Machine learning in trading: theory, models, practice and algo-trading - page 2676
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Well, subtract the trend, normalise the amplitudes and you're left with a sine wave(s).
Using the same conditional commodity as an example: we stock the warehouses for production - the price rises, we stock up - it stopped growing or started to fall. After a while, having sold out stocks, we return to the market and sell again - the price rises again. It is clear that in reality everything is much more complicated, but the basic model is exactly the same.
Well, there is an understandable factor here - we tare goods, the price goes up. It can be taken into account in the formula and track the dynamics. And the price change is a reaction. In Forex, then the signal will be something similar, but not the chart itself, which simply reflects the exchange rate and does not carry information about the future
I don't see any fundamental difference between a concrete factory that trades sand for production and an importer of electronics that trades currency to buy goods abroad. Yes, different markets, but the physics of the process are the same.
"Something similar" from different participants adds up to a common signal. The goods are bought not by one player, but by many. Some part of this set acts on one time horizon, thus drawing a more or less stable signal in the price.
Maxim Dmitrievsky #:
And TS are built not on forecasting, but on errors (inefficiencies) of various kinds. But there is no signal in them, as well as in the rest of the chart. You can somehow filter them out, if they exist, but it is very difficult in an efficient market
Difficult, no argument. Is it easy to find inefficiencies in an efficient market?)
I don't see any fundamental differences between a reinforced concrete factory, which trades sand for production, and an electronics importer, which trades currency to buy goods abroad. Yes, different markets, but the physics of the process is the same.
"Something similar" from different participants adds up to a common signal. The goods are bought not by one player, but by many. Some part of this set acts on one time horizon, thus drawing a more or less stable signal in the price.
Using the same conditional goods as an example: we stock the warehouses for production - the price rises, we stock up - it stopped growing or started to fall. After a while, having sold off stocks, we return to the market and sell again - the price rises again. It is clear that in reality everything is much more complicated, but the basic model is exactly the same.
The goods are purchased at certain price levels, for this purpose time series are analysed (price changes at suppliers), then we buy from who is cheaper and then sell to the one who has a higher price. And the warehouse does not need to be maintained 😄. I see it like this ))
Difficult, no argument. But is it easy to find inefficiencies in an efficient market?)
Leave sinusoids alone if you know what to do with them.)
So we're asking what to do with them.