Econometric Investgation of the Random Walk Hypothesis in the Nigerian Stock Market
Dr. J. N. Mojekwu
Department of Actuarial Science and Insurance
University of Lagos, Nigeria
Tel: 234-80-3306-3363; E-mail: jnmoje@yahoo.com
and
Samson Ogege
Department of Finance
University of Lagos, Lagos
Nigeria
Tel. No: +234-803-6691-036; Email: ogegesamson@yahoo.com
Abstract
In this paper, we evaluate the weak-form efficiency of the Nigerian stock market. Using monthly
data over the period January 1985 to December 2010, econometric methods was used to
investigate stock prices in the context of the Random Walk Hypothesis. However, based on the
empirical results of the paper it appears that there is strong correlation between past prices and
present prices, meaning that investors will be able to earn abnormal profit. Hence, the Nigerian
stock market is not efficient in the weak-form
1
Introduction
The most important role of the Nigerian Capital Market is the mobilization and efficient
allocation of capital for investment purposes.
The market puts in place structures for the
mobilization of savings from numerous surplus economic units for the purposes of the
productive process and thus enhances economic growth and development. However, because of
certain problems inherent in or affecting the market, the performance of the capital market has
always been questioned. Some of these problems include stringent listing conditions especially
in the first and second tier markets. There is also lack of awareness by the investing public,
leading to low activity and insufficient funds in the market arising from the buy and hold attitude
of majority of investors. Other problems are poor economic conditions making companies not to
perform well in terms of product availability and dividend payment. This further leads to loss of
confidence by investors in the institutions operating, and also divestment of funds to some other
areas outside the capital market where appropriate returns are envisaged. In doing this, the
investors shy away from investment in the capital market resulting in the reductions of securities
traded in the market. Since the amount of securities traded could determine the amount of funds
mobilized, a reduction in securities traded thus creates insufficient funds. This affects the
economic growth and development in the country since companies cannot raise sufficient funds
for expansion, modernization and optimum utilization of their operational capacities.
2.0
Theoretical Framework and Literature Review
The paper is anchored mainly on the Efficient Market Hypothesis (EMH). Generally, the
issue for stock market efficiency is categorized into two major areas: operational efficiency and
informational efficiency (Bumol, 1965; Fama, 1970; Jensen, 1978; Copland and Weston, 1983;
Thygerson, 1993; among others). Thus, a stock market that is operationally efficient may not be
informational efficient and vice versa. And to be inefficient, it means that a stock market is either
operationally or informational inefficient. What it also means is that in whichever way the stock
market becomes efficient (either operationally or informational), the economy is better for it.
Fama (1970), Khoury (1983), Olowe (1996, 1997), view capital market efficiency from the roles
the capital markets are expected to play in an economy, which can be classified into three:
i)
Allocation Efficiency: The role of a capital market here is to optimally allocate scarce
savings to productive investments in a way that benefits everyone. Thus, share prices are
determined in away that equates the marginal rates of return or all lenders (savers) and
borrowers.
ii)
Operational Efficiency: A market is said to be operationally efficient if intermediaries
which provide the service of channeling funds from savers to investors do so at the
minimum cost that provides them a fair return for their services.
iii)
Pricing Efficiency: This is a market where prices are used as signals for capital
allocation. Forces of demand and supply set the prices. A market that is price efficient
implies efficiency in the processing of information. The prices of capital assets anytime
are based on the correct evaluation of all information available at that time. Thus, in
finance literature, the focus is more on pricing efficiency, although pricing efficiency
implies in a limited sense operational and allocative efficiency. Formally, the study
defines capital market efficiency as a market where security prices quickly and fully
reflect all available information. If a market is efficient, any/all devices intended to outperform the market will be rendered useless. No scheme devised by any individual
should result in consistently higher returns than those realized on a buy and hold strategy.
In an efficient market, the same rate of return for a given level of risk should be realized
by all investors. The behaviour of any participant or group should not influence the price
of a security in the market.
