Download ФИТАТ U.U. Umbetov1, A.N. Murzakhmetov2 1, 2 M.Kh. Dulaty

ФИТАТ U.U. Umbetov1, A.N. Murzakhmetov2
1, 2
M.Kh. Dulaty Taraz state university, Taraz, Kazakhstan,
[email protected], [email protected]
UDC 004.891.2
MODELING THE INFLUENCE OF INTERNET NEWS ON THE DECISION-MAKING
PROCESS OF INVESTORS
Abstract. At the present time stock market plays a very important role in economy of many
countries. Development of computer technology makes the participation in the market more accessible
and therefore increasing interest in operations with securities from investors. Market prices are formed
considering different factors. One of them is the news flows coming from the different sources. In this
paper, we explore the impact of information on decision-making of investors and the market dynamics in
general, because in many respects this aspect determines the behavior of the individual participants and
choice of analysis tools.
Keywords: internet news, news influence, investor, text mining, stock market, information
diffusion, information systems.
Introduction. A number of researchers have documented the market response to various
recommendations from the mass media over different periods and summarized two main hypotheses for
the underlying mechanisms: price pressure hypothesis (PPH) and information diffusion hypothesis (IDH).
However, few studies have investigated the underlying mechanisms of the market reaction to Internet
news [1].
With coming of new information, the market conditions are changing. Is known that one or another
interpretation of incoming information is defines further solutions of expert. They affect to adoption for
investors decision and is considered an important source of data that can be used to make financial
forecasting. In recent times information from news articles became part of the financial forecasting
systems. Using the news articles and their forecasting on market, widely been studied. However, research
in this area are still actual. We will explore the internet news articles related to the stock market, having
different degrees of importance and can improve the performance of financial forecasting and support for
decision-making of investors and traders. One of the main task of the investors is to involves extracting
profits by investing to different financial instruments.
Investment Portfolio Management - an investment of certain money resources at present time to
obtain the maximum income in the future with a certain level of risk. The investment portfolio is
purposefully formed in accordance with a particular investment strategy set of investments in investment
properties. The main objective of such a strategy - to ensure the implementation of developed investment
policy by the selection of the most efficient and reliable investments [2].
Literature review.. To the best of our knowledge, Wysocki (1999) firstly addresses this issue by
examining the cross-sectional and time-series determinants of posting a volume of Yahoo! message
boards, finding that the overnight posting volume can predict changes in the next day stock trading
volume and stock returns. Contrary to these anecdotal findings, Tumarkin and Whitelaw (2001) further
investigate the relations between message board activity and stock market behavior on Raging Bull,
finding that the message board activity has no predictive power for industry-adjusted returns or abnormal
trading volume. Da et al. (2011) use the search frequency in Google as the direct measure of investor
attention and find that this proxy can predict stock prices in the next 2 weeks. Zhang et al. (2014) employ
the number of news appeared in Baidu News as the proxy for information arrival and find that this kind of
Internet information can explain the volatility persistence in the framework of mixture of distribution
hypothesis (MDH). Dergiades et al. (2015) show that the key phrases related to the Greek debt crisis in
Google Trends, Twitter and Facebook can provide significant short-run information primarily for the
Greek–German government bond yield differential. The abovementioned studies belong to the
quantitative measurements of Internet information, which has gained popularity and is used in empirical
studies, e.g., in Hanke and Hauser (2008); Vlastakis and Markellos (2012); Aouadi et al. (2013) and
Zhang et al. (2013a, 2013b), among others. Another stream of literature focuses on the relations between
the tonality or sentiment of Internet information content (positive or negative) and the trends in stock
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prices (upward or downward). Antweiler and Frank (2004) find that the information content of the
postings on Yahoo! Finance and Raging Bull can predict market volatility. Das and Chen (2007) employ
the voting algorithm to extract sentiment from the message board and document the relations between
extracted sentiment and trading volume. Bollen et al. (2011) derive the collective mood from Twitter
feeds and find that the mood index is correlated to the value of the Dow Jones Industrial Average (DJIA)
over time. Kim and Kim (2014) use large dataset of more than 32 million messages in Yahoo! Finance to
construct a proxy for investor sentiment and find no correlation between the sentiment and future stock
returns. Siganos et al. (2014) provide international evidence that the Facebook's Gross National
Happiness Index has positive contemporaneous relations to stock returns. All these studies have proved
that the Internet has changed the way in which information is diffused and reexamined some financial
theories with Internet-based new proxies [1].
Theoretical part. The investment process is a mechanism of interaction between the market
participants offering investments with members that represent the demand for these investments.
Preferences of the investor define the strategy of stock market game.
For order to take a decision on the inclusion of securities in the portfolio or for its exclusion, the
investor must be able to predict motion of stock indices: rise and fall courses. Based on its assessment of
the changes in rates or other securities, the investor makes a decision by following the certain strategies.
