Intro to crude position manager for cyrpto currency algo trading
This video focuses on a crude ‘position manager’ which I have shown many examples, I say crude, this is because there are so many bugs still in this. There also so many various conditions to factor in but most of my focus will be in this area. I would think this part of the entire will be the most valuable as it will:
calculate the up and lower range of current (or original) price +- a multiplier of 3 * average true range. This is will be the range that states with a equivalent of of a virtual trailing stop.
calculate up and lower range of current price .+- with a multiplier of 1*average true range.
This is fully explained in my video.
Note that I do stress this is theoretical with the ranges explained above.
How to protect your account with this virtual position manager
As you know, I like using this method to protect your account especially if your broker/exchange has a market making division. If you signal back your stop losses, your broker/exchange can prematurely kick you out of a potentially very profitable trade. With this virtual way, you can pretty well guarantee this will not happen as many brokers are corrupt in manipulating your trading potential. I have many videos on this exact topic.
This position manager will have some very helpful into on the latest info on your pricing targets once your positions is put on. This will be very useful if you plan to use the Analytics service.
NOTE I now post myTRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!
regression <— most appropriate line but available in Visual Jforex but part of Jforex
in visual jforex (under trend indicator):
fib pivot not appropriate
trend envelope most appropriate
wadded at may work combine with trend envelope
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:
1. Download the closing price of your stock and index( i.e. S&P 500) to calculate returns
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.