Hearst index - page 43
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yes the same... market conditions are the determining factor
Well, that's why it is useful (potentially). But it is necessary to move your mind seriously. And give up almost all the crap that is called classical TA.
If you think in that direction, the starting point is :
Does it make sense to predict the states of a one-dimensional world?
If you think along these lines, the starting premise is :
Does it make sense to predict the states of a one-dimensional world?
And from whose point of view is the question of prediction posed, the "population" of this world or an outsider?
And from the point of view of whom is the question of forecasting posed, the "population" of this world or an outsider?
The question, as I understand it, is rhetorical.
But to answer the question: Reading esotericism I constantly encounter explanations of predictions as information from the outside.
As for the point, let me remind you that I am neither a mathematician nor a programmer.
A graph has a quotient and time. Renco only has a quotient.
And nowhere is time properly analyzed, it sort of doesn't exist.
Although if you analyse both graphs, time remains in the difference according to peasant logic.
And maybe the renko in its pristine form won't work. Maybe you have to knit them by reference points or make up a redraw. I don't know.
This is my primitive reasoning. In short, it's all nonsense.
Renko, Kagi, Range and so on also have time: the moments of candlestick changes are strictly ordered and have a clear criterion of construction. Thus there is a monotonous but non-linear transformation of the timeline... So to say, the "new" time goes at a different pace in relation to our, usual time - it accelerates, then slows down.
I am of the same opinion.
You have formalised my understanding.
Nevertheless, something in my reasoning is holding me back.
OK...
That's not the result, unfortunately.
As Munchausen used to say: "Not that!"
Let's keep looking.
This paper by Eric Nyman (2010), which in turn was written from a book by Adgar Peters (1990), who took this method from Mandelbort (1960-70), who first described the method invented by 70 year old Harold Edwin Hirst in far 1951. It all means that when asked about novelty of proposed theme at dissertation advice, you should imagine that old Edwin from XIX century is an innovator of fractal geometry:)
But seriously, the method was developed, as seen above, to a specific and highly abnormal process - the Nile spill. In the picture below, the disproportionality of the spill spread to the overall trend or mathematical expectation is obvious. And so for a specific process - the Nile spill - this method is good and works, but for financial markets as Mandelbort has tried to present it, it is no longer sufficient. Under any circumstance and in any market, including SB, your calculation will show a value of about 0.54. You need other, more accurate methods. And as soon as you write a dissertation, you can not do without fractional integrated autoregressive moving average FARIMA, and it is only available in specialized statistical packages. H can be set arbitrary there. But this does not solve the problem, because in order to at least fit the market to the model, you need to calculate its H, and how can you do it if the most simple and common method does not work? There are other works on this theme, works by Pastukhov and Shiryaev. Look at them. They are more scientific and better suited for a dissertation, but whether they are more accurate is a question. There is also a related thread on the same topic, look here.
Good day! In general, the idea was the following: to calculate the indicator H, build a function of the price of metal, then impose a change in the cost of production of this metal and analyze the change (the so-called profit that the organization can get). Analyse in terms of those factors that are influenced and not influenced by external factors.
To be honest, I intuitively understand that this is little like something worthwhile, because, well, it should be programmed, such skills do not have. But the supervisor of my dissertation strongly recommended to use this factor in calculations. So it turns out to be nonsense.... at the initial stage. ((((
Good afternoon! In general, the idea was as follows: calculate the H indicator, build a function on the price of metal, then impose the change in the cost of production of this metal and analyse the change (the so-called profit that can be obtained by the organisation). Analyse in terms of those factors that are influenced and not influenced by external factors.
I, frankly, intuitively understand that this is little like something worthwhile, because, well, it should be programmed, such skills do not have. But the supervisor of my dissertation strongly recommended to use this factor in calculations. So it turns out to be nonsense.... at the initial stage. ((((
Sorry, but all this is too little for a dissertation. There is no scientific novelty in it, the topic is already known, at least for forty years. And if you are going to start it "as all", that is something you will take from Internet, somewhere from books 20-30 years old, you will receive result "as all", namely the next thesis with a proud label "Dissertation". Firstly, you must rely on advanced methods of statistical analysis. You won't find them on the Internet or in your latest Excel version. Given the dismal state of our science - you can't get much useful information from theses and dissertations. They are nothing but copypastes and empty into empty. Worthwhile works there - units, and that would find them need to know first what to look for and understand the subject deeply. The only source where you can get the latest and most innovative statistical methods are specialized statistical packages, namely, the statistical analysis package R. In general, this environment is worth mentioning separately. It is the de facto standard of the researcher. Download and install it from the official website http://www.r-project.org/ and install on top of it, the visual environment RStudio. From now on, forbid yourself from using Excel. It is bad form to do dissertations in Excel. In addition, an information vacuum in Excel will be assured. Then, look for packages which include methods of Hurst index calculation. There are many of them, but first, install 'pracma' package. Here is an example of Hurst index calculation for the Nile. Note that you don't need anything at all, all data and methods are already available in R:
# Скачиваем из Интернета пакет 'pracma' >install.packages('pracma') #Устанавливаем его в системе >library('pracma') #Теперь нам доступна функция 'hurst', вычисляющая коэффициент херста #Смотрим справку по этой функции >?hurst #Загружаем один из базовых пакетов, в котором храниться информация о разливе Нила за 100 лет >library(datasets) # Отобразим несколько диаграмм на одном графике >par(mfrow = c(3,1)) #Строим график разливов Нила >plot(Nile, t='l', main="Nile owerflow 1971-1970") #Под ним отображаем первые разности (доходности) >Nile.diff <- diff(Nile) >plot(Nile.diff, t='h', main="Returns") #Еще ниже строим гистограмму распределения частоты >hist(Nile.diff, breaks=20, main='Distribution') #Рассчитываем собственно показатель Херста. (Будет равен 0,34, т.е. разливы Нила по версии функции hurst() антиперсисенты) >hurst(Nile.diff)Let's look at the resulting graph:
This is where the flight of fancy should begin. First question: "Why is the Nile spill in the function antipersistent, while in Manedlebort and Peters it is a persistent process!". Let's see how the hurst function is set up, the environment R is a free environment, so the gist of all the methods can easily be gleaned from the sources:
#Чтобы посмотреть исходники функции достаточно набрать ее имя без фигурных скобок >hurstWell then, having understood the specifics of all the methods, you will easily be able to write your own calculation method. Formalize it in the form of an appropriate package R for the judgment of the world scientific community. Then write several articles in some econometric magazines about your method, which would clearly demonstrate its advantages over known methods. Then gradually move on to the analysis of gold. By this time you will be fluent in proven models like AR, Arima, etc. Very soon, you will be at the forefront of "scientific thought". And the question of what to write about will no longer arise.