Description
Assignment: Time Series Analysis using ARDL Technique using (EViews 12 Student Version)
Objective:
The purpose of this assignment is to apply the Autoregressive Distributed Lag (ARDL) technique to analyze time series data for a listed company in Saudi Arabia (KSA). You will investigate the relationship between Return on Equity (ROE) as the dependent variable and selected independent variables, including Close price and two other variables of your choice. The assignment aims to assess your understanding of unit root tests, cointegration, short-term and long-term models, and diagnostic tests.
Instructions:
Data Collection: Choose a KSA-listed company and collect time series data for the dependent variable (ROE), independent variables; Close price and any other relevant variable.
Company: SABIC (data are provided in the Excel file)
Data:
– ROE -Dependent variable
– Closing Price, Gross Margin, Net Margin – Independent variables
– Number of observations: 60 observations
Analysis:
a. Unit Root Test Table (2 Marks): Conduct unit root tests for all the variables in your dataset and provide a table summarizing the results.
b. Cointegration (Bound Test) Table (2 Marks): Apply the bound test for cointegration to check if there is a long-term relationship between ROE and the independent variables. Present the results in a table.
c. Short-term Model (2 Marks): Estimate a short-term ARDL model using appropriate lag lengths. Discuss the model’s results, coefficients, and statistical significance.
d. Long Run Model (2 Marks): Estimate a long-run ARDL model based on the cointegration results. Analyze the long-run relationships between ROE and the independent variables.
e. Diagnostic Test (2 Marks): Perform diagnostic tests to evaluate the goodness-of-fit and the validity of your models. Discuss any potential issues and suggest improvements if necessary.
Notes:
– Prepare a clear and organized report that includes all the components mentioned above.
– Make sure to provide interpretations and explanations for your findings.
– Make sure to avoid Plagiarism as much as possible.
– The report must be in WORD format.
References:
– The reference section must be using APA writing style.
– List all references alphabetically by first author’s last name. If there is more than one reference by the same author, list them in date order (newest to oldest).
Unformatted Attachment Preview
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
FORECASTING THE IMPACT OF SHARE MARKET
DEVELOPMENT INDICATORS ON FIXED CAPITAL
FORMATION AND TRADE
Elhachemi Abdelkader Hacine Gherbi, College of Business Administration,
Imam Abdulrahman Bin Faisal University, Saudi Arabia
ABSTRACT
This paper investigates the long-run impact of share market development in terms of size
and activity on gross fixed capital formation and trade in Saudi Arabia. It also demonstrated the
existence of the causality hypothesis for the period from 1985 to 2018. The study uses AutoRegressive Distributed Lag ARDL analysis to demonstrate that the long-run share market
activity development proxies (value of shares traded and stock transaction) are insignificantly
linked to the economic growth indicators (GFCF and trade). Meanwhile, the share market size
development proxies (market value and number of shares traded) are positively and significantly
linked to the economic growth indicators. It is thus imperative for Saudi policymakers to
establish policies that improve the financial stock market, particularly in terms of market activity
development. We recommend that the entire stock trading market be transformed to achieve
superior exchange performance.
Keywords: Share, Capital, Trade, Value, Causality, ARDL.
INTRODUCTION
The transformation of an underdeveloped economy to a developed one calls for a high
proportion of the population to be inclined towards immaterial well-being, to look ahead and to
be exposed to risks, to be interested in innovation, to persevere and collaborate with others, and
to adhere to specific rules. Solow (1956) proposed a fundamental equation that identifies the
time path of capital accumulation that must be adhered to if all the available labour is to be used.
In this regard, Solow’s growth model displayed diminishing returns to labour and capital. It also
highlights how technological progress results from long-term growth and is exogenously
determined (Todaro, 1997).
In addition to the supply side of the financial sector and its activities, the demand side and
the economic units that may require financial services are covered under the financial system
concept. Several economic units require these financial services. Households accumulating
wealth or carrying earnings over from one period to the next along with firms needing capital for
investment make up the majority of their clients. Hence, a nation’s financial system can be
understood by exploring real investment undertaken by households and how surplus units
accumulate and transfer assets. This can be determined by answering how households and other
surplus units finance firms and deficit units, and how households and firms ensure risk
protection. Moreover, the state plays a part in the financial system not just regarding the supply
and demand of financial services, but also the regulation and oversight of the financial sector.
