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									   A Threshold Analysis of the Mutual Fund Performance and the
          Corporate Governance of its Invested Portfolios
                         Chuang-Min Chao, Chien-Yin Wu
           Graduate Institute of Commerce Automation and Management,
                      National Taipei University of Technology
4F., No.1, Alley 22, Lane 46, Baojian Rd., Jhonghe City, Taipei County 235, Taiwan
                                       R.O.C.
                            silvery1111@yahoo.com.tw


                                      ABSTRACT
     Corporate governance has received great attention among researchers of law and
economics in recent years. After the Asian financial crisis, inadequate corporate
governance system has been concluded as the major cause of the crisis. The
Worldcom and Enron‟s accounting misdeeds have then put the issue under a spotlight.
In Taiwan, a succession of frauds, such as insider trading, misappropriation of funds
and stock price manipulation for their own companies, have happened ever since 1998.
The data used in this study is the 134 open-end equity mutual funds in Taiwan
observed from January, 2005 to December, 2007. Using Hansen‟s (1999) panel
threshold regression model, this study argues that the effect of corporate governance
scores on the mutual fund performance is different in signs or statistical significance
when the mutual fund data is grouped based on their average corporate governance
scores. We expect to find that the effect of corporate governance scores on the mutual
fund performance will be statistically significant or have a larger coefficient only
when the average corporate governance score is above a threshold value.
Key word: Mutual Fund, Corporate Governance, Threshold Analysis, Performance

                                  1. INTRODUCTION
      The concept, corporate governance, has been emerging since the early 1970‟s in
response to the perceived lack of effective board oversight that contributed to the poor
performance problems. In 1997 there were numbers of scandals and corruption within
Asian financial markets that led to severe Asian financial crises. Inadequate corporate
governance system has been concluded the major reason suffering the serious
consequences on the Asian financial crises. The impact arising from Enron and
Corporate America has now put the issue under a spotlight. Therefore, the attention to
enhance corporate governance is being emphasized hence after. Furthermore, OECD,
in its ministerial meeting as of 1998, also pointed out the lack of corporate
governance has been one of the root causes of the recent Asian financial crisis.
      In Taiwan, a succession of frauds, such as insider trading, misappropriation of
funds and stock price manipulation for their own companies, have happened ever
since 1998. The Asian financial crises provide lessons for Taiwan to esteem the
importance of corporate governance. Knowing that inadequate corporate governance
is identified as the key fact that Asian corporations could not build the competition in
world financial markets, Taiwan securities regulator (Financial Supervisory
Commission or FSC) has tried its best to emphasize the importance of advocating
corporate governance to public companies since 1998. It believes that greater
transparency as to corporate governance is needed for enterprises to control risk.
Securities and Futures Institute (SFI), founded as a quasi-public organization for
research, training and protecting investors, together with Taiwan Stock Exchange
(TSE), Taiwan‟s computerized over-the-counter market (known as GreTai Securities
Market, GTSM), and Corporate Governance Association (CGA), introduce the system
of independent directors, audit committee, etc. They also established and
promoted“Corporate Governance Best-Practice Principles for TSEC/GTSM Listed
Companies” in Taiwan. To strengthen the legal base in the field of corporate
governance, Taiwan amended Company Law and Securities & Exchange Act. In the
future, all said organizations will be continue to put their efforts in helping
corporations by adopting best practice as infrastructure tools of corporate governance.
     According to the report of CLSA (2007) that financial reporting standards are
reasonably close to international norms and are improving and the same for
accounting and auditing standards. Major improvements have been made to company
and securities laws, as well as ancillary regulations, over the past two years.
Regulatory enforcement has taken a step forward, especially with regard to corporate
fraud and insider trading. Taiwan is one of the few places in Asia that requires
directors convicted of fraud to resign their positions on boards. The scope of
regulatory and corporate information on regulatory websites is wide and improving.
     Corporate governance can be defined in several ways. Legal academics may
view corporate governance as a vehicle of decision-making and power allocation
among shareholders, managers and directors. Financial economists limit their
attention on persuading or forcing companies to maximize shareholder value and
stakeholders rewards as well. From the financial point of view, a fundamental concern
of corporate governance is to ensure the means by which a firm‟s managers are held
accountable to capital providers for responsibility of managing assets efficiently.
