The implementation of International Accounting Standard 32 Financial Instruments: Disclosure and Presentation (lAS 32), International Accounting Standard 39 Financial Instruments: Recognition and Measurement (lAS 39) and International Financial Reporting Standard 7 Financial Instruments: Disclosures (IFRS 7) by developing countries has been met with mixed reactions largely due to the extensive use of the fair value concept by the three accounting standards. The use of the fair value concept in developing countries has proved to be a significant challenge due to either a Jack of formal capital market systems or very thinly traded capital markets. This study investigates the obstacles to determining fair values of equity share investments, government bonds and corporate bonds, treasury bills and loan advances in Mozambique. The study was done through a combination of literature review and empirical research using a questionnaire. The trading statistics of the financial instruments on the Mozambique Stock Exchange and the prospectuses of bonds were used. The empirical research was carried out using a type of non-probability sampling technique called purposive sampling. A subcategory of purposive sampling called expert sampling was used to select the eventual sample which was composed of people with specialised knowledge on the capital market system in Mozambique. The results of the empirical research were analysed using pie charts to summarise the responses. The research concluded that the Mozambique Stock Exchange is an inactive market for financial instruments characterised by thin trading in both equity shares and bonds. The estimation of fair values evidenced by observable market transactions is therefore impossible. The absence of credit rating agencies in Mozambique presents a significant challenge in assigning credit risk and pricing financial instruments such as bonds. The research also noted that significant volatility of the main economic indicators such as treasury bills interest rates and inflation made it difficult to determine fair values of financial instruments using financial modelling techniques. Due to the above obstacles to determining fair values of certain financial instruments in Mozambique, the best alternatives are to value these financial instruments at either cost or amortised cost. / Financial Accounting / M. Com. (Accounting)

by Leung Chui-wa. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 72-75). / ABSTRACT --- p.ii / TABLE OF CONTENTS --- p.iii / LIST OF TABLES --- p.v / ACKNOWLEDGEMENT --- p.vii / Chapters / Chapter I. --- introduction --- p.1 / Purpose of the project --- p.2 / Scope of the project --- p.2 / Methodology and literature review --- p.2 / Chapter II. --- BACKGROUND OF OFFSHORE LISTING OF CHINA ENTERPRISES --- p.5 / Reform of China state-owned enterprise --- p.5 / Development of China securities market --- p.8 / Capital needs of China --- p.11 / China's participation in global economy --- p.12 / China's resumption of Hong Kong's sovereignty --- p.13 / Chapter III --- OVERVIEW OF OFFSHORE LISTING OF CHINA ENTERPRISES.…… --- p.15 / China policies over offshore listings of China enterprises --- p.15 / Overall policy --- p.16 / Selection of State-owned enterprises for offshore listings --- p.17 / Selection of listing venue --- p.19 / Competition among stock exchanges worldwide --- p.20 / Australia --- p.21 / Canada --- p.22 / London --- p.22 / Singapore --- p.23 / Tokyo --- p.24 / Chapter IV. --- listings of china enterprises in hong kong and the united states --- p.26 / Current situation in Hong Kong and New York --- p.26 / China enterprises listed in Hong Kong and New York --- p.28 / Hong Kong --- p.28 / New York --- p.30 / Important issues for consideration --- p.32 / Regulatory regime --- p.32 / Offering mechanism --- p.35 / Market characteristics --- p.38 / Advantages and disadvantages of listing in Hong Kong and the US --- p.39 / Chapter V. --- trading performance of h shares and h/n share adrs … --- p.41 / Scope and methodology of the analysis --- p.41 / Findings --- p.42 / Discussion --- p.45 / Chapter VI. --- discussion and conclusion --- p.47 / Implications on SOEs and China economy --- p.47 / Implications on the Hong Kong stock market --- p.50 / appendix --- p.54 / bibliography --- p.72

