- Practically speaking, one key tool…in algorithmic trading is risk management.…Risk management is crucial to making sure that your…portfolio will do well under a variety of market conditions.…There's two tools that you should…consider for risk management purposes.…One is VAR, or value at risk,…and the other is expected shortfall.…VAR is a statistical measure that tells us the expected…losses under certain ordinary market conditions.…
As we see in this diagram, VAR refers to the losses…that we expect in the negative tail of our distribution,…but excluding our worst five percent of outcomes here.…So, VAR tells us, in essence, 95 percent of the time,…we will lose no more money than X.…For example, a 95 percent VAR might say…that 95 percent of the time, we expect to lose…no more money than one million dollars.…If we have VAR set up properly then,…it can insulate us from great risk…that we're not willing to take on as a business.…
If our VAR limit is two million dollars…and instead, our actual VAR, our value at risk…
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.