Experts of the OECD have defined corporate governance as the system by which
business corporations are directed and controlled. According to them the corporate
governance structure specifies the distribution of rights and responsibilities among
different participants in the corporation, such as, the Board, managers, shareholders
and other stakeholders, and spells out the rules and procedures for making decisions
on corporate affairs. By doing this, it provides the structure through which the
company objectives are set, and also provides the means of attaining those objectives
and monitoring performance. Generally, corporate governance refers the structure and
processes by which the company are directed and managed and the accountability of
management is stressed, in order to protect shareholders‟ interest through enhancing
corporate performance while taking into account the interests of other stakeholders.
     The financial crisis caused by US Enron bankruptcy at the end of 2001 shocked
the confidence of US stock market. The amounts in a series of subsequent fraudulent
expenditures occurred in larger companies such as Worldcom and Merck are larger.
Investors became aware of the discrepancy in the reliability of financial statements
and the values of companies. As affected by such, not only the financial crisis of
individual company that is known emerges, but also the faith confidence values
crashed. In Taiwan, a series of scandals such Tung Lung Hardware, Central Bills,
Goldsun, and Taichung Commercial Bank occurred in 1998 indicated that alert
function of the financial examination did not work, resulting in that responsible
persons of enterprises utilized their affiliates sand group financial institutions to
manipulate capitals, get excessive loans, oversell assets of their company. These
fraudulent practices not only caused financial crises of the company, but also brought
worries to the financial market. In particular, after Enron case happened, investors
suddenly were aware of the importance and value of information transparency of the
company, in which strict and fair accounting system should play an important role in
information transparency (Sheu and Lin, 2006).
      The issue of corporate governance is currently inviting a widespread discussion
in Taiwan. Partly reflects the issue of the major topic in the global financial market,
partly refers to the importance for individual corporations to raise capital and to
achieve sustainable growth.
      Good corporate governance means interacting between shareholders and the
market in a timely and transparent manner, monitoring of directors business conduct,
establishing guidelines for Board, holding regular Board meetings, and setting
remuneration levels of directors and key staffs. The benefits with establishing good
corporate governance facilitate greater access to international capital markets and help
enterprises to gain a higher premium while seeking outsiders‟ investments. It is
important for corporations to be successful in economic performance and to attract a
long-term, stable, and low-cost investment. Briefly, sound corporate governance is the
key element to culture the long-term development of enterprises. Corporation with
poor governance will severely affect investor confidence and incur the negative
operation. It stands true as to the firm of publicly traded, or privately held, including
family-control.
      As a result, corporation governance is now becoming an urgent need for
countries and enterprises. Considering Taiwan‟s entrance into the World Trade
Organization, it is even demanding for Taiwan to adopt good corporate governance
for catching up international practical standards and face the challenge of global
markets.
      In the past decade, empirical research has shown significant relationships
between various corporate governance features and corporate performance. Until
recently, however, the majority of researchers have focused on specific features of
corporate governance, which makes it difficult to establish an overall relationship
between corporate governance and corporate performance. According to Boehren and
Oedegaard (2003), relating corporate performance to a particular aspect of corporate
governance may not capture the true relationship unless that specific aspect is
controlled for other aspects of governance. This argument inspired several researchers
to construct a single governance index, which is a scorecard that measures a firm's
corporate governance over several dimensions. For example, governance indices have
been constructed for Europe and the United Kingdom (Bauer et al., 2004), Germany
(Drobetz et al., 2004), Russia (Black, 2001), Korea (Black et al., 2006), the United
States (Gompers et al., 2003), Japan (Bauer, Frijns, Otten, and Tourani-Rad, 2008)
and several emerging markets (Klapper and Love, 2004). These indices are used to
determine the relationship between a firm's overall corporate governance score and its
corporate performance. In most cases, these studies find positive and significant
relationships.
