock goes below 30, it is suitable to
buy it. The value of the stock may or may not increase
immediately, but it will increase within a short period of time.
The following chart shows the price movement of Lakshmi
Mill Limited by means of RSI.
From the above chart, we can see that, the RSI values of
Lakshmi Mill goes below 30 during the beginning of may
and it nears 25 before trend reversal occurs (upward trend). It
is suitable to buy this stock as soon as the RSI value goes
below 30.
Divergence
Disagreement between the price and the indicator is called as
divergence. Divergence, as stated by Wilder suggests a
potential reversal of trend, divergence may be bullish or
bearish. A bearish divergence occurs when the security
records a higher high and RSI forms a lower high. RSI does
not confirm the new high and this shows weakening
momentum. In case of bearish divergence, the momentum
shifts downwards in due course of time. A bullish divergence
occurs when the security records a lower low and RSI forms a
higher low. RSI does not confirm the new low and this shows
increasing momentum. In case of bullish divergence, the
momentum shifts upwards in due course of time. Before
considering divergence as trade signals, one must be very
careful. Because, it must be noted that divergences are
misleading in a strong trend. A strong uptrend can show
numerous bearish divergences before a top actually occurs.
Failure swings
Another indicator suggested by Wilder is failure swings.
Failure swings may be both bullish and bearish. Failure
swings focus solely on RSI for signals and ignore the concept
of divergences. A bullish failure swing forms when RSI
moves below 30 (oversold), bounces above 30, pulls back and
holds above 30 and then breaks its prior high. It is basically a
move to oversold levels and then a higher low above oversold
levels. A bearish failure swing forms when RSI moves above
70, pulls back, bounces, fails to exceed 70 and then breaks its
prior low. It is basically a move to overbought levels and then
a lower high below overbought levels.
Apart from the proposals made by Wilder, other technical
analysts have also made certain proposals so as to enhance
RSI. One such proposal is made by technical
analyst Constance Brown. He suggests that in a bullish market
the RSI tends to fluctuate between 40 and 90 with 40-50 range
acting as support point. The ranges may vary depending on
RSI parameters, strength of trend and volatility of the
underlying security. In a bearish market RSI tends to fluctuate
between 10 and 60 with the 50-60 zone acting as resistance
range.
RSI is a versatile momentum oscillator that has stood the test
of time. Despite changes in volatility and the markets over the
years, RSI remains as relevant now as it was in Wilder's days.
and Cardwell takes RSI interpretation to a new level. While
Wilder's original interpretations are useful to understanding
the indicator, the work of Brown
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© Research India Publications. http://www.ripublication.com
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LITERATURE REVIEW
Reena Baral, Abhishek Kumar Chintu (2013), Technical
Analysis serves the investment decision-maker by pointing the
direction that is most likely to produce the desired results and
to meet the expectations of the investors. Technical indicators
are capable of playing a useful role in timing the entry and
exit of stock market. RSI is one of the best tools available.
Whenever there is a decrease in share price, RSI value
decreases indicating share holders that it is a strong buy signal
and vice versa. Terence Tai-Leung Chong, Wing-Kam Ng,
Venus Khim-Sen Liew(2014),"Revisiting the Performance of
MACD and RSI Oscillators", It has been found that the
predictive ability of RSI and MACD works well in most of the
exchanges throughout the world. It is found that the MACD
and RSI rules consistently generate significant abnormal
returns in most of the developed and developing markets.
Investors can generate significant profit by using these tools
while making investment decisions. Renaud Beaupain, Lei
Meng, Romain Belair (2010), "The Impact of Volatility on
the Implementation of RSI”, This paper examines the impact
of volatility (measured as an exponentially-weighted moving
average) on the implementation of a trading rule, based on the
relative strength index (RSI) in the Chinese stock markets. In
particular, using tick-by-tick data from the Shanghai stock
exchange, the authors investigate how sensitive is the choice
of RSI boundaries to different volatility regimes. The study
reports empirical evidence that the return and the risk of our
portfolios, in regimes of high and low volatility, are not
significantly affected by the boundaries imposed to this
technical indicator. However, we show that within each
volatility regime some techniques provide a more desirable
return-risk package than others. Adrian Taran-Morosan
(2011), “The relative strength index revisited”, the relative
strength index (RSI) is one of the best known and most widely
use technical analysis indicators. In this paper, the study
empirically tests the functioning of the RSI in its classic form,
on a set of data and to reconfigure the indicator by also taking
account of the trading volume in its calculation formula. After
adjusting the RSI with the trading volume, the study tests its
new form on the same set of data. Finally, it compares the
obtained results by applying the classic form of the indicator
with those obtained by using the adjusted form. It concludes
that RSI works perfectly in current form but its performance
can be improved by considering additional factors such as
volume.
