Analyzing Market Trends using a Visual Approach
HSUEH-YING WU 1, SHU-WEN LEI 2, JIH-LIAN HA2
1Department of Accounting Information, Aletheia University
Taipei, TAIWAN
2Department of Innovation Design and Entrepreneurship Management Far East University
Tainan, TAIWAN
Abstract: - This research discusses various technical analysis methods and their flaws in the stock market price
trend, and proposes a plan that integrates several technical indicators to analyze the price trend. Changes in
price trends are mainly due to market uncertainty about the future. The macro investment sentiment is crucial to
the impact of price trends. Any political and financial decision-making changes or events can affect the
market's investment sentiment. Changes in securities market prices usually have a direct response to changes in
the macro investment environment. A single technical indicator captures this change. But when multiple
technical indicators are used, there is the potential for conflicting signals. Investors can judge future trends
based on their familiarity with the market or experience. For resolving the conflict of technical indicator signals
and managing future uncertainty, this study uses information entropy theory as an algorithm for integrating
technical indicators and then forms an easy-to-read price trend chart. The K-line chart with various color
changes provides a visual price trend judgment to facilitate investors to make decisions. This study uses several
exponential moving averages as the main component indicators of price information entropy to test the Dow
Jones futures and many individual stock research objects. The emphasis of this study is not on finding
indicators that are 100% profitable, but on the management of market uncertainty. The liquidity of investment
products is very important, and sufficient liquidity is needed to accurately judge the trend. When the price trend
is uncertain, the K-line chart designed in this study is displayed in different colors, and investors can directly
observe whether they can enter the market for trading. The timing of entry and exit proposed in this study is
entirely based on the certainty of the trend. In the verification, strictly observe the timing of entering and
exiting the investment strategy, and only enter the market when you are sure of the trend, so that the investment
profit is significant. This study verifies the practicability of this method with past historical data.
Keywords: - Price trend, Technical indicators, Information entropy theory, K-line chart.
Received: September 23, 2021. Revised: May 29, 2022. Accepted: June 19, 2022. Published: July 25, 2022.
1 Introduction
The methods of stock market price trend can be
divided into fundamental analysis and technical
analysis. Fundamental analysis focuses on the
company's operating conditions and financial data,
while technical analysis focuses on current price
trends and uses various technical indicators as
analysis methods. Due to the often incomplete
expected cycle of price action changes, a single
technical indicator fails. The analysis method must
use several indicators at the same time to make
more accurate predictions. When a variety of
indicators are used together, it is easy to cause
contradictions in the analysis results. This study
argues that a simple and easy-to-read single decision
indicator should be established to avoid this
phenomenon. The method of technical analysis is
mainly to generate some indicators and trend
patterns of stock prices, such as RSI, KD, MACD,
etc. Then make an analysis based on such indicators
for investment. Due to the variety of indicators in
technical analysis, some methods use a single
indicator as a strategy, and some use multiple
indicators to analyze at the same time as an
investment strategy. When multiple indicators are
used together, visual confusion can easily occur.
The purpose of this research is to simplify the way
of technical analysis and to generate an easy-to-read
visual chart by synthesizing multiple indicators. The
basic thinking is similar to the blackjack poker
calculation method [4], which calculates the best
entry opportunity to invest, makes a profit in the
proportion of the final winning rate, and does not
pursue success every time. The method used is to
use information entropy theory [2] to summarize
several technical indicators and patterns into one,
and then generate trend graphs for investors to make
trading decisions.
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2 Literature Survey
Technical analysis can be roughly divided into four
categories, trend indicators, momentum indicators,
volatility indicators, and volume indicators. Among
them, Moving Average, MACD, and RSI are the
most commonly used. Combining volume and other
indicators at the same time, the Volume Weighted
Average Price Indicator is also often used.
