If you have not yet read this post, please do so first, and try to draw your own conclusions about which charts are random and which are not.
So the lesson here is that random data can look a lot like market data, and a lot of the patterns we (think) we see in markets can actually be generated by randomness. You can interpret this in many ways, but for me the lessons are that markets are a lot more random than we think. As traders, we really do not have an edge very often. (There is no edge possible in a purely random market, contrary to some of the suggestions in the comments to these last posts. For instance, all a good money management strategy will do in a random market is cause you to lose money more slowly as the vig (slippage, commission, the spread, financing costs, etc) slowly chips away at your capital.) It is, therefore, extremely important that we wait and pick our spots well.
As you struggled to sort out which charts were real (and if you haven’t done so, please do it before skipping to the answers), I hope you made notes for why you thought some were real and some were random. In my opinion, this is where the lesson is. There are, in fact, slight non-random elements to markets that make this exercise just barely do-able. For instance, volatility is often identifiable as a non-random element. Volatility shocks (an academic term, but a useful one. Think of a quiet market reacting to sudden news.) tend to persist. What this means from a practical standpoint is that the ranges of bars usually fluctuate in less-than-random ways: A sudden large bar will usually be followed by more large bars and vice versa. (For those of you who like math, there are a number of price models that capture this tendency in various ways.) It is extremely odd to see a very large bar followed by a tiny bar… but even then, anything can happen. If you haven’t done the game yet, approach it with that tool in your toolkit and see if it helps. Two approaches I have seen people try that will probably mislead you are to look for runs of white or black candles, or support and resistance. These appear just about the same to the naked eye on random charts as real charts.
Just so you know, I generated these charts as part of another project, but I had someone rename the files so I would not know which were real and which were fake. (Why? Because I thought it would be fun to try to tell the difference. We can debate my definition of “fun” later…) Here are my notes from my attempt to tell the difference. I correctly identified 4 of the fakes, and missed one. The fakes are: A,B, F, G, and J. Here are my guesses and my reasons. I am not saying this is the only way or the right way to think about it, but maybe my thought process will be interesting to some of you:
A – I guessed FAKE and was correct. There is a bar where H=L=C=O, which should never happen in an active trading day. This is theoretically possible on a very low volume (maybe preholiday) session, but extremely unlikely. At any rate, the rest of the chart was too active for this to have occurred. This one was a free gift. Had that bar not existed, I still would have guessed fake due to the presence of tiny bars near the extremes of some large bars. This is a price pattern that just does not happen very often.
B – I guessed FAKE because of the structure of the long string of white candles. This suggests a trend that picks up steam and then slows down… very unlikely to have this series without a black bar in real market data. Someone else who did this exercise said that this chart had to be real because you would not have 12+ bars close in the same direction due to randomness. This, actually, is one of my main points in this whole series of articles–it is very easy to underestimate how “streaky” random data can be.
C – I guessed REAL (without a ton of confidence) and was correct. I think I see typical consolidations and breaks through the low of the day, and the multiple strings of black candles with long consolidations in between also feel “real” to me.
D – I guessed REAL (with high confidence) and was correct. This is extremely typical trend day structure, inflection points come at the right time of day, and it just feels real. I know this could be random but I’m willing to take a big bet that it’s not.
E – I guessed REAL and was correct. Not a lot to go on here, but the 10:00 bar looks like a reaction to an economic number to me, so that’s enough to go on. If I didn’t have the first part of the day, I don’t think I would have gotten this.
F – I didn’t vote on this one, couldn’t decide. It was FAKE. On one hand, I see that the volatility profile of the day is bizarre. Very quiet morning, and then it goes crazy, but the afternoon looks like a reasonable reaction to that. I don’t know, maybe this is reaction to some very strange news item. I also think I see some short-term patterns that feel real to me. If I had to vote I would have guessed REAL and been wrong, but I just didn’t make a decision on this one.
G – Another O=H=L=C candle, so another giveaway. This one is obviously FAKE. Ugh… this is a problem I should correct if I ever do this again. Regardless, it is very unusual to see so many “violent” up bars followed by down bars, etc. I would like to think I would have seen that anyway, but as a valid test, this one is shot because of the little doji.
H – I guessed real and was correct. Classic trend day in every respect… so many little details that are unlikely to be random. Could be, but not likely.
I -I guessed REAL (with low confidence) and was correct. I am thrown off by the fact that the inflection points and shocks seem to be at random times of the day, but I also see such clear trend structure that it feels real. Most importantly, the volatility profile looks right… tightening consolidation, followed by breakout which leads to trend.
J – I guessed FAKE and was correct. My notes say “too weird”, and that pretty much sums it up.
So, there you go. Hope this was fun (and sorry the answer key was delayed!) I think another lesson is that it is much easier to tell trending real markets from random data. Randomly generated data will have trends, but there are some slight differences that will often be easier to catch than in trading ranges. There is a reason that I keep saying the best technical edges are to be found in trending markets rather than ranges….