The Random – Walk Theory
Empirical support for the view that share prices do not behave in a systematic manner but
are more akin to a random walk was initially put forward by Kendall (1950) and has since been
supported by many other studies of share price behaviour (Foley, 1991). Fama (1978) provides a
comprehensive review of the early development of both the theory and empirical work. A
random walk simply means that successive price changes are independent of each other.
According to Mbat (2001) random – walk theory which is the brainchild of academics based on
extensive research states that the future price of stocks are completely independent of past trends.
In other words, there is a statistically independent relationship between future prices of stocks
and their past prices. This is the main characteristic, which is fundamental for market efficiency.
Notable among those who support the efficient market theory are Van Horne and Parker. It
should however be noted that efficient market theory is a weaker form of random – walk theory.
This is because well random walk theory asserts that there is a statistically independent
relationship between past records of price movements and future price movements, the efficient
market theorist have asserted the existence of a weak statistical dependency between the two.
Efficient Market Hypothesis (Emh)
The efficient market hypothesis supplies a theoretical framework, which leads to support
the random walk character of share prices. But what exactly do we means by an “efficient”
market? An efficient market is one where at any one-time prices take into account all available
information. Market participants are assumed to act in an intelligent, self-motivated manner and
to assess and act upon available information about share prices when formulating their buy or
sell decisions. If some available information about a specific share is not acted upon, then an
opportunity will arise for at least some market participants to use that information to their
advantage by buying or selling the share. Thus as market individuals or organizations act upon
this information the price of the share will adjust accordingly until there are further profit
opportunities. This has been referred to as “information arbitrage” efficiency (Tobin, 1958).
Evolution of the Nigerian Stock Market
The Nigerian Stock Exchange (NSE) was formed in September 1960 following the adoption of
the Barback Committee Report of 1959 (Nwankwo (1980), Anyanwu (1993), Olowe (1997),
Onoh (2002), Akpan (2004), and Nzotta (2004). This Committee investigated the ways and
means of promoting a stock market in Nigeria. The Committee recommended the creation of
facilities for transacting in shares, the establishment of rules regulating transfers, the reduction or
elimination of stamp duties on transfer and the elimination of tax deduction at source, including
measures to encourage saving and issue of securities by the government and other organizations
(Nwankwo, 1980). The recommendations made by the committee led to the promulgation of the
Lagos Stock Exchange Act of 1961. The Exchange was thus incorporated in 1961 by a group of
businessmen, the NIDB, the CBN (provide full meaning in first use before abbreviation) and the
Federal Government of Nigeria, and it began operation on June 5, 1961.
Thirteen securities were listed at the Exchange when it began operations in 1961.
These
securities include development stocks issued by the Government, preference share and ordinary
share of various companies. Asalu (1996 in Nzotta (2004) revealed that seven securities of
British companies operating in Nigeria, whose shares were already quoted on the London Stock
Exchange. These companies, to a large extent, influenced activities at the capital market. The
Lagos Stock Exchange later metamorphosed into the Nigerian Stock Exchange following the
Okigbo Financial System Review Committee Report of 1976. This Committee recommended
the establishment of two independent stock exchanges in addition to the Lagos Stock Exchange.
Government rather approved the establishment of the Nigerian Stock Exchange but with branch
exchanges at Kano, Kaduna, Port Harcourt and Onitsha. The Nigerian Stock Exchange operated
as the only stock exchange in Nigeria until 1998 when the government approved the
establishment of the Abuja Stock Exchange, as an independent stock exchange.
The Exchange also provides a means for trading in existing securities, thus, making the securities
marketable.
The ready marketable feature which the stock exchange provides for listed
securities enables investments which were inherently illiquid to become liquid. This, thus,
encourage investors to invest in listed securities.
The ownership of the Nigerian Stock Exchange (NSE) is vested in its members. There are two
types of membership-ordinary and dealing numbers.
An ordinary member (institution or
individual) of the NSE is a member who has, in accordance with the Articles of the exchange,
taken up qualifying shares of the issued share capital of the exchange and has been admitted into
the register of members.
