[Python] Breakout trading strategy along with various technical indicators error

Breakout Trading Strategy to say whether there has been a breakout and should we invest our money. I am writing a code for the same.

My code:

import pandas as pd
import pandas_ta as ta
import math
import matplotlib.pyplot as plt

# Parameters
length = 14
k = 1.0
method = 'Atr'
show = False

# Data
# Replace [...] with your price and volume data
data = pd.read_csv('data.csv')
close = data['close']
high = data['high']
low = data['low']
src = close

# Calculate pivot highs and lows

def find_pivot_highs(data, length):
pivot_highs = []
for i in range(length, len(data) - length):
if (
data > max(data[i - length : i])
and data > max(data[i + 1 : i + length + 1])
):
pivot_highs.append(i)
return pivot_highs


def find_pivot_lows(data, length):
pivot_lows = []
for i in range(length, len(data) - length):
if (
data < min(data[i - length : i])
and data < min(data[i + 1 : i + length + 1])
):
pivot_lows.append(i)
return pivot_lows

ph = find_pivot_highs(high, length)
pl = find_pivot_lows(low, length)

# Calculate slope
def calculate_slope():
if method == 'Atr':
return ta.atr(high, low, close, length) / length * k
elif method == 'Stdev':
return ta.STDDEV(src, length) / length * k
elif method == 'Linreg':
sma1 = ta.SMA(src * n, length)
sma2 = ta.SMA(src, length)
return math.fabs(sma1 - sma2 * ta.SMA(n, length)) / ta.VAR(n, length) / 2 * k


slope = calculate_slope()
slope_ph = [0] * len(close)
slope_pl = [0] * len(close)
slope_ph = [slope if i in ph else slope_ph[i-1] for i in range(len(close))]
slope_pl = [slope if i in pl else slope_pl[i-1] for i in range(len(close))]

upper = [0] * len(close)
lower = [0] * len(close)
upper = [src if i in ph else upper[i-1] - slope_ph for i in range(len(src))]
lower = [src if i in pl else lower[i-1] + slope_pl for i in range(len(src))]

# ----
single_upper = [0] * len(src)
single_lower = [0] * len(src)

for i in range(length, len(close)):
if close > upper[i-length]:
single_upper = 1
elif i in ph:
single_upper = single_upper[i-1]

if close < lower[i-length]:
single_lower = 1
elif i in pl:
single_lower = single_lower[i-1]

upper_breakout= [False] * len(src)
for i in range(len(src)):
if src > upper:
upper_breakout = True
else:
upper_breakout = False

lower_breakout= [False] * len(src)
for i in range(len(src)):
if src[i] < lower[i]:
lower_breakout[i] = True
else:
lower_breakout[i] = False

# Trading strategy
trades = []
trade_type = None
entry_price = None
stop_loss = None
take_profit = None

for i in range(len(close)):
if trade_type is None:
if upper_breakout[i]:
trade_type = 'Long'
entry_price = close[i]
stop_loss = entry_price - 0.02 * entry_price # Example stop loss calculation
take_profit = entry_price + 0.03 * entry_price # Example take profit calculation
elif lower_breakout[i]:
trade_type = 'Short'
entry_price = close[i]
stop_loss = entry_price + 0.02 * entry_price # Example stop loss calculation
take_profit = entry_price - 0.03 * entry_price # Example take profit calculation
else:
if trade_type == 'Long':
if close[i] <= stop_loss or close[i] >= take_profit:
trades.append((entry_price, stop_loss, take_profit))
trade_type = None
entry_price = None
stop_loss = None
take_profit = None
elif trade_type == 'Short':
if close[i] >= stop_loss or close[i] <= take_profit:
trades.append((entry_price, stop_loss, take_profit))
trade_type = None
entry_price = None
stop_loss = None
take_profit = None

