Conduits of Capital

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It is important to recognise that financial centre assessments are discounted according to how recently they were provided—assessments from the current month are given full weighting (1.0) and the weighting decreases with the age of the assessments (to approximately 80% after 12 months and 60% after 18 months). The financial centre assessments and instrumental factors are used to build a predictive model of centre competitiveness using a support vector machine (SVM). The SVM used for the GFCI is PropheZy—Z/Yen’s proprietary system. SVMs are based upon statistical techniques that classify and model complex historic data in order to make predictions of new data. SVMs work well on discrete, categorical data but also handle continuous numerical or time series data. The GFCI is constructed by creating a large data table which contains a row for each respondent / centre combination with the rating each respondent give to each centre together with the score that that centre has for all of the instrumental factors: Respondent Number Centre Number Assessments Instrumental Factor 1 Instrumental Factor 2 Instrumental Factor 3 Instrumental Factor 103 Respondent 1 Centre 1 8 AAA.AA AAA.AA AAA.AA AAA.AA Respondent 1 Centre 2 7 BBB.BB BBB.BB BBB.BB BBB.BB Respondent 1 Centre 3 9 CCC.CC CCC.CC CCC.CC CCC.CC Respondent 1 Centre 4 6 DDD.DD DDD.DD DDD.DD DDD.DD Respondent 1 Centre 5 EEE.EE EEE.EE EEE.EE EEE.EE Respondent 1 Centre 6 FFF.FF FFF.FF FFF.FF FFF.FF Respondent 1 Centre 7 GGG.GG GGG.GG GGG.GG GGG.GG Respondent 1 Centre 83 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Respondent 2 Centre 1 7 AAA.AA AAA.AA AAA.AA AAA.AA Respondent 2 Centre 2 6 BBB.BB BBB.BB BBB.BB BBB.BB Respondent 2 Centre 83 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Respondent 3 Centre 1 6 AAA.AA AAA.AA AAA.AA AAA.AA Respondent 3 Centre 2 6 BBB.BB BBB.BB BBB.BB BBB.BB Respondent 3 Centre 83 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Respondent XX Centre 1 7 AAA.AA AAA.AA AAA.AA AAA.AA Respondent XX Centre 2 9 BBB.BB BBB.BB BBB.BB BBB.BB Respondent XX Centre 83 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ 136 |
The SVM then uses the data to predict values for all the centres that a respondent has not assessed: Respondent Number Centre Number Assessments / Predictions Instrumental Factor 1 Instrumental Factor 2 Instrumental Factor 3 Instrumental Factor 103 Respondent 1 Centre 1 8 AAA.AA AAA.AA AAA.AA AAA.AA Respondent 1 Centre 2 7 BBB.BB BBB.BB BBB.BB BBB.BB Respondent 1 Centre 3 9 CCC.CC CCC.CC CCC.CC CCC.CC Respondent 1 Centre 4 6 DDD.DD DDD.DD DDD.DD DDD.DD Respondent 1 Centre 5 4 EEE.EE EEE.EE EEE.EE EEE.EE Respondent 1 Centre 6 3 FFF.FF FFF.FF FFF.FF FFF.FF Respondent 1 Centre 7 5 GGG.GG GGG.GG GGG.GG GGG.GG Respondent 1 Centre 83 7 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ PropheZy uses the assessments given by Respondent 2 Centre 1 7 AAA.AA AAA.AA AAA.AA AAA.AA a respondent to predict the assessments Respondent 2 Centre 2 6 BBB.BB BBB.BB BBB.BB BBB.BB that they would have given if they were familiar with the other centres Respondent 2 Centre 83 5 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Respondent 3 Centre 1 6 AAA.AA AAA.AA AAA.AA AAA.AA Respondent 3 Centre 2 6 BBB.BB BBB.BB BBB.BB BBB.BB Respondent 3 Centre 83 6 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Respondent XX Centre 1 7 AAA.AA AAA.AA AAA.AA AAA.AA Respondent XX Centre 2 9 BBB.BB BBB.BB BBB.BB BBB.BB Respondent XX Centre 83 8 ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ ZZZ.ZZ Assessments from respondents’ home centres are excluded from the factor assessment model to remove home bias. In effect, the model predicts how respondents would have assessed centres they are not familiar with, by answering questions such as: If an investment banker gives Casablanca and Dubai certain assessments then, based on the relevant data for Casablanca and Dubai, how would that person assess Tel Aviv? or If a pension fund manager gives Istanbul and Tel Aviv a certain assessment then, based on the relevant data for Istanbul, Tel Aviv and Doha, how would that person assess Doha? The SVM used for the GFCI provides information about the confidence with which each specific classification is made and the likelihood of other possible classifications. Conduits of Capital – Onshore Financial Centres and Their Relevance to African Private Equity | 137
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Conduits of Capital Onshore Financi
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TABLE OF CONTENTS I. FOREWORD .....
