Forecasting with neural networks: how and where it is applied
Neural networks are used to predict accidents, traffic, asset values, and other situations in various fields
Price prediction based on trading history
The neural network estimates the value and volume of trades for past periods, and based on this information, predicts future price trends. In addition to analyzing price trends, the neural network analyzes the trends of indicators and oscillators. For example, moving average crossover and RSI index.
The neural network estimates the value and volume of trades for past periods, and based on this information, predicts future price trends. In addition to analyzing price trends, the neural network analyzes the trends of indicators and oscillators. For example, moving average crossover and RSI index.
Determining the moment of closing a position
Neural networks help determine the moment to close a position based on price, support, resistance, indicator data, oscillators, and future trend forecasts.
Neural networks help determine the moment to close a position based on price, support, resistance, indicator data, oscillators, and future trend forecasts.
Risk management
Neural networks determine the level of risk of each trade and the size of the position to be opened in order to minimize potential losses. Also, neural networks can be used to select the position of stop loss and take profit limit orders.
Neural networks determine the level of risk of each trade and the size of the position to be opened in order to minimize potential losses. Also, neural networks can be used to select the position of stop loss and take profit limit orders.
News analysis
Neural networks analyze news and social media to determine how they affect the price of assets. Thanks to this data, the investor builds an investment strategy.
Neural networks analyze news and social media to determine how they affect the price of assets. Thanks to this data, the investor builds an investment strategy.
How it is applied in stock trading
DVR accident prediction
The system is able to predict dangerous situations according to the data from the DVR and notify the driver about them.
The system is able to predict dangerous situations according to the data from the DVR and notify the driver about them.
Traffic estimation
The neural network can count the number of cars and evaluate the traffic density. In life, this helps predict traffic jams and regulate traffic lights.
The neural network can count the number of cars and evaluate the traffic density. In life, this helps predict traffic jams and regulate traffic lights.
We have experience in developing systems that can predict the price of stock assets using news analysis and trading history. The goal of the project is to quickly test hypotheses and apply them in trading. The system is able to collect, process and track data changes. And also automatically add and test new financial models on the trading emulator, leaving only effective ones.
Our cases in the field of forecasting
traffic is obstructed
camera line of sight
danger