That's interesting - page 25
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. I don't want to repeat the same thing a second time. So, I'll be brief - it all depends on what is meant by TA. (For example, see the quote from Elder, taking into account the explanations about "psychology".)
The semantic content of the quotes is pure shamanism, dancing with tambourines
. I'm the leader of the people's movement, "the simpler, the better!" ;)
Yeah, but simpler is not better.
. You know, I personally don't like what I saw in the picture. But at the same time, I admit that I have no idea how and what was tested. So, my "liking - disliking" should not bother anyone. My favourite rule about "deposit dynamics should not follow the price dynamics" is only my rule. Yes, I was able to prove to myself, with sufficient accuracy for me, that this semi-empirical rule is a reflection of the properties of martingales. So what - all this matters only to me. Others may not give a damn about it all. I wish you do too!
I frankly confessed - and I do not like the "crookedness". You also understand, no optimisation was carried out. The system made its own decisions.
. Not the completeness of martingale - it's so insidious, so not permanent...
Are you cynically mocking me?
. Dear fellow citizens, you are so restless. I told you, I don't want to discuss these matters. So here's my rebuttal.
Do I understand correctly that if a market model is found, it will be formulas that can predict BP probabilistically.
. The question is inherently flawed. At least in its two assumptions.
It seems that the weather model (formulas) is no more complex than the market model. Some existing weather models are able to make high probability weather predictions for small periods of time.
Obviously, the more information the model has, the more likely the forecast. You can't get all the information, of course.
. My understanding is that, for you, the pain of pinched balls is much more evident in practice than in theory. So, go ahead! stretch the weather model into the market. And please, no need to share your feelings with me afterwards.
The semantic content of the quotes is pure shamanism, dancing with tambourines
. Elder is not my favourite author. It's just that his quote was the first to come up. My favourite quote is " ...But the point of the game is still to find out what everyone else is doing. (c) Adam Smith. Essentially the same thing as Elder's, but in a much more appealing form to me.
Yeah, but it doesn't get any simpler than that.
I honestly admitted it - and I don't like the "crookedness". You also understand, no optimisation was carried out. The system made its own decisions.
. Well, you tell me.
Are you cynically mocking me?
. Not at all. I just think you should put your efforts in the right direction... But we've already discussed it, so there's no point in going back there again.
Do I understand correctly that if a market model is found, it will be formulas that can predict BP probabilistically.
A market model is too general and complex. A model of individual processes that will help to make money at some point in time.
It seems that a weather model (formulas) is no more complex than a market model. Some existing weather models are able to make high probability weather forecasts for small periods of time.
Obviously, the more information a model has, the more likely the forecast. You can't get all the information, of course.
it is obvious if we are obliged to always give a forecast, not when we know how to do it.
Such models are built on the assumption of individual group actions. Trying to make a trade before they act coherently enough to create a move. After all, a speculator's gain is always someone else's loss or shortfall in profits. If earnings are systemic/regular, it's a systemic loss (or shortfall in profits) for some participants. Not necessarily the same ones every time, but acting in a similar way.
Assumptions about the processes for a particular market are made on the basis of gathering information about the market. Who the participants are, what their interest is, what tools and methods they use, what constraints they have (time, legislation, risk management), etc.
A purely statistical approach is also possible, but then more statistics are needed than when the model has been found based on fundamental assumptions about the processes of a particular market.
There is talk of breaking up the market into familiar chunks-processes. Identification of such pieces still goes by BP. It's like dividing the market into pieces of flat and trend, which are not difficult to trade.
So, by analogy with flat and trend, the approach is not clear. So we have broken the history into pieces, and what? Making an early identification is the same as fitting it with formulas.
But it is possible to make formulas out of spite, and it is possible on the basis of some considerations. For example, that cash flows are sedentary:
If we imagine that the bulk of the market's money is stored in one place - a BANK - and the money is distributed among its clients. Then the trading of customers among themselves within the BANK does not cause cash flows, despite the formation of prices as supply-demand. The money hardly goes anywhere. If the potatoes can be eaten, the money is not so easy.
There is talk of breaking up the market into familiar chunks-processes. Identification of such chunks goes by BP anyway. It's like dividing the market into pieces of flat and trend, which are not difficult to trade.
So, by analogy with flat and trend, the approach is not clear. So we have broken the history into pieces, and what? Making an early identification is the same as fitting it with formulas.
But it is possible to make formulas out of spite, and it is possible on the basis of some considerations. For example, that cash flows are sedentary:
If we imagine that the bulk of the market's money is stored in one place - a BANK - and the money is distributed among its clients. Then the trading of customers among themselves within the BANK does not cause cash flows, despite the formation of prices as supply-demand. The money hardly goes anywhere. If potatoes can be eaten, money is not so easy.
This is roughly what it's about. Identifying that the process is ours (the one we studied) and something can be gained. It is a probabilistic prediction that adhering to a certain strategy will result in an average profit as long as the process objectively exists. We are predicting that the process has certain properties, which are preserved from deal to deal and which lead to a certain behavior of the price.
But statistical research is more appropriate for FX as the market is fairly closed to outsiders. But again, one can study statistically not just by testers of some strategies, but by marking certain moments and studying the properties of the price in them. Although the results of strategy testers are also statistical research, if they are interpreted correctly. On the basis of the results of the studies, if there is something to hold on to, we should try to generalize the results, simplify and assume what we are dealing with. It is a bit of a gut feeling and it takes a lot of time and statistics to study. At least we have to take into account that we are studying individual processes, which are usually very limited in time. Not to mix everything up.
From the simple to the complex:
The market is an alternation of flat and trend pieces. Let's build two strategies: one for trend and one for flat.
Let's run each one on the history, get BP of Equity changes. Let's name them Equity_Flat, Equity_Trend.
We should change the weight coefficient Koef so that Equity_BEST[i] = Equity_Flat[i] * Koef[i] + Equity_Flat[i] * (1 - Koef[i]) would curve upwards (type of curve not considered). I.e. we need to see what the time series of Koef coefficients looks like.
Obviously, it would be a kind of "sine wave" (varying from 0 to 1) with constantly changing half-period. The use of the word "sine wave" is, of course, for clarity. We would need to see how the half-periods (distances between neighbouring local extrema) change.
Let us plot the BP of the half-periods. Let us look at its MO (mean), variance (RMS). Let us analyze how its different sample MO and variance change with shifting sliding windows and from the window size itself. On the basis of this data, let's do some witching.
Now let's do the same reasoning, but for the market that appears not as an alternation of two flat and trend pieces, but as an alternation of N pieces and an Unknown piece. All the same reasoning. The same studies of the behaviour of BP half-periods. The same shamanism.
As a result, the consideration of the market model as a set of pieces-processes comes down to the same analysis of the initial BP.
The market is an alternation of flat and trend chunks.
But statistical research is more suitable for FX because the market is quite closed to outsiders. But again, statistical research can be done not just by testing some strategies, but by consistently identifying certain moments and examining the properties of the price in them. Although the results of strategy testers are also statistical research, if they are interpreted correctly. On the basis of the results of the studies, if there is something to hold on to, we should try to generalize the results, simplify and assume what we are dealing with. It is a bit of a gut feeling and it takes a lot of time and statistics to study. At least we have to take into account that we are studying individual processes, which are usually very limited in time. Not to mix everything up.