METHODOLOGY
Need For Study
This paper offers investment and trading solutions to the
investors in short run and also in long run. Investors often get
confused on choosing securities for investment. RSI is a
powerful tool which helps investors to make investment
decision. To add credence, testing and validation of RSI will
be of help, particularly for portfolio construction. The use of
RSI helps in minimizing the risk and maximizing the return in
respect of the portfolio.
Problem Definition
The research problem undertaken for this study is to provide
inputs trading strategies. In many cases, investors suffer due
to wrong selection of securities in a portfolio. Selection of
inappropriate securities may lead to losses being suffered by
the investor. In order to overcome this, many tools are
available of which RSI is a powerful analytical tool which
will help the investor choose the right combination of
securities for their portfolio construction.
The scope of the study is confined to select 20 companies
listed NSE. Selection of listed scripts is based on Earnings Per
Share and Profit/Earning parameters. And the period of study
is from 2011 to 2013.
Primary Objective of this study is test the validity of RSI
results in trading strategies in short term and in long term.
Along with primary objective the following secondary
objectives are considered for the study.
Secondary Objectives
1. To evaluate the performance of RSI in case of short term
investments.
2. To find the validity of RSI in Indian stock markets.
3. To find if P/E ratio or EPS better reflects the profitability
of an organisation.
Research design is descriptive and analytical in nature. The
data used is secondary data. It is data of price moving pattern
of twenty scripts listed in NSE, chosen based on EPS and P/E
ratios. Tools for analysis include, Relative Strength Index (14
day) and Relative Strength Index (56 day)
Data cleansing or data cleaning is the process of detecting and
correcting corrupt or inaccurate data from a database. In this
case inconsistent data and redundant data are carefully found
out and removed. Here, the data in which RSI is computed
had some data which are repeated. The repeated data were
found out and removed. Similarly, in certain cases, irrelevant
data was found between relevant data. These irrelevant data
were also found out and removed.
Initial data analysis doesn’t deal with answering the original
research question, instead it deals with Quality of data,
Quality of measurement instrument, Initial transformations
etc. Here the quality of data is found to be good and accurate.
It has been verified from more than one source. RSI is the
measurement instrument to be used and it is found to be one
of the most reliable measurement instruments. Missing data
has been identified at certain instances and they have been
filled.
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Main data analysis is focused on answering the research
question. Here our main aim is to find suitable stocks for
investment using RSI.RSI is calculated using the following
formulae,
RSI = 100 - 100/(1 + RS*)
RS = Average of 14 days' up closes / Average of 14 days'
down closes. (for short term investment purpose).
RS = Average of 56 days' up closes / Average of 56 days'
down closes. (for long term investment purpose).
The current RSI values of 20 stocks are given below:
RSI values as of 31/12/2013
COMPANY
NAME
CURRENT
EPS
CURRENT
P/E
RATIO
14 DAY
RSI
56 DAY
RSI
MRF
1890.72
11.73
61.08
69.096
TIDE WATER OIL
807.39
9.48
66.944
59.552
STRIDES
ARCOLAB
597.86
0.61
5.167
27.707
LAKSHMI MILL
368.33
4.29
36.291
47.92
BOSCH
292.29
35.99
74.275
63.012
JK BANK
243.81
6.23
73.84
67.366
SHREE CEMENTS
242.88
21.41
52.114
49.900
GODFREY
PHILLIP
184.76
17.05
28.77
48.737
UB HOLDINGS
169.44
0.15
70.566
59.603
INFOSYS
167.46
23.10
62.673
61.799
TGB BANQUETS
0.07
734.29
46.666
52.437
SUN PHARMA
0.95
661.16
39.663
39.901
RUCH INFRA
0.02
607.50
53.191
44.702
TAJ GVK
HOTELS
0.10
592.50
71.562
60.887
FEDERAL
MOGUL
0.41
469.27
53.698
46.6107
BAJAJ ELECTRIC
0.60
410.67
88.203
74.052
FUTURE RETAIL
0.21
386.90
62.424
50.351
NITINFIRE
PROTECTION
0.18
322.22
51.339
55.188
GMR INFRA
0.09
294.29
79.591
54.505
BF UTILITIES
2.03
267.64
80.421
3.238
RSI Chart
The 14 day and 56 day RSI chart of the twenty stocks which
are under consideration are given below.