# Calculate metrics
total_trades = len(trades)
positive_trades = sum(1 for t in trades if t[2] > t[0])
win_rate = positive_trades / total_trades if total_trades > 0 else 0

cumulative_returns = sum((t[2] - t[0]) / t[0] for t in trades)
sharpe_ratio = (cumulative_returns - 0.01) / (cumulative_returns.std() + 1e-9)
sortino_ratio = (cumulative_returns - 0.01) / (cumulative_returns[cumulative_returns < 0].std() + 1e-9)
profit_factor = sum(t[2] - t[0] for t in trades if t[2] > t[0]) / abs(sum(t[2] - t[0] for t in trades if t[2] < t[0]))

# Print metrics
print(f"Total Trades: {total_trades}")
print(f"Positive Trades: {positive_trades}")
print(f"Win Rate: {win_rate * 100}%")
print(f"Cumulative Returns: {cumulative_returns * 100}%")
print(f"Sharpe Ratio: {sharpe_ratio}")
print(f"Sortino Ratio: {sortino_ratio}")
print(f"Profit Factor: {profit_factor}")

# Plotting
plt.plot(close[length:], label='Closing Price')
plt.plot(upper[length:], label='Upper Trendline', color='#26a69a')
plt.plot(lower[length:], label='Lower Trendline', color='#ef5350')

for i in range(len(close)):
if upper_breakout[i]:
plt.scatter(i, close[i-length], marker='^', color='r', label='Upper Break')
if lower_breakout[i]:
plt.scatter(i, close[i-length], marker='v', color='g', label='Lower Break')

plt.legend()
plt.show()



Here if the lower_breakout is True, one must short and vice versa for upper_breakout.

While running the code: I'm getting an error saying:

/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/numpy/core/_methods.py:265: RuntimeWarning: Degrees of freedom <= 0 for slice
ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/numpy/core/_methods.py:223: RuntimeWarning: invalid value encountered in divide
arrmean = um.true_divide(arrmean, div, out=arrmean, casting='unsafe',
/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/numpy/core/_methods.py:257: RuntimeWarning: invalid value encountered in double_scalars
ret = ret.dtype.type(ret / rcount)
/Users/dev.barbhaya9gmail.com/Library/CloudStorage/OneDrive-IITKanpur/Beyond/BRAINWorks/Internship/Project #304/strategy (ta-lib).py:141: RuntimeWarning: divide by zero encountered in double_scalars
profit_factor = sum(t[2] - t[0] for t in trades if t[2] > t[0]) / abs(sum(t[2] - t[0] for t in trades if t[2] < t[0]))
Total Trades: 82
Positive Trades: 82
Win Rate: 100.0%
Cumulative Returns: 246.0%
Sharpe Ratio: 2450000000.0
Sortino Ratio: nan
Profit Factor: inf
/Users/dev.barbhaya9gmail.com/Library/CloudStorage/OneDrive-IITKanpur/Beyond/BRAINWorks/Internship/Project #304/strategy (ta-lib).py:153: MatplotlibDeprecationWarning: The resize_event function was deprecated in Matplotlib 3.6 and will be removed two minor releases later. Use callbacks.process('resize_event', ResizeEvent(...)) instead.
plt.plot(close[length:], label='Closing Price')
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/core/indexes/range.py", line 391, in get_loc
return self._range.index(new_key)
ValueError: -14 is not in range

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "/Users/dev.barbhaya9gmail.com/Library/CloudStorage/OneDrive-IITKanpur/Beyond/BRAINWorks/Internship/Project #304/strategy (ta-lib).py", line 159, in <module>
plt.scatter(i, close[i-length], marker='^', color='r', label='Upper Break')
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/core/series.py", line 981, in __getitem__
return self._get_value(key)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/core/series.py", line 1089, in _get_value
loc = self.index.get_loc(label)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pandas/core/indexes/range.py", line 393, in get_loc
raise KeyError(key) from err
KeyError: -14


I'm trying to understand if the code has any errors, but I can't find any issues.

I'm very new to python and all your help will be truly appreciated.

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