The implementation of International Accounting Standard 32 Financial Instruments: Disclosure and Presentation (lAS 32), International Accounting Standard 39 Financial Instruments: Recognition and Measurement (lAS 39) and International Financial Reporting Standard 7 Financial Instruments: Disclosures (IFRS 7) by developing countries has been met with mixed reactions largely due to the extensive use of the fair value concept by the three accounting standards. The use of the fair value concept in developing countries has proved to be a significant challenge due to either a Jack of formal capital market systems or very thinly traded capital markets. This study investigates the obstacles to determining fair values of equity share investments, government bonds and corporate bonds, treasury bills and loan advances in Mozambique. The study was done through a combination of literature review and empirical research using a questionnaire. The trading statistics of the financial instruments on the Mozambique Stock Exchange and the prospectuses of bonds were used. The empirical research was carried out using a type of non-probability sampling technique called purposive sampling. A subcategory of purposive sampling called expert sampling was used to select the eventual sample which was composed of people with specialised knowledge on the capital market system in Mozambique. The results of the empirical research were analysed using pie charts to summarise the responses. The research concluded that the Mozambique Stock Exchange is an inactive market for financial instruments characterised by thin trading in both equity shares and bonds. The estimation of fair values evidenced by observable market transactions is therefore impossible. The absence of credit rating agencies in Mozambique presents a significant challenge in assigning credit risk and pricing financial instruments such as bonds. The research also noted that significant volatility of the main economic indicators such as treasury bills interest rates and inflation made it difficult to determine fair values of financial instruments using financial modelling techniques. Due to the above obstacles to determining fair values of certain financial instruments in Mozambique, the best alternatives are to value these financial instruments at either cost or amortised cost. / Financial Accounting / M. Com. (Accounting)

by Cheung, Wing Hang, Sakaguchi, Hitoshi. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 86-87). / ABSTRACT --- p.ii / TABLE OF CONTENT --- p.iii / LIST OF FIGURES --- p.vi / LIST OF TABLES --- p.vii / CHAPTER / Chapter I. --- INTRODUCTION --- p.1 / Chapter I.I. --- Why do we study H-share companies? --- p.1 / Chapter I.II. --- Why do PRC state-owned enterprises need to raise capital overseas? --- p.3 / Chapter I.II.I. --- Capacity of PRC equity market --- p.3 / Chapter I.II.II. --- Foreign Currency --- p.3 / Chapter I.II.III. --- Accumulate experience for future SOEs reform --- p.4 / Chapter I.II.IV. --- Promotion --- p.4 / Chapter I.III. --- Why do most SOEs prefer listing in Hong Kong to listing in other places? --- p.5 / Chapter I.III.I --- IPO P/E ratio in overseas market --- p.5 / Chapter I.III.II. --- Cost of listing: IPO & annual operation cost --- p.6 / Chapter I.III.III. --- Understanding of the overseas market by SOEs management --- p.6 / Chapter I.IV. --- Background of SOEs reform --- p.6 / Chapter I.IV.I. --- First stage (1979 to 1983) --- p.6 / Chapter I.IV.II. --- Second stage (1984 to 1988) --- p.7 / Chapter