MRF Limited
Tide Water Oil Limited
Strides Arcolab Limited
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Lakshmi Mill Limited
Bosch Limited
JK Bank Limited
Shree Cements Limited
Godfrey Phillip Limited
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UB Holdings Limited
Infosys Limited
TGB Banquets and Hotels Limited
Sun Pharmaceuticals Limited
Ruchi Infrastructure Limited
Taj GVK Hotels Limited
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Federal Mogul Limited
Bajaj Electric Limited
Future Retail Limited
Nitin Fire Protection
GMR Infrastructure Limited
BF Utilities Limited
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Interpretation
Based on the buy/sell indicators developed by Wilder and by
means of basic stock selection principles, the stocks are
chosen both for short term investment and long term
investment.
Short term Investment:
The following stocks have been chosen for short term
investment: Sree Cements Limited, Nitin Fire Protect Limited,
Godfrey Phillip India Limited, TGB Banquets Limited and
Sun Pharmaceuticals Limited
Now, let us see why the above stocks have been chosen by
viewing their RSI charts.
Sree Cements Limited
In this case, we can see that, it is quite rare to see the graph
drop below 40, and whenever it has dropped to such an extent
it has come back strongly. At this point of time the RSI value
is 36, so we can expect it to increase significantly within a
short period of time. Although it may extent its downward
trend for a week or two, it will change its momentum within a
short period of time. Also, in this case the standard deviation
or risk is low when compared to many other stocks, so we
choose this stock for short term investment.
Nitin Fire Protection Limited
The RSI graph shows a strong upward trend in case of Nitin
Fire Protect. RSI value is just above 50 and it signifies that,
the market is strong for this particular stock, so it is suitable to
invest in this stock for short term till the RSI value reaches 70.
It may not be suitable to invest in this stock for long term
given its high rate of fluctuation which signifies high risk.
Godfrey Phillip India Limited
The RSI graph of Godfrey Phillip has just reached its lower
low and currently its trend is upward but still RSI value is
under 30 which mean it is still over sold. Also the upward
trend is expected to be sustained for quite some time, so one
can invest in Godfrey Philip for short term till RSI value
reaches 70, it is a safe bet.
TGB Banquets and Hotels Limited
The RSI graph of TGB Banquets has reached its lower low by
the end of November and currently its trend is upward.
Although there is a significant volatility in the movement of
the RSI graph, The current RSI value is around 46 and the
upward momentum is likely to be sustained till it reaches the
overbought level, so it is advisable to invest in TGB Banquets
for short term.
Sun Pharmaceuticals Limited
In case of Sun Pharmaceuticals, there has been some
variability in the movement of RSI values. The RSI value
reached lower low 30 by the end of September, and since
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 19 (2017) pp. 8926-8936
© Research India Publications. http://www.ripublication.com
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then, there has been a slight increase and the RSI value hovers
around 40. However, the momentum can be expected to shift
upwards as the graph has already hit the lower bottom and is
unlikely to shift downwards.
Long Term Investment
The following stocks have been chosen for long term
investment. Laxmi Mill Limited, Federal Mogul Limited, UB
Holdings Limited, Future Retail Limited and Ruchi
Infrastructure Limited
Laxmi Mill Limited
The RSI graph of Laxmi Mill shows that its performance has
been consistent. It was only once during the considered time
period that the graph dropped below 40. Its performance has
been strong over the past few years. Also, the standard
deviation is low which signifies lower risk. These factors
make Laxmi Mill suitable for long term investment.
