Machine learning in trading: theory, models, practice and algo-trading - page 3421
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I mean, if there is a pattern, it's the same both ways.
So if there is a seasonal pattern, such as "sell in may and go away", which way exactly is it the same?
So if there is a seasonal pattern, such as "sell in may and go away", in which specific ways is it the same?
The statistical significance of such a strategy is close to zero.
The statistical significance of such a strategy is close to zero.
Printed it out like this - got zeros
Did I print it correctly?
Wrong. Read access as in a 2-dimensional array
And if it's not close to zero
Then I'll be reevaluating my gut.
Wrong. Read access as in a 2-dimensional array
It's still zeros.
Even if I just assign.
MatrixLearn[row][col]=5;I don't understand what's wrong :(
Even so.
Prints zeros.
The representation of the EUR=USD Infinite Balancing Model requires abstraction from the real market and the adoption of several key assumptions. In the real world, exchange rates are affected by many factors including economic indicators, political events, central banks and market sentiment. However, for a model that seeks to keep EUR and USD in a state of infinite equilibrium (1 EUR = 1 USD), we can consider the following theoretical approach:
Automatic Correction: The model will automatically adjust the exchange rate in real time using an algorithmic approach. Every time the exchange rate deviates from 1:1, the system will perform operations in the market to restore equilibrium. This may include buying a currency that has become cheaper and selling a more expensive currency.
Infinite reserve of cur rencies: To maintain equilibrium, the model must have access to virtually unlimited reserves of both currencies. This will allow the model to intervene in the market with whatever volume is needed to correct the exchange rate.
Monitoring external factors: The model should continuously analyse market data and external factors that may affect the exchange rate. This includes economic indicators, political events and changes in trade policy.
Use of derivatives: The model can use various financial instruments such as futures, options and swaps to balance the exchange rate. This will effectively hedge risks and influence the exchange rate without having to directly buy or sell large amounts of currency.
Artificial intelligence and machine learning: The model will incorporate artificial intelligence and machine learning algorithms to predict market trends and optimise its operations. This will allow the system to adapt to changing market conditions and improve its ability to maintain a 1:1 exchange rate.
While such a model is interesting from a theoretical point of view, in practice its implementation faces significant challenges. First, the need for infinite resources makes such a system impossible to implement. Second, market forces and external factors are too numerous and unpredictable, which makes the task of infinite balancing of exchange rates extremely difficult. Third, intervening in the market to maintain a fixed exchange rate may have unintended consequences for the economy.
It's still zeros.
Even if I just assign
I don't understand what's wrong :(
Do you even look at the examples?
Assignment
Reading like thisv= MatrixLearn[row][col];Do you even look at the examples?
Where can I see them except your code? I see in the library code that this is how they read data - by cell address - I did it by analogy.
Assignment like this
Read like thisReceive
Have you tried it, does it work?