A dealing number (referred to as a stockbroker) is a person or
institution who, in addition to being an ordinary member, is licensed to buy and sell securities on
the trading floor of the exchange on behalf of the investing public (Onoh, 2002).
The Nigerian Stock Exchange is a self-regulatory organization in the capital market. The
Securities and Exchange Commission (SEC) Decree of 1988 provides that the Securities and
Exchange Commission can delegate part of its functions to the stock exchange (Onoh, 2002).
Empirical Literature
In early literature test on weak form efficiency were based on the random walk theory. The
researches prove the weak form efficiency was hinged on two premises:
i.
that share price movements are random.
ii.
There exist no relationship between past price movement and new share price changes.
Osei (2002) studied the asset pricing characteristics of the Ghana stock market as well as the
response of the market to annual company empowerment. The study, which covered a 17- week
event window, looked at the performance of 16 out of the 21 stocks listed in the market. And by
measuring the abnormal returns (AR) including the cumulative abnormal returns of the market,
showed that the Ghana stock market is inefficient in response to earnings announcements.
Ronald and Grandbois (1999) studied the efficiency of the Securities Exchange of Barbados over
the period 1987 to 1997 using the Augmented Dickeg – Fuller and Philips and Perron test and in
both cases found the exchange inefficient. Again Husain and Kevin (1999) tested the weak form
efficiency of the Pakistani equity market using both the Runs test and the serial correlation tests.
They found out that the Pakistani equity market is inefficient. Ahmed (1998) studied the equity
market performance in Bangladesh for the period 1981 to 1997 tested for the Risk – return tradeoff, the Return investments and other with really testing the efficiency of the market but
concluded that the market has characteristics of a well-functioning market. The weak form
efficiency hypothesis has also been tested variously by Fama (1965) for the USA, Dryden (1970)
for the UK, Solnik (1973) for 8 European markets, Conrad and Jutter (1973) for Germany,
Laurence (1986) for Malaysia and Singapore, Malaikah (1990) for Saudi Arabia and Kuwait,
among others. Mixed results are discernible from their studies. The developed markets like
U.S.A. and some European countries are found to be weak form efficient while in general terms
those from the developing or emerging markets do not satisfy the weak form hypothesis.
The results of researcher on the Nigerian Stock Market pose a barge of conflicting signals.
Yacout (1980) tested the correlation weekly price of 21 companies quoted at the Nigerian Stock
Exchange (NSE) between July 1977 and July 1979. The result showed that the price follow a
random walk thus confirming the efficiency of the market. Also Ayadi (1984) tested the price
behaviour of 30 securities quoted at the Nigerian Stock Exchange (NSE) from 1977-1980 using
the Monday closing prices of these shares after adjusting for cash dividends and scripts issues.
He found out that the share price movements followed a random walk. That is to say that the
past prices of shares are of no value in predicting future prices, thus confirming the efficiency of
the market. Again Osisioma (1989) tested 30 securities of the Nigerian Stock Exchange (NSE)
over a 6year period (1981-1985). He had sought to find out the randomness in the movement in
security prices and whether the price changes conform to a stable distribution. The results did
not confirm a stable distribution in the price movements, which suggested efficiency.
Anyanwu (1998) looks at the efficiency of the Nigerian Stock Market from the border angle of
the market’s relationship to the economic growth of the nation. He used indices of stock market
development – liquidity, capitalisation, market size, among other – to construct an aggregate
index of stock market development and related it to the long-run economic growth index,
emphasizing the GDP growth rate. He found out a positive association between the two indexes
and so concluded that the stock market is efficient to the extent that is affects the economic
development of the nation.
Ofobike (1992) showed how accounting infrastructure aids the share pricing and resource
allocation mechanism in the Nigerian economy through the Nigerian Stock Exchange (NSE). He
discussed the relationship which accountancy has with the efficiency and resource allocation
process in the economy through the generation of relevant information. This is supported by the
works of Ball and Brown (1968) and Beaver (1968), which documented a statistical association
between accounting, numbers especially earnings, with the prices of shares. But Ofobike did not
go further to examine empirical the efficiency question of Nigerian Stock Exchange (NSE).
