How you could have made massive gains in 7 months buying selling Bitcoins - Results that might help you ahead

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This paper (version 2) focuses on an extremely simple method for predicting bitcoin price trends, not prices, and is intended to provide we non-pro's a simple way to achieve large gains in a short period of time without risking lots of money.

Price volatility is the 'bane' of investors, especially when price is not trending up — But volatility is the 'boon' of traders, no matter what the price trend is, up, down or steady. Investors hate volatility, traders love it. We are not aware of any other price-prediction tools that do not use price data to predict prices. We are also not aware of any other price-prediction tools that do not require a computer, except what we are showing in this paper.

What is a Run? A Run is the number of days bitcoin price remains UP or DOWN — e.g. if price is up 2 days, that's a positive 2-day Run 2, down 2 days, a negative 2-day Run -2

Here's a 4-year summary of bitcoin Runs from July 18, 2010 to July 18, 2014 when price increased from $0.0.0858 to $628.22 (Coindesk):

Table 1
 Runs # #  Days Runs Range 
# Days
# of Diff
Runs
 Average
Run Days
 Run Average
Gain/Loss
 Positive  353  812  +1 to +10  10  2.30  11.51% 
 Negative  353  649   -1 to -8    8  1.84  -6.58% 
Total  706  1461   18   

Table 1 suggests, not surprisingly, that enormous theoretical gains could have been achieved buying the same amount on positive-Run opens and selling on positive-Run last-day close, 353x11.51% = 4064% assuming no fees, commissions and 'misses' and no reinvestment. Even more astounding, but not surprising too, $100 invested on July 18, 2010 would be worth 
$628.22 / 0.0858 * 100 = $732,191, nearly a million dollars on July 18, 2014.

This raises the very basic and important question — How do we know as soon as Runs begin and end? Trying to help answer this question, we spent an enormous amount of time analyzing statistical probabilities of every positive and negative Run occurring (Table 3). Then we analyzed the probabilities of what Runs occurred after every one of these Runs. 

From these analyses, something became clear that we should have realized before doing the massive probability analyses — Every positive Run begins when every negative Run ends, and vice versa. 

Eureka! All we would have to know is when the next day after a negative Run appears to be positive, or an up day. Then we could buy on the today negative day close to catch the next-day positive, or up day open. Similarly, the last day of a positive, or up Run would be when the next day appears to be a negative, or down day. Looks very simple — but not guaranteed to identify all positive, or up Runs' beginnings and ends because price trends can and will change within a day due to unexpected adverse events, like bad news midday. See Table 3 below for Bitcoins Runs Data July 18, 2010 to July 18, 2014.

So, here it is folks — Simple, easy to understand, no computer required and you should be able to make money even when bitcoin price is trending down: 
  • How to buy bitcoin at best possible time? 
    Buy on any day bitcoin closes down and the next day appears to be positive, or an up day.

  • How to sell bitcoin at best possible time? 
    Sell on any day bitcoin closes up and the next day appears to be negative, or a down day.
One result from the statistical analyses in Table 1 might help you decide whether the next day will be up after a down day — Positive days occurred 55.58% (812 / 1461) of the time and negative days 44.42% in 1461 days. Even if you just flipped a coin after every down day, you could be right 55.58% of the time predicting next day positive or negative. If you were wrong, you could know quickly (hours) to sell your position with little loss.

A lot of you 'bitcoiners' appear very smart. I would guess that if I asked you all at the close of a down day whether the next day will be up or down, you and most of the other 'bitcoiners' would predict correctly. Where we all have trouble is long term predictions.

If you're still not confident predicting whether the next day after a down day will be an up day, here's a suggestion — Do not buy immediately on down day close, but wait until, say midday, next day to see if it's going to be an up day. Chances are if it's up by midday, it will probably be up at least by the close and maybe up for more days if it's the beginning of a Run >1. You will just be giving up a part of that first up-day's gain.

To decide when to sell, you can do the same on the day you think next day will be a down day — wait until, say midday, next day to see if it's going to be a down day.

We put this non-computer method to a test from Dec 15, 2013 to July 18, 2014 assuming 2% commissions, fees and 'misses' using $100 invested on Dec 15th, then reinvesting all proceeds from the previous positive Run in next positive Run:

  • Chart 1 and Table 2 below show that $100 invested returned $1,037.37 
     a gain of 1,037% in 7 months
     assuming 
    2% commissions, fees and 'misses.' 

  • The maximum possible gain with no commissions, fees and 'misses would be $2986.11.  
    Commissions, fees and 'misses' of 6.40% would break even.

  • Chart 1
    20140825 Bitcoin profit 1,000%+ buying all (+) Runs immediately after price turns UP from DOWN selling after price turns DOWN from UP from Dec 15, 2013 to July 18, 2014 718x654.png
    Chart 1 Bitcoin profit 1,000%+ buying all (+) Runs immediately after price turns UP from DOWN
    selling after price turns DOWN from UP from Dec 15, 2013 to July 18, 2014


    Table 2
    20140825 Bitcoin Chart showing $1037.37 gain investing $100 initially then reinvesting on each first price UP after last price DOWN 473x1371.png
    Table 2 Bitcoin profit 1,000%+ buying all (+) Runs immediately after price turns UP from Down
    Selling after price turns DOWN from UP from Dec 15, 3013 to July 18, 2014
    Source: Bankless Money         Aug 25, 2014


    Table 3
    29140825 Bitcoins Runs Data July 18, 2010 to July 18, 2014 800x407 .png
    Table 3 Bitcoins Runs Data July 18, 2010 to July 18, 2014


    Aug 25, 2014