Topic: Wall Observer BTC/USD - Bitcoin price movement tracking & discussion - page 30025. (Read 26709945 times)

Sure is slow lately =/

Sure is slow lately =/

i sure am. but there is some cause for resentment when, all other things equal, they wouldnt have 1% of BTC if they werent simply born with silver spoons in hand. clearly many smaller holders got in long before them, but have far fewer coins not by virtue of foresight or skill, but by virtue of birth. in that sense, i have far less respect for the twins than i do for many of the smaller fish around since 2010.

who's getting bent out of shape? someone mentioned jealousy and i said, yeah i am jealous.

Life ain't fair. No point getting bent out of shape about it.

There are many with far more wealth than the Winklevii with zero bitcoin holdings. Foresight, skill and/or luck certainly have something to do with their choice of holdings. If it was purely about money, then the 1% would have a much larger share of BTC in the market.

i sure am. but there is some cause for resentment when, all other things equal, they wouldnt have 1% of BTC if they werent simply born with silver spoons in hand. clearly many smaller holders got in long before them, but have far fewer coins not by virtue of foresight or skill, but by virtue of birth. in that sense, i have far less respect for the twins than i do for many of the smaller fish around since 2010.

i sure am. but there is some cause for resentment when, all other things equal, they wouldnt have 1% of BTC if they werent simply born with silver spoons in hand. clearly many smaller holders got in long before them, but have far fewer coins not by virtue of foresight or skill, but by virtue of birth. in that sense, i have far less respect for the twins than i do for many of the smaller fish around since 2010.

For example, I claim that on Feb/22 the price will be between 300 USD and 2200 USD with 95% probability.

You sound jealous.

You sound jealous.

Here is my prediction for the coming month:



The plot shows the Bitstamp prices from Nov/2013 to Jan/2014 (purple) and estimated lower and upper bounds for Feb/2014 (green).  I claim that, in any 1-hour interval in the coming month, the Bitstamp price will be within the two green lines above, with 95% probability.

For example, I claim that on Feb/22 the price will be between 300 USD and 2200 USD with 95% probability.

(Note that this is not the same thing as saying that the entire price plot will stay in that region for the whole month with 95% probability.)

This prediction is based on the simple "log Brownian" model that I described a while ago.  Namely, it assumes that the price change from one 1-hour interval to the next, in log scale, is a normal random variable that is independent of the previous history. 

More precisely let P(i) be the weighted mean transaction price in the 1-hourinterval number i.  Let Z(i) be log_10(P(i)). The model assumes that

  Z(i+1) = Z(i) + C*RAND(i)

where the factors RAND(i) are independent random variabls with zero mean, unit deviation, and Gaussian distribution.  Therefore, for any n > 0,

  Z(i+n) = Z(i) + C*sqrt(n)*RAND(i,n)

where factors RAND(i,n) are again random (but not independent) variables with zero mean, unit deviation, and Gaussian distribution.

Analysis of the Bitstamp prices from Sep/2013 to Jan/2014 yields 0.00964 as the best fit for the parameter C.

Since 95% of the probability of the Gaussian distribution is within 2 deviations of the mean, the model implies that, n steps in the future,
the value Z(i+n) will be within the values

  Zmin(i,n) = Z(i) - 2*C*sqrt(n) and
  Zmax(i,n) = Z(i) + 2*C*sqrt(n)

with 95% probability, where Z(i) is the current (last known) price.  The green lines are these two bounds, converted back to linear scale (Pmin(i,n) = 10**Zmin(i,n), etc.)

More specifically, according to the model, at any specific 1-hour interval i+n in the future, the log price Z(i+n) will be

   below Zmin(i,n) with 2.5% probability;
   between Zmin(i,n) and the current price Z(i) with 47.5% probability;
   between the current price Z(i) and Zmax(i,n) with 47.5% probability;
   above Zmax(i,n) with 2.5% probability.

Note that, by this model, the future prices P(i+n) may be on either side of the current price (red line) with equal probability, even though the inverse log mapping yields a much wider range above than below.
 
Of course this model is quite rudimentary and basically useless for traders.  There may be more sophisticated models, but I doubt that they can yield better predictions. 