Some practitioners and writer have expressed their view that the Nigerian Stock Market is
inefficient. These include Alice and Anao (1986), Akingbohunde (1990), Odife (1990), Osaze
(1991), and Mobolirin (1993). Since these assertions bother on personal opinion, for they were
not supported by any empirical research.
Akpan (1995) while studying the efficiency of the Nigerian Stock Exchange (NSE) used time
series data of stock market price indices covering the period 1989 to 1992. He described the
efficiency of the market in the part, in terms of thickness of the market he considered the
informational efficiency of the market including the risk implications and found that the Nigerian
Stock Exchange (NSE) is inefficient. First the study worries at the use of seven sub index (or
industrial price indices) data instead of the average share prices for the various industries in the
period under study. On account of this, it seems that there may be informational losses on actual
stock price movements. Again stock returns do not only mean stock price but also include
dividend received. The method used does not capture the impact of dividend paid in the period
of research.
Synthesis of Related Literature
It is evident from the review of literature on the efficient market theory that the studies by
different scholars did not all produce results that were mutually consistent or agreeable. Some
supported the random walk hypothesis while others refuted it. The different studies on efficiency
of the Nigerian stock market showed conflicting results. Some researchers are of the opinion
that the Nigerian stock market is efficient why others looked at the market as inefficient. The
following researchers confirmed the efficiency of the Nigerian stock market, Yacout (1980) who
tested the weekly price correlation of 21 companies between 1977 and 1979. Also Ayadi (1984)
tested the efficiency of the Nigerian stock market using 30 securities quoted in the stock
exchange and found that the market is efficient. In addition, Anyanwu (1998) studied the
efficiency of the Nigerian stock market he looked at the contribution of the market to economic
development and concluded that the market is efficient.
On the other hand, Akpan (1995) who used time series data of the Nigerian stock market from
1989 to 1992 and found that the market is inefficient.
Also writers like Osaze (1991), Mobolirin (1993), Odife (1990), Akingbohunde (1990), are of
the opinion that the Nigerian stock market is inefficient. Ako (1977) studied the efficiency of the
Nigerian stock market from a sample of 45 quoted companies and also found that the market is
inefficient.
However, in this study efforts would be made to overcome the various weaknesses of these
studied discussed above. This is to establish the true position of the Nigerian stock market with
respect to the level of its efficiency.
3. Research Methodology
Based on the efficient market theory, stock prices should indicate random walk overtime. This
implies that no systematic price movements or monopoly profits would be expected as large
number of buyers and sellers seek to make profit by frequent trading on even the smallest piece
of information. Thus, properly anticipated prices will fluctuate randomly (Fama, 1970). The
movement of series overtime can be considered under the following scenario.
LetΔSMPt = price of stock at a given time period t (current price)
ΔSMPt-1 = Price of stock at previous time period
The objective of the study is to establish whether there is a relationship between price of period
(t) (SMPt) and price at previous time period (t-1) (SMPt-1). Thus, the random walk model stocks
price that where SMPt-1 should be independent and identically distributed that is randomly.
Therefore, where SMPt depends on SMPt-1, then there is serial correlation. On the other hand
where SMPt does not depend on SMPt-1, and then the price variables are random and therefore
independent. The functional relationship may then be represented as:
1.
SMPt
=  (SMPt-1) ..............................................1
SMPt =0 + 1 SMPt-1 + µ .................................2
Smpt
=
current period
Smpt-1 =
previous period
o
=
equation constant
1
=
equation parameters
µ
=
stochastic error terms
Stationarity in a time series data is a desirable property for an estimate AR model. This is
because a model whose co-efficients are non-stationary will have a non-declining effects on the
current values of the dependent variable as time progress which is counter-productive,
empirically defective and could lead to spivicus regressions. In this staning, the Augmented
Dickey-fuller(ADF) and Philips-Perron (PP) unit root test are employed to handle the problem of
data stationarity.
