You are currently accessing the institutional-grade blueprint for <b>Algorithmic Trading and Stocks Essential Training – Michael McDonald</b>. Instant digital deployment and lifetime encrypted access are guaranteed immediately upon transaction clearance.
Many stock market trades are now conducted with algorithms: computer programs that buy or sell stocks according to mathematical formulas. These trades are conducted at a speed and frequency that is hard for humans to replicate. Therefore, it's important for finance professionals, and indeed everyone who invests in the stock market, to know how these algorithms work. This course shows how to develop a back-tested, rules-based trading strategy and program a simple trading algorithm of your own.
Professor Michael McDonald provides a brief primer on securities markets. He explains how data helps investors forecast performance and automate trading. Then he moves into the practical steps: coming up with algorithmic trading rules and developing and testing an algorithm. Finally, he shows how the algorithm can be applied and eventually expanded to other securities. Anyone working in financial services, or interested in investing in the stock market, will be able to use these tutorials to understand and develop simple trading algorithms of their own.
Topics include:
- Define what a share of stock is.
- Classify the type of trading that attempts to capitalize on the bid-ask spread.
- Name the rule that can be used as a metric for Fed interference in the market.
- State the first step in a data analysis project.
- Identify the type of characteristic algorithmic trading relies on.
- Break down how VAR is used to manage risk
Get Algorithmic Trading and Stocks Essential Training – Michael McDonald, Only Price $37
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Trading foreign exchange, cryptocurrencies, and algorithmic assets on margin carries a high level of risk and may not be suitable for all investors. Past performance of any trading system or quantitative blueprint does not guarantee future results.<br><br><b>Asset Classification:</b>

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