Topic: Price vs Difficulty Charts - indicators for buying or mining - page 6. (Read 81450 times)

I'll do it, give me time:)
That chart is a non linear estimation of price/network speed using an exponential growth model.
I tried also fourier, and even ARIMA model with statistica 7 by statsoft.com, analyzing detrended daily data, there is a vague 12 days cycle not so strong,nothing exceptional apart a 90 days cycle on volume, every 3 months there is a new wave of investors buying, it seems so.

This post is very interesting.

oh man, this is pretty great. time to break out TISEAN!

Hi smooth,

i put the data I have here
https://spreadsheets0.google.com/spreadsheet/pub?key=0Arbegqx_2nKadEl5czMxZWZqazlFUzBiQkkzMFYtVEE&gid=0

Price data is available from MtGox in csv form and difficulty etc. from http://blockexplorer.com/q/nethash you can use /number at the end of the blockexplorer query to change the block size, e.g. http://blockexplorer.com/q/nethash/2016 will give data for ever 2016 blocks)

 Edit:

sorry I said above that I got price data from MtGox. In fact I got MtGox from here http://bitcoincharts.com/about/markets-api/

Anybody going to do this?  If not, please send me the time series or a script to extract it from the block chain and I will post the results.

Ah, good point.

Thanks for the graph!  It actually doesn't look much different

On the left up until October the ratio drops in about five steps.  I wonder if those are difficulty readjustments upward.

Could plot this as a shadow line against the ratio using estimated difficulty (or vise-versa).

I went ahead and did what I was asking you myself. Hope you don't mind.



Plotted the daily average price from MtGox(*10^5) over the actual difficulty on that day (rather than the implied difficulty based on the hash rate). In fact it doesn't make that much difference. You can see the latest difficulty change has had an impact, making mining less attractive as would be expected.

Anybody going to do this?  If not, please send me the time series or a script to extract it from the block chain and I will post the results.

I was thinking to use the actual difficulty from each 2016 blocks (not a moving average of 2016 blocks, the actual difficulty) because that's the difficulty when people are doing the mining - the difficult is not constantly adjusting on a 504 block moving average . So if you are looking at the price/difficulty to decide the relative merits of buying over mining then would price/actual difficulty not be better?

man i really like that second graph, wonder if Enky1974 would be nice enough to update it for us. Also, it looks like log of price may reveal some spikes in the frequency domain. Anyone do fourier analysis on this beast yet? Nonlinear time series analysis?

There are some other threads which chart difficulty against price.

In $/BTC—Difficulty Correlation chodpaba provided this graph:


And in Re: Will Bitcoin ever drop down below 2 USD? Enky1974 provided:



Also, back in November tcatm of bitcoincharts.com posted Price vs. Difficulty Graphs but the image files are missing now.  The price data I use for my charts is from bitcoincharts.com.

See http://bitcoin.sipa.be for good difficulty charts.

Nah.  We're trying measure the size/power of the network at the time, so we want to take the average hash rate over as small a window as possible.  We want to see intra-week fluctuations but not random fluctuations.  A 2014 block estimate would smooth things out more than necessary.

Doing 144-blocks (representing 6x24 hours, but more often a 12-hour estimate) is too small, producing a messy a graph of random fluctuations: http://i.imgur.com/unGHI.png

hi bitcoinBull,

great charts. Would it be better to use the actual difficulty for a particular 2016 blocks rather than the difficulty implied by the calculated hashing rate for 504 blocks?

Indeed, obviously price drives difficulty.  Less obvious other way around: difficulty driving the price. 

They are correlated, which isn't necessarily a causal relationship, but could be.

I think its causal in both directions (Two-Way Causality).

The log(price)/log(difficulty) looks almost the same: http://i.imgur.com/sytsN.png


btw, the collection of charts is here:  http://bitcoinbull.imgur.com/all/

bitcoinbull. Thanks for providing these charts. I hope to see them more frequently. Keep up the good work.