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Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
THEORETICAL FRAMEWORK
The more robust arguments promulgating the importance of finance in bringing about
economic growth are encompassed within various growth models theories, namely the classical,
neo-classical, and endogenous theory. More specifically, the Harrod-Domar classical growth
model has been proposed for a closed economy and posits that the ratios of national savings and
national capital-output facilitate the growth of the gross national product (GNP). Following this
argument, the expansion of new capital stock via investments occurs when the economies save a
part of their national income. The new income produced via savings will result in economic
growth and development. The Harrod-Domar growth model was expanded by Kennedy (1966) to
be applicable to open economies where savings were given similar implications.
The leading economic development strategies are industrialisation, rapid accumulation of
capital, movement of underemployed workers, and economic planning. Moreover, the limitations
of classical development economics stem from the lack of recognition that economic growth is
just a means to other aims and that it focuses on national product, aggregate income and the total
supply of specific goods as opposed to non-entitlements of individuals and the capabilities such
entitlements produce (Sen, 1983). However, three economic development failure interpretations
have been presented Mukherjee et al. (1994), which are; the failure to use output permitted by
the current technical knowledge, outdated level and character of economic performance related
to some country, and failure to achieve an acceptable level of living in a significant population
proportion.
LITERATURE REVIEW
Financial markets and banking intermediation ensure superior savings mobilisation and
sustainable economic growth. They also assist in the agglomeration of the financial resources of
the economy. They enable risk diversification for individual investment projects and offer savers
increased benefit investments which, in turn, leads to financial savings, as opposed to the
retention of only a few profitable assets. Such an approach supports the development of the
financial system (Goaied & Sassi, 2010).
Following a thorough review of the literature concerning finance and economy, Levine
(1997) categorised several primary functions of a financial market. According to him, financial
systems function to trade, hedge, diversify and pool risk, allocation resources, oversee managers
and take complete corporate control, mobilise savings, and exchange goods and services.
Atje & Jovanovic (1993) and Beck & Levine (2004) examined the impact of stock markets
development on economic growth for 94 countries over the period from 1960-1985 and for 40
countries over a period from 1976-1998, respectively. Both studies found that stock markets
have a positive and significant effect on economic growth. Whereas, Berthelemy & Varoudakis
(1998) investigated the integration between the financial market and real economic sectors in 82
countries for the period from 1960-1990. They indicated three different levels of integration.
First is an underdeveloped financial sector with a low equilibrium and weak growth
performance. Second is an acceptable development of the financial market with higher
equilibrium and normal growth. The third is an unstable equilibrium with no relationship
between financial market development and economic development.
In addition, Ansari (2002) found a positive impact of national income, financial
development and money supply on income growth for the Malaysian economy. Furthermore,
Jalil et al. (2010) found that supply-leading causality exists between finance and growth in
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Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
China. Here policymakers may have emphasised financial system development to support longrun economic growth and stability.
Naceur & Ghazouani (2007) and Mathenge & Nikolaidou (2018) support the theory that no
relationship exists between growth and stock market development and that financial structure
model is not significant in explaining economic growth. Furthermore, Naceur & Ghazouani
(2007) examined the relationship in the MENA region using stock market capitalisation over
GDP as a proxy of equity market development, and GDP as growth. While, Mathenge &
Nikolaidou (2018) examined 14 SSA countries in Sub Saharan Africa over the period from 19802014. They concluded that the underdeveloped financial systems in the MENA region led to
insufficient support for economic growth.
In addition, a significant body of literature dedicated to the financial market development
and economic growth relationship found a lack of consensus on the nature of this relationship
and the causality direction. Patrick & Reimer (1966) proposed three different hypotheses to this
end; supply-leading, demand-following, and bidirectional causality. The fourth and final view
contends the absence of the causality between the two (Graff, 1999; Lucas Jr, 1988).
FUTURE ECONOMIC AND INVESTMENT OBJECTIVES IN KSA BASED ON VISION
2030
In 2017, the Saudi government published a new economic strategy called Vision 2030.
This strategy established several key objectives for national development consisting of deep and
ambitious socio-economic change, long-term budgetary balance, develop a financial sector and
supporting non-oil revenues, local content, and long-term spending strategy based on
programmes and projects. Vision 2030 consisted of three economic objectives, namely
decreasing the unemployment rate from 11.6% to 7%, supporting small and medium-sized
enterprises (SMEs) to increase their contribution to GDP from 20% to 35%, and increasing
female participation from 22% to 30% by 2030.