Federal Mogul Limited
The RSI graph of Federal Mogul has been constantly above
40, and it has experienced only once a significant dip below
40. As a matter of fact the graph has stayed between 40 and
60 for most of the time, this shows that the performance of
Federal Mogul has been consistent for the past three years and
the risk is low. Consistent performance and low risk are the
factors that induce the investor to invest. So, we can say that
Federal Mogul is safe for long term investment.
UB Holdings Limited
The current trend of UB Holdings is bullish failure swing.
Irrespective of the trend, the performance has been consistent
other than for a bearish failure swing during September 2012
to march 2013. Since the performance has been quite
consistent and the risk being acceptable, we go for UB
Holdings for long term investment.
Future Retail Limited
Future retail, like the other chosen stocks for long term
investment has shown consistent performance and its risk is
low. During the past three years, the graph has stood above 40
during most of the time period, there has only been two
significant drops. Also, the current momentum is upward, so
Future Retail will prove to be a good long term investment.
Ruchi Infrastructure Limited
The RSI graph of Ruchi Infrastructure has both upward trends
and downward trends, but during most of the time the trend
has been upward and the movement has been positive. Also,
the current trend is upward. It is also to be noticed that the risk
is acceptable as the volatility is quite low, so Ruchi
Infrastructure may make a suitable long term investment.
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© Research India Publications. http://www.ripublication.com
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Portfolio
NAME
SYMBOL
RSI
LAXMI MILLS
LAKSHMIMIL
47.920
FEDERAL MOGUL
FMGOETZE
46.61
UNITED BREWERIES
HOLDINGS
UBHOLDINGS
59.603
FUTURE RETAIL
FRL
50.351
RUCHI INFRASTRUCTURE
RUCHINFRA
44.702
SREE CEMENTS
SHREECEM
52.114
NITIN FIRE PROTECTION
NITINFIRE
51.339
GODFREY PHILLIPS
GODFRYPHLP
28.77
TGB BANQUETS AND HOTELS
TGBHOTELS
46.66
SUN PHARMACEUTICALS
SUNPHARMA
39.66
Performance Evaluation of Short Term Investment
The performance of short term stocks has been evaluated by
checking with their RSI graph after a period of three months.
These are the results obtained:
Sree Cements Limited
It can be clearly seen that from the position in December 2013
the graph experienced a few ups and downs, but then, the
trend of the graph shifted upward and it breached the 70 mark.
The point at which reversal of trend occurs is 90, although one
might sell the stock when the RSI reaches 70. In this case, the
stock selection has been accurate.
Nitin Fire Protection Limited
In case of Nitin Fire Protect, although, the graph took a dip
immediately after December 2013, it has improved since then
and the trend in currently upward and soon the RSI graph is
expected to breach the 70 mark. The current RSI value is 61.
As there is an improvement the position of graph, when
considering its position in December 2013, we may consider
this investment as profitable.
Godfrey Phillip India Limited
In case of Godfrey Philip, we can see that the graph has
bounced back strongly during January 2014 from its
downward trend in December 2013. The graph simultaneously
breaches the 70 mark and keeps on increasing; it changes its
trend only after it has breached 90. Investment in Godfrey
Philip has proved successful and very fruitful.
TGB Banquets and Hotels Limited
In case of TGB Banquets, the trend was upward initially
during January 2014, but since then the trend became
downward with the graph reaching its lower low during
February. After that there was a slight improvement in the
graph and its current position is similar to its position in
December 2013. This investment, unlike other short term
investments has not performed up to expectation.
Sun Pharmaceuticals Limited
The RSI graph shows that there has been a significant
improvement in the performance of Sun Pharma after
December 2013 as it has breached the 70 mark twice. Its
current mark is around 47, but it is obvious that one would sell
the stock once it has breached the 70 mark. SO, investment in
Sun Pharma has proved fruitful. In this case, it is to be noted
that, in case of short term investments, out of the five chosen
stocks, by means of evaluation we have received positive
results for four stocks.
