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I am not particularly a gold bug or even a fan of this site, but I have found this chart interesting for a long time: http://pricedingold.com/charts/DJIA-1900.

• lutusp 13y ago
  > but it definitely argues for some sort of pulsing macro business cycle. Not really. Without an explanation, it's three bumps having no significance. If you watched a sequence of coin toss outcomes, some heads, some tails, and called the heads outcomes "market surges", you would see the same kind of pattern, but without any real meaning. Remember that to a scientist, the default assumption is not that an observed pattern has significance, but that it doesn't -- it's called the "null hypothesis". There's a world of difference between describing a pattern, and explaining a pattern. More here: http://arachnoid.com/randomness http://arachnoid.com/randomness
  • api 13y ago
    Don't repeating patterns increase the likelihood that the pattern is non-random with each repetition? If you saw a graph of coin flips that showed a clear sinusoidal pattern and that pattern continued over many cycles, wouldn't it be reasonable to at least suspect that the coin was not "fair"? One cycle, maybe not. Two, okay, I'm slightly suspicious. Three, four, five? Of course the pattern says nothing about causation, just that something is biasing the output somehow. I am not a statistician but I do have a fair amount of background in things like information theory, and I find it very hard to believe that regularity has zero significance. Plug that output into Shannon's equations and compare it with a random source. Or doing VBR mp3 compression on /dev/urandom vs. a piece of music. The fooled by randomness argument can be taken too far. In a reductio ad absurdium you could argue that I do not exist because theoretically a random source could produce what I just typed. You would theoretically be correct. If you output digits of pi long enough, they will contain this text.
    • lutusp 13y ago
      > Don't repeating patterns increase the likelihood that the pattern is non-random with each repetition? 1. No, not for finite-length patterns anyway. 2. Your question is deeper than it appears, and it alludes to some complex theories about randomness. Let's say I present a series of decimal digits that is a million digits long, and I claim that they're random, in this context meaning they have no exploitable internal order (i.e. have high entropy). If you understand the risks in making assumptions about randomness, and in spite of all sorts of apparent non-random sequences within the list, you might say, "the list isn't long enough to draw any conclusion about randomness." And you would be right. My million-digit list might actually be a sequence of digits of Pi starting at some arbitrary point within Pi and extending for a million digits from that point. The list appears random, but it isn't -- it actually has very low entropy. On that basis, guess how many digits you would need to be assured that they represent a random sequence? Spoiler: an infinite number. All the principles that apply to a claim of randomness, apply to a claim of non-randomness, and for the same reasons. > I am not a statistician but I do have a fair amount of background in things like information theory, and I find it very hard to believe that regularity has zero significance. Okay. If I flip a fair, unbiased coin and record all the flips, counting heads as 1 and tails as zero, over time I will see any number of apparently significant patterns, and the longer the sequence, the more likely that I will see "significance". In a long sequence of flips of a fair coin, for any particular sequence of length n to have >= 50% probability requires 2^n flips. For example, this means after 256 flips, the chance for an uninterrupted sequence of 8 heads has risen above 50%. Therein lies the problem -- with a large enough data set, you will see all sorts of meaningless patterns. The only way to sort this kind of thing out is to: 1. Adopt the "null hypothesis" -- meaning start out assuming that a correlation means nothing, then gather evidence to contradict that assumption. In other words, don't start out by assuming what you must prove. 2. Consider alternative explanations for the tested outcome -- avoid confirmation bias. 3. Remember lex parsimoniae, otherwise known as "Occam's razor", the precept that the simplest explanation tends to be correct. And the simplest explanation is that a pattern that lacks an explanation, also lacks significance. In the final analysis, one cannot make any reliable statement about a data pattern without knowing how the sequence was generated, in other words the result data ultimately has no meaning, only knowledge of the generating function can offer that kind of significance. > If you output digits of pi long enough, they will contain this text. Yes, but that's an argument against the meaning of perceived patterns, not in favor of it.