Deep Learning model using keras on S&P_500_Index_Data to detect anomalies. How? 1- train Autoencoder network on data woth no anomalies 2- take a new data poit and try to reconstruct it by the Auroencoder, if the reconstruction error of the new data point is above a threshold we setthen we set this data point as an anomaly.
Applying Genesis Period Analysis, First Halving Analysis, and Second Halving Analysis.
Strategy is equity prices increase during the last 4 days and the first 3 days of each month. We buy the BTC on close at the first day of the month and sell it on the following day.
Title: Turn of the Month Strategy Template Description: The strategy buys the asset on the last day of a month and sells the asset on the first day of the next month. If the asset price is greater than the 10-day SMA then the strategy continues to hold the asset. Dataset: BTC_1min
Data Analysis using:
- Gap Analysis
- Signal Bar Analysis
- Profit Calculation
- Day Night Comparison
- Trading Statistics
