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Vena Network as an Open Protocol for Asset Financing and Token Exchange in the future
Topic: How to Predict the Future with the Past? This Method May Give You the Answer (Read 93 times)
October 17, 2018, 04:09:01 AM
October 17, 2018, 04:02:21 AM
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October 17, 2018, 03:57:43 AM
Predicting the future is what humans have been dreaming of for thousands of years, but so far, humans have been very limited in doing this. Considering the current level of technology, it is obviously impossible to accurately predict future events. However, predicting the future is something that every one of us likes, after all, in daily life, we need to make judgments about the future to decide our current action.
This is also widely reflected in the financial market. Perhaps the most common thing for investors to do every day is to predict whether a stock will rise or not in the future. Venture capital institutions are also predicting whether their investment projects can develop well in the future, and the government's forecast has also never stopped. These predictions have their own basis and reason, but from the probabilistic level, there are also some mathematical methods that can give relevant predictions from different angles.
The Monte Carlo method is one of them. This is widely used in the fields of financial economy, computer technology, statistics, machine learning, etc. The person who proposed the Monte Carlo method is John von Neumann, and Monte Carlo is the name of the casino street in Monaco. As can be seen, this is a way to study probability.
Although the descriptions we have used so far are very exclusive, in fact this method is not difficult to understand. The Monte Carlo method does not have profound theoretical support, and its simple description of the basic principles is very easy to understand.
Let us imagine an example of a square with a side length of 1. How can we calculate the area of the inscribed circle?
I believe this problem is very simple. The radius of this inscribed circle is 0.5. According to the area formula of the circle, the area is equal to π multiplied by the square of the radius. We can know that the area of this circle is 0.25π.
But what if we don't know the area formula of the circle? Or what if it is not a circle, but an irregular figure? At this time, we can use the Monte Carlo method to find the approximate area.
Let the machine generate a huge amount of random points, let’s say, 10,000 points, in this square. Then we can see how many points fall within the circle. If there are 8,000, then the area of this circle is four-fifths of the square area. That is 0.8.
The more random points there are, the more accurate the final result will be. Therefore, we can see that the basic idea of Monte Carlo method is to obtain a large number of random events, and then to obtain the probability of occurrence of such events, based on the ratio of the number of times and the total number of times. The larger the sample size of a random event, the more reliable the results are.
In the financial market, the application of Monte Carlo method is also very extensive. To give an example, we can randomly select a large number of points in the historical trend of Bitcoin, and then observe the ups and downs of these points over a period of time. Then what do we get? We get the probability that Bitcoin would go up and down over a period of time.
Such a probability has limited uses for individual investors. After all, it cannot predict when bitcoin will rise or fall sharply. But this probability has other meanings. For example, in the digital currency mortgage business (that’s what Vena Network is focusing on), the mortgage rate can be determined from this. For example, we see through the Monte Carlo method that, the probability of bitcoin dropping by 30% in one month is less than 1% in history, so we can determine the loan-to-value ratio as 70%, or slightly lower. This example is not necessarily accurate, but it will minimize the occurrence of collateral value falling below the value of the loan.
This is a way to predict the future with the past. Of course, this method does not accurately predict the future, but it can judge the most likely events in the future based on a certain probability, and provide a reliable basis for our judgment.
Now Vena Network is working on bitcoin mortgage with Monte Carlo method. Vena Network is an open protocol for tokenized asset financing and exchange. Vena is building a decentralized digital asset financing and exchange network, in which everyone can process P2P cryptocurrency collateral lending and OTC trading anytime and anywhere, enabling free exchange between cryptocurrency and fiat currency.
Vena is going to start ICO in the end of October or the beginning of November. If you are interested, you can follow us in Facebook, Twitter, Telegram, Instagram, Reddit, etc. just by searching ”Vena Network“.
Our partner includes KuCoin, DigiFinex, tekrise, F’enhance, vipexc, etc. And the ICO will be held on Leek ICO, KICKICO and TOKENPLUS.
This is also widely reflected in the financial market. Perhaps the most common thing for investors to do every day is to predict whether a stock will rise or not in the future. Venture capital institutions are also predicting whether their investment projects can develop well in the future, and the government's forecast has also never stopped. These predictions have their own basis and reason, but from the probabilistic level, there are also some mathematical methods that can give relevant predictions from different angles.
The Monte Carlo method is one of them. This is widely used in the fields of financial economy, computer technology, statistics, machine learning, etc. The person who proposed the Monte Carlo method is John von Neumann, and Monte Carlo is the name of the casino street in Monaco. As can be seen, this is a way to study probability.
Although the descriptions we have used so far are very exclusive, in fact this method is not difficult to understand. The Monte Carlo method does not have profound theoretical support, and its simple description of the basic principles is very easy to understand.
Let us imagine an example of a square with a side length of 1. How can we calculate the area of the inscribed circle?
I believe this problem is very simple. The radius of this inscribed circle is 0.5. According to the area formula of the circle, the area is equal to π multiplied by the square of the radius. We can know that the area of this circle is 0.25π.
But what if we don't know the area formula of the circle? Or what if it is not a circle, but an irregular figure? At this time, we can use the Monte Carlo method to find the approximate area.
Let the machine generate a huge amount of random points, let’s say, 10,000 points, in this square. Then we can see how many points fall within the circle. If there are 8,000, then the area of this circle is four-fifths of the square area. That is 0.8.
The more random points there are, the more accurate the final result will be. Therefore, we can see that the basic idea of Monte Carlo method is to obtain a large number of random events, and then to obtain the probability of occurrence of such events, based on the ratio of the number of times and the total number of times. The larger the sample size of a random event, the more reliable the results are.
In the financial market, the application of Monte Carlo method is also very extensive. To give an example, we can randomly select a large number of points in the historical trend of Bitcoin, and then observe the ups and downs of these points over a period of time. Then what do we get? We get the probability that Bitcoin would go up and down over a period of time.
Such a probability has limited uses for individual investors. After all, it cannot predict when bitcoin will rise or fall sharply. But this probability has other meanings. For example, in the digital currency mortgage business (that’s what Vena Network is focusing on), the mortgage rate can be determined from this. For example, we see through the Monte Carlo method that, the probability of bitcoin dropping by 30% in one month is less than 1% in history, so we can determine the loan-to-value ratio as 70%, or slightly lower. This example is not necessarily accurate, but it will minimize the occurrence of collateral value falling below the value of the loan.
This is a way to predict the future with the past. Of course, this method does not accurately predict the future, but it can judge the most likely events in the future based on a certain probability, and provide a reliable basis for our judgment.
Now Vena Network is working on bitcoin mortgage with Monte Carlo method. Vena Network is an open protocol for tokenized asset financing and exchange. Vena is building a decentralized digital asset financing and exchange network, in which everyone can process P2P cryptocurrency collateral lending and OTC trading anytime and anywhere, enabling free exchange between cryptocurrency and fiat currency.
Vena is going to start ICO in the end of October or the beginning of November. If you are interested, you can follow us in Facebook, Twitter, Telegram, Instagram, Reddit, etc. just by searching ”Vena Network“.
Our partner includes KuCoin, DigiFinex, tekrise, F’enhance, vipexc, etc. And the ICO will be held on Leek ICO, KICKICO and TOKENPLUS.
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