Machine learning in trading: theory, models, practice and algo-trading - page 1586
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By the way, there are some statistics
the length of the synthetic observation period affects the time during which the synthetic is "stationary"
something like Markovian dynamic reg. models you can try yet, but I am weak in this subject
i.e. find the switching probabilities of reg model intercept modes, and maybe the coefficients
I'm digging this topic now, using clustering and Gaussian mixes, hidden Markov models as examplessomething like Markovian dynamic regression models can be tried yet, but I am weak in this topic
i.e. to find probabilities of switching modes of intercept of reg. model, and maybe coefficients
I am digging this topic now, using clustering and Gaussian mixes, hidden Markov modelssynthetic, which briefly becomes "stationary"
And then the choice of which value of the coefficient to take as an extreme - 0.01 or 0.05 is also possible
Matstat and politics.
I hope they won't ban me)
Good article, thank you. Lysenkovshchina in the 21st century, this is something, I did not think it was possible.
Synthetic, which briefly becomes "stationary"
And then it's up to you which coefficient to take as an extreme value - 0.01 or 0.05.
The topic of switching modes is more than 20 years old, but there's not much on the Internet in relation to trading. Although the topic is interesting.
The topic of mode switching is more than 20 years old, but there's not much on the Internet in relation to trading. Although the topic is interesting.
And with lowering TF total time of "stationarity" of synthetics increases in percentage
Not cardinally, but nevertheless
I wonder if there is any way to use this?
Good article, thank you. Lysenkovshchina in the 21st century is something, I did not think it was possible.
More interesting is the substantive side of the question. Basically, the argument is about whether or not there has been a trend change (trough).
The whole thing looks like a pretty non-boring illustration of the science of testing statistical hypotheses)
More interesting is the content side of the question. Basically, the argument is about whether or not there has been a trend change (trough).
The whole thing looks like a pretty non-boring illustration of the science of testing statistical hypotheses)
In my opinion there are periodic fluctuations in the temperature of the planet due to natural causes. In the last hundred years natural warming has begun, with anthropogenic factors superimposed on it.
To break it down in terms of theses:
1. The greenhouse effect is just one of many factors affecting the average temperature on Earth.
2. To account for the anthropogenic impact, the percentage of anthropogenic CO2 to all that is in the atmosphere is important. Right now it is at one percent, i.e. quite small. Much more of it is brought in by forest fires and grass burning. Plus CO2 sequestration, deforestation, reduces it.
3. the balance of CO2 entering the atmosphere and its sequestration is almost like a balance of supply and demand on the forex market, many different channels with differentinvestment times burial. It's not exactly easy to model it. But there are experimental observations.
At the end of the 20th century, machines like AMS machines - gas pedal mass spectrometers - appeared primarily for the needs of archaeologists. Their main feature is that samples to determine isotope ratios can be very small - milligrams. They were quickly adapted for other technological, medical, and in particular climatic research purposes. These machines measure the C12/C14 ratio very accurately. In natural genesis, it is determined by the cosmic background and this ratio is quite stable. But when the era of nuclear testing began, the concentration of C14 increased dramatically, it was spread all over the world and absorbed by trees. The locations and dates of the tests are known, the annual tree rings are easily counted, you can determine exactly how the C14 concentration was changing in the place where the tree was growing. By making such measurements around the world it was possible to track how quickly CO2 migrated in the atmosphere - it turned out that very quickly half a year to a year the concentration leveled out around the world. And more importantly it took less than ten years for the concentration to decrease to background concentration. i.e. all atmospheric CO2 is constantly renewed. This means that the current concentration is a balance of emissions/absorption in which the role of man-made CO2 from burning coal, oil, gas is not as significant as it is declared in the media.
That is, in my opinion:
a) The amount of man-made CO2 does not significantly increase its natural concentration as it is propagandized.
b) CO2 is not the only cause of the greenhouse effect.
c) The greenhouse effect is far from being the only cause of temperature change on Earth.
Found it. Don't wait the next couple of weeks, let the world rest while I enjoy learning )
link correction
I'm not at all ready to get into another pointy-headed and obtuse-headed argument.)
In my opinion, the article is a good illustration of how statistical conclusions can be completely opposite on the same raw data without proper validation. Especially when there is a researcher bias.
Article is powerful, thank you, if everything stated there is not a fiction, it confirms the age-old saying about statistics)
You can figure out the library in about 5 days. Just sit down and read the code, write comments on it, describing what each line does.
After that you can edit the forest however you want.
I also filtered the leaves. But not manually, but just by percentage of successful hits on a training area. For example, I took all leaves with a 90% success rate. But even they were 50/50 on the forward slope.
In general I gave up. And I don't have the time.
I am now doing other things, which really feed me, not only promises, like Forex with scaffolds.
Forests work where there are regularities. Physical processes, for example. Once I read an article about using MO to control and manage natural gas purification and liquefaction processes. There MO works better than any automatics...
If the same scaffolding does not work at Forex, it means that there are no regularities. At least I did not find them in price returnees and in real SME volumes too. The simple traders cannot get any other information.
What library are you talking about, my fellow countrymen? I'm writing my own, maybe you can show me a ready one.
And by the way - as it seems to me all statistical studies and MO in the field of trading work with returns.
Were there any attempts to apply statistical methods to graphical, candlestick analysis and other higher level stuff?