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Author Topic: Sounds of Gox (the last 24 hours)  (Read 1220 times)
bb113 (OP)
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July 17, 2012, 12:46:33 AM
 #1

In case the person with the big walls is around. Here is the song you played today:

http://www.youtube.com/watch?v=6GzzBI5bOJk

Now how can sonification be used to speculate?
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ElectricMucus
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July 17, 2012, 12:55:21 AM
 #2

Why assign the price to pitch?

The plain market data would sound far more interesting. Of course you won't capture the big movements because you have to consider it a dc offset but you could pitch-shift as much as possible into the audio range. This way natural oscillations would be recognizable, like a high pitched baseline from the bots and the more interesting part of noisy movements & swings.  Grin
bb113 (OP)
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July 17, 2012, 01:00:16 AM
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Sounds interesting but what do you mean by "plain market data"? Something needs to get assigned to pitch. Do you mean treat the volume of each buy or sell as a click, then treat those clicks like samples of a wave?
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July 17, 2012, 01:17:47 AM
 #4

LOL

could be better, but I like it Cheesy


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July 17, 2012, 01:20:54 AM
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I prefer "The Screams of Gox".  By the Bears.
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July 17, 2012, 01:23:52 AM
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Sounds interesting but what do you mean by "plain market data"? Something needs to get assigned to pitch. Do you mean treat the volume of each buy or sell as a click, then treat those clicks like samples of a wave?
yes

Every tick would be a sample. The volume could be used to do some stereo mangling (phase difference for example). Pitch shifting because the frequency range would be beyond the hearing range of 10 octaves.

Your approach isn't that bad either, read up on granular synthesis to perfect it Wink
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July 17, 2012, 01:43:37 AM
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I prefer "The Screams of Gox".  By the Bears.

hilarious


Sounds interesting but what do you mean by "plain market data"? Something needs to get assigned to pitch. Do you mean treat the volume of each buy or sell as a click, then treat those clicks like samples of a wave?
yes

Every tick would be a sample. The volume could be used to do some stereo mangling (phase difference for example). Pitch shifting because the frequency range would be beyond the hearing range of 10 octaves.

Your approach isn't that bad either, read up on granular synthesis to perfect it Wink

Sounds like a plan. I just started messing around with this concept, I'd like to mess around with topological-like data using it as well and see if anything useful can come of it.
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July 17, 2012, 09:11:28 AM
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This is fantastic! More please!

Bitcoin combines money, the wrongest thing in the world, with software, the easiest thing in the world to get wrong.
Visit www.thevenusproject.com and www.theZeitgeistMovement.com.
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July 17, 2012, 10:02:11 AM
 #9

I really enjoyed this. Thank you

Suggest though it goes offtopic

don't let me make you question your assumptions
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July 17, 2012, 10:24:00 AM
 #10

Sonarify (is that a word?) mtgox up to a depth if 32 on each side, grouped by 0.01USD.

Pitch, length and volume of the sound should be determined by volume,  price, and updated every change in each.

would sound like whales, i guess.... but still cool!
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July 17, 2012, 02:02:48 PM
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Sounds interesting but what do you mean by "plain market data"? Something needs to get assigned to pitch. Do you mean treat the volume of each buy or sell as a click, then treat those clicks like samples of a wave?
yes

Every tick would be a sample. The volume could be used to do some stereo mangling (phase difference for example). Pitch shifting because the frequency range would be beyond the hearing range of 10 octaves.

Your approach isn't that bad either, read up on granular synthesis to perfect it Wink

Your ideas about sound mangling are hideous. Hideous i tell you!
You cannot change phase by modulating amplitude (well, actually, to be completely nerdy, you do sortof distort the phase temporarily while the volume change is in the process of actually changing, but its nothing like you mean).
You don't want to pitch shift, you want to reframe the data into hearable frequencies, which in this case would be a simple rescaling of a frequency representation of the data.
Anyway, the above 'auralisation' is pretty useless.
No new information is presented in the audio that could not be observed in a single gaze at the actual data.
Also, it is horribly coarse.

It may be interesting to hear high res derivatives of the original data, but making the sound meaningfull is just going to be very difficult, no matter how you look at it.
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