These objectives will be achieved by supporting small businesses and productive families.
In addition, SMEs are among the main agents of economic growth as they support job creation,
innovation and stimulate exports. The SMEs of the Kingdom are yet to contribute significantly to
the GDP, especially compared to advanced economies. Therefore, the Kingdom decides to strive
to create appropriate employment opportunities for citizens by supporting SME
entrepreneurship, privatisation and investments in new industries.
The primary strategy is supporting the private sector in the Kingdom, especially SMEs to
create more jobs and help them develop their business scale in local and international markets by
promoting sound governance principles. There is a national focus on priority sectors, mobility
and automotive parts, battery technology, industrial and electrical equipment, renewables,
metalworking, industrial digital software and hardware, and robotics.
RESEARCH METHODOLOGY
This study adopted the Autoregressive Distributive Lag (ADRL) model to determine the
long-run impact of share market indicators development on KSA economic growth in term of
gross fixed capital formation and trade using yearly data from 1985 to 2018 gathered from the
World Bank and Saudi Arabian Monetary Agency (SAMA) websites.
This study used Number of Shares Traded (NST) and Market Value of Shares (MVS) as
share market size development. It considered Value of Shares Traded (VST) and Number of
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1528-2651-23-4-609
Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
Transactions (NT) as share market activity development. The specific equation, within which
each variable follows the dependent variable, is presented as follows.
∑
∑
∑
∑
∑
∑
….(01)
∑
∑
∑
∑
∑
∑
….(02)
Upon completing the equation, the Granger-causality test is conducted to calculate the
long- and short-run estimation and the relationships between variables. The corresponding
equation is a composite of short-run and error correction estimation presented as follows.
∑
∑
∑
…..(03)
∑
∑
∑
∑
∑
∑
∑
∑
…(04)
In this study, the ARDL model analysis involved three phases adopted from Kouakou
(2011). First, the variables are determined and calculated using unit root test, then the cointegration relationship among the variables was tested through the bounds test. Lastly, the
causality test of Ganger was determined to examine and determine the relationship between
variables.
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Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
Table 1
UNIT ROOT TESTS
ADF
Variables
L
FD
LNST
-5.96***
LVST
-3.89**
LMVS
-6.74***
LNT
-3.34**
GFCF
-5.66***
TRADE
-4.44***
Note: The null hypothesis represents no stationarity, and the
significance levels of *** represent stationarity at 1% and ** and
represent stationarity at 5%.
The results of the unit root stationarity for the variables are tabulated in Table 1. The table
shows that all variables are stationary at first using the ADF test. As such, the suitable analytical
technique to be utilised is the ARDL model.
The previous step is followed by the examination of the bounds test (refer to Table 2).
From the table, F-statistics values of GFCF and TRADE exceeded the upper bound of 1% in
significance, indicating a significant co-integration relationship between variables at the
significance level of 1%.
Table 2
Bound Test Result
Dependent
Variable
GFCF
F-statistics
I(0)(10%)
I(1)(10%)
I(0) (5%)
I(1)(5%)
I(0) (1%)
I(1) (1%)
6.01***
2.26
3.35
2.62
3.79
3.41
4.68
TRADE
2.75
3.79
3.12
4.25
3.93
5.23
7.37***
Note: * denotes 10%, ** denotes 5% and *** denotes 1% significance levels. The null hypothesis represents no
co-integration. Critical values were adopted form Pesaran et al. (2001).
The bound test results indicated a significant long-run relationship between share market
development and gross fixed capital formation in term of size and activity and sum of exports
and imports of goods and services (TRADE) represented by the following equation.
GFCF=+11.55 LMVS***+0.21LNST-8.48 LNT**+3.35 LVST+0.34 TRADE **
…(05)
TRADE=+29.37LMVS***+4.78 LNST***+2.13 LNT-17.1 LVST***-2.5 GFCF***
…(06)
The diagnostic test results for long-run equilibrium model are presented in Table 3.
Test Statistic
Serial Correlation
Heteroscedasticity
Normality
Table 3
DIAGNOSTIC TEST RESULTS
GFCF Model
Prob
0.62
0.92
0.4
5
TRADE Model
Prob
0.71
0.13
0.78
1528-2651-23-4-609
Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
The diagnostic test results show that the model does not suffer from serial correlation,
normality and heteroscedasticity problems. The lag order for GFCF and TRADE models are
(1.2.1.2.0.2) and (1.1.1.1.1.1), respectively, on the basis of the Akaike information criterion.