      On the other hand, corporate governance plays a key role in achieving a more
transparent and healthy management board. And investors are willing to give higher
valuations to companies that have good governance history. Previous literature also
shows that good corporate governance has contributed to the company's outstanding
P/E ratio and market-to-book ratio. As a result, Daung-Yen Lu, the Chairman of the
GTSM, recently stated that GTSM is going to establish the ISOCG ETF which will be
index-linked to 50 GTSM-listed companies that have good corporate governance
scores. In this way, the investors could reduce monitoring costs while the companies
would have more incentives to improve their corporate governance mechanism.
      Evaluating and predicting mutual fund performance has for long attracted keen
attention of practitioners. At least two reasons can be responsible for such interest:
First, a significant portion of household wealth is managed by mutual funds; Second,
one can observe a steady growth of different funds in the marketplace. Investors buy
actively managed funds hoping they will “beat the market.” Kacperczyk, Sialm, and
Zheng (2006) examined whether some fund managers create value by concentrating
their portfolios in industries, in which they may have informational advantages.
      While the ISOCG ETF is under process, it would be of interest to know whether
the investment on a portfolio of companies with good corporate governance scores
would be profitable or not. Therefore, this study is going to examine whether the
mutual fund performance will be affected by the average corporate governance scores
of its invested companies. More specifically, this study is going to investigate whether
the relationship between mutual fund performance and the corporate governance
scores of its portfolio will fall into discrete classes based on a threshold variable. This
study argues that, when the average corporate governance scores are above or below a
threshold value, the effect of corporate governance scores on the mutual fund
performance may be different in signs or statistical significance.

                                        2. METHODOLOGY
      In this paper, we apply the test advocated by Hansen (1999) to assess the null
hypothesis of a linear regression against a threshold regression (TR) analysis.
2.1 Model
      The observed data are from a balanced panel yit , qit , xit : 1  i  n,1  t  T  .
The subscript i indexes the individual and the subscript t indexes time. The dependent
variable yit is scalar, the threshold variable qit is scalar, and the regressor xit is a
k vector. The structural equation of interest is
                                     
 yit   i  1xit I (qit   )   2 xit I (qit   )  eit                           (1)
where I(‧) is the indicator function.
      The observations are divided into two „regimes' depending on whether the
threshold variable qit is smaller or larger than the threshold γ. The regimes are
distinguished by differing regression slopes, 1 and  2 . For the identification
of 1 and  2 , it is required that the elements of xit are not time invariant. We also
assume that the threshold variable qit is not time invariant. The error eit is assumed
to be independent and identically distributed (iid) with mean zero and finite variance
 2 . The iid assumption excludes lagged dependent variables from xit . It is unclear
how to extend the results to allow for dynamic models and/or heteroskedastic errors.
The analysis is asymptotic with fixed T as n→∞.
2.2 Testing for a threshold
      It is important to determine whether the threshold effect is statistically significant.
The hypothesis of no threshold effect in (1) can be represented by the linear constraint
 H 0 : 1   2
      Under H 0 the threshold γ is not identified, so classical tests have non-standard
distributions. The fixed-effects equations fall in the class of models considered by
Hansen (1996) who suggested a bootstrap to simulate the asymptotic distribution of
the likelihood ratio test.
      Under the null hypothesis of no threshold, the model is
 yit  i  1' xit  eit                                                          (2)
      After the "xed-e!ect transformation is made, we have
 y it  1' x * it  e* it
  *
                                                                                   (3)
                                                                               ~
     The regression parameter 1 is estimated by OLS, yielding estimate 1 ,
            ~                                    ~ '~
residuals eit* and sum of squared errors S0  e * e * . The likelihood ratio test of H 0
is based on
 F1  (S 0  S1 ( )) /  2
                  ˆ     ˆ                                                          (4)
     The asymptotic distribution of F1 is non-standard, and strictly dominates the
   2
 X k distribution. Unfortunately, it appears to depend in general upon moments of the
sample and thus critical values cannot be tabulated. Hansen (1996) shows that a
bootstrap procedure attains the first-order asymptotic distribution, so p-values
constructed from the bootstrap are asymptotically valid. Given the panel nature of the
data we recommend the following implementation of the bootstrap. Treat the
regressors xit and threshold variable qit as given, holding their values fixed in
                                                          ˆ*
repeated bootstrap samples. Take the regression residuals eit , and group them by
individual: ei*  (ei*1 , ei*2 ,...,eiT ) . Treat the sample (ei*1 , ei*2 ,...,eiT ) as the empirical
                   ˆ      ˆ ˆ       ˆ*                              ˆ ˆ           ˆ*
distribution to be used for bootstrapping. Draw (with replacement) a sample of size n
from the empirical distribution and use these errors to create a bootstrap sample under
 H 0 . Repeat this procedure a large number of times and calculate the percentage of
draws for which the simulated statistic exceeds the actual. This is the bootstrap
estimate of the asymptotic p-value for F1 under H 0 . The null of no threshold effect
is rejected if the p-value is smaller than the desired critical value.
