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NoDaddyNo
New member
Here are the trading stats for spreading it over all tickers given.
For instance, if you are given 10 stocks that are predicted to move, and you had N dollars to spend - you would spend N/10 on each stock.
Then if it went up the amount it is supposed to, sell it off, otherwise, if the time goes by and it isn't up enough, sell it off.
(this is traded over a 30 day period)
For 2% over 21 trading days:
Return on $10K: 8902.91
Return on $50K: 49543.14
Return on $100K: 100341.57
Return on $250K: 252750.66
Return on $500K: 506757.02
Return on $1M: 1014762.78
(traded over a 30 days period)
For 1% over 5 days:
Return on $10K: 5822.31
Return on $50K: 47205.26
Return on $100K: 98940.77
Return on $250K: 254151.50
Return on $500K: 512827.68
Return on $1M: 1030184.17
That shows that you can make good money if you have more to spread out over it. But it is generally a waste to use that method if you don't have at least $250K to put into it.
The $1M starting point would return about 30% on the year with the 1% over 5 days code, and the 2% over 21 days would return over 17% on the year.
I am now going to modify the stats code to see what it would do if you only traded with the higher volume stocks that it predicts (spread your money out over all the stocks given as long as they are high volume).
I will later do one with low volume as well just to show how it does (not well I would imagine).
Whichever trading scenerio you went with, you would have better chances by putting it into higher volume stocks since the money wouldn't have as much as an effect, wouldn't be noticed, and the accuracy is higher in those as well.
Spreading it out this way helps negate some of the risk involved - but as a result, also negates some of the possible gains as well of course.
All of the simulated trades have a $20 trading fee used on execution of sell or buy.
For instance, if you are given 10 stocks that are predicted to move, and you had N dollars to spend - you would spend N/10 on each stock.
Then if it went up the amount it is supposed to, sell it off, otherwise, if the time goes by and it isn't up enough, sell it off.
(this is traded over a 30 day period)
For 2% over 21 trading days:
Return on $10K: 8902.91
Return on $50K: 49543.14
Return on $100K: 100341.57
Return on $250K: 252750.66
Return on $500K: 506757.02
Return on $1M: 1014762.78
(traded over a 30 days period)
For 1% over 5 days:
Return on $10K: 5822.31
Return on $50K: 47205.26
Return on $100K: 98940.77
Return on $250K: 254151.50
Return on $500K: 512827.68
Return on $1M: 1030184.17
That shows that you can make good money if you have more to spread out over it. But it is generally a waste to use that method if you don't have at least $250K to put into it.
The $1M starting point would return about 30% on the year with the 1% over 5 days code, and the 2% over 21 days would return over 17% on the year.
I am now going to modify the stats code to see what it would do if you only traded with the higher volume stocks that it predicts (spread your money out over all the stocks given as long as they are high volume).
I will later do one with low volume as well just to show how it does (not well I would imagine).
Whichever trading scenerio you went with, you would have better chances by putting it into higher volume stocks since the money wouldn't have as much as an effect, wouldn't be noticed, and the accuracy is higher in those as well.
Spreading it out this way helps negate some of the risk involved - but as a result, also negates some of the possible gains as well of course.
All of the simulated trades have a $20 trading fee used on execution of sell or buy.