There are several basic strategies of the game on a stock exchange [3]:
Investment Strategy. Defines potential growth stocks, for example, estimates of location by using
fundamental analysis. Formed portfolio of these shares with the aim to keep them for a long time and
make a profit at the expense of dividends and market value growth. The portfolio sometimes can be
revised in the event of changed circumstances or just on a regular basis, such as once a quarter.
Following the trend. The essence of this strategy is the using of the trend power. It is supposed to
enter the position when the trend is formed or already formed, and exit when the trend seems to be faint
or obvious correction started. A feature of this strategy is to buy growing shares, which is not always
psychologically comfortable. The principle of the trend game, "buy expensive to sell more expensive."
The counter-trend strategy. Often the meaning of speculation is meant by principle "buy cheaper,
sell more expensive." Shares bought at the drop in order to sell when the price will rise. This approach
can lead to success if the lateral trend (when the price remains relatively stable), lasting a long time.
However, with slow growth or slow decline of the index, this strategy often leads to losses.
Patterns. A trader registers the presence of some price patterns called "head and shoulders",
"double top", etc. and connects the changing course or preserve the appearance of such figures.
News game. In fact is a simplified view of fundamental analysis, "bad" and "good" news lead
respectively to the movement of the index up or down. It can be follow the news tape and try to react
quickly to changes in the news background around this or that company. Fundamental analysis
procedures are laborious, require the collection, compilation and processing big information contained in
various sources and documents [4]. Are known some projects were automate the analysis of news
publications in the media and analysis of financial time series coming from the financial markets, and
establishing correlations between "bad" and "good" news and the increase or decrease in share prices. All
these projects are based on Text Mining technology.
Solution. In this paper we will consider strategy "News Game." News have complex nature. First,
every news by classifier system may be associated with several subjects. At the same time, each subject is
associated with various classifiers with different coefficients. Thus, the model is implemented in which
the events can only partially affect the interests of some investors. Let 𝐾 ∈ 𝐴 - the company issuing the
shares. It is associated with a plurality of classifiers 𝜑 with coefficients𝜑1 … 𝜑𝑘 ,, where k - a natural
number, 𝜑 – real number. With these provisions, we have that 𝑚 < 𝑛 and 𝑚 ≤ 𝑘. Let these events have
the power 𝜀1 … 𝜀𝑚 . If 𝑚 < 𝑘, then for all classifiers 𝜑 ∉ 𝜀 we believe that 𝜀 = 0. Then, a new series of
events will be in the form 𝜀1 … 𝜀𝑘 , and the overall impact of the news on the company can be calculated
by the formula [5]:
𝑘
𝑁𝐾𝑖′
= ∑(𝜀𝑗 𝜑𝑗 )
𝑗=0
(1)
Secondly, each investor can differently interpret incoming news. For example, it can not to
consider some classifiers or to exaggerate the role of other classifiers and its formula is 𝑁𝐾𝑖′ will be look
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bit differently. Some investors may not follow the news, and only operate on technical indicators. Also,
many investors consider the effect of accumulation and attenuation. Let say that in 𝑖 iteration investor
wants to aggregate news background for the K company for the last h iteration. News background for
(𝑖−𝑗)′
each iteration was irrelevant𝑁𝐾
… 𝑁𝐾𝑖′ . Then the coefficients attenuation L for the last h iteration will
be calculated according by the formula:
ℒ𝑗 = 𝐸𝑥𝑝(−𝜇 ∗ (𝑗 − ℎ) ),
(Error!
Reference
source not
found.)
where the parameter is μ characterizes the rate of news decay. Total K Company news background
in the i-th iteration will be equal to the amount of news in the previous iteration multiplied by the
attenuation coefficients ℒℎ :
ℎ
𝑄𝐾𝑖′
𝑗′
= ∑ (𝑁𝐾 ∗ 𝐸𝑥𝑝(−𝜇 ∗ (𝑗 − ℎ) ))
(3)
𝑗=𝑖−ℎ
For the experiments use the software package "FIMAS". This program is quite simple for users and
has many libraries. Figure 1 shows the dynamics of the world of news and its impact on the stock price
quotes of some companies.
a)
b)
Figure 1 – Diffusion of news
a) dynamics of word news b) news background for several companies
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a)
b)
Figure 2 – Graphs of changes in stock prices
a) prices for several companies shares b) share price
Conclusions. Using the internet news for research asset pricing in the stock market are interested
experts from many fields, financial investors, computer scientists and practitioners. Positive (negative)
news have significant positive (negative) effects on stock returns in all cases. Their volatility has a
significant impact on both stock returns and volatility; specifically, an increase in news volatility is
always associated with a decrease in stock returns. Markets are particularly responsive to negative news,
and the reaction is effects on one or another processes. The price pressure hypothesis (PPH) poses that the
Internet news creates temporary buying pressure in the highlighted stocks and this buying pressure causes
the observed abnormal returns, which will reverse to their fundamental value in a relatively short period.
The information diffusion hypothesis (IDH) poses that the Internet news reveals relevant information
about the fundamentals and thus the observed abnormal returns will not reverse to their fundamental
value in a relatively short period. This paper can be used to describe the behavior of investors in the stock
market.
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