# Dr Ernie Chan Answers to rank or weight a long or short of out this market sector according to Yahoo Finance

Dr Ernie Chan Answers to rank or weight a long or short of out this market sector according to Yahoo Finance

https://quantlabs.net/blog/2015/01/how-would-rank-or-weight-a-long-or-short-of-out-this-market-sector-according-to-yahoo-finance/

Hi Bryan,
There are various methods of including a subset of predictive
variables for returns prediction.
You can try stepwise regression, which picks successively the most
predictive variable in a linear regression, and stops when an
You can also try a regression tree, with a similar principle.
Both are available from Matlab Statistics toolbox.
Hope this helps!
Best,
Ernie

We won’t know a priori which piece of information is important, and what weight it should have.

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

# Simplest way to calculate your own beta to measure position weight allocation against portfolio or theme

Simplest way to calculate your own beta to measure position weight allocation against portfolio or theme

This calculation can be used to figure out your beta of returns of closing price. Do this in order:

2. Use both returns to run a regression. Use Excel Data Analysis option plugin pack.

3. Calculate your output range with a plot. You should see a regression summary once calculated

4. To interpret the graph, you will see the returns with an observed regression line. This is caclulated by ordinary least squares. If the index is your x axis while the Y axis is the stock, it measures the response against the index. THe line is the gradient of the slope which measures if < 1, the beta amount could be calculated the stock is defensive.

5. The beta value is displayed in the summary. The R^2 is tha variation in returns of the stock. Beta x amount can mean the returns of the stock can be explained by the stock market from a statistical POV.

6. P-values of the X variable which is beta. If < 0.05, it is considered statistically insignificant. The P-value lets you know the probability that the beta could be 0.

Hope this helps somewhat