(The Brownian model is visibly inadequate for small n, since the log price increments from one interval to the next do not have a Gaussian distribution.  As a consequence, the 2*sigma interval Zmin(i,n) to Zmax(i,n) contains somewhat less than 95% of the probability.  However, by the Law of Large Numbers the distribution becomes almost Gaussian after a few hours. )

(before people ask: no, a model with a linear "historical trend" term Z(i+n) = Z(i) + T*n + C*sqrt(n)*RAND(i,n) does not seem appropriate, and its predictions for the next month would not be significantly different.)

I really dont like these Winklevossies. It seems they only try to make more money outta other people hard work and with daddy's money. They dont see the interest in bitcoin but only that grabbing 1% of it all would make them richer. They just pretend to be so smart but they just seems to get f**cking second if not last all the time.

ergo Zuckerberg ditched them
ergo Satoshi (and even FBI) got way more BTCs than they can ever dream of
ergo them ETF is far from opening.
ergo i wont consider a single news related to them as they mean nothing.

Here is my prediction for the coming month:



The plot shows the Bitstamp prices from Nov/2013 to Jan/2014 (purple) and estimated lower and upper bounds for Feb/2014 (green).  I claim that, in any 1-hour interval in the coming month, the Bitstamp price will be within the two green lines above, with 95% probability.

For example, I claim that on Feb/22 the price will be between 300 USD and 2200 USD with 95% probability.

(Note that this is not the same thing as saying that the entire price plot will stay in that region for the whole month with 95% probability.)

This prediction is based on the simple "log Brownian" model that I described a while ago.  Namely, it assumes that the price change from one 1-hour interval to the next, in log scale, is a normal random variable that is independent of the previous history.  

More precisely let P(i) be the weighted mean transaction price in the 1-hourinterval number i.  Let Z(i) be log_10(P(i)). The model assumes that

  Z(i+1) = Z(i) + C*RAND(i)

where the factors RAND(i) are independent random variabls with zero mean, unit deviation, and Gaussian distribution.  Therefore, for any n > 0,

  Z(i+n) = Z(i) + C*sqrt(n)*RAND(i,n)

where factors RAND(i,n) are again random (but not independent) variables with zero mean, unit deviation, and Gaussian distribution.

Analysis of the Bitstamp prices from Sep/2013 to Jan/2014 yields 0.00964 as the best fit for the parameter C.

Since 95% of the probability of the Gaussian distribution is within 2 deviations of the mean, the model implies that, n steps in the future,
the value Z(i+n) will be within the values

  Zmin(i,n) = Z(i) - 2*C*sqrt(n) and
  Zmax(i,n) = Z(i) + 2*C*sqrt(n)

with 95% probability, where Z(i) is the current (last known) price.  The green lines are these two bounds, converted back to linear scale (Pmin(i,n) = 10**Zmin(i,n), etc.)

More specifically, according to the model, at any specific 1-hour interval i+n in the future, the log price Z(i+n) will be

   below Zmin(i,n) with 2.5% probability;
   between Zmin(i,n) and the current price Z(i) with 47.5% probability;
   between the current price Z(i) and Zmax(i,n) with 47.5% probability;
   above Zmax(i,n) with 2.5% probability.

Note that, by this model, the future prices P(i+n) may be on either side of the current price (red line) with equal probability, even though the inverse log mapping yields a much wider range above than below.
 
Of course this model is quite rudimentary and basically useless for traders.  There may be more sophisticated models, but I doubt that they can yield better predictions.  

(The Brownian model is visibly inadequate for small n, since the log price increments from one interval to the next do not have a Gaussian distribution.  As a consequence, the 2*sigma interval Zmin(i,n) to Zmax(i,n) contains somewhat less than 95% of the probability.  However, by the Law of Large Numbers the distribution becomes almost Gaussian after a few hours. )

(before people ask: no, a model with a linear "historical trend" term Z(i+n) = Z(i) + T*n + C*sqrt(n)*RAND(i,n) does not seem appropriate, and its predictions for the next month would not be significantly different.)

I want expancive coins.

Here is my prediction for the coming month:

I really dont like these Winklevossies. It seems they only try to make more money outta other people hard work and with daddy's money. They dont see the interest in bitcoin but only that grabbing 1% of it all would make them richer. They just pretend to be so smart but they just seems to get f**cking second if not last all the time.

ergo Zuckerberg ditched them
ergo Satoshi (and even FBI) got way more BTCs than they can ever dream of
ergo them ETF is far from opening.
ergo i wont consider a single news related to them as they mean nothing.

For example, I claim that on Feb/22 the price will be between 300 USD and 2200 USD with 95% probability.

I want expancive coins.