The ECM coefficients for both of GFCF and TRADE models are negative and significant
at 1% significant level (-0.69) and (-0.74), respectively. This reinforces the idea of the existence
of the long-run relationship among the variables. For both models, the R2 is approximately 75%
which provides accepted explanatory power.
Table 4 shows the Granger-causality test, providing that share market development
indicators in terms of size and activity (MVS, NST, NT and VST) Granger cause gross fixed
capital formation, while, GFCF does not Granger cause share market development indicators. In
other words, the supply-leading causality hypothesis exists between share market development
indicators and fixed capital formation in KSA.
Furthermore, the table shows that no Granger-causality exists between share market
development indicators in terms of size and activity (MVS, NST, NT and VST) and trade
indicator as a proxy of growth. Moreover, only trade granger causes fixed capital formation in
KSA. As such, a unidirectional hypothesis exists between the indicators.
Variables
GFCF
TRADE
LMVS
LNST
LNT
Table 4
GRANGER-CAUSALITY HYPOTHESIS RESULTS
GFCF
TRADE
Uni-directional (TRADE cause GFCF)
Uni-directional (TRADE cause GFCF)
Supply Leading
Bi-Directional
Supply Leading
Bi-Directional
Supply Leading
Bi-Directional
The results in equations 05 and 06 show that share market activity development indicators
have an insignificant impact on fixed capital formation and trade, which is contrary to the theory.
Vaithilingam et al. (2006) argued that the financial system forms a crucial part of the economy.
A weak financial system would jeopardise long-term economic sustainability and ultimately lead
to a financial crisis. Furthermore, Romer (1986) believes that the financial system functions
influence steady-state growth through the changes in the technology innovation rate. Levine
(1997) stated that an increasing volume of the body of literature had urged sceptics to consider
the notion that the development of financial markets and institutions is a critical and
interconnected part of the process of growth, as opposed to limiting their beliefs to the view that
the financial system merely reacts passively to economic growth and industrialisation. Whereas,
the results in equations 05 and 06 show that share market size development indicators have a
significant positive impact on fixed capital formation and trade, which aligns with theory.
Lucas Jr (1988) and Rebelo (1992) state that there are two streams through which every
financial function may affect growth in the economy. These streams are capital accumulation and
technological innovation. In other words, steady-state growth is influenced by the financial
system functions via the rate of capital formation. Capital formation is influenced by the
financial system through changes in the rate of savings or the reallocation of savings among
differing capital generating technologies.
In addition, according to Harrod et al. (1966), the expansion of new capital stock via
investments occurs when the economies save a part of their national income. The new income
produced via savings will result in economic growth and development. Moreover, Goaied &
6
1528-2651-23-4-609
Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
Sassi (2010) state that financial markets ensure superior savings mobilisation and sustainable
economic growth, as well as assists in the agglomeration of the financial resources of the
economy. It also enables the conduct of risk diversification to individual investment projects and
offers savers increased benefit investments which, in turn, lead to financial savings, as opposed
to the retention of only a few profitable assets.
It is noticeable from the above long-run estimated results that KSA financial market is
suffering from high speculations capital volume. This led to a negative and insignificant impact
on capital accumulation and technological innovation. Moreover, the results show that financial
market development in terms of size based on supporting foreigner consumption product rather
than domestic products, which led to a decrease in the value of the Saudi riyal. Moreover, KSA
share market indicators show that Saudi’s economy is dependent on external markets for its
consumption as opposed to producing products for its consumption.
CONCLUSION
Based on the findings, it is thus imperative for Saudi policymakers to establish policies that
bring improvements to the share market, particularly in terms of secondary market development.
We recommend that the entire stock trading market be transformed to achieve superior exchange
performance.
Several measures need to be established to boost share market development in terms of
capital and liquidity. Such measures may include the enhancement of second-tier stock markets,
the launching of online trading, minimising the period of settlement, adding more branches,
stock market integration in other markets (particularly in the context of emerging nations) and
the introduction of more instruments into stock exchanges which are aligned with the people’s
demands and needs such as Islamic financial products which are aligned with shariah
compliance. These will gradually cultivate economic growth, prevent internal financial crisis,
and contribute towards the management of the global financial crisis.