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 12, Number 19 (2017) pp. 8926-8936
© Research India Publications. http://www.ripublication.com
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FINDINGS
RSI can be effectively used in the construction of portfolio. It
can be used both for short term investment and long term
investment. It accurately predicts the buy and sells signals for
different stocks. RSI in most cases successfully predicts the
future trend of the stocks. Although many researchers have
been conducted on RSI across different stock markets around
the world, no significant research has been done using RSI in
Indian Stock Market. Now in our research, the results of short
term investment indicate that RSI can also be successfully
used in Indian stock market. The study also shows that P/E
ratio is a better indicator of profitability when compared to
EPS. The study has also listed the following signals for the
twenty stocks for short term and long term investment.
Table 4.3: Short term and Long term RSI signal for the 20
Stocks
SIGNAL
COMPANY NAME
SHORT TERM
LONG TERM
MRF LIMITED
SELL
SELL
TIDE WATER OIL
SELL
HOLD
STRIDES ARCOLAB
SELL
HOLD
LAKSHMI MILL
BUY
BUY
BOSCH LIMITED
SELL
SELL
JK BANK LIMITED
SELL
SELL
SHREE CEMENTS
BUY
HOLD
GODFREY PHILLIP
BUY
BUY
UB HOLDINGS
HOLD
BUY
INFOSYS LIMITED
HOLD
HOLD
TGB BANQUETS
BUY
HOLD
SUN PHARMA
BUY
SELL
RUCH INFRA
BUY
BUY
TAJ GVK HOTELS
SELL
SELL
FEDERAL MOGUL
SELL
BUY
BAJAJ ELECTRIC
SELL
SELL
FUTURE RETAIL
BUY
BUY
NITIN FIRE PROTECTION
BUY
HOLD
GMR INFRASTRUCTURE
SELL
HOLD
BF UTILITIES
SELL
SELL
CONCLUSION
From the results obtained, we can clearly find that RSI is one
of the most effective technical analysis tools available, it can
be effectively used to create a portfolio. Just as it performs
well in other stock markets around the world, it also works
well in Indian stock market. It has also been found out that
P/E ratio better reflects the performance of an organization
when compared to EPS. Although RSI in itself is a very
powerful analytical tool, using fundamental analysis and other
technical analytical tools along with it gives better results.
REFERENCES
[1] Reena Baral, Abhishek Kumar Chintu (2013), “Study of
Technical Analysis for Finding Buying and Selling
Signal in Stock Market Through Technical Indicators ”,
International Journal of Entrepreneurship & Business
Environment Perspectives , Volume 2, Number 1,
pg.288-296.
[2] Terence Tai-Leung Chong, Wing-Kam Ng, Venus
Khim-Sen Liew(2014),"Revisiting the Performance of
MACD and RSI Oscillators", Journal of Risk and
Financial Management, vol.7,pg.1-12.
[3] Renaud Beaupain, Lei Meng, Romain Belair (2010),
"The Impact of Volatility on the Implementation of
RSI”, Insurance Markets and Companies: Analyses and
Actuarial Computations, Vol. 1, Issue 3, pp. 73-78.
[4] Adrian Taran-Morosan (2011), “The relative strength
index revisited”, African Journal of Business
Management, Vol. 5(14), pp. 5855-5862.
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http://articles.economictimes.indiatimes.com/
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http://finance.yahoo.com/
http://www.chartnexus.com/
... Values >70 (conservative variant 80) indicate an overbought market, generating a signal to close a long position or open a short position [Kannan et al., 2010]. The opposite signal, in turn, is generated when the value of the RSI is below the level of 30 (conservative variant 20), which is in turn referred to as the oversold level [Gumparthi, 2017]. The method of calculating the RSI is presented in Eq. (1): ...
... where: a -average value of increase in closing prices from the analyzed period, b -average value of decrease in closing prices from the analyzed period. The level of accuracy of signals generated by the RSI in the Indian stock market in the short and long terms was studied by Gumparthi [2017]. The study was conducted using data for 20 companies from January 2011 to December 2013. ...
... A 14-period RSI was applied, and levels of 30 and 70 were used as trading signals. The results obtained by the authors indicate that in the Indian market, the RSI allows generating accurate buy and sell signals for stocks, helps identify overbought and oversold levels, and that the best results can be obtained by using it in combination with other technical indicators such as moving averages -confirming the results obtained by Gumparthi [2017] with his research team. Tanoe [2019] in his research presented the forecasting possibilities provided by the use of the RSI, moving average and Deep Q-Learning reinforcement learning in forecasting the price of the US company Apple, based on data from 2018 to 2019. ...