I.IV.III. --- Third stage (1989 to before 15th Communist Party Congress) --- p.7 / Chapter I.V. --- Profile and Development of H-share companies --- p.8 / Chapter I.VI. --- PRC SOES equity shareholding structure --- p.10 / Chapter II. --- METHODOLOGIES --- p.11 / Chapter II.I. --- Agency cost problems --- p.13 / Chapter II.II. --- Government control --- p.15 / Chapter II.III. --- Asymmetric Information --- p.15 / Chapter II.IV. --- Industry --- p.16 / Chapter II.V. --- Strategy --- p.17 / Chapter III. --- CASE STUDY: YIZHENG CHEMICAL FIBRE COMPANY LTD --- p.18 / Chapter III.I. --- Background --- p.18 / Chapter III.II. --- Agency Cost --- p.21 / Chapter III.II.I. --- Management Structure --- p.21 / Chapter III.II.II. --- Remuneration --- p.24 / Chapter III.II.III. --- Management Ownership --- p.26 / Chapter III.III. --- Government Control --- p.27 / Chapter III.III.I --- Product and raw material prices --- p.27 / Chapter III.III.II. --- Taxation --- p.27 / Chapter III.III.III. --- Import custom --- p.27 / Chapter III.III.IV. --- Product mix --- p.28 / Chapter III.III.V. --- Mergers & Acquisition under Government Policies --- p.28 / Chapter III.III.VI. --- Government intervention on capital raising decisions --- p.29 / Chapter III.IV. --- Asymmetric Information --- p.31 / Chapter III.IV.I. --- Analyst coverage --- p.37 / Chapter III.IV.II. --- Investment of Institutional Investors --- p.31 / Chapter III.IV.III. --- Incorrect forecast on product prices and profit margin --- p.31 / Chapter III.IV.IV. --- Acquisition of Foshan Chemical Fibre Complex --- p.31 / Chapter III.V. --- Industry Analysis --- p.31 / Chapter III.V.I. --- Background of the industry: 21 --- p.31 / Chapter III.V.II. --- Porter Five's Forces Analysis - Polyester industry in the PRC --- p.31 / Chapter III.VI. --- Strategy --- p.31 / Chapter IV. --- CASE STUDY: HARBIN POWER EQUIPMENT COMPANY LIMITED --- p.31 / Chapter IV.I. --- Background --- p.31 / Chapter IV.II. --- Agency Cost --- p.31 / Chapter IV.II.I --- Management Structure --- p.3] / Chapter IV.II.II. --- Remuneration --- p.31 / Chapter IV.II.III. --- Management Ownership --- p.53 / Chapter IV.III. --- Government Regulation --- p.53 / Chapter IV.III.I. --- Product and Raw Material Price --- p.53 / Chapter IV.III.II. --- Taxation --- p.54 / Chapter IV.III.III. --- Monetary Policy --- p.54 / Chapter IV.IV. --- Asymmetric Information --- p.56 / Chapter IV.IV.I. --- Analyst Coverage --- p.56 / Chapter IV.IV.II. --- Investment of Institutional Investors --- p.56 / Chapter IV.IV.III. --- Information disclosure --- p.57 / Chapter IV.V. --- Industry --- p.57 / Chapter IV.V.I. --- Industry Growth --- p.57 / Chapter IV.V.II. --- Porter Five's Forces Analysis ´ؤ Power Equipment Industry in the PRC --- p.58 / Chapter IV.VI. --- Strategy --- p.63 / Chapter V. --- DISCUSSION AND CONCLUSION --- p.66 / Chapter V.I. --- Agency Cost --- p.66 / Chapter V.II. --- Government Control --- p.66 / Chapter V.III. --- Asymmetric Information --- p.67 / Chapter V.IV. --- Industry --- p.68 / Chapter V.V. --- Strategy --- p.68 / Chapter V.VI. --- Explanations for the first year price performance of Yizheng and HPEC --- p.68 / Chapter V.VII. --- Conclusion --- p.72 / Appendix I - List of Capital Raising of H-shares companies (up to 3 1st December 1997) --- p.74 / Appendix II ´ؤ Results of companies selection methodology --- p.82 / Appendix III - History of Yizheng Chemical --- p.85 / BIBLIOGRAPHY --- p.86