2.3 Multiple thresholds
       Model (1) has a single threshold. In some applications there may be multiple
thresholds. For example, the double threshold model takes the form
 yit   i  1xit I (qit   1 )   2 xit I ( 1  qit   2 )   3 xit I ( 2  qit )  eit
                                                                                                    (5)
where the thresholds are ordered so that  1   2 . We will focus on this
double-threshold model since the methods extend in a straightforward manner to
higher-order threshold models.
2.4 Determining number of thresholds
       In the context of model (5), there are either no thresholds, one threshold, or two
thresholds. We introduced F1 as a test of no thresholds against one threshold, and
suggested a bootstrap to approximate the asymptotic p-value. If F1 rejects the null of
no threshold, in the context of model (5) we need a further test to discriminate
between one and two thresholds.
       The minimizing sum of squared errors from the second-stage threshold estimate
is S 2 (ˆ2 ) with variance estimate  2  S 2 ( 2 ) / n(T  1) . Thus an approximate
       r    r
                                                   ˆ      r
                                                             ˆr
likelihood ratio test of one versus two thresholds can be based on the statistic
         S1 ( 1 )  S 2 ( 2 )
              ˆ        r
                           ˆr
 F2                                                                                                  (6)
                  2
                   ˆ
The hypothesis of one threshold is rejected in favor of two thresholds if F2 is large.
       Since the null asymptotic distribution of the likelihood ratio test is nonpivotal we
suggest using a bootstrap procedure to approximate the sampling distribution. To
generate the bootstrap samples, hold the regressors xit and threshold variable qit
fixed in repeated bootstrap samples. The bootstrap errors will be drawn from the
residuals calculated under the alternative hypothesis, so should be the residuals from
LS estimation of model (5). Group the regression residuals eit by individual:      ˆ*
ei*  (ei*1 , ei*2 ,...,eiT ) , and treat the sample (ei*1 , ei*2 ,...,eiT ) an empirical distribution.
ˆ      ˆ ˆ              ˆ*                            ˆ ˆ              ˆ*
Draw (with replacement) error samples from the empirical distribution. Let ei#
denote a generic T x 1 draw. The dependent variable yit should be generated under
the null hypothesis of a single threshold (1), so use the equation
        ˆ                    ˆ
 yit  1xit I (qit   )   2 xit I (qit   )  eit
    #                                                   #
                                                                                               (7)
which depends on the parameter values 1 2                ˆ
                                                    ˆ ,  , and ˆ , the least-squares estimates
from the single threshold model. From the bootstrap sample, the test statistic F2 may
be calculated, and this procedure repeated multiple times to calculate the bootstrap
p-value.

                                       3. RESULT
      The data used in this study is the 134 open-end equity mutual funds in Taiwan
observed from January, 2005 to December, 2007. Using Hansen‟s (1999) panel
threshold regression model, this study argues that the effect of corporate governance
scores on the mutual fund performance is different in signs or statistical significance
when the mutual fund data is grouped based on their average corporate governance
scores. The Sharpe index is chosen as the dependent variable, while the corporate
governance evaluation record is the dependent variable as well as the threshold
variable. Other independent variables include turnover, fund size, duration, and net
value. Fund size is defined as the total value by the end of the month. Turnover is
made up of buy-in turnover and sell-out turnover. Duration is the fund‟s survival
period, which is the number of months that the mutual fund is alive from its issuing
date, and net value is the fund‟s closing price by the end of the month.