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Accurate forecasting of the level of volatility of financial instrument prices is important from the point of view of stock exchange investors. The aim of this paper is to measure the value relevance of transaction signals (buy/sell) by the relative strength index (RSI) in the case of State Treasury companies listed on the Warsaw Stock Exchange (WSE). The research covered the two hypotheses stating that stock buy (sell) transaction signals generated by the RSI indicator cause the occurrence of statistically significant positive (negative) abnormal returns (AR). These, in turn, support that RSI generates value-relevant signals, which are valuable investment tools and can be used to earn money on the stock exchanges. Based on the final research sample, including 75 buy signals and 88 sell signals, generated by the RSI indicator on the shares of State Treasury companies listed on WSE, an event study methodology was carried out. In 7-day event windows, calculations were made of AR, which is the difference between the realized and the expected return (estimated on the basis of the market model). The averaged ARs did not differ statistically significantly from zero on any of the tested days for both buy and sell signals. Therefore, research results do not indicate that share purchase (sell) transaction signals generated by the RSI indicator result in the occurrence of statistically significant positive (negative) average abnormal returns (AAR).
... To predict the weather, a GBM+HQLoss technique has been devised in this work. For that, firstly time series data is fed as input to the technical indicator extraction phase, and here various technical indicators, like WMA [6], RSI [7], MACD [8], Bollinger bands [9], and ATR [10] are mined. After extracting the technical indicators from the data, feature selection is carried out by employing IG [11]. ...
... It is also employed for optimizing the operations and lessening the risks that are related to weather variability. Various technical indicators, like WMA [6], RSI [7], MACD [8], Bollinger bands [9], and ATR [10] are considered and then mined. Moreover, V  is taken as input for mining the technical indicators. ...
... (ii) RSI RSI [7] refers to the frequency of weather changes when correlated to historical averages during a specific period. This indicator is employed for interpreting and analyzing the weather data effectively. ...
... First of all, the Relative Strength Index (RSI) is a crucial technical indicator introduced by J. Welles Wilder, designed to measure momentum and price change. RSI typically ranges from 0 to 100 and is used to identify overbought (above 70) or oversold (below 30) market conditions, helping investors determine optimal entry and exit points (Hari & Dewi, 2018;Ăran-Moroan, 2011;Bhargavi et al., 2017;Xing, 2022). RSI has been successfully applied not only to stock trading but also to volatile assets such as gold and Bitcoin, enabling investors to optimize trading strategies, minimize risks, and enhance profitability (Bhargavi et al., 2017;Xing, 2022). ...
... RSI typically ranges from 0 to 100 and is used to identify overbought (above 70) or oversold (below 30) market conditions, helping investors determine optimal entry and exit points (Hari & Dewi, 2018;Ăran-Moroan, 2011;Bhargavi et al., 2017;Xing, 2022). RSI has been successfully applied not only to stock trading but also to volatile assets such as gold and Bitcoin, enabling investors to optimize trading strategies, minimize risks, and enhance profitability (Bhargavi et al., 2017;Xing, 2022). Recent studies have even integrated RSI with computational models like recurrent neural networks and XGBoost to develop more effective quantitative trading strategies (Xing, 2022). ...
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Forecasting gold prices remains a complex challenge due to the volatile macroeconomic variables, market sentiment, and global events. This study explores the application of technical analysis indicators, including the Relative Strength Index (RSI), Money Flow Index (MFI), Commodity Channel Index (CCI), and Moving Average Convergence Divergence (MACD) in order to predict short-term and long-term gold price movements. By analyzing these indicators across 1-month and 3-month timeframes on chart, the study provides a dual perspective on gold's behavior, capturing immediate price fluctuations and broader market trends. The results reveal that these indicators effectively identify overbought and oversold conditions, key support and resistance levels, and potential trend reversals. While gold prices are expected to maintain a bullish trajectory through 2025, the study highlights the possibility of moderate corrections in the short term. This research contributes to the literature on gold price forecasting, offering practical insights for investors and financial institutions aiming to refine their investing strategies in dynamic markets. Keywords: Gold Prices, Technical Analysis, RSI, MFI, CCI, MACD.
