As the digital economy continues to accelerate, large sources of data will continue to become more accessible to today’s business leaders to make highly informed, data-driven decisions. The Business Analytics secondary concentration recognizes the need for future leaders to be well-versed in how to manage large sets of data and leverage them to both communicate and make decisions to drive business results.
Applications of financial theory through computer modeling. Financial forecasting, cash flow modeling, and valuation.
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Application of financial theory using computer modeling. Portfolio optimization, risk measurement, and option pricing.
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Introduction to pricing, trading strategies, and hedging applications of forward and futures contracts, swaps, and options.
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Derivatives pricing and applications to corporate securities, structured products, and credit default swaps.
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Fundamental analysis of individual stocks. Discounted cash flow valuation, relative valuation, and special situations. Management of student-run investment fund.
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Traditional and emerging research tools that organizations use to capture the voice of the customer. Application of behavioral science research in developing deep understanding of customers that can be used in developing marketing strategies, including segmentation, positioning, branding, advertising, customer satisfaction and loyalty.
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Design, management, and integration of pricing into the marketing mix and the revenue yield strategies of the firm. Analytic, empirical and simulation approaches to pricing.
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Brand strategy consumer and customer analysis, competitive brand analysis and brand planning.
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Fundamentals of online marketplace. Analysis of online consumer behavior and corporate digital marketing strategy, including online advertisement, search engine marketing, and social media strategy. Introduction to web analytic tools, online advertising platforms and social media analysis tools.
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Analytical models to support decision making with specific supply chain focus. Topics include multiple regression, linear optimization, decisions under uncertainty, and forecasting.
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