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    • Algorithmic Trading

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    104 results for "algorithmic trading"

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      Indian School of Business

      Trading Strategies in Emerging Markets

      Skills you'll gain: Finance, Investment Management, Accounting, Financial Analysis, Business Analysis, Data Analysis, Entrepreneurship, Market Analysis, Market Research, Marketing, Research and Design, Probability & Statistics, Basic Descriptive Statistics, Risk Management, Securities Trading, Banking, Cash Management, Financial Accounting, Financial Management, Forecasting, General Accounting, Generally Accepted Accounting Principles (GAAP), Accounts Payable and Receivable, Algorithms, Audit, Brand Management, Business Psychology, Change Management, Communication, Corporate Accouting, Design and Product, General Statistics, Human Resources, Journalism, Leadership and Management, Operations Research, Planning, Project Management, Sales, Strategy, Strategy and Operations, Supply Chain and Logistics, Theoretical Computer Science, Training, Visual Design, Writing

      4.2

      (2.5k reviews)

      Beginner · Specialization · 3-6 Months

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      EDHEC Business School

      Investment Management with Python and Machine Learning

      Skills you'll gain: Finance, Computer Programming, Investment Management, Python Programming, Statistical Programming, Data Analysis, Machine Learning, Probability & Statistics, Data Analysis Software, Machine Learning Algorithms, Algorithms, Theoretical Computer Science, Data Mining, Natural Language Processing, Risk Management, Applied Machine Learning, Regression, Mathematics, Network Analysis, Leadership and Management, Accounting, Business Analysis, Computer Science, Financial Analysis, Statistical Analysis

      4.6

      (1.6k reviews)

      Beginner · Specialization · 3-6 Months

    • Free

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      The Hong Kong University of Science and Technology

      Python and Statistics for Financial Analysis

      Skills you'll gain: Business Analysis, Computer Programming, Data Analysis, Financial Analysis, Python Programming, Statistical Programming, Finance, Investment Management, Probability & Statistics, Probability Distribution, Statistical Analysis, Basic Descriptive Statistics, Correlation And Dependence, General Statistics, Regression, Risk Management, Securities Trading, Statistical Tests, Accounting, Estimation

      4.4

      (3.6k reviews)

      Intermediate · Course · 1-4 Weeks

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      Indian School of Business

      Trading Algorithms

      Skills you'll gain: Entrepreneurship, Market Analysis, Market Research, Marketing, Research and Design, Finance, Investment Management, Forecasting, Probability & Statistics, Accounting, Business Analysis, Data Analysis, Financial Analysis, Leadership and Management, Sales, Strategy, Strategy and Operations

      4.6

      (1k reviews)

      Intermediate · Course · 1-4 Weeks

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      New York University

      Machine Learning and Reinforcement Learning in Finance

      Skills you'll gain: Machine Learning, Finance, Machine Learning Algorithms, Mathematics, Algorithms, Probability & Statistics, Theoretical Computer Science, Applied Mathematics, Calculus, General Statistics, Investment Management, Applied Machine Learning, Artificial Neural Networks, Business Analysis, Data Analysis, Deep Learning, Financial Analysis, Machine Learning Software, Tensorflow, Advertising, Communication, Computer Programming, Entrepreneurship, Marketing, Markov Model, Operations Research, Python Programming, Research and Design, Statistical Machine Learning, Strategy and Operations

      3.7

      (771 reviews)

      Intermediate · Specialization · 3-6 Months

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      Columbia University

      Financial Engineering and Risk Management

      Skills you'll gain: Finance, Probability & Statistics, Risk Management, Mathematics, General Statistics, Probability Distribution, Investment Management, Accounting, Mathematical Theory & Analysis, Securities Sales, Securities Trading, Audit, Algebra, Calculus, Correlation And Dependence, Linear Algebra, Applied Mathematics, BlockChain, Communication, Computer Programming, Entrepreneurship, FinTech, Leadership and Management, Machine Learning, Markov Model, Product Marketing, Sales, Strategy

      4.5

      (124 reviews)

      Intermediate · Specialization · 3-6 Months

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      Google Cloud

      Machine Learning for Trading

      Skills you'll gain: Machine Learning, Finance, Leadership and Management, Cloud Computing, Cloud Platforms, Risk Management, Strategy, Applied Machine Learning, Artificial Neural Networks, Entrepreneurship, Investment Management, Marketing, Probability & Statistics, Sales, Securities Trading, Strategy and Operations, Business Psychology, Computer Programming, General Statistics, Mathematics, Python Programming, Reinforcement Learning, Statistical Programming

      3.9

      (1k reviews)

      Intermediate · Specialization · 1-3 Months

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      Coursera Project Network

      Tesla Stock Price Prediction using Facebook Prophet

      Skills you'll gain: Accounting, Business Analysis, Data Analysis, Data Visualization, Financial Analysis, Forecasting, General Statistics, Plot (Graphics), Probability & Statistics, Advertising, Communication, Machine Learning, Marketing

      4.4

      (76 reviews)

      Beginner · Guided Project · Less Than 2 Hours

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      New York Institute of Finance

      Using Machine Learning in Trading and Finance

      Skills you'll gain: Finance, Risk Management, Applied Machine Learning, Probability & Statistics, Securities Trading, Strategy, Investment Management, Machine Learning, Python Programming

      4.0

      (320 reviews)

      Intermediate · Course · 1-3 Months

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      Indian School of Business

      Advanced Trading Algorithms

      Skills you'll gain: Accounting, Business Analysis, Data Analysis, Financial Analysis, Finance, Investment Management, Basic Descriptive Statistics, Probability & Statistics, Financial Accounting, Algorithms, Entrepreneurship, Securities Trading, Theoretical Computer Science

      4.6

      (504 reviews)