Further, serious local investors should be given the opportunity to participate in the market
and take part in formulating policy. Policies that contribute to active participation, specifically by
local real investors, will enhance liquidity and attract foreign investors. Such policies may
include tax holidays, relaxation of tax withholding, capital gain tax, and the establishment of a
high degree of transparency in order to attract investors. Such transparency may be in the form of
integrating periodic review of listed companies’ reports and the sanctioning of firms that commit
errors. Policymakers should also review the legal and institutional arrangements which
contribute towards financial repression in order to hinder financial sector’s efficiency and restrict
speculation.
When the Saudi financial sector was badly affected in the past few years, rather than
dealing with the situation via the international financial system, it dealt with international
brokers, black market traders, brokers and currency traders. The impact of such activities
affected not only the government of KSA but also its private sector owing to the country’s weak
financial institutions. This weakness resulted in the bankruptcy of such institutions, the shutting
down of some and the merging of others.
Another justification for the outcome of the study is that one of the major functions of the
stock market is risk management as implemented by the facilitation of risk pooling and risk
allocation by households and firms (Merton & Bodie, 1995). In this regard, financial
malpractices lead to the financial crisis. Ahmed (2009) shed light that the mismanagement of
risks at institutional, organisational and production levels precipitated the 2008 financial crisis.
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Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Journal of Entrepreneurship Education
Volume 23, Issue 4, 2020
Risk can be categorised into inherent and residual risk, where the former refers to risks that exist
prior to taking controls, and the latter refers to the exposure following the implementation of
certain corrective measures/effective controls. Risk management tools would be to minimise
inherent risks and keep them at manageable levels in order to satisfy stakeholders’ risk appetite.
This will, in turn, boost their engagement in growth-developing and wealth-generating economic
activities.
Several approached can be adopted by policymakers to bring about such developments.
These include the creation of real business, a supportive economic environment and review of
the application of the financial market regulation that adheres to the aim of realising discipline in
applying governance, to enhance and develop understanding and to manage risks.
REFERENCES
Ahmed, H. (2009). Financial crisis, risks and lessons for Islamic finance. ISRA International Journal of Islamic
Finance, 1(1), 7-32.
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an econometric study. Journal of Asian Economics, 13(1), 72-93.
Atje, R., & Jovanovic, B. (1993). Stock markets and development. European Economic Review, 37(2), 632-640.
Beck, T., & Levine, R. (2004). Stock markets, banks, and growth: Panel evidence. Journal of Banking & Finance,
28(3), 423-442.
Berthelemy, J.C., & Varoudakis, A. (1998). Financial development, financial reforms and growth: A panel data
approach. Rèvue Economique, 49(1), 195-206.
Goaied, M., & Sassi, S. (2010). Financial development and economic growth in the MENA region: What about
Islamic banking development. Institut des Hautes Etudes Commerciales, Carthage, 1-23.
Graff, M. (1999). Financial Development and Economic Growth-A New Empirical Analysis. Dresden Discussion
Papers in Economics, 5, 99.
Harrod, R.F., Friedman, M., & Jacobson, A. (1966). A Monetary History of the United States 1867-1960. JSTOR.
Jalil, A., Feridun, M., & Ma, Y. (2010). Finance-growth nexus in China revisited: New evidence from principal
components and ARDL bounds tests. International Review of Economics & Finance, 19(2), 189-195.
Kennedy, C. (1966). Samuelson on induced innovation. The Review of Economics and Statistics, 442-444.
Kouakou, A.K. (2011). Economic growth and electricity consumption in Cote d’Ivoire: Evidence from time series
analysis. Energy Policy, 39 (6), 3638-3644.
Levine, R. (1997). Financial development and economic growth: views and agenda. Journal of economic literature,
35(2), 688-726.
Lucas Jr, R.E. (1988). On the mechanics of economic development. Journal of monetary economics, 22(1), 3-42.
Mathenge, N., & Nikolaidou, E. (2018). Financial structure and economic growth: Evidence from Sub-Saharan
Africa. Economic Research Southern Africa, 732.
Merton, R.C., & Bodie, Z. (1995). A conceptual framework for analyzing the financial environment. The global
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Mukherjee, B., Heberlein, L.T., & Levitt, K.N. (1994). Network intrusion detection. IEEE network, 8(3), 26-41.
