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    • Financial Engineering

    필터링 기준

    "financial engineering"에 대한 624개의 결과

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      Columbia University

      Financial Engineering and Risk Management

      획득할 기술: Accounting, Algebra, Analysis, Applied Mathematics, Audit, BlockChain, Calculus, Communication, Euler'S Totient Function, FinTech, Finance, General Statistics, Investment Management, Linear Algebra, Machine Learning, Markov Model, Mathematical Optimization, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Probability Distribution, Risk, Risk Management

      4.4

      (80개의 검토)

      Intermediate · Specialization · 3-6 Months

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      EDHEC Business School

      Investment Management with Python and Machine Learning

      획득할 기술: Accounting, Applied Machine Learning, Business Analysis, Computer Programming, Data Analysis, Data Mining, Finance, Financial Analysis, Investment, Investment Management, Leadership and Management, Machine Learning, Machine Learning Algorithms, Markov Model, Natural Language Processing, Probability & Statistics, Python Programming, Regression, Risk, Risk Management, Statistical Analysis, Statistical Programming

      4.6

      (1.5k개의 검토)

      Beginner · Specialization · 3-6 Months

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      Columbia University

      Introduction to Financial Engineering and Risk Management

      획득할 기술: Mathematical Theory & Analysis, Calculus, BlockChain, FinTech, Markov Model, General Statistics, Algebra, Linear Algebra, Probability Distribution, Pricing, Mathematics, Modeling, Machine Learning, Probability, Applied Mathematics, Probability & Statistics, Finance

      4.6

      (61개의 검토)

      Intermediate · Course · 1-3 Months

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      Columbia University

      Advanced Topics in Derivative Pricing

      획득할 기술: Accounting, Audit, Finance, Investment Management

      Intermediate · Course · 1-3 Months

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      Google

      Google Data Analytics

      획득할 기술: Algorithms, Application Development, Bias, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Security, Data Structures, Data Type, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Metadata, Network Security, Other Programming Languages, Plot (Graphics), Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Tableau Software, Theoretical Computer Science, Visual Design, Web Development

      4.8

      (70.4k개의 검토)

      Beginner · Professional Certificate · 3-6 Months

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      University of Pennsylvania

      Fundamentals of Quantitative Modeling

      획득할 기술: Strategy, Linearity, Analysis, Entrepreneurship, Market Research, General Statistics, Modeling, Leadership and Management, Probability Distribution, Strategy and Operations, Product Management, Mathematics, Linear Regression, Product Marketing, Regression Analysis, Research and Design, Regression, Probability, Sales, Design and Product, Marketing, Probability & Statistics

      4.6

      (8k개의 검토)

      Mixed · Course · 1-4 Weeks

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      Columbia University

      Computational Methods in Pricing and Model Calibration

      획득할 기술: Euler'S Totient Function, Mathematical Theory & Analysis, Mathematical Optimization, Probability Distribution, Communication, Analysis, Mathematics, Modeling, Probability & Statistics

      3.5

      (6개의 검토)

      Intermediate · Course · 1-3 Months

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      University of Illinois at Urbana-Champaign

      Introduction to Finance: The Role of Financial Markets

      획득할 기술: Software Engineering, Data Analysis, Business Analysis, Accounting, Software Testing, Financial Analysis, Investment Management, Financial Markets, Market (Economics), Finance, Leadership, Investment, Economics, Audit, Budget Management

      4.7

      (53개의 검토)

      Mixed · Course · 1-3 Months

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      무료

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      Georgia Institute of Technology

      Introduction to Engineering Mechanics

      획득할 기술: Entrepreneurship, Leadership and Management, Mechanical Engineering, Mathematics, Research and Design, Problem Solving, C Dynamic Memory Allocation

      4.8

      (4.4k개의 검토)

      Mixed · Course · 1-3 Months

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      Columbia University

      Term-Structure and Credit Derivatives

      획득할 기술: Finance

      4.5

      (15개의 검토)

      Intermediate · Course · 1-3 Months

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      Columbia University

      Optimization Methods in Asset Management

      획득할 기술: Mathematical Optimization, Risk, Finance, Probability & Statistics, Risk Management

      4.3

      (14개의 검토)

      Intermediate · Course · 1-3 Months

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      Copenhagen Business School

      Digital Transformation in Financial Services

      획득할 기술: Agile Software Development, Banking, BlockChain, Business Analysis, Business Transformation, Collaboration, Communication, DevOps, Devops Tools, Entrepreneurial Finance, Entrepreneurship, FinTech, Finance, Innovation, Leadership and Management, Marketing, Payments, Regulations and Compliance, Research and Design, Sales, Social Media, Software Engineering, Strategy, Strategy and Operations

      4.4

      (1.7k개의 검토)

      Beginner · Specialization · 3-6 Months

    financial engineering과(와) 관련된 검색

    financial engineering and risk management
    introduction to financial engineering and risk management
    financing and initiating major engineering projects
    1234…52

    요약하자면, 여기에 가장 인기 있는 financial engineering 강좌 10개가 있습니다.

