Ok, random #7:
Your said, we get to 375 to 385. Real price was 425$. Error: 10.5%
Counter prediction: "price now will be price in 24hours": Error: 1.2%
If you know
statitics and assume a normal distribution, you know how unlikely your real prediction error is only 1.3%. It is rather like 5-7% and worse like the counter prediction. 7 random tests are a lot. 7 times an 500% error in a row.
Again: I don't say 7 random predictions are enough to to measure your
accurancy. I just say disprove the average error of 1.3% for real predictions.
Ok, another one:
Current price: 414.3$
Your neural network predicts: 417$
The good thing is, that this time, the counter prediction(same price in 24h) will be not really better than your neural network prediction
You're obviously not reading anything that I'm writing at all. Here is an equally biased method of measuring error to yours: at 11am EST, it says the price will be $410.1. Let's see how far off that is. Then I'll measure the prediction for one hour after that and we'll see how far off it is. I'll average those two numbers and say that is the average error of the entire system.
Please, can we stay at UTC. I am not from the east cost. In Germany we have summer time, so 2 hours instead of 1 hour off. This is confusing enough.
So your system predicted 417$ for 1pm 14.April. Let's look a the actual price: Oh, over $450. So the error was 8%.
In this times, when the price is not moving, you error might be really low. But same with the prediction "price in 24h is the same like current price".
Look at the 24h predictions of the last 4 days (so 72 predictions). The average error was 1.05%.
New prediction:
23.4.2014 6pm. Current price 485$. Your prediction for 24.4.2014 is 494$.
And once again, I don't see how you can take 6 measurements, compare them to my 40,000 or so (recalculated every hour, so really I've taken somewhere around 30 million measurements), and say that yours are more accurate than mine. The ONLY way you can do any reasonable test of accuracy would be if you did what I describe in the previous post. Until you do, please don't post here with your "random" measurements claiming that my neural network (which will almost definitely predict more accurately than any human) has an average error of 5+%. Your methods of calculations are terrible and your data is misleading and just straight up false. I don't believe that you know anything about statistics.
No it isn't. What is your standard deviation or the measurement error? I don't have that data. I am not on your page every hour. But fair enough. With stable prices your predictions seems to result in low errors. I know I cannot proof that I took 7 random samples. The last 8% error was in fact random like you could see. But I know it was random. And 6 measurements 500% over the claimed average error is huge and make it highly unlikely that your average error is that low.
Let's compare that. For sure there is no normal distribution because your error can only be 1.2% off in one direction and limitless in the other direction. So we can compare this more like the income distribution of US households. The median income level is about 50 000$. So every second random picked household should get us an income below 50k. Over 250 000$ accounts only for 2.3%. So let's pick 6 different random households and let's see how much they earn.
-> All households over 250 000$, 5times more than the median. How high is the possibility? 0.023^6. So to be 500% off you need in average 7 billions picks to get that result. (I know median and average are different, but to be honset, this doesn't improve the odds). So please don't tell me that 6 random picks are meaningless. And the 7th was 800% off again.
But fair enough, I have no idea over how many predictions you calculate your average error. So I think over many thousands?
Ah you still don't get the think with learning and test data. You claim you made 40,000 predictions. You would need 4.5 years for that. So you didn't! I tested the real prediction into the future. You didn't!