... The Relative Strength Index (RSI) [62]is a momentum oscillator that measures the speed and change of close price movements. It is used to identify overbought or oversold conditions in a market. ...
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Accurately predicting stock prices remains a formidable challenge in financial markets. Traditional predictive models often aggregate data from multiple companies, failing to account for the unique characteristics of each firm, which can hinder the model’s ability to identify company-specific patterns. Moreover, existing research on stock price prediction frequently trains and tests models within the same group of companies, neglecting to assess their generalizability on ’Out-of-Sample’ companies. This study addresses these limitations by employing BERT to encode business descriptions into vectors, capturing the distinctive attributes of each company.We further enhance the predictive modeling framework by developing features that describe the percentage change of existing indicators, adding significant novelty to the existing research. Additionally, we apply a Restricted Boltzmann Machine (RBM) for dimensionality reduction after the BERT encoding process. In our approach, both the technical indicators and the vectorized descriptions are treated as distinct elements within the transformer encoder. By integrating these representations, our model is better equipped to differentiate between firms and recognize their individual patterns. The proposed model demonstrates superior performance over baseline models, particularly when tested on ’Out-of-Sample’ companies, highlighting its ability to learn, understand, and analyze company-specific descriptions for more accurate predictions. This research offers novel insights into addressing the heterogeneity in stock price prediction.
... Moving Average Convergence Divergence (MACD), a popular momentum indicator, identifies trend changes and potential buy-or-sell signals by analyzing the relationship between two moving averages (Hoang Hung, 2016). Relative Strength Index (RSI) is another widely used momentum oscillator that measures the speed and change of price movements to determine overbought or oversold conditions (Bhargavi et al., 2017). Bollinger bands, developed by John Bollinger, consist of a middle band, typically a simple moving average, and upper and lower bands representing standard deviations from the middle band, helping to identify price volatility and potential trend reversals (3). ...
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Algorithmic trading has become increasingly prevalent in financial markets, and traders and investors seeking to leverage computational techniques and data analysis to gain a competitive edge. This paper presents a comprehensive analysis of algorithmic trading strategies, focusing on the efficacy of technical indicators in predicting market trends and generating profitable trading signals. The research framework outlines a systematic process for investigating and evaluating stock market investment strategies, beginning with a clear research objective and a comprehensive review of the literature. Data collected from various stock exchanges, including the S&P 500, undergo rigorous preprocessing, cleaning, and transformation. The subsequent stages involve generating investment signals, calculating relevant indicators such as RSI, EMAs, and MACD, and conducting backtesting to compare the strategy's historical performance to benchmarks. The key findings reveal notable returns generated by the indicators analyzed, though falling short of benchmark performance, highlighting the need for further refinement. The study underscores the importance of a multi-indicator approach in enhancing the interpretability and predictive accuracy of algorithmic trading models. This research contributes to understanding of algorithmic trading strategies and provides valuable information for traders and investors looking to optimize their investment decisions in financial markets.
... To enhance the model's predictive capability, additional feature engineering was performed, allowing, in addition to the short-term patterns, to add medium-term trends averaged over time. This involved creating new features based on the historical data, including but not limited to Moving averages of different time frames (Figure 4), Relative Strength Index (RSI) (Gumparthi, 2017) and Moving Average Convergence Divergence (MACD) (Aguirre et at., 2020). This section describes the process of label generation, a crucial step in preparing the dataset for predictive modelling. ...
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Study of Technical Analysis for Finding Buying and Selling Signal in Stock Market Through Technical Indicators
  • Reena Baral
  • Abhishek Kumar Chintu
Reena Baral, Abhishek Kumar Chintu (2013), "Study of Technical Analysis for Finding Buying and Selling Signal in Stock Market Through Technical Indicators ", International Journal of Entrepreneurship & Business Environment Perspectives, Volume 2, Number 1, pg.288-296.
The Impact of Volatility on the Implementation of RSI
  • Renaud Beaupain
  • Lei Meng
  • Romain Belair
Renaud Beaupain, Lei Meng, Romain Belair (2010), "The Impact of Volatility on the Implementation of RSI", Insurance Markets and Companies: Analyses and Actuarial Computations, Vol. 1, Issue 3, pp. 73-78.