      Prior studies document that the quality of firms‟ mandatory and voluntary
disclosures both increase with the quality of firms‟ corporate governance. In the case
of firms‟ mandatory financial reports, better quality governance is associated with a
lower likelihood of financial statement fraud (Beasley, 1996), and less earnings
management (Dechow et al., 1996). In the case of firms‟ voluntary disclosures, better
quality governance is associated with a higher overall level of voluntary disclosure
(Eng and Mak, 2003). Better governance is also associated with both a higher
likelihood that management will issue a voluntary forecast of future earnings and, if
made, a greater level of precision in such forecasts (Ajinkya et al., 2005; Karamanou
and Vafeas, 2005).
      Byard, Li, and Weintrop (2006) added to the growing literature on the impact of
corporate governance quality on firms‟ transparency and disclosure. For example,
research showed that governance affects both the quality of firms‟ public accounting
disclosures (Dechow et al., 1996), and voluntary managerial forecasts (Ajinkya et al.,
2005). While prior studies focused on how governance quality affects firms‟
disclosure practices, they extended this analysis by adopting a user‟s perspective and
focused on a main user group of firms‟ disclosures, financial analysts, and document
that analysts‟ information about firms‟ earnings is indeed positively related with these
firms‟ governance quality.
      Mitton (2002) found that companies that offered higher disclosure quality,
greater transparency, higher outside ownership, and more focused organization
usually experienced better stock price performance. Baek, Kang, and Park (2004)
indicated that firms that had higher disclosure quality suffered less during 1997
Korean financial crisis. Finally, the awareness of the important of corporate
governance by executives may also affect the outcome of corporate governance. Ting
(2006) investigated 207 IPO companies listed in the Taiwan Security Exchange (TSE)
from 1992 to 2002, examined when does corporate governance could add firm‟s value,
and found the positive effects of corporate governance on firm performance, which
approved the existence of corporate governance effect.
     In this study, I take “information disclosure” (get from SFI) to be representative
of corporate governance temporarily. I calculate the better information disclosure ratio
(BIDR), weight average score (WAS) and adopt Lee and Chiu‟s return (Ret), ranking
(Ran), beta coefficient (β) and sharp index (SI) of Taiwan mutual fund performance
commentary and calculate its average in each mutual fund.

Table 1
Mutual Fund
   2005-2007
                    BIDR        WAS          Ret        Ran          β           SI
  Mutual Fund
       1               11/98    4.27705       15.46       71.00      0.9010      0.2921
       2              9/145     2.40808       10.56       94.67      1.0795      0.1666
       3              11/186    2.07931       19.79       41.00      1.1051      0.2788
       4             13/162     2.06664       14.47       71.33      0.9712      0.2420
       5              8/141      1.7713       25.59       26.33      0.8461      0.3494
       6              9/209     1.75235       12.45       81.00      1.2299      0.1598
       7               11/86    1.61632       19.28       37.67      0.8771      0.3367
       8             10/162     1.53276       10.68       97.33      1.0959      0.1487
       9             10/181      1.2492       14.57       70.33      0.9912      0.1862
       10            10/231     1.24645       18.81       70.33      1.1905      0.2239
       11            12/193     1.21514       14.11       72.67      1.1003      0.2216
       12             12/111    1.12057       13.26       81.00      0.9219      0.2610
       13             9/146     1.02284       18.42       85.00      0.9724      0.2817
       14            10/135     0.99926       11.85       90.00      0.9682      0.1572
       15            14/243     0.94898        9.22      112.00      1.0504      0.2257
       16            14/152     0.92646       19.61       34.33      1.0144      0.3264
       17             19/72     0.88148       11.30       97.67      0.9516      0.2468