Naceur, S.B., & Ghazouani, S. (2007). Stock markets, banks, and economic growth: Empirical evidence from the
MENA region. Research in International Business and Finance, 21(2), 297-315.
Patrick, R., & Reimer, C.W. (1966). The diatoms of the United States. Academy of Natural Sciences
Pesaran, M.H., Shin, Y., & Smith, R.J. (2001). Bounds testing approaches to the analysis of level
relationships. Journal of Applied Econometrics, 16(3), 289-326.
Rebelo, S. (1992). Inflation in fixed exchange rate regimes: The recent Portuguese experience. IIES.
Romer, P.M. (1986). Increasing returns and long-run growth. Journal of political economy, 94(5), 1002-1037.
Sen, A. (1983). Development: Which way now? The Economic Journal, 93(372), 745-76
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Todaro, M. (1997). Economic development beyond regulation: the informal economy in Latin America. 6th Edition,
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Citation Information: Gherbi, E.A.H. (2020). Forecasting the impact of share market development indicators on fixed capital formation
and trade. Journal of Entrepreneurship Education, 23(4).
Price History: 2020-SA
Date
Price CVol
Change % Change % Return Total Return (Gross) Cumulative Return %
11/08/23 132.20 146843
-0.80
-0.60
-0.60
143.76
-6.28
11/07/23 133.00 244686
-1.40
-1.04
-1.04
144.63
-5.71
11/06/23 134.40 408822
-0.60
-0.44
0.60
146.16
-4.72
11/05/23 135.00 356683
1.40
1.05
145.29
-5.29
11/02/23 133.60 220500
-0.20
-0.15
-0.15
145.29
-5.29
11/01/23 133.80 447708
145.50
-5.15
10/31/23 133.80 547915
5.00
3.88
3.88
145.50
-5.15
10/30/23 128.80 398527
1.40
1.10
-0.46
140.07
-8.69
10/29/23 127.40 143767
-2.00
-1.55
140.72
-8.27
10/26/23 129.40 247622
-1.60
-1.22
-1.22
140.72
-8.27
10/25/23 131.00 261660
2.60
2.02
2.02
142.46
-7.13
10/24/23 128.40 429356
1.40
1.10
1.10
139.63
-8.98
10/23/23 127.00 404299
-4.40
-3.35
-4.51
138.11
-9.97
10/22/23 131.40 158027
-1.60
-1.20
144.63
-5.71
10/19/23 133.00 257721
-0.40
-0.30
-0.30
144.63
-5.71
10/18/23 133.40 862715
-2.20
-1.62
-1.62
145.07
-5.43
10/17/23 135.60 307327
-0.20
-0.15
-0.15
147.46
-3.87
10/16/23 135.80 432411
1.80
1.34
1.34
147.68
-3.73
10/15/23 134.00 105472
145.72
-5.01
10/12/23 134.00 352395
1.20
0.90
0.90
145.72
-5.01
10/11/23 132.80 448913
0.20
0.15
0.15
144.42
-5.86
10/10/23 132.60 286146
1.00
0.76
0.76
144.20
-6.00
10/09/23 131.60 382873
1.40
1.08
-0.30
143.11
-6.71
10/08/23 130.20 393230
-1.80
-1.36
143.55
-6.42
10/05/23 132.00 405095
-0.20
-0.15
-0.15
143.55
-6.42
10/04/23 132.20 238230
-2.20
-1.64
-1.64
143.76
-6.28
10/03/23 134.40 217801
-1.60
-1.18
-1.18
146.16
-4.72
10/02/23 136.00 351220
1.20
0.89
2.26
147.90
-3.59
10/01/23 134.80 402585
1.80
1.35
144.63
-5.71
09/28/23 133.00 471223
-3.00
-2.21
-2.21
144.63
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09/27/23 136.00 246754
3.00
2.26
2.26
147.90
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09/26/23 133.00 459182
1.00
0.76
0.76
144.63
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09/25/23 132.00 583859
-4.80
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-3.51
143.55
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09/21/23 136.80 175393
-0.80
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148.77
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09/20/23 137.60 156228
149.64
-2.45
09/19/23 137.60 394263
149.64
-2.45
09/18/23 137.60 299993
-1.20
-0.86
-1.85
149.64
-2.45
09/17/23 138.80 223561
-1.40
-1.00
152.46
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09/14/23 140.20 713569
1.20
0.86
0.86
152.46
-0.61
09/13/23 139.00 189998
-0.80
-0.57
-0.57
151.16
-1.46
09/12/23 139.80 307002
-0.60
-0.43
-0.43
152.03
-0.89
09/11/23
09/10/23
09/07/23
09/06/23
09/05/23
09/04/23
09/03/23
08/31/23
08/30/23
08/29/23
08/28/23
08/27/23
08/24/23
08/23/23
08/22/23
08/21/23
08/20/23
08/17/23
08/16/23
08/15/23
08/14/23
08/13/23
08/10/23
08/09/23
08/08/23
08/07/23
08/06/23
08/03/23
08/02/23
08/01/23
07/31/23
07/30/23
07/27/23
07/26/23
07/25/23
07/24/23
07/23/23
07/20/23
07/19/23
07/18/23
07/17/23
07/16/23
07/13/23
07/12/23
140.40
139.00
139.60
140.00
137.80
136.40
137.20
137.60
139.80
139.60
138.20
136.00
135.80
136.00
136.60
137.80
137.20
138.00
138.80
139.80
139.60
141.20
138.80
136.60
134.60
135.40
135.00
137.60
136.20
142.20
144.20
142.00
142.80
140.00
134.00
131.60
131.60
132.00
129.40
129.00
129.20
131.40
132.20
131.00
296138
348392
361167
1152759
