Poll
Question: Closing BTC Price June 28:
$0 - 5 (2.6%)
<$7,000 - 4 (2.1%)
$7,000-$7,499 - 0 (0%)
$7,500-$7,999 - 0 (0%)
$8,000-$8,499 - 1 (0.5%)
$8,500-$8,999 - 3 (1.6%)
$9,000-$9,499 - 4 (2.1%)
$9,500-$9,999 - 27 (14.2%)
$10,000-$10,499 - 26 (13.7%)
$10,500-10,999 - 15 (7.9%)
$11,000-$11,499 - 14 (7.4%)
$11,500-$12,000 - 17 (8.9%)
>$12,000 - 59 (31.1%)
>$20,000 - 15 (7.9%)
Total Voters: 190

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Author Topic: Wall Observer BTC/USD - Bitcoin price movement tracking & discussion  (Read 21253638 times)
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CoinDox
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February 19, 2014, 12:06:24 AM

The Chinese Slumber Method Prediction almost worked this time!!!

Checking the prediction for Huobi

Prediction posted: Tuesday 2014-02-18, 01:14 UTC
Prediction valid for: Tuesday 2014-02-18, 19:00--19:59 UTC (not before, not after)
Huobi's predicted price:  3860 -- 3920 CNY (3890 plus or minus 30)
Huobi's actual price (L -- H): 3810 -- 3824 CNY (3817 plus or minus 7)
Error center-to-center: 73 CNY

The prediction is the rightmost blue rectangle in the chart below, just above the red/green price bars. 

The big dots on top of the price plot are the Slumber Points (prices at 19:00 UTC every day).  The True points (yellow) are those which had nearly zero trading volume at 19:00; the False ones (olive-brown) are those where Huobi's clients and/or their robots kept trading through the night.

The yellow line is the least-squares-fitted  trend line that was used to make the prediction.




Checking the prediction for Bitstamp

The Bitstamp predicition is the Huobi prediciton divided by 6.12

Bitstamp's predicted price: 625 -- 645 USD (635 plus or minus 10)
Bitstamp's actual price (L -- H):  617 -- 625 USD (621 plusor minus 4)
Error center-to-center: 14 USD

In the chart below, the dots are Huobi's Slumber Point prices divided by 6.12 (or 6.40  for feb 7--9)




I appreciate your combined use of regression analysis and volume analysis Smiley

Houbi's artificially inflated trading activity is well known by now, and I am glad to see someone using a creative fit of analytical tools to play of off this information. By combining the points of a linear regression trend line with the understanding that the best time to measure the underlying direction of Houbi is at points of low-activity, you have really created a good understanding of the general trend of the asset in that exchange.