{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

money_manag03

# money_manag03 - An Introduction to Money Management III by...

This preview shows pages 1–9. Sign up to view the full content.

An Introduction to Money Management III by Dr. Fernando Diz Syracuse University

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
We shall now tackle.. 2. Deciding what amount of risk to take on a  trade or portfolio. 3. Determining the amount of potential return  for a given level of risk. 4. Analyzing the risk-reward tradeoffs. 5. Implementing the trade, strategy, etc.  based on the previous process.
Useful Statistics We shall look at how we can use  two  numbers in a trading system or  investment approach that are sufficient  statistics for the distribution of trading  system results. Assumptions: Each trade result is independent of  previous trades results. The probability of of a winning trade is  constant. (thus, p of losing is constant).

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Useful Statistics We shall take as an example the following  hypothetical trading system: Percent of winning trades 60% (p = 0.6) Average winning trade: \$666.67 Average losing trade: \$500.00
Useful Statistics As you can probably see, the outcome of  any particular trade is modeled as a  Bernoulli trial. What is the expected outcome of a trade? E 1 (profit) = p(Win) + (1-p)(Loss)                 = 0.6 (666.67) + 0.4 (500) =  \$200.00

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Useful Statistics In the previous example we simply use  the expected value of a Bernoulli trial. But what about the expected value of 10  trades? E 10 (Profit) = 10 E 1 (Profit) = 10 (\$200) =  \$2000 Formally:  E(Profit) = np(Win)(1-p)(Loss) Where n  is the number of trades.
Useful Statistics From the previous equation we learn a  couple of important facts. The expected profit per unit of time  will  depend on the number of trades per unit  of time. Why is this important?

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Useful Statistics 1. It helps us choose the better systems. If  two systems have the same expected  profit per trade but one trades two times  as often the latter will be better.
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}