- [Instructor] Now that we understand the basics…around practically putting together a trading algorithm,…it's important to understand a few pragmatic rules.…First of all, buying and selling with algorithms…is more complicated than it seems.…The reality is that the strategies and rules…behind an algorithm are just the beginning.…The process for buying or selling securities…based on those algorithms is going to vary significantly.…High-frequency trading firms, for example,…will often tap directly into a network…for an exchange in order to trade.…
In other words, they want that algorithm to be able…to seamlessly make all of the decisions…and then trade directly through the exchange…to do this as fast as possible.…Outside of the high-frequency traders though,…most quant firms have separate systems…for research versus trading.…So you might develop an algorithm…and then test it on one system and then put it into practice…on a completely different system.…Practically speaking, automating an algorithm to make…trade decisions directly can actually be very dangerous.…
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.
- 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.