2.1 Moving Average
Well-known mathematician ED Throp, Patterson
[17] used the Moving Average method to
successfully make profits in the US stock market in
the early 1950s. Moving average is to calculate the
average price for some time. ED Throp uses this
average price as an investment indicator. When the
price rises above the average price, it buys, and
when it is lower than the average price, it sells. The
way to improve is to use two average price lines to
analyze, short-term and long-term. But when the
short-term average price line rises above the long-
term average price line. Conversely, sell when the
average price line falls below. In this way, there will
still be frequent transactions during the price
consolidation phase. When this happens, the
analysis of average prices fails [9].
2.2 MACD
Moving Average Convergence Divergence was
proposed by Gerald [1], and its method is to
calculate the difference between the short-term and
long-term average prices to measure the price trend.
A difference below zero indicates a downward
trend, and a difference greater than zero indicates an
upward trend [5]. Since the calculation is based on
the average price, this indicator will lag.
2.3 RSI
The scholar J. Welles Wider (1978) proposed the
RSI indicator in 1978, the Relative Strength Index,
which is a momentum-based indicator. It mainly
calculates the magnitude and rate of price changes.
This indicator is often used to assess oversold and
overbought price movements [6]. The value of RSI
ranges from 0 to 100. When the RSI exceeds 80, it
indicates that the price rises too fast and maybe
overbought. The most likely follow-on reaction to
overbought is a fall in price. When the RSI is too
low, such as below 25, it will be oversold, and the
subsequent price trend may rebound at any time.
2.4 Volume Weighted Average Price
Indicator (VWAP)
Volume as a measure of price trends was first
proposed by Osborne [14]. Osborne built a
mathematical model to analyze the correlation
between price action and volume. In his research, he
found a statistically significant correlation between
volume and price period changes. The average
experienced investor must have noticed that when
the price plummets, there will be a last large volume
of instantaneous decline. After that, the price will
see a situation where the price is hovering around
the low price. This phenomenon usually occurs in a
market where the overall average trading volume is
relatively fixed. Scholars Li and Zhu (2014) studied
the efficiency of a volume-weighted average price
indicator. Its research found that including volume
in trend analysis can improve the efficiency of
forecasting.
3 Research Method
3.1 Market Uncertainty
In general, when people feel uncertain about the
future of something, they feel uneasy or hesitant to
move forward. In the stock market, investors react
similarly to uncertain events. For example, when the
U.S. Federal Reserve talks about increasing the base
rate for borrowing, the stock market's first reaction
is usually a decline or stagflation. One of the
uncertainties is that the market cannot predict how
much the US Federal Reserve will raise interest
rates in the future. But when the decision is
officially announced, the stock market sometimes
rises instead because the uncertainty has been lifted.
For example, on March 16, 2022, the U.S. Federal
Reserve raised interest rates by 25 basis points, and
the three major U.S. indexes all rose sharply the
next day. In the operation of stock trading, people's
reaction to future uncertainty can make definite
speculation on investment decisions, that is, the
market will fall or stagnate, or even fluctuate
violently, which is not conducive to investment.
When uncertainty turns to certainty, people's
reactions change with it. This could be seen as a
turning point in the stock market's reaction. If you
can grasp the turning points of the stock market, the
success rate of buying and selling decisions will also
be relatively improved.
3.2 Measuring Uncertainty
The difficulty in analyzing price trends is that the
influence of external factors leads to uncertainty in
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future prices. By grasping the turning point of
uncertainty, you can grasp the future trend.
However, there is no technical indicator that can
fully predict future price movements. When using
various technical indicators, the phenomenon of
conflicting indicator signals often occurs. When
indicators conflict, how to make a decision becomes
an investment strategy issue. If such uncertainty can
be represented by quantifiable data, the situation of
index conflict can be quantified as data. Investment
strategies can then make decisions based on this
data.
The method used in this study to quantify
uncertainty refers to Shannon's information entropy
theory [2]. Information entropy is used to quantify
the uncertainty of text transmission during
communication. The method is, to sum up, all
possible situations probabilistically to get a value.