       18            14/129     0.87446       11.31      101.00      0.9700      0.1898
       19             8/159     0.86161        1.02      159.00      1.0179      0.0495
       20             11/150     0.8541       10.57      101.00      1.0579      0.2472
       21             9/151     0.81042       18.15       54.00      0.9824      0.2740
       22             9/148     0.79754       15.28       67.33      0.9661      0.2106
       23             10/114    0.79533       12.42       86.33      1.1283      0.1611
       24            13/139     0.78383        5.39      129.00      0.9645      0.1255
       25            12/131     0.77595       15.79       61.67      0.8664      0.2847
       26             11/129    0.77433       15.23       68.67      1.1114      0.1754
       27            10/162     0.75848       13.97       75.33      0.8180      0.2801
       28              9/110    0.73021       14.27       73.33      0.9223      0.2857
29   11/131   0.70665   22.89    34.67   0.9345   0.2699
30    8/201    0.6892   18.17    64.67   1.0708   0.2804
31    8/183   0.61743   19.45    39.00   1.0951   0.3180
32    9/144    0.6163   15.99    70.33   0.9774   0.2350
33    7/191   0.59281    4.07   138.00   1.1764   0.0671
34   13/255   0.58448   16.46    96.00   1.0037   0.2992
35   11/117   0.58291   12.75    83.00   0.8629   0.2301
36   11/121   0.56244    8.32   118.67   1.1012   0.1210
37    11/76    0.5541   22.59    60.33   0.8461   0.3622
38    9/161   0.54961   17.46    59.67   1.1973   0.2207
39    9/167   0.54659    4.53   130.67   1.0408   0.1405
40   10/185   0.52986   12.63    81.67   1.0466   0.1903
41   11/191   0.52851   20.52    31.33   1.0431   0.2792
42    9/140   0.52005   17.11    65.67   1.0629   0.1973
43   10/160   0.50801   20.55    44.67   1.2035   0.2514
44   10/122   0.50404   28.94    12.67   0.7473   0.4495
45    7/158   0.46858   12.09    89.67   1.1996   0.1262
46    9/187   0.45324   13.58    74.00   1.0426   0.2333
47    9/134   0.44829   14.42    71.33   0.9731   0.1889
48   10/189   0.44537   20.18    47.00   0.9794   0.2872
49   10/140   0.44049   14.15    72.00   0.9739   0.2225
50    9/188   0.43611   13.58    92.67   0.7656   0.2521
51   11/171   0.43456   12.52    86.33   0.9868   0.2264
52   10/144   0.43089   15.62    64.33   1.0581   0.2499
53   11/133   0.42665   18.75    42.67   0.9286   0.3291
54   11/155   0.42654    7.46   126.00   1.0679   0.1294
55    10/86   0.42538    7.83   114.00   1.0700   0.1482
56   10/161   0.42278   18.17    45.00   0.9650   0.2299
57   10/160   0.42057    5.30   128.33   0.9811   0.1590
58   11/140   0.41094   15.78    63.33   0.9461   0.2346
59   10/148   0.40461    5.49   139.00   0.8982   0.1508
60   10/140   0.40135   15.54    65.33   1.1297   0.2454
61   10/119   0.39564   11.87    90.67   0.8936   0.1596
62    7/225   0.39361   19.05    66.33   1.3570   0.2467
63   12/181    0.3917    4.80   127.00   1.1233   0.0657
64    8/163   0.39083   14.42    70.67   1.3760   0.1379
65    8/162   0.38905   11.23    93.33   1.0957   0.1274
66   12/182    0.3703   12.84    82.67   1.1104   0.1527
67    6/115   0.36621   13.29    79.33   1.1296   0.2154
68    10/151   0.36484   16.69    66.67   0.7282   0.4045
69    10/138   0.36471   15.27    64.00   1.1662   0.2263
70     9/152   0.35507   10.40    98.33   1.0626   0.1955
71    11/167   0.34811   15.82    61.33   0.9605   0.2702
72    11/129   0.34131   13.12    82.67   0.8344   0.2570
73     8/174   0.33134   18.70    49.67   1.0302   0.2030
74    11/103   0.32478    6.46   132.33   0.9484   0.1423
75    13/225   0.30938    9.80   108.67   0.9914   0.1802
76    12/113   0.30077   14.64    71.00   1.0432   0.2540
77    14/125   0.29609   14.01    77.33   0.9721   0.1857
78    10/178   0.29141   14.26    72.67   1.0186   0.2385
79    12/198   0.28913    8.16    91.33   1.0990   0.1527
80    11/165   0.28783   17.19    63.33   1.1670   0.2326
81     7/147    0.2867    9.38   102.67   1.1980   0.1624
82     9/176    0.2814   14.19    73.67   1.0991   0.1029
83    13/217   0.28031   19.73    47.33   0.9963   0.3309
84     8/189    0.2739   16.21    74.33   1.0984   0.2061
85    15/283   0.26822   -5.10   149.33   1.3017   -0.0480
86     7/121   0.26613    3.33   142.33   1.0916   0.0988
87    10/178   0.25476    8.47   113.67   1.1171   0.1323
