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Abstrak :
The purpose of this thesis is to analyze feasibility study based marketing and financial analysis of factory expansion of Olympic Group in Surabaya. Nowadays Olympic has more and more order from customer both domestic market and international market. Now the capacity of production has been already 720,000 units per year or value 250 M per year but it is still not enough to cover the orders. In order to fulfil the order and to reduce delivery cost from manufacturing Bogor to customers in Surabaya, Olympic has to increase the production capacity by expansion factory in several cities around in Indonesia. One of the city is Surabaya. In these thesis, I would like to examine the profitability in commencing the expansion of new factory in Surabaya and the feasibility of the business through the use of financial tools namely Payback Period, Profitability Index, Net Present Value (NPV) and Internal Rate of Return (IRR). Criteria for a project to be accepted is where Net Present Value is positive, Internal Rate of Return exceed the cost of capital and Profitability Index exceed 1. The project has result positive Net Present Value as Rp. 231,000,000.00; Internal Rate of Return (IRR) as 26 % which is exceed the cost of capital; Profitability Index exceeding to 1 as 2.47 ; Payback period is 2.06 years which is less than the period of project 10 years. Based on real option analysis, this factory expansion have positive Net Present Value as Rp 293,500,000. It means that there is no option to expand to some other location both of the optimistic and pessimistic forecast. Based on analysis, the project is feasible . The marketing mix strategy used to serve Olympic target market is SIVA (Solution, Information, Value, Access) model. The SIVA model take into account both buyers and sellers objectives by focusing primarily on the buyer . that adapted by combination between the 4Ps and 4Cs model, where 4Ps is a product ? centric approach while 4Cs is customer ? centric approach. When valuing capital budgeting project, firstly, it is recommended better to use real option analysis. Because from a valuation standpoint, these options are valuable because they allow decision makers to react to favorable or unfavorable new situations by dynamically adjusting the capital budgeting decision process for flexibility associated with the project. And secondly, it is recommended for marketing strategy should focus comprehensively on customer orientation by SIVA (Solution, Information, Value and Access) for all activities in Strategic Business Unit (SBU) rather than 4 Ps which on product-centric orientation.

Abstrak :
Data runtun waktu keuangan umum digunakan oleh investor untuk menganalisis pergerakan harga suatu aset investasi. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) adalah model runtun waktu yang biasa digunakan untuk menganalisis data keuangan. GARCH dapat menangkap pengelompokkan volatilitas yang menjadi karakteristik pada data-data keuangan. Pada dunia perekonomian terdapat keterkaitan antara suatu data keuangan dengan data keuangan yang lain. Oleh karena itu dikembangkan model multivariat GARCH (MGARCH) untuk memperlihatkan informasi tentang pergerakan bersama dua variabel atau lebih serta menggambarkan interaksi antardata keuangan yang diteliti. Pada skiripsi ini dibahas versi multivariat dari GARCH, yaitu Baba Engle Kroner dan Kraft (BEKK) GARCH. Pembahasan dimulai dari bagaimana pembentukan struktur varian kovarian bersyarat model BEKK MGARCH, penaksiran parameter, sampai analisis data menggunakan model BEKK MGARCH dengan asumsi error model berdistribusi normal multivariat. Metode yang digunakan untuk mengestimasi parameter adalah metode maximum likelihood. Penurunan analitik pada metode maximum likelihood dibantu dengan sifat yang ada pada quasi maximum likelihood di mana penurunan fungsi likelihood dilakukan dengan menurunkan setiap elemen pada matriks varian kovarian bersyaratnya. Namun estimasi secara analitik tidak dapat digunakan karena persamaan yang non linear, maka digunakan penyelesaian secara numerik menggunakan algoritma quasi-Newton Broyden, Fletcher, Goldfarb, dan Shanno (BFGS). Kemudian model diimplementasikan pada data harian harga penutupan saham BMRI dan BBCA. Hasil analisis menunjukkan bahwa volatilitas saham BMRI dan BBCA tanggal 01 April 2021 sampai dengan 31 Maret 2022 dipengaruhi oleh shock perusahaan sendiri pada masa lampau. ......Financial time series data has been widely used by investors to analyze the movement of any asset pricing. Generalized Autoregressive Conditional Heteroskedasticity (GARCH) is a time series model that usually used to analyze financial datas. GARCH can capture the volatility clustering phenomenon found in most financial datas. In the economic world, there is relation between one to another financial data. Hence, GARCH model has been developed into its multivariate version called multivariate GARCH (MGARCH) to capture the information about comovement also the relationship between two or more variables. In this undergraduate thesis, we explain Baba Engle Kroner and Kraft (BEKK) multivariat GARCH, starting from how the structure of variance and covariance developed, parameter estimation, to implementation of BEKK MGARCH model assuming the error model has multivariate normal distribution. Parameter estimation will be done using the maximum likelihood method with property of quasi maximum likelihood. Parameter estimation can not be solved analytically because the likelihood function is non linear, so we used numerically method called quasi-Newton with Broyden, Fletcher, Goldfarb, dan Shanno (BFGS) algorithms. Then, this BEKK MGARCH model will be used to check the volatility spillover between BMRI and BBCA stock return. The analysis in chapter 4 shows that there is no volatility spillover between BMRI and BBCA. The volatility of their return is affected by their own past shock.