Yt=B+αYt-1+Ut..............................................................(3),
Where B and α are parameter of the model and Ut is a white noise disturbance term.
If and only if, -1˂/α/˂1, then α=1, then Yt is a non-stationary series.
ΔY=B+RYt-1+Ut.........................................................(4)
Where R=(α-1) and the null hypothesis can be tested as
Ho: R=0
ΔYt=B+RYt-1+∑pi=1ΔYt-1+Ut......................................(5)
Table 1
Descriptive Statistics
Returns
Mean
0.019151
Meadian
0.017063
Maximum
0.381977
Minimum
-0.306416
Std. Dev.
0.062243
Skewness
0.283577
Kurtosis
11.16230
Jarque-Bera
828.4418
Source: Authors’ computation (2012)
Table 1 above provides the descriptive statistics of stock returns. The indexes have a low means
and standard deviation, and high kurtosis more 3, meaning that it is abnormal.
Table 2
Unit Root Test Summary Results
Variables ADF
Test PP Test First Diff.
First Diff.
Order
of
Integration
SMPt-1
-3.32749
-4.225291
1(1)
SMPt-2
-3.476165
-4.257053
1(1)
SMPt-3
-3.669656
-4.617708
1(1)
SMPt-4
-3.691536
-4.822994
1(1)
SMPt-5
-3.811157
-4.834839
1(1)
SMPt-6
-3.765661
-5.229483
1(1)
SMPt-7
-3.541808
-6.034926
1(1)
SMPt-8
-3.813339
-5.907986
1(1)
SMPt-9
-3.807402
-5.891338
1(1)
SMPt-10
-3.743147
-5.198152
1(1)
SMPt-11
-3.702147
-5.225751
1(1)
SMPt-12
-3.638949
-5.010133
1(1)
Table 3
Correlation Matrix
SMP
T2
SMP
T3
SMP
T4
SMP
T5
SMP
T6
SMP
T7
SMP
T8
SMP
T9
SMP
T10
SMP
T11
0.992
767
0.993
5
0.978
275
0.985
884
0.979
797
0.975
793
0.971
631
0.935
412
0.906
21
0.882
01
0.997
079
0.992
584
0.969
548
0.978
711
0.971
285
0.963
903
0.957
738
0.911
041
0.880
335
0.855
848
1
0.996
442
0.965
193
0.980
939
0.976
758
0.971
254
0.966
161
0.920
969
0.894
958
0.874
47
0.996
442
1
0.976
191
0.992
782
0.990
592
0.986
251
0.981
922
0.946
902
0.925
293
0.907
168
0.965
193
0.976
191
1
0.989
166
0.984
254
0.977
664
0.970
829
0.947
977
0.926
469
0.901
788
Source: Authors’ computation (2012)
0.980
939
0.992
782
0.989
166
1
0.998
524
0.994
488
0.989
714
0.967
33
0.950
301
0.933
163
0.976
758
0.990
592
0.984
254
0.998
524
1
0.998
013
0.994
587
0.975
585
0.961
893
0.947
519
0.971
254
0.986
251
0.977
664
0.994
488
0.998
013
1
0.999
056
0.985
382
0.973
365
0.960
632
0.966
161
0.981
922
0.970
829
0.989
714
0.994
587
0.999
056
1
0.989
642
0.978
581
0.966
884
0.920
969
0.946
902
0.947
977
0.967
33
0.975
585
0.985
382
0.989
642
1
0.996
362
0.988
774
0.894
958
0.925
293
0.926
469
0.950
301
0.961
893
0.973
365
0.978
581
0.996
362
1
0.997
495
0.874
47
0.907
168
0.901
788
0.933
163
0.947
519
0.960
632
0.966
884
0.988
774
0.997
495
1
Table 4
Testing the weak-form of Efficiency in The Nigerian Stock Exchange
Dependent Variable:D( Returns)
Method: Least Squares
Variable
D(Returns)(-1)
D(Returns)(-2)
D(Returns)(-3)
D(Returns)(-4)
D(Returns)(-5)
D(Returns)(-6)
D(Returns)(-7)
D(Returns)(-8)
D(Returns)(-9)
D(Returns)(-10)
D(Returns)(-11)
D(Returns)(-12)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared residual
Log likelihood
Durbin-Watson stat
Coefficient Std. Error
t-Statistic
Prob.