      Intermediate · Course · 1-4 Weeks

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      Indian School of Business

      Trading Basics

      Skills you'll gain: Finance, Accounting, Securities Trading, Banking, Cash Management, Financial Analysis, Financial Management, General Accounting, Generally Accepted Accounting Principles (GAAP), Investment Management, Accounts Payable and Receivable, Audit, Business Analysis, Data Analysis, Design and Product, Financial Accounting, Leadership and Management, Risk Management

      3.9

      (1.7k reviews)

      Beginner · Course · 1-4 Weeks

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      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Skills you'll gain: Leadership and Management, Machine Learning, Finance, Cloud Computing, Cloud Platforms, Artificial Neural Networks, Entrepreneurship, Investment Management, Marketing, Sales, Strategy, Strategy and Operations

      4.0

      (773 reviews)

      Intermediate · Course · 1-4 Weeks

    Searches related to algorithmic trading

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    In summary, here are 10 of our most popular algorithmic trading courses

    • Trading Strategies in Emerging Markets: Indian School of Business
    • Investment Management with Python and Machine Learning: EDHEC Business School
    • Python and Statistics for Financial Analysis: The Hong Kong University of Science and Technology
    • Trading Algorithms: Indian School of Business
    • Machine Learning and Reinforcement Learning in Finance: New York University
    • Financial Engineering and Risk Management: Columbia University
    • Machine Learning for Trading: Google Cloud
    • Tesla Stock Price Prediction using Facebook Prophet: Coursera Project Network
    • Using Machine Learning in Trading and Finance: New York Institute of Finance
    • Advanced Trading Algorithms: Indian School of Business

    Skills you can learn in Design And Product

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    Video Game Development (7)
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    Adobe Photoshop (6)

    Frequently Asked Questions about Algorithmic Trading

    • Algorithmic trading, also known as automated trading or “algo trading,” is the use of computers and high-speed internet connections to execute large volumes of trading in financial markets much faster than would be possible for human traders. “Algos” leverage machine learning algorithms, typically created using reinforcement learning techniques in Python, to build high-frequency trading strategies that can make orders based on electronically-received information on variables like time, share price, and volume.

      Understanding algorithmic trading is critically important to understanding financial markets today. It is estimated that algorithms are responsible for 80% of trading on U.S. stock markets, and it is widely used by investment banks, hedge funds, and other institutional investors. There are debates over the impacts of this rapid change in the market; some argue that it has benefitted traders by increasing liquidity, while others fear the speed of trading has created more volatility.

      However, there is no question that algo trading is here to stay, and day traders as well as finance professionals need to understand how they work at a minimum - and, ideally, be able to make use of these powerful tools themselves.‎

    • Because of their ubiquity in today’s financial markets, a baseline familiarity with algorithmic trading is increasingly essential for careers as a trader, analyst, portfolio manager, or other finance jobs. These highly-paid professionals may work at institutions such as banks, asset management firms, and hedge funds, and they are increasingly adding courses in algorithms, machine learning, and other related areas to their education in order to understand this critical topic.

      Career opportunities in this field are also attracting professionals with high-level computer science skills, who have gained nearly as high of a profile in the finance industry as algorithmic trading itself. Quantitative analysts, or “quants,” are highly prized for their ability to apply their programming skills to massive datasets, statistics, and other high-velocity market inputs to create the mathematical models required for algorithmic trading and other financial engineering techniques.

      In a sense, then, algorithmic trading is where finance and programming meet, giving professionals with the ability to span these worlds the opportunity to create enormous value for their firms.‎

    • Absolutely. Coursera offers a wealth of courses and Specializations about relevant topics in both finance and computer science, including opportunities to learn specifically about algorithmic trading. These courses are offered by top-ranked schools from around the world such as New York University and the Indian School of Business, as well as leading companies like Google Cloud.

      In addition to being able to access a high-quality education remotely from anywhere in the world, learning online through Coursera offers other advantages. The ability to virtually attend lectures and complete coursework on a flexible schedule makes online courses ideal for working professionals in finance or computer programming that want to add algorithmic trading to their skillset. And the lower cost of online courses compared to on-campus alternatives means that this high-value education can be surprisingly affordable.‎

    • The skills and experience that you might need to already have before starting to learn algorithmic trading are generally financial in nature, covering areas like programming skills, knowledge of trading and financial markets, and a solid understanding of financial modeling and quantitative analysis. These are deep subjects that would involve having a fundamental basis of mathematics concepts, data science, and programming capabilities. You might also learn more about algorithmic trading in other ways, from studying online webinars, taking online courses, reading informative blogs, or watching video content. Conversely, you might also attend college to gain a degree in mathematics, computer science, or statistical analysis. Having a good education would be a good benefit before starting to learn algorithmic trading.‎

    • The kind of people that are best suited for work that involves algorithmic trading are people who are comfortable working with numbers, data, computer algorithms, and financial concepts. People working in algorithmic trading are known as ‘quants’, short for quantitative analysts, or financial quantitative analysts. A person who works as a quant uses knowledge, skills, and experience to help financial organizations generate profits while reducing risk. These quants must be able to analyze data, develop statistical scenarios, and implement complex mathematical models for banks, hedge funds, and investment firms to make smart decisions about pricing structures, investments, and risk management opportunities.‎

    • You might know if learning algorithmic trading is right for you if you have a sharp mind that can scan and analyze numbers in math, data, and financial areas quickly and decisively. You would most likely love aspects of technology and finance, working with programming languages, scrutinizing data, crunching numbers, and having a good grasp of principles with ratios and percentages. If you want to learn if algorithmic trading is right for you, then you might want to take online courses in statistical modeling, quantitative analyses, financial trading, computer programming and related areas to gauge your interest and capability for this subject.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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