Higher numbers indicate higher uncertainty. The
basic concept of information entropy believes that
the role of information is to eliminate people's
uncertainty about things. When a message has a
higher probability of appearing, it means that it is
more widely spread. From the perspective of the
breadth of information dissemination, information
entropy can represent the value of information. The
calculation method of information entropy is as
follows:
(1)
x represents a random factor, and P(x) represents the
output probability function
Assuming that there are n observed events, the
probability of occurrence is P1, P2, …, Pn, the
probability combination can be written as
(P1,P2,…,Pn), then according to the above formula,
the uncertain value is H(P1, P2,…, Pn)
In this study, the uncertainty of the price trend takes
the prediction of future trends of technical indicators
as a random factor, and the sum of several technical
indicators is used as the value of information
entropy, which is defined as price information
entropy. Each of these technical indicators predicts
that the probability of rising is regarded as an event
in the price information entropy formula. The
formula for price information entropy is as follows:
(2)
Where (3)
P(X) is the price information entropy value of an
event, x is the probability of event occurrence, a is
the rate of change of price information entropy, and
k is the minimum price information entropy. When
x is closer to 50, that is, when the probability of
event occurrence is close to 50%, the value of price
information entropy is lower. When the price
information entropy value is lower, it means that the
uncertainty is high, which means that it is not
suitable for any investment behavior. For example,
three indicators are used to make predictions. At
time A, the calculated rise probability of each
indicator is 50%, 60%, and 50%. At time B, the
calculated ascent probabilities are 40%, 70%, and
65%. The entropy value calculated at time A will be
lower than that at time B, indicating that the price
trend at time A has high uncertainty and is not
suitable for any operation.
3.3 Research Methods
This study is divided into three steps:
(1) Select appropriate technical indicators and
establish a price information entropy calculation
model.
(2) Design visual graphics to show price trends.
(3) Test the price information entropy calculation
model with the actual market price trend.
The main research object is the US Dow Jones
futures index.
Screening of technical analysis indicators:
In simple terms, price information entropy is a way
of making decision-making judgments by
combining multiple indicators into one value. Any
technical indicator can be used as one of the factors
of judgment, and this method also provides
decision-making flexibility. Investors can set it in
the calculation formula of price information entropy
according to their familiarity with various technical
indicators.
Embedded Cycle:
Based on the historical data of market price changes
for many years, the results of induction and analysis
of this research show that the trend-type technical
indicators are the most suitable for trend analysis
and forecasting. Such indicators are directly related
to the average value of the price. By analyzing the
way of Exponential Moving Average (EMA), a
natural law phenomenon of price trend can be
obtained. The price of a product is analyzed by 4
exponential moving averages with values of 24, 60,
120, and 240. When the exponential moving
average of 24 falls below the exponential moving
average of 60, the price action begins to decline.
When the price bounces up to meet the exponential
moving average near 60, this price becomes the
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upward resistance and the price will fall again.
Exponential moving averages of 120, and
exponential moving averages of 240 also show such
price movements. This kind of price change trend is
suitable for the K-line chart drawn in any period, 1
minute, 3 minutes, 5 minutes, 30 minutes, 1 hour, 4
hours, daily chart, etc., and similar trend phenomena
can be obtained. That is, the price trend
phenomenon can be observed in the K-line chart at
any time. This study calls it the Embedded Cycle.
This phenomenon also provides the basis for the
observation of uncertainty and certainty in this study.
From the K-line chart of a longer period, the
certainty of the price increase is judged according to
the price resistance and support area of this group of
moving averages and then subdivided into the price
trend of the K-line chart of a shorter period. For
example, in the 4-hour chart, the trend is down, if
the hourly chart is used for operations, the 4-hour
trend can be used as a judging factor for the price
information entropy.
