2/25/2023 0 Comments Qm area mean forexThe prediction accuracy is better than other prediction models. Through the forecast trend analysis under different models, LSTM predicts that the stock change trend of the enterprise model is closest to the changing trend of the actual earnings price. This figure is closest to the average real return price of 13.89. The average return price of the LSTM prediction model is 14.01. The results show that as the number of iterations increases, the loss rate of the LSTM training curve keeps decreasing until 0. The 20-day change trend of the company’s stock returns under different models is predicted and analyzed. LSTM prediction models are used to perform error analysis on company data training. The uniqueness and innovation lie in using the stock returns of Bank of China securities in 2022 as the training data set. A prediction trend model of enterprise stock is established based on long short-term memory (LSTM). Secondly, the inadequacies of deep neural network (DNN) models are discussed. Firstly, the relevant theories of stock forecasting are discussed, and problems in stock forecasting are raised. In building a financial forecasting model, historical data and learned parameters are used to predict future stock prices. This study aims to accurately predict the changing trend of stocks in stock trading so that company investors can obtain higher returns. Our proposed hybrid model, which combines two separate LSTMs corresponding to these two data sets, was found to be quite successful in experiments using real data. We utilized two different data sets-namely, macroeconomic data and technical indicator data-since in the financial world, fundamental and technical analysis are two main techniques, and they use those two data sets, respectively. In this work, we used a popular deep learning tool called “long short-term memory” (LSTM), which has been shown to be very effective in many time-series forecasting problems, to make direction predictions in Forex. The direction prediction requirement makes the problem quite different from other typical time-series forecasting problems. However, incorrect predictions in Forex may cause much higher losses than in other typical financial markets. It is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two currencies. I will try later to see if I can get some charts to explain this narration.Forex (foreign exchange) is a special financial market that entails both high risks and high profit opportunities for traders. If there are no strong supply and demand zones to the left, I can place my TP as far as possible. Remember that the market leaves behind clues of potential reversal points and it is just a matter of determining which zones are weak and which are strong. TP profit would also depend on the price action to the left. This yields an much better risk-reward and is also a realistic place. Otherwise, I just place it 2-5 pips above the QM level to take care of spread. That reduces my risk-reward but it is a more realistic place to place the SL. If for example there is a supply zone near the HH and above the QM level in a bearish QM set-up, I may enter at the QM level and place my stop above the HH. It should depend on one's reading of the market at that point in time. The issues of placing stops (SL and TP) are more trade-management related issue and I generally prefer to talk of trade execution rather than trade management because there are no general rules for SL and TP. I have tried several systems but none of them have helped me in understanding market movements like these concepts have. I find that the concepts of engulfing patterns, quasimodo, supply and demand are invaluable if one is to be able to read the market well. I think that beyond having a strategy it is important to be learn how to read the market well and to understand what story the price action is saying.
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