Methodology
To independently verify the EA system’s trading plan, I will use a combination of technical indicators and pattern recognition. The key steps include:
- Calculate Moving Averages (MA): Specifically, the 5-period moving average (MA(5)) and the 288-period Bollinger Bands.
- Bollinger Bands Calculation: Calculate the upper and lower bands for the 288-period Bollinger Bands.
- Trend Analysis: Analyze the direction and strength of the trend using the MA(5) and Bollinger Bands.
- Pattern Recognition: Look for specific candlestick patterns and support/resistance levels.
- Session Considerations: Factor in the time of day and session-specific volatility and liquidity.
Data Preparation
First, let’s parse the provided data and calculate the necessary indicators.
`python
import pandas as pd
import numpy as np
Parse the data
data = [
# … (all the data points)
]
df = pd.DataFrame(data, columns=[‘Timestamp’, ‘Open’, ‘High’, ‘Low’, ‘Close’, ‘Volume’])
df[‘Timestamp’] = pd.to_datetime(df[‘Timestamp’], format=’%Y.%m.%d %H:%M’)
df.set_index(‘Timestamp’, inplace=True)
Convert to float
df = df.astype(float)
Calculate 5-period Moving Average
df[‘MA_5’] = df[‘Close’].rolling(window=5).mean()
Calculate 288-period Bollinger Bands
df[‘BB_Middle’] = df[‘Close’].rolling(window=288).mean()
df[‘BB_Std’] = df[‘Close’].rolling(window=288).std()
df[‘BB_Upper’] = df[‘BB_Middle’] + 2 * df[‘BB_Std’]
df[‘BB_Lower’] = df[‘BB_Middle’] – 2 * df[‘BB_Std’]
Display the last few rows to check the calculations
print(df.tail())
`
Trend and Pattern Analysis
Next, we will analyze the current market state by examining the latest values of the calculated indicators and the recent price action.
`python
Get the latest values
latest_close = df[‘Close’].iloc[-1]
ma_5_latest = df[‘MA_5’].iloc[-1]
bb_upper_latest = df[‘BB_Upper’].iloc[-1]
Check if MA(5) has broken below the upper Bollinger Band
ma_below_bb_upper = ma_5_latest < bb_upper_latest
Determine the trend
trend_downward = ma_5_latest < df['MA_5'].iloc[-2] and ma_5_latest < df['MA_5'].iloc[-3]
Identify key support and resistance levels
support_level = df[‘Low’].tail(20).min()
resistance_level = df[‘High’].tail(20).max()
Print the results
print(f”Latest Close: {latest_close}”)
print(f”MA(5) Latest: {ma_5_latest}”)
print(f”BB Upper Latest: {bb_upper_latest}”)
print(f”MA(5) below BB Upper: {ma_below_bb_upper}”)
print(f”Trend Downward: {trend_downward}”)
print(f”Support Level: {support_level}”)
print(f”Resistance Level: {resistance_level}”)
`
Final Analysis and Signal
Based on the above calculations and analysis, we can now make an independent assessment of the market state and generate a trading signal.
- Latest Close: 4938.20
- MA(5) Latest: [Calculated value]
- BB Upper Latest: [Calculated value]
- MA(5) below BB Upper: [True/False]
- Trend Downward: [True/False]
- Support Level: [Calculated value]
- Resistance Level: [Calculated value]
#### Conclusion
- If the MA(5) is indeed below the upper Bollinger Band and the trend is downward, the EA system’s short sell signal is supported.
- If the conditions are not met, we will output a “Maintain Watch” signal.
Final Trading Signal
Based on the analysis, the final trading signal is:
- Direction signal: [Short/Maintain Watch]
- Trade entry price: [Price if Short]
- Signal Strength: [Strength if Short]
- Stop-Loss price: [Price if Short]
- Take-Profit price: [Price if Short]
- Latest Close: 4938.20
- Support level: [Calculated value]
- Resistance level: [Calculated value]
Let’s finalize the signal based on the actual calculations.
`python
if ma_below_bb_upper and trend_downward:
# Generate a short sell signal
trade_entry_price = latest_close
signal_strength = -5 # Example strength, adjust as needed
stop_loss_price = resistance_level
take_profit_price = support_level
print(f”Direction signal: Short”)
print(f”Trade entry price: >>> {trade_entry_price} <<<")
print(f”Signal Strength: =>> {signal_strength} <<= ")
print(f"Stop-Loss price: <span class="resistance"> {stop_loss_price} </span> ")
print(f"Take-Profit price: <span class="support"> {take_profit_price} </span> ")
else:
# Maintain Watch
print(f”Direction signal: Watch”)
print(f”Latest Close: >>> {latest_close} <<<")
print(f”Signal Strength: =>> 0 <<= ")
print(f"Support level: <span class="support"> {support_level} </span> ")
print(f"Resistance level: <span class="resistance"> {resistance_level} </span> ")
`
Output
After running the above code, the final output will be:
- Direction signal: [Short/Maintain Watch]
- Trade entry price: [Price if Short]
- Signal Strength: [Strength if Short]
- Stop-Loss price: [Price if Short]
- Take-Profit price: [Price if Short]
- Latest Close: 4938.20
- Support level: [Calculated value]
- Resistance level: [Calculated value]
This will provide a clear and independent verification of the EA system’s trading plan.