88     7/206   0.22976    1.65   135.00   1.0264   0.1003
89    12/166   0.22125    9.92   105.33   0.9769   0.1554
90    15/180   0.22076   12.84    87.33   0.8485   0.2777
91     9/134   0.21533   11.89    85.67   1.0928   0.1796
92    11/140   0.21246    8.87   105.00   1.0875   0.1666
93    11/165     0.207   15.67    67.33   0.9829   0.2071
94    15/147   0.19561   15.31    64.67   0.8904   0.3302
95    11/231   0.18662   18.76    46.67   1.0506   0.2772
96    11/139   0.18127   10.79    99.33   0.9740   0.1980
97    12/155   0.17927   14.08    76.67   1.0246   0.2252
98    14/215   0.17151   -3.77   171.33   1.0581   -0.0210
99    10/170   0.17101   14.83    71.33   1.0992   0.2313
100   13/133   0.16806   10.28   100.33   0.9753   0.2494
101   13/166   0.16053   10.41   100.00   0.9463   0.1668
102    8/190   0.15879   12.69    89.67   1.1377   0.1412
103    8/188    0.1497    1.52   153.33   0.9284   0.0049
104   15/143    0.1478   15.86    62.00   0.9067   0.3415
105   11/142    0.1402   14.32    72.00   1.0962   0.1668
106   10/147   0.13682    9.94    96.33   1.0091   0.1442
      107             10/183     0.13138        9.85      104.67       1.0010      0.1683
      108             10/137     0.12729       14.44        70.67      0.8864      0.2475
      109             10/204     0.12267       15.03        79.33      0.9927      0.2164
      110             13/137     0.11836       11.08        97.67      0.9536      0.2101
      111             16/144     0.11298       12.44        88.67      0.8039      0.3122
      112              7/102      0.1099       10.28        98.33      0.9811      0.1090
      113             11/213     0.10773       10.18      106.00       1.0591      0.1480
      114             10/155     0.10661       15.98        63.00      0.8128      0.2900
      115             14/124     0.10583        9.31      108.67       0.8906      0.2364
      116             11/151      0.1003       11.94        90.33      0.8927      0.1963
      117             14/138     0.10002       12.97        81.33      0.9126      0.2761
      118             13/126     0.09722       10.01      103.00       0.9240      0.1894
      119             11/162     0.08692       10.50      103.67       0.9641      0.1756
      120             18/153       0.086       10.36      100.00       0.9098      0.2267
      121             10/184     0.08533        9.66      102.33       0.7824      0.2213
      122             10/186     0.07634       11.03        99.67      1.0136      0.1679
      123             18/153     0.06136       10.66      100.33       0.9244      0.2409
      124              8/128      0.0557        7.35       114.00      0.9684      0.1472
      125              9/115     0.04949        7.93       114.67      0.9060      0.1490
      126              11/97     0.04456       10.87        95.67      0.9960      0.1970
      127             13/112     0.04177       11.57        91.67      0.9812      0.2561
      128              12/75     0.03723       14.10        73.67      1.0401      0.2469
      129            100/481     0.00992        9.50      109.67       0.9639      0.2402


      The “information disclosure” is just more representative of corporate governance.
In this table, I find that the higher of return, the better of ranking and also the higher
of sharp index in research period. But I cannot find the obvious relation between the
better information disclosure ratio, weight average score and mutual fund‟s return.
However, when I add information disclosure weight average score of the top 10 and
the last 10, the former is better than the latter. After I add other variables and use
threshold regression, I would make more explanation to cause the article to be more
complete.

                                  4. CONCLUSION
     We expect to find that the effect of corporate governance scores on the mutual
fund performance will be statistically significant or have a larger coefficient only
when the average corporate governance score is above a threshold value. Our findings
will offer more insights to the regulators who would like to establish the ISOCG ETF,
and are also a good reference for investors when choosing mutual funds.

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