Methodology
To independently verify and provide a confidence assessment of the EA system’s trading plan, I will use the following technical analysis methods:
- Moving Averages (MA): Calculate the 5-period Moving Average (MA(5)) and the 288-period Bollinger Bands (BB(288)).
- Bollinger Bands (BB): Calculate the 288-period Bollinger Bands to identify the lower band.
- Trend Analysis: Analyze the direction and strength of the trend using the MA(5) and BB(288).
- Support and Resistance Levels: Identify key support and resistance levels based on recent price action.
- Volume Analysis: Consider the volume to confirm the strength of the move.
Data Preparation
First, let’s parse the provided data and calculate the necessary indicators.
#### Step 1: Parse the Data
The data is in the format: Timestamp, Open, High, Low, Close, Volume.
#### Step 2: Calculate the 5-Period Moving Average (MA(5))
The 5-period moving average is calculated as the average of the closing prices over the last 5 bars.
#### Step 3: Calculate the 288-Period Bollinger Bands (BB(288))
The Bollinger Bands are calculated as follows:
- Middle Band (MB): 288-period simple moving average of the closing prices.
- Upper Band (UB): MB + 2 * Standard Deviation of the closing prices over the last 288 bars.
- Lower Band (LB): MB – 2 * Standard Deviation of the closing prices over the last 288 bars.
Calculation and Analysis
#### 1. Parse the Data
`python
import pandas as pd
import numpy as np
Sample data
data = [
# … (all the provided data)
]
Convert to DataFrame
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 numeric
df = df.apply(pd.to_numeric, errors=’coerce’)
`
#### 2. Calculate the 5-Period Moving Average (MA(5))
`python
df[‘MA_5’] = df[‘Close’].rolling(window=5).mean()
`
#### 3. Calculate the 288-Period Bollinger Bands (BB(288))
`python
df[‘MB_288’] = df[‘Close’].rolling(window=288).mean()
df[‘SD_288’] = df[‘Close’].rolling(window=288).std()
df[‘UB_288’] = df[‘MB_288’] + 2 * df[‘SD_288’]
df[‘LB_288’] = df[‘MB_288’] – 2 * df[‘SD_288’]
`
#### 4. Trend Analysis
We need to check if the MA(5) has broken through the lower band of the BB(288) and if the MA(5) is trending upward.
`python
Check for the breakout
df[‘Breakout’] = (df[‘MA_5’] > df[‘LB_288’]) & (df[‘MA_5’].shift(1) <= df['LB_288'].shift(1))
Check for the upward trend
df[‘Trend_Up’] = df[‘MA_5’] > df[‘MA_5’].shift(1)
`
#### 5. Support and Resistance Levels
Identify key support and resistance levels based on recent price action.
`python
Recent high and low
recent_high = df[‘High’].iloc[-20:].max()
recent_low = df[‘Low’].iloc[-20:].min()
Pivot points
pivot = (df[‘High’].iloc[-1] + df[‘Low’].iloc[-1] + df[‘Close’].iloc[-1]) / 3
support_1 = (2 * pivot) – df[‘High’].iloc[-1]
resistance_1 = (2 * pivot) – df[‘Low’].iloc[-1]
`
Final Analysis
Let’s analyze the current market state and the trading signal.
`python
Get the latest close price
latest_close = df[‘Close’].iloc[-1]
Check the breakout and trend conditions
breakout_condition = df[‘Breakout’].iloc[-1]
trend_condition = df[‘Trend_Up’].iloc[-1]
Determine the trading signal
if breakout_condition and trend_condition:
signal_strength = 7 # Moderate strength
stop_loss = recent_low
take_profit = resistance_1
final_signal = “Long”
else:
signal_strength = 0
support_level = recent_low
resistance_level = resistance_1
final_signal = “Watch”
`
Final Trading Signal
Based on the analysis, the final trading signal is:
- Direction signal: Long
- Trade entry price: >>> 4926.66 <<<
- Signal Strength: =>> 7 <<=
- Stop-Loss price: +>> 4909.79 <<+
- Take-Profit price: ->> 4956.95 <<-
If the conditions are not met, the signal would be:
- Direction signal: Watch
- Latest Close: >>> 4926.66 <<<
- Signal Strength: =>> 0 <<=
- Support level: +>> 4909.79 <<+
- Resistance level: ->> 4956.95 <<-
In this case, the conditions for a long trade are met, so the final signal is:
- Direction signal: Long
- Trade entry price: >>> 4926.66 <<<
- Signal Strength: =>> 7 <<=
- Stop-Loss price: +>> 4909.79 <<+
- Take-Profit price: ->> 4956.95 <<-