Here is the latest chart, sorry for the long delay. 

These new charts use a finer measurements: 504-block difficulty estimates and the weighted average mtgox price over the same time interval.  With a flat difficulty or 6 blocks per hour, this is 3.5 days.  But when the difficulty is doubling like it is lately, and blocks are being generated at 12 an hour, it is half of 3.5 or 1.75 days.  This number is the interval between data points.


Last update was beginning of May and price/difficulty ratio was just above 2:1.  That seemed high at the time because over the previous month bitcoin had went from an average around $1.00 to about $3.00.  So the price increased by 300% but difficulty only 50% (from around 100,000 to 150,000), so the ratio went from below one at $1.00:100,000 to over two at $3.00:150,000.

Then the price jumped to $5 and to $8 (touching $8.90 but averaging $8), sending the ratio has as just over 3:1.  So when bitcoin was at $8.00, the estimated difficulty (average hash rate over 504 blocks) was at 266,000 (8 divided by 3). 

Then the price sank down to a $6 average.  Whilst the hash rate increased even faster than before, crossing 350,000.  So $6/350,000 is 1.7 - the ratio dropped to under two.


Today.  A jump to $9.50, currently $8.30.  With the difficulty estimate of 426,000, we have a ratio of $8.3/4.26 = 1.95.

This is the on-the-fly calculation one can do to estimate the current ratio.

So even though the price jumped today to $8.3, the difficulty increase has been equal and we remain at a ratio just under 2:1.


What will happen next? 

Scenario 1)  Sideways price movement coupled with the increasing difficulty means that the ratio declines to 1:1, e.g. with a price of $10.00 when there is an estimated difficulty of 1,000,000.

Scenario 2)  Rapidly increasing difficulty is met with equal increase in price, keeping the ratio at 2:1.  For example, the price breaks $10 when difficulty estimate surpasses 500,000.  Bitcoin is at $20.00 by the time the difficulty estimate is at 1,000,000.

Scenario 3)  Another pop in price pushes the ratio back up from 2:1 to 3:1.  At an estimated difficulty of 500,000 the price goes to $15.  It could come back down as low as $10 or even lower like $7.50, while difficulty increases to 1,000,000, sinking the ratio to 1:1 or 0.75:1.


These are the optimistic scenarios.  Pessimistic scenarios, like a drop in price and/or a rapidly slowing difficulty growth, don't seem likely.  As in the chart, the record low price/difficulty ratio was around 0.75 at the beginning of April.

Am I doing something wrong?

425000/850000 = 0.51 = Mine

850000/425000 = 2 = Buy

Which graph is right?

There are additional reasons why I agree with that.

When the BTC/USD was declining, holding on to your bitcoins meant the buying power (in terms of USD) was becoming less over time. (i.e., we had "price inflation").   So selling bitcoins as soon as they were earned provided the greatest results (again, in terms of USD).

Now the opposite is happening, and thus the longer one holds onto bitcoins the greater the spending power from those coins.

There is another factor at play as well, though I only have anecdotal evidence of it occuring:
New miners appear to generally sell much of their mining output earned until their breakeven point is reached (i.e., until total revenue matches the amount invested.)  But after breakeven has been reached the bitcoin proceeds earned are kept for investment.  Many of those new miners resulting from the February boost have either recently just reached breakeven or they will be hitting that point very shortly.

Thus as the price rise results in breakeven being reached faster for many, the number of bitcoins these miners are supplying to the market decreases faster as the result.

Of course both of these contribute to and are vulnerable to cycles where found are peaks needing correction and troughs that offer a buying opportunity.

[edited]

It is also important to remember that the transaction costs involved in selling BTC for other currencies means that, at the margins, the most efficient miners are those who hoard their bitcoins.  This means that (given unchanged transaction costs) the percentage of hoarders-cum-miners relative to profit-taking-miners is usually increasing.