0.186394
0.061427
3.03439
0.0027
0.13117
0.062086
2.112705
0.0356
0.114079
0.062746
1.818115
0.0702
-0.175802
0.06278
-2.800297
0.0055
0.274953
0.063817
4.308459
0
-0.018922
0.066546
-0.284347
0.7764
-0.036191
0.066514
-0.544115
0.5868
-0.001072
0.070322
-0.015248
0.9878
0.164579
0.070537
2.333234
0.0204
0.005896
0.072042
0.081846
0.9348
-0.130548
0.071288
-1.831292
0.0682
0.139125
0.072433
1.920751
0.0559
0.13714
0.10078
0.06065
0.95992
383.907
1.99084
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
F-statistic
Prob(F-statistic)
0.01846
0.06395
-2.7246
-2.5659
3.77123
0.00005
Source: Authors’ computation (2012)
The result in table 3 above revealed that most of the returns are significant
indicating a serial correlation between past returns and present returns. The
D.W statistics of 1.990840 which is very close to 2 showed absent of auto
correlation. Also, the overall F-statistics is significant. But both the Rsquare and the adjusted R-square are very low, it is not important since our
main concern is look for serial correlation
Data was analyzed using correlation matrix estimation technique to found out if present stock
prices are correlated with past stock prices order to ascertain the level of efficiency of the
Nigerian stock market. Also the least square estimation method was used to test for the
significant. The result shows that all the predictors are significant 5 per cent as indicated by the
P-vaule in the table above. The explanability of the model measured by the R2 is very high
which stood at 99 per cent. Also the result of the correlation matrix reveals that there is strong
correlation between present stock prices and past stock prices
However, the result shows the presence of serial correlation regarding past and current stock
prices in the Nigerian stock market. The stock prices tend to display a systematic movement
rather than random movement overtime. This trend indicates imperfection in the market with
great price volatility, which could allow a certain class of investors with superior information to
reap abnormal returns from the market.
5. Conclusions and Recommendations
In the study we have attempted to provide a theoretical and empirical analysis of efficiency of
the Nigerian stock market. Our result indicates that the Nigerian stock market is inefficient in
price determination, which provides the opportunity for a given class of investors to reap
abnormal returns. Some factors were identified, as being responsible for the imperfection in the
market, which is believed, should provide a basis for sound policy actions. We know from the
theory of choice that decision-makers stock the best option out of available alternatives in order
to attain optimal benefits in the same way the availability of information plays a key role for
investors to make optimal decisions on choice of securities in the stock market. This matter is
weighty because in the absence of adequate information, securities in the market may either be
overpriced or under priced. No wonder, Kitchen (1993) notes that risk estimates may be hazy
because of lack of information. Based on the findings of this study, the following policy