3.4 Judgment of Uncertainty
There are various analytical methods for judging
price movements, this study focuses on the
exponential moving average method [3]. Repeated
analysis of historical data found that when the price
entered between several exponential moving
averages, the trend immediately became unclear.
When the price enters between the two exponential
moving averages, the trend is very likely to be
range-bound and uncertainty increases.
3.5 Visual Presentation Method
In this study, K-line charts with different colors are
used to display the numerical range of price
information entropy [7]. Figure 1 4-hour K-line
chart of the US Dow Jones futures index in
February 2020, the numerical information of the
price information entropy is displayed below the
figure. The red line represents the decline, the green
line represents the increase, and the other colors
represent high uncertainty and are not suitable for
trading. The value and color of the price information
entropy are set as rising and falling. The rising price
information entropy color ranges from dark green to
light green, with dark colors indicating low and light
colors indicating high. The price information
entropy color of the downward trend is from light
red to dark red, with light color indicating low and
dark color indicating high. Arrows indicate price
trend turning points. The downward arrow indicates
that the trend is very likely to decline. On the
contrary, the upward arrow indicates that the trend
is very likely to rise. [11]
In this study, candlesticks that are in a downtrend
are shown in red. Among them, red and pink are
negative lines, and orange is positive lines.
Although the positive line is rising, according to the
judgment of price information entropy, the
probability of rising is less than 40%, so it is
displayed by the orange Kline [12]. The K-lines that
is in an uptrend are shown in green. Among them,
dark green, light green, and apple green are positive
lines, and blue is negative lines. The negative line is
down. According to the judgment of price
information entropy, the probability of downside is
less than 40%, so it is displayed by the blue Kline.
The color bar below the candlestick chart shows the
change in long-term price information entropy. The
long-term judgment is the price change of the last
240 K-lines. Red represents a long-term downtrend,
and blue represents a rebound in a downtrend.
Green represents a long-term uptrend, and pink
represents profit-taking on an uptrend [8].
Fig. 1: 4-hour K-line chart of the US Dow Jones
futures index in February 2020
4 Validation of Research Methods
No single indicator or investment strategy can be
100% accurate in predicting stock market price
movements. Rather than seeking 100 percent
forecasts, the approach of this research focuses on
managing uncertainty and planning investment
strategies to deal with it. Uncertainties include
actual trends in the stock market and
macroeconomic sentiment. When the market feels
uncertain about the future, investment judgment
becomes a definite factor that affects price trends,
namely stagflation or decline [10]. This chapter
discusses the utility of price information entropy.
The investment strategy is as follows:
(1) Only enter the market when a turning signal
appears.
(2) Follow the long-term price information entropy
data as the main, supplemented by the short-term
price information entropy.
(3) According to the macroeconomic climate, the
long-term information entropy is used as the actual
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reaction of the market to the investment climate,
rather than the subjective psychological impact of
economic events.
Investment methods:
Investment methods are divided into long and short.
Going long means buying, if the index rises, it will
make a profit, and if it falls, it will make a loss.
Conversely, shorting means buying, if the index
falls, it will make a profit, and if it rises, it will
make a loss. [13]
Time of entry:
Observe the color change of the K-line chart, the K-
bar, and the long-term price information entropy
below
Go long: When the upward arrow at the turning
point appears, the K bar shows apple green and the
long-term price information entropy below is green.
Go short: When the downward arrow of the turning
point appears, the K bar is red and the long-term
price information entropy below is red.
Time to play:
Go long: The K bar appears 2 consecutive blues or
the second blue appears, or a red K bar appears.
Going short: The K bar appears 2 consecutive
oranges or oranges for the second time or a green K
bar appears.
Main research object:
4-hour chart of the US Dow Jones futures index.
4.1 US Subprime Mortgage Crisis
Time: July 2007
Event point
July 27: Global stock markets plummeted for the
first time due to the U.S. subprime mortgage crisis.