This thesis aims to better understand the process of the funding of young innovative<p>ventures, and how a deeper understanding of this process can help public policy to better<p>stimulate entrepreneurial firms—especially in high-technology industries. I interpret<p>entrepreneurial finance broadly to mean financing issues facing young innovative<p>ventures. It includes three essays which deal with a set of economic, institutional, and<p>public policy issues to examine entrepreneurial finance. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Abstracts in English, Zulu and Southern Sotho / The advent of Basel II Capital Accord has revolutionised credit risk measurement (CRM) to the extent that the once “perceived riskier bank assets” are now accommodated for lending. The Small and Medium Enterprise (SME) sector has been traditionally perceived as a riskier and unprofitable asset for lending activity by Commercial Banks, in particular. But empirical studies on the implementation of the Basel II internal-ratings-based (IRB) framework have demonstrated that SME credit risk is measurable. Banks are still finding it difficult to forecast SME loan default and to provide credit to the sector that meet Basel’s capital requirements. The thesis proposes to construct an empirical credit risk measurement (CRM) model, specifically for SMEs, to ameliorate the adverse effects of SME credit inaccessibility due to high information asymmetry between financial institutions (FI) and SMEs in Zimbabwe. A well-performing and accurate CRM helps FIs to control their risk exposure through selective granting of credit based on a thorough statistical analysis of historical customer data. This thesis develops a CRM model, built on a statistically random sample, known-good-bad (KGB) sample, which is a better representation of the through-the-door (TTD) population of SME loan applicants. The KGB sample incorporates both accepted and rejected applications, through reject inference (RI). A model-based bound and collapse (BC) reject inference methodology was empirically used to correct selectivity bias inherent in CRM domain. The results have shown great improvement in the classification power and aggregate supply of credit supply to the SME portfolio of the case-studied bank, as evidenced by substantial decrease of bad rates across models developed; from the preliminary model to final model designed for the case-studied bank. The final model was validated using both bad rate, confusion matrix metrics and Area under Receiver Operating Characteristic (AUROC) curve to assess the classification power of the model within-sample and out-of-sample. The AUROC for the final model (weak model) was found to be 0.9782 whilst bad rate was found to be 14.69%. There was 28.76% improvement in the bad rate in the final model in comparison with the current CRM model being used by the case-studied bank. / Isivumelwano seBasel II Capital Accord sesishintshe indlela yokulinganisa ubungozi bokunikezana ngesikweletu credit risk measurement (CRM) kwaze kwafika ezingeni lapho izimpahla ezazithathwa njengamagugu anobungozi “riskier bank assets” sezimukelwa njengesibambiso sokuboleka imali. Umkhakha wezamaBhizinisi Amancane naSafufusayo, phecelezi, Small and Medium Enterprise (SME) kudala uqondakala njengomkhakha onobungozi obukhulu futhi njengomkhakha ongangenisi inzuzo, ikakhulu njengesibambiso sokubolekwa imali ngamabhange ahwebayo. Kodwa izifundo zocwaningo ezimayelana nokusetshenziswa nokusetshenziswa kwesakhiwo iBasel II internal-ratings-based (IRB) sezikhombisile ukuthi ubungozi bokunikeza isikweletu kumabhizinisi amancane nasafufusayo (SME) sebuyalinganiseka. Yize kunjalo, amabhange asathola ukuthi kusenzima ukubona ngaphambili inkinga yokungabhadeleki kahle kwezikweletu kanye nokunikeza isikweletu imikhakha enemigomo edingekayo yezimali kaBasel. Lolu cwaningo beluphakamisa ukwakha uhlelo imodeli ephathekayo yokulinganisa izinga lobungozi bokubolekisa ngemali (CRM) kwihlelo lokuxhasa ngezimali ama-SME, okuyihlelo elilawulwa yiziko lezimali ezweni laseZimbabwe. Imodeli ye-CRM esebenza kahle futhi eshaya khona inceda amaziko ezimali ukugwema ubungozi bokunikezana ngezikweletu ngokusebenzisa uhlelo lokunikeza isikweletu ababoleki abakhethekile, lokhu kususelwa ohlelweni oluhlaziya amanani edatha engumlando wekhasimende. Imodeli ye-CRM ephakanyisiwe yaqala yakhiwa ngohlelo lwamanani, phecelezi