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predictable, legal systems that res
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works and that everyone loves.” D
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Because of the fragmented nature of
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Industry Views: EMPEA 2015 African
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EXECUTIVE SUMMARY In April 2015, FS
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INTRODUCTION Across the emerging ma
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As a general rule, GPs tend to foll
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“Offshore” refers to a jurisdic
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expressed by GPs). Over 61% of GP r
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“The industry has found a very sa
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INDUSTRY ATTITUDES TOWARD ONSHORE A
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A RANKING OF ONSHORE FUND DOMICILES
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Conduits of Capital - Onshore Finan
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WHAT COULD MAKE ONSHORE SUB-SAHARAN
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“Other” actions include: “rem
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“ STAKEHOLDER VIEWS ON THE RELATI
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APPENDIX 1 - DETAILS ON SURVEY PART
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Expert Perspectives: Onshore Financ
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Experts were asked to make recommen
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Table 2 - Prerequisites for a succe
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3. FINDINGS 3.1 Evolution and Compa
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particular jurisdiction (communicat
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that it is obvious: a well-function
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• The development of an onshore f
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amined the impact that venture capi
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4.1. Where do Private Equity Fund M
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in absolute terms, or relative to t
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average. With respect to regulatory
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For future research, it is importan
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ENDNOTES 1 World Bank Enterprise Su
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33 African Development Bank. Maurit
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71 Unfortunately, the DTAAs lists b
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The financial activities carried in
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The OECD has reviewed over 100 juri
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Importance of Domestic Flows The re
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Rwanda is not included in any of th
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Other possible contenders may emerg
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APPENDIX 1: LISTING OF COUNTRIES IN
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Country / Territory Palau Listed by
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Country Mauritius Morocco 16 Nigeri
Page 85 and 86: Onshore Options for Africa-focussed
Page 87 and 88: Developing skills in these areas re
Page 89 and 90: 2.2 Policy Issues Related to Onshor
Page 91 and 92: • Good accessibility. Good commun
Page 93 and 94: 4. ROLE OF DONORS AND TECHNICAL ASS
Page 95 and 96: Thus, while some PE general partner
Page 97 and 98: management extends to monitoring co
Page 99 and 100: ANNEX 1: CATALOGUE OF FINANCIAL CEN
Page 101 and 102: Dublin Mauritius Dubai Botswana Cap
Page 103 and 104: To some extent, policymakers also n
Page 105 and 106: In administrative financial centres
Page 107 and 108: services industry. However, recent
Page 109 and 110: gains, even if it involves offshore
Page 111 and 112: ather than an onshore centre that i
Page 113 and 114: generally look to London or in some
Page 115 and 116: Onshore Options for Africa-focussed
Page 117 and 118: whether it is ‘Local,’ ‘Trans
Page 119 and 120: are suited to particular financial
Page 121 and 122: In GFCI 16, only three African cent
Page 123 and 124: The ‘stable’ centres in the bot
Page 125 and 126: GFCI 16 Investment Management Centr
Page 127 and 128: Professional service providers tend
Page 129 and 130: Busan and Doha have been advancing
Page 131 and 132: Zambia and Zimbabwe, the report not
Page 133 and 134: Get Connected - Ease Scaling Up In
Page 135: Financial centres are added to the
Page 139 and 140: Instrumental Factor Country or City
Page 141 and 142: Instrumental Factor CA* BU DO DU IS
Page 143 and 144: Open Government The World Justice P
Page 145 and 146: Securitisation TheCityUK http://www
Page 147 and 148: Human Capital Instrumental Factor S
Page 149 and 150: Global City Competitiveness EIU htt
Page 151 and 152: 6.4 Appendix D - Group Respondent P
Page 153 and 154: Dubai Istanbul Conduits of Capital
Page 155 and 156: 6.5 Appendix E - Country Summary Ov
Page 157 and 158: Uganda 26.086 33,800,000 772 Kampal
Page 159 and 160: Page intentionally left blank Condu
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