Fig. 2: US subprime mortgage crisis July 2007 US
subprime mortgage crisis Dow Jones futures chart
4.2 The U.S. Subprime Mortgage Crisis
Expands
Date: February 2008
Event point
Feb. 12: Big six U.S. mortgage lenders announce
lifeline plan
March 6: U.S. ADP payrolls plummet by more than
20,000 in February
March 19: The Fed announces a 75 basis point rate
cut.
Fig. 3: The U.S. subprime mortgage crisis expanded
in February and March 2008. The Dow Jones
futures index chart
4.3 Lehman Brothers goes bankrupt
Time: September-October 2008
Event point
September 15: Lehman Brothers files for
bankruptcy protection
September 29: The U.S. House of Representatives
rejects the $700 billion rescue plan
October 2: Rescue plan passed
October 8: The U.S. Federal Reserve announces a
50 basis point rate cut.
Fig. 4: Dow Jones futures chart in September 2008
after Lehman Brothers went bankrupt
4.4 US President Trump Inauguration
Month
Time: January 2017
Event description:
In November 2016, President Trump was elected.
The U.S. stock market surged until the Dow rose to
an all-time high of nearly 20,000 in January of the
following year. Psychological pressure is formed
here, and the stock market stagnates but does not
fall. At the same time, the U.S. federal government
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was shut down for several days due to budget
problems. Until January 25, 2017, US President
Trump signed a temporary appropriation bill to
allow the US federal government, which had been
shut down for 35 days, to resume operations until
February 15.
Fig. 5: The Dow Jones Futures Chart in January
2017, the month of US President Trump's
inauguration
4.5 Covid-19 New Corona-virus Outbreak
Timepoint: January-February 2020
Event point
January 23: Covid-19 outbreak, lockdown in
mainland China
February 23: Cases surge in Europe
Fig. 6: Trend chart of the Dow Jones futures index
from January to February 2020 due to the new
Corona-virus epidemic
4.6 US Fed Rate Hike Expectations and the
Russian-Ukrainian War
Time: January-February 2022
Event description:
On December 15, 2021, the U.S. Federal Reserve
announced that it will keep interest rates unchanged,
and it is expected to end bond purchases as early as
March 2022. From January 2022, the US Federal
Reserve officials believe that inflation is not
temporary, leading to a change in market sentiment,
and it is expected that interest rates will be raised
more than three times in 2022. Uncertainty emerged
in the market, speculation about the rate hike in
2022 began, and stock market prices began to fall.
On January 26, the U.S. Federal Reserve announced
no change in interest rates. On February 14, U.S.
intelligence officials informed that Russia would
invade Ukraine on February 16. On February 24,
Russia announced a special military operation
against Ukraine.
Fig. 7: The Dow Jones Futures Index Trend Chart in
January-February 2022 for the US Federal Reserve
to Raise Interest Rate Expectations and the Russian-
Ukrainian War.
4.7 Stock Operation Strategy
Operating period: daily chart of individual stocks.
From April 1, 2021, to March 11, 2022.
Trend judgment: Observe the color change of the
long-term price information entropy below. Green
represents an uptrend and red represents a
downtrend. In an uptrend, pink represents a profit-
taking phase. In a downtrend, blue represents the
price rally phase. [15]
How it works: Go long.
When to enter the market: when the long-term price
information entropy below is in an upward trend.
The green K-stick comes into play. The rebound
trend of the downtrend does not enter the market.
Timing of appearance: When the red K-stick
appears.
Re-entry timing: After the red K-bar appears, you
need to observe the trend, and not enter the market
immediately when the color of the next long-term
price information entropy turns green. Wait for the
market to absorb selling pressure and remove
market uncertainty before entering the market.