    • Financial Engineering and Risk Management: Columbia University
    • Investment Management with Python and Machine Learning: EDHEC Business School
    • Introduction to Financial Engineering and Risk Management: Columbia University
    • Advanced Topics in Derivative Pricing: Columbia University
    • Google Data Analytics: Google
    • Fundamentals of Quantitative Modeling: University of Pennsylvania
    • Computational Methods in Pricing and Model Calibration: Columbia University
    • Introduction to Finance: The Role of Financial Markets: University of Illinois at Urbana-Champaign
    • Introduction to Engineering Mechanics: Georgia Institute of Technology
    • Term-Structure and Credit Derivatives: Columbia University

    Finance에서 학습할 수 있는 스킬

    투자 (23)
    시장(경제학) (20)
    주식 (18)
    재무제표 (14)
    재무 회계 (13)
    모델링 (13)
    기업 금융 (11)
    재무 분석 (11)
    거래 (11)
    평가 (10)
    금융 시장 (10)
    가격 (10)

    Financial Engineering에 대한 자주 묻는 질문

    • Financial engineering is an interdisciplinary field that combines applied mathematics, statistics, and computer science to guide investment decisions. While finance has always emphasized quantitative analysis, today’s technology has made it possible to apply these approaches at an unprecedented scale and speed. Massive datasets are now delivered via hardwired internet connections into financial modeling programs built in software like Solver in Microsoft Excel, or even machine learning tools created through Python programming or other techniques.

      The power of financial engineering has made it incredibly important for trading, portfolio optimization and risk management, valuation of derivatives and real options, and a host of other purposes at virtually all of today’s largest financial institutions. Indeed, it has been estimated that as much as 80% of the activity on the U.S. stock market today is computer-led algorithmic trading, making the use of financial engineering absolutely essential to competitiveness in the market.

      By automating financial decision-making, these approaches have unquestionably created enormous value for the firms deploying them. However, the prominence of financial engineering has caused some economists to question whether it is contributing to market volatility during financial turbulence, including the COVID-19 crisis, even if many others claim that it has a positive effect on market liquidity. Regardless, financial engineering is here to stay, making it a critical topic to understand for any finance professional.‎

    • Today, any career in finance requires at least a familiarity with financial engineering. Whether you go to work at an investment bank, a hedge fund, an insurance company, or in government treasuries or regulatory agencies, these techniques will continue to shape the landscape of your job. Thus, understanding how to use financial engineering approaches and how they impact financial problems is a valuable asset regardless of your role in this industry.

      If you have a particular talent for applied mathematics and computer science, you can pursue a lucrative career in financial engineering yourself, as quantitative analysts or “quants” are some of the most highly sought after professionals in the industry. “Back office” quants generally build and validate complex financial engineering tools, while “front office” quants work directly with traders to help them deploy the pricing and trading tools they need.‎

    • Absolutely. Coursera offers a wide range of courses in financial engineering as well as related areas of this interdisciplinary field, including business, computer science, and mathematics and statistics. These courses as well as multi-course Specializations are offered by some of the top undergraduate and business schools in the country, including Columbia University, Yale University, and the University of Pennsylvania.

      In addition to being able to learn remotely on your own schedule, these courses are also available at a significantly lower tuition than their on-campus counterparts. Thus, you won’t need a spreadsheet to determine that learning about financial engineering online is a smart investment in your future, whether you’re just starting your career or are an experienced finance professional looking to update your understanding of this vital topic.‎

    • The skills and experience that you might need to already have before starting to learn financial engineering include a healthy knowledge of mathematics, statistics, economics, and computer science. These aspects come together in financial engineering, which uses financial theory to solve financial problems and to create new financial products. As you begin to learn about financial engineering, you’ll see that a background or knowledge in data science and data management is also very important for the work involved in areas like statistics, indices, quadratic equations, functions, and graphs. Knowing how to use your mathematics and statistics knowledge in building financial models could also be a benefit to learning financial engineering.‎

    • The kind of people that are best suited for work that involves financial engineering are those who are data geeks, quantitative analysts, and other numbers-focused practitioners. These people may have already gained experience and skills from working in corporate finance, risk management, stock trading, and financial regulation. Being comfortable with spreadsheets, financial theories, computer programming, and financial models is likely a key requisite for work that involves financial engineering. Aside from these hard skills that are required, the kind of persons best suited for financial engineering work might also be analytically-minded, with a keen attention to details, and the ability to extract and communicate complex statistical information into common-sense problem solving.‎

    • You might know if learning financial engineering is right for you if you have interest and knowledge of financial theories and financial methods. Having a quantitative analysis background and numbers-focused skills may help you find a career in financial engineering. If you’re the person who reads financial statements and digs into computer-based financial models to figure out financial strategies, then becoming involved with work in financial engineering may be a great fit for you. Combining all your knowledge of data and statistics in this area may help you to achieve future success in financial engineering jobs.‎

    이 FAQ 콘텐츠는 정보 전달 목적만으로 사용할 수 있습니다. 학습자는 과정 및 기타 학점 정보가 개인적, 직업적 및 재정적 목표에 부합하는지 확인하기 위해 추가 조사를 수행하는 것이 좋습니다.
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