istatistically random sample, okuluphawu olungcono olumele uhlelo lwe through-the-door (TTD) population lokukhetha abafakizicelo zokubolekwa imali bama SME, kanti lokhu kuxuba zona zombili izicelo eziphumelele kanye nezingaphumelelanga. Indlela yokukhetha abafakizicelo, phecelezi model-based bound-and-collapse (BC) reject-inference methodology isetshenzisiwe ukulungisa indlela yokukhetha ngokukhetha ngendlela yokucwasa kwisizinda seCRM. Imiphumela iye yakhombisa intuthuko enkulu mayelana namandla okwehlukanisa kanye nokunikezwa kwezikweletu kuma SME okungamamabhange enziwe ucwaningo lotho., njengoba lokhu kufakazelwa ukuncipha okukhulu kwe-bad rate kuwo wonke amamodeli athuthukisiwe. Imodeli yokuqala kanye neyokugcina zazidizayinelwe ibhange. Imodeli yokugcina yaqinisekiswa ngokusebenzisa zombili indlela isikweletu esingagculisi kanye negrafu ye-Area under Receiver Operating Characteristic (AUROC) ukulinganisa ukwehlukaniswa kwamandla emodeli engaphakathi kwesampuli nangaphandle kwesampuli. Uhlelo lwe-AUROC lwemodeli yokugcina (weak model) lwatholakala ukuthi luyi 0.9782, kanti ibad rate yatholakala ukuthi yenza i-14.69%. Kwaba khona ukuthuthuka nge-28.76% kwi-bad rate kwimodeli yokugcina uma iqhathaniswa nemodeli yamanje iCRM model ukuba isetshenziswe yibhange elithile. / Basel II Capital Accord e fetotse tekanyo ya kotsi ya mokitlane (credit risk measurement (CRM)) hoo “thepa e kotsi ya dibanka” ka moo e neng e bonwa ka teng, e seng e fuwa sebaka dikadimong. Lekala la Dikgwebo tse Nyane le tse Mahareng (SME) le bonwa ka tlwaelo jwalo ka lekala le kotsi e hodimo le senang ditswala bakeng sa ditshebetso tsa dikadimo haholo ke dibanka tsa kgwebo. Empa dipatlisiso tse thehilweng hodima se bonweng kapa se etsahetseng tsa tshebetso ya moralo wa Basel II internal-ratings-based (IRB) di supile hore kotsi ya mokitlane ya SME e kgona ho lekanngwa. Leha ho le jwalo, dibanka di ntse di thatafallwa ke ho bonelapele palo ya ditlholeho tsa ho lefa tsa diSME le ho fana ka mokitla lekaleng leo le kgotsofatsang ditlhoko tsa Basel tsa ditjhelete. Phuputso ena e ne sisinya ho etsa tekanyo ya se bonwang ho mmotlolo wa kotsi ya mokitlane (CRM) tshebetsong ya phano ya tjhelete ya diSME e etswang ke setsi sa ditjhelete (FI) ho la Zimbabwe. Mmotlolo o sebetsang hantle hape o fanang ka dipalo tse nepahetseng o dusa diFI hore di laole pepeso ya tsona ho kotsi ka phano e kgethang ya mokitlane, e thehilweng hodima manollo ya dipalopalo ya dintlha tsa histori ya bareki. Mmotlolo o sisingwang wa CRM o hlahisitswe ho tswa ho sampole e sa hlophiswang, e leng pontsho e betere ya setjhaba se ikenelang le monyako (TTD) ya batho bao e kang bakadimi ba tjhelete ho diSME, hobane e kenyelletsa bakopi ba amohetsweng le ba hannweng. Mokgwatshebetso wa bound-and-collapse (BC) reject-inference o kentswe tshebetsong ho nepahatsa tshekamelo ya kgetho e leng teng ho lekala la CRM. Diphetho tsena di bontshitse ntlafalo e kgolo ho matla a tlhophiso le palohare ya phano ya mokitlane ho diSME tsa banka eo ho ithutilweng ka yona, jwalo ka ha ho pakilwe ke ho phokotseho ya direite tse mpe ho pharalla le dimmotlolo tse hlahisitsweng. Mmotlolo wa ho qala le wa ho qetela e ile ya ralwa bakeng sa banka. Mmotlolo wa ho qetela o ile wa netefatswa ka tshebediso ya bobedi reite e mpe le mothinya wa Area under Receiver Operating Characteristic (AUROC) ho lekanya matla a kenyo mekgahlelong a mmotlolo kahare ho sampole le kantle ho yona. AUROC bakeng sa mmotlo wa ho qetela (mmotlolo o fokotseng) e fumanwe e le 0.9782, ha reite e mpe e fumanwe e le 14.69%. Ho bile le ntlafalo ya 28.76% ho reite e mpe bakeng sa mmotlolo wa ho qetela ha ho bapiswa le mmotlolo wa CRM ha o sebediswa bankeng yona eo. / Graduate School of Business Leadership / D.B.L.

This item contains the agenda, minutes, and attachments for the Faculty Senate meeting on this date. There may be additional materials from the meeting available at the Faculty Center.