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English to Malay: Abstract General field: Bus/Financial Detailed field: Finance (general)
Source text - English Nowadays, studying the correlation-based network of financial markets has received more attention, especially, of stocks market. This thesis consists of two parts which are important for conducting the stocks network analysis. The first part is the similarity measure uses to measure the similarity among stocks. The second part is the tools to analyze the corresponding similarities network. Stocks network is a complex system of n stocks. In traditional approach, the interrelations among stocks are customarily quantified by using Pearson correlation coefficient (PCC) among univariate time series of logarithmic closing price returns. However, in fact, the stock’s price is not only represented by closing price but also its opening, highest, and lowest prices. This motivates us to propose the use of Escoufier vector correlation (EVC), a multivariate generalization of PCC, to measure the similarity among stocks. In this case, the multivariate time series of four prices is considered; each of which is under geometric Brownian motion. To filter the information contained in EVCs network, the methodology based on minimal spanning tree (MST) is used. In the literature, there are two most suggested algorithms for constructing MST from similarities network, namely, Kruskal’s or Prim’s algorithms. However, as we will show, both algorithms are time consuming when n is large. This motivates us to develop an algorithm which is of faster computational efficiency than them. Since both algorithms provide only one MST among all MSTs that might possibly exist in the system, the optimality of that MST is of our concern. We show the MST issued from Kruskal’s or Prim’s algorithms depend on the way the stocks ordered in similarities matrix. To overcome the non-optimality problem of MST, a set of optimality criteria is introduced and a selection procedure of optimal MST is proposed. The significance and limitations of the research are outlined.
Translation - Malay Pada masa kini, kajian rangkaian berasaskan korelasi bagi pasaran kewangan telah mendapat lebih perhatian, terutamanya pasaran saham. Tesis ini terdiri daripada dua bahagian yang penting bagi menjalankan analisis rangkaian saham. Bahagian pertama ialah ukuran persamaan yang digunakan untuk mengukur persamaan antara saham. Bahagian kedua ialah alat untuk menganalisis rangkaian persamaan yang berkaitan. Rangkaian saham merupakan sistem saham n yang kompleks. Dalam pendekatan tradisional, hubungan antara saham lazimnya diukur dengan menggunakan pekali hubung kait Pearson (PCC) antara siri masa univariat logaritma pulangan harga penutup. Walau bagaimanapun, pada hakikatnya, harga saham itu tidak hanya diwakili oleh harga penutup tetapi juga harga pembukaan, tertinggi dan terendah. Ini mendorong kami untuk mencadangkan penggunaan pekali vektor Escoufier (EVC) dan generalisasi multivariat PCC untuk mengukur persamaan antara saham. Dalam kes ini, siri masa multivariat empat harga dipertimbangkan; iaitu setiap daripadanya berada di bawah gerakan Brownian geometri. Metodologi berdasarkan pokok perentang minimum (MST) digunakan untuk menapis maklumat yang terkandung dalam rangkaian EVC. Dalam kesusasteraan, terdapat dua algoritma yang paling disyorkan untuk membina MST daripada rangkaian persamaan iaitu algoritma Kruskal ataupun Prim. Walau bagaimanapun, seperti yang akan kami tunjukkan, kedua-dua algoritma memakan masa sekiranya n adalah besar. Ini mendorong kami untuk membangunkan satu algoritma yang cekap bagi membuat pengiraan dengan lebih cepat berbanding kedua-dua algoritma. Keoptimuman MST menjadi tumpuan kami kerana kedua-dua algoritma menyediakan hanya satu MST antara semua MST yang mungkin wujud dalam sistem. Ini menunjukkan bahawa MST yang dihasilkan daripada algoritma Kruskal ataupun Prim bergantung kepada cara pesanan saham dalam matriks persamaan. Satu set kriteria optimum diperkenalkan dan prosedur pemilihan MST optimum telah dicadangkan bagi mengatasi masalah MST yang tidak optimum. Kepentingan dan batasan dalam penyelidikan telah digariskan.
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Translation education
Bachelor's degree - Universiti Teknologi Mara, ShahAlam
Experience
Years of experience: 12. Registered at ProZ.com: Jul 2016.
Microsoft Excel, Microsoft Office Pro, Microsoft Word, Powerpoint, SDLX, Trados Studio
CV/Resume
CV available upon request
Bio
I am a native speaker of Malay and an expert user of English, educated in English from primary school up to tertiary education. A Bachelor Degree of Business Administration majored in Insurance with Honour holder from Universiti Teknologi MARA (UiTM).
2 years worked in corporate world of international company specifically in Insurance Software and 4 years worked in Insurance industry which requires good command of English both speaking and writing and strong ability to translate and interpret from English to Malay and vice versa.
With 5 years experienced in translating business proposals, financial statements, management reports, contracts and agreements, product description, terms & condition, process flow from English to Malay as part of work assignments.
Experienced in translating annual reports, software, user interface, blog, contract and agreements, letters, questionnaires, instructions, abstracts, project papers, user manuals and other document type since became a part-time freelance translator.
Keywords: Insurance, accounting, marketing, tele-communications, manufacturing, banking, investment, Human Resources, English Malay translator, freelance translator. See more.Insurance, accounting, marketing, tele-communications, manufacturing, banking, investment, Human Resources, English Malay translator, freelance translator, Native Malay Translator, manuals, Questionnaire, Survey, Operating Manual, Language Translator, Penterjemah, English Malay language translator, Penterjemah Melayu, Penterjemah Inggeris ke Bahasa Malaysia, Translation service from English to Malay, English-Malay translator, English > Malay translator. See less.