Individual stock research objects: Apple (AAPL),
Microsoft (MSFT), Nvidia (NVDA), Facebook (FB),
Google (Google), Tesla (TSLA),
The display method of buying and selling: In the K-
line chart, the orange arrow indicates the buying
point, and the horizontal line indicates the selling
point. Losing trades show losses or flats at the end
of the arrow. [16]
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Fig. 8: Apple (AAPL)
Fig. 9: Microsoft (MSFT)
Fig. 10: Nvidia (NVDA)
Fig. 11: Facebook (FB)
Fig. 12: Google (Google)
Fig. 13: Tesla (TSLA)
4.8 Analysis of Verification Results
This section uses several exponential moving
averages and filtered average prices as the main
components of price information entropy to test
several individual stock trends. Overall, the
investment strategy is appropriate. All products
have made significant profits. Because this research
adopts the most conservative investment strategy,
that is, when the trend weakens, stop loss
immediately and complete other trend-turning
signals before entering the market, which can avoid
high-risk situations.
This section uses several exponential moving
averages as the main component indicators of price
information entropy to test the Dow Jones futures.
The emphasis of this study is not on finding
indicators that are 100% profitable, but on the
management of market uncertainty. The liquidity of
investment products is very important, and
sufficient liquidity is needed to accurately judge the
trend. When the price trend is uncertain, the K-line
chart designed in this study is displayed in different
colors, and investors can directly observe whether
they can enter the market for trading. The timing of
entry and exit proposed in this study is entirely
based on the certainty of the trend. In the
verification, strictly observe the timing of entering
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and exiting the investment strategy, and only enter
the market when you are sure of the trend, so that
the investment profit is significant. There are
various methods of technical analysis, which can be
judged according to the trend pattern and can also
be integrated with several technical indicators to
design investment strategies. As long as you can use
these indicators to find out when the trend is
uncertain and avoid investing in the market, you can
reduce losses and increase profit opportunities.
5 Conclusion
This study discusses the technical analysis method
of the price trend of the securities market. Changes
in price trends are mainly due to uncertainty about
the future of the market. The macro investment
climate is crucial to the impact of price trends. Any
kind of political or financial decision-making
change or event can affect the market's investment
sentiment. Changes in securities market prices
usually have a direct response to changes in the
macro investment environment. The three
theoretical bases of technical analysis are that
market prices have fully reflected the status quo,
prices have moved according to a trend, and history
will repeat itself. These three points are also the
research basis of this study, which is based on
observing the market price's response to
macroeconomic events and managing the
uncertainty of price trends to achieve judgments on
price trends. This study uses the information entropy
theory as the basic basis for the fusion of technical
indicators to quantify the uncertainty of prices. The
value of price information entropy is based on the
long-term and short-term exponential moving
average price of the market price as the main
judgment indicator and sets its value in combination
with other indicators mainly based on average price.
Colors are mainly divided into red series and green
series. Based on this K-line color change, investors
are given an easy-to-understand investment
decision-making method.
Validating the method proposed in this study from
past historical data yields positive results. This
research analyzes the changes in the past six
important macro-investment environments and uses
the trend of the Dow Jones futures index to verify.
During this period, the investment strategies of this
study can be very profitable. The index composition
of the price information entropy proposed in this
study can be changed at any time according to
investors' familiarity with technical indicators, to
adapt to the changes in the public's investment
psychology in the future. The emphasis of this study
is not on finding a 100 percent profitable model, but
on building a model that can manage market
uncertainty. Various possibilities for future market
changes are based on this model. The logical
analysis model of price information entropy, from
the verification of this study, can provide investors
closer to realizing wealth freedom.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
-Hsueh-Ying Wu carried out the simulation and the
optimization.
-Jih-Lian Ha has organized and executed the
experiments of Section 4.
-Shu-Wen Lei was responsible for the Statistics.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.114
Hsueh-Ying Wu, Shu-Wen Lei, Jih-Lian Ha
E-ISSN: 2224-2899
1288
Volume 19, 2022