recommendations are suggested toward resolving some of the underlying problems of the
Nigerian stock market: Full automation of the market, mass enlightenment and stable
macroeconomic environment to be created
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APPENDIX 1
Year
SMP
SMPt1
SMPt2
SMPt3
SMPT4
SMPt5
SMPt6
SMPt7
1985
111.3
112.2
113.4
115.6
116.5
116.3
117.2
117
1986
134.6
139.7
140.8
146.2
144.2
147.4
150.9
1987
166.9
166.2
161.7
157.5
154.2
196.1
193.4
1988
190.8
191.4
195.5
200.1
199.2
206
1989
239.7
251
256.9
257.5
257.1
1990
343
349.3
356
362
1991
528.7
557
601
1992
794
810.7
1993
1,113.40
1994
1995
SMPt8
SMPt9
SMPt10
SMPt11
116.9
119.1
124.6
127.3
151
155
160.9
163.3
163.8
193
194.9
154.8
193.4
190.9
211.5
217.6
224.1
228.5
231.4
233.6
259.2
269.2
281
279.9
298.4
311.2
325.3
382.3
417.4
445.4
463.6
468.2
480.3
502.6
513.8
625
649
651.8
688
712.1
737.3
757.5
769
783
839.1
844
860.5
870.8
879.7
969.3
1,022.00
1,076.50
1,098.00
1,107.60
1,119.90
1,130.50
1,147.30
1,186.90
1,187.50
1,180.80
1,195.50
1,217.30
1,310.90
1,414.50
1,543.80
1,666.30
1,715.30
1,792.80
1,845.60
1,875.50
1,919.10
1,926.30
1,914.10
1,956.00
2,023.40
2,119.30
2,205.00
2,285.30
2,379.80
2,551.10
2,785.50
3,100.80
3,586.50
4,314.30
4,664.60
4,858.10
5,068.00
5,095.20
5,092.20
1996
5,135.10
5,180.40
5,266.20
5,412.40
5,704.10
5,798.70
5,919.40
6,141.00
6,501.90
6,634.80
6,775.60
6,992.10
1997
7,268.30
7,699.30
8,561.40
8,729.80
8,592.30
8,459.30
8,148.80
7,682.00
7,130.80
6,554.80
6,395.80
6,440.50
1998
6,435.60
6,426.20
6,298.50
6,113.90
6,033.90
5,892.10
5,817.00
5,795.70
5,697.70
5,671.00
5,688.20
5,672.70
1999
5,494.80
5,376.50
5,456.20
5,315.70
5,315.70
5,977.90
4,964.40
4,946.20
4,890.80
5,032.50
5,133.20
5,266.40
2000
5,752.90
5,955.70
5,966.20
5,892.80
6,095.40
6,466.70
6,900.70
7,394.10
7,298.90
7,415.30
7,164.40
8,111.00
2001
8,794.20
9,180.50
9,159.80
9,591.60
10,153.80
10,937.30
10,576.40
10,329.00
10,274.20
11,091.40
11,169.60
10,963.10
2002
10,650.00
10,581.90
11,214.40
11,399.10
11,486.70
12,440.70
12,458.20
12,327.90
11,811.60
11,451.50
11,622.70
12,137.70
2003
13,298.80
13,668.80
13,531.10
13,488.00
14,086.30
14,565.50
13,962.00
15,426.00
16,500.50
18,743.50
19,319.30
20,128.90
2004
22,712.90
24,797.40
22,896.40
25,793.00
27,730.80
28,887.40
27,062.10
23,774.30
22,739.70
23,354.80
23,270.50
23,844.50
2005
23,078.30
21,953.50
20,682.40
21,961.70
21,482.10
21,564.80
21,911.00
22,935.40
24,635.90
25,873.80
24,355.90
24,085.80
2006
23,679.40
23,843.00
23,336.60
23,301.20
24,745.70
26,316.10
27,880.50
33,096.4
32,554.60
32,643.70
32,632.50
33,189.30
2007
36,784.50
40,730.70
43,456.10
47,124.00
49,930.20
51,330.50
53,021.70
50,291.10
50,229.00
50,201.80
54,189.90
57,990.20
2008
54,189.92
65,652.38
63,016.56
59,440.90
58,929.00
55,949.00
53,110.90
47,789.20
46,216.10
36,325.90
33,025.80
31,450.80
2009
21,813.76
23,377.14
19,851.89
21,491.10
29,700.20
26,861.60
25,286.60
23,009.10
22,065.00
21,804.70
21,010.30
20,827.20
2010
22,813.76
23,477.17
20,851.80
22,491.61
39,700.32
27,861.32
26,286.21
24,009.30
23,067.00
23,804.32
23,010.56
20,627.78