The Hammer Pattern is a chart pattern in technical analysis that typically appears on the price charts of stocks, forex, or other financial markets.

It is a type of candlestick pattern used by traders to identify potential market reversal signals.

It can be either red (indicating a decline) or green (indicating a rise)

Key Characteristics:

• Small real body at the upper end of the trading range
• Long lower shadow (at least twice the length of the real body)
• Little or no upper shadow

The hammer suggests that sellers drove prices lower during the trading session, but strong buying pressure pushed the price back up by the close, potentially indicating a bullish reversal.

How to Identify Hammer Candlestick Pattern in Python:

Here is a simple code snippet in python, You can adjust the weight parameter; the larger it is, the longer the lower shadow, making the pattern more pronounced.

import pandas as pd
def is_hammer(open, high, low, close):
    body = abs(open - close)
    # default is 2
    weight = 3
    wick = min(open, close) - low
    return wick >= weight * body and high - max(open, close) <= body

def find_hammers(df):
    df['is_hammer'] = df.apply(lambda row: is_hammer(row['Open'], row['High'], row['Low'], row['Close']), axis=1)
    return df[df['is_hammer']]

# Example usage

#Assuming df is a DataFrame that contains OHLC data (Open, High, Low, Close prices).
df = pd.read_csv('stock_data.csv')
hammers = find_hammers(df)
print(hammers)

Real Historical Stock Price Chart Example:

I have compiled a list of the top 50 stocks in the S&P 500 from January 1, 2000, to August 31, 2024, totaling 260,000 records. There are 247 records that match the hammer technical pattern.

Among them:

1. 46.15% will GO UP after 1 day, avg go up ratio is 2.19%

2. 53.44% will GO DOWN after 1 day, avg go down ratio is -2.80%

3. 46.56% will GO UP after 5 days, avg go up ratio is 5.64%

4. 53.04% will GO DOWN after 5 days, avg go down ratio is -5.39%

Here are several real stock charts examples featuring hammer patterns

Conclusion

When a hammer pattern forms in an uptrend, it may signal that the market is testing support, but it doesn't guarantee a trend reversal.

The hammer pattern isn't a foolproof reversal signal on its own. To make a reliable judgment, you should use it alongside other technical indicators and consider market sentiment. The pattern's effectiveness also depends on its position, timing, and how the market behaves afterward..

The Shooting Star Candlestick is a common candlestick pattern in technical analysis, typically appearing at the top of an uptrend, signaling a potential imminent price reversal.

It is a type of candlestick pattern used by traders to identify potential market reversal signals.

It can be either red (indicating a decline) or green (indicating a rise)

Key Characteristics:

• Small real body near the low, long upper shadow
• Short or No Lower Shadow
• Opposite of the Hammer Candlestick, where buyers regain control after a downtrend

How to Identify Shooting Star Candlestick Pattern in Python:

Here is a simple code snippet in python, You can adjust the weight parameter; the larger it is, the longer the lower shadow, making the pattern more pronounced.

import pandas as pd

# Fetch historical stock data
df = pd.read_csv('stock_data.csv')

# Create a new column to calculate body size and shadow sizes
data['Body'] = abs(data['Open'] - data['Close'])
data['Upper_Shadow'] = data['High'] - data[['Open', 'Close']].max(axis=1)
data['Lower_Shadow'] = data[['Open', 'Close']].min(axis=1) - data['Low']

# Shooting Star criteria:
# 1. Small real body (e.g., less than 10% of the total range)
# 2. Long upper shadow (e.g., more than twice the body)
# 3. Little or no lower shadow (e.g., lower shadow less than 20% of the total range)

body_threshold = 0.1
upper_shadow_factor = 2
lower_shadow_threshold = 0.2

# Calculate total range (high - low)
data['Range'] = data['High'] - data['Low']

# Shooting Star condition
data['Shooting_Star'] = (
    (data['Body'] < body_threshold * data['Range']) &  # Small body
    (data['Upper_Shadow'] > upper_shadow_factor * data['Body']) &  # Long upper shadow
    (data['Lower_Shadow'] < lower_shadow_threshold * data['Range'])  # Little/no lower shadow
)

# Filter rows where a Shooting Star is detected
shooting_star_dates = data[data['Shooting_Star']]

print(shooting_star_dates[['Open', 'High', 'Low', 'Close', 'Shooting_Star']])

I have compiled a list of the top 50 stocks in the S&P 500 from January 1, 2000, to August 31, 2024, totaling 260,000 records. There are 1536 records that match the hammer technical pattern.

Among them:

1. 56.71% will GO UP after 1 day, avg go up ratio is 1.31%

2. 42.51% will GO DOWN after 1 day, avg go down ratio is -1.30%

3. 55.86% will GO UP after 5 days, avg go up ratio is 3.11%

4. 44.08% will GO DOWN after 5 days, avg go down ratio is -2.77%

Here are several real stock charts featuring Shooting Star candlestick patterns

Conclusion

While both the Shooting Star and Hammer Candlestick patterns indicate reversals, they occur in opposite market conditions. The Shooting Star signals a bearish reversal at the top of an uptrend, while the Hammer Candlestick appears at the bottom of a downtrend, indicating a potential bullish reversal. Understanding the nuances of both patterns can help traders make more informed decisions