265912
199475
318136
680702
429890
541532
380682
118399
389141
300095
331081
428628
172325
493889
489910
315294
621698
809579
663756
562022
413046
688879
471171
749433
1342565
1408438
966139
1338753
2328384
2931301
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562082
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1390001
348444
421870
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764192
745307
664672
1.40
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2.20
1.40
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0.20
1.40
2.20
0.20
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0.60
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0.20
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2.40
2.20
2.00
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1.40
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2.20
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2.80
6.00
2.40
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1.60
1.03
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0.14
1.01
1.62
0.15
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0.14
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1.49
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0.30
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1.03
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1.55
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2.00
4.48
1.82
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0.40
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1.20
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2.01
0.31
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1.61
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0.98
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4.48
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0.92
152.68
151.81
151.81
152.25
149.85
148.33
149.64
149.64
152.03
151.81
150.29
147.68
147.68
147.90
148.55
149.85
150.07
150.07
150.94
152.03
151.81
150.94
150.94
148.55
146.37
147.24
149.64
149.64
148.11
154.64
156.81
155.29
155.29
152.25
145.72
143.11
143.55
143.55
140.72
140.28
140.50
140.50
140.50
139.23
-0.47
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-8.41
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07/11/23
07/10/23
07/09/23
07/06/23
07/05/23
07/04/23
07/03/23
07/02/23
06/22/23
06/21/23
06/20/23
06/19/23
06/18/23
06/15/23
06/14/23
06/13/23
06/12/23
06/11/23
06/08/23
06/07/23
06/06/23
06/05/23
06/04/23
06/01/23
05/31/23
05/30/23
05/29/23
05/28/23
05/25/23
05/24/23
05/23/23
05/22/23
05/21/23
05/18/23
05/17/23
05/16/23
05/15/23
05/14/23
05/11/23
05/10/23
05/09/23
05/08/23
05/07/23
05/04/23
131.00 604252
131.20 570294
131.60 266453
131.20 509814
131.60 770175
130.80 308679
130.60 524369
130.40 424846
129.60 415903
129.00 240620
128.40 389221
129.00 417769
130.20 517134
130.40 982557
129.60 553739
129.60 571687
130.40 926019
129.20 513179
128.40 436306
127.60 490493
127.20 802860
128.00 1068163
125.80 425148
124.00 768112
125.00 2398294
126.80 915048
128.80 406122
127.80 503781
128.60 389270
128.00 809808
129.20 518215
129.60 480762
130.20 332525
129.80 580038
130.60 393686
130.00 836141
131.40 679864
132.80 773374
132.40 1089267
131.40 781371
129.80 779583
130.40 877163
131.80 733292
130.20 502645
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0.40
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0.80
0.20
0.20
0.80
0.60
0.60
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0.80
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0.30
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0.47
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1.20
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0.40
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2.20
1.80
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1.00
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0.40
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0.40
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0.40
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1.75
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0.78
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0.31
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0.30
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0.76
1.23
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0.15
0.31
139.23
139.44
139.44
139.44
139.86
139.01
138.80
137.7
