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I am trying to get my head around stock data and it's implementation in python. In starting I am using MACD indicator in Python stockstats library.
Thing I want to know, if I have 100 OHLC entries of a certain stock, how can I use MACD output to produce signals whether I should Buy or Sell or Hold? In Graph one can visualize but in terms of programming how do I get the idea? Sample code given below:
import pandas as pd
from stockstats import StockDataFrame as Sdf
from pandas_datareader import data, wb
data = pd.read_csv('data.csv')
stock = Sdf.retype(data)
print(stock.get('pdi'))
It produces output as given below:
0 0.000000e+00
1 -8.951923e-08
2 1.758777e-07
3 -3.844324e-08
4 -2.217396e-07
5 -3.893329e-07
6 -2.373225e-07
7 -5.082528e-07
8 -8.260595e-07
9 -1.099751e-06
10 -1.429675e-06
11 -1.211562e-06
12 -8.230303e-07
13 -5.163039e-07
14 -4.979626e-07
15 -4.777865e-07
16 -6.217018e-07
17 -1.145459e-06
18 -1.461550e-06
19 -1.744250e-06
20 -1.677791e-06
21 -1.820319e-06
22 -2.024092e-06
23 -1.958413e-06
24 -2.450087e-06
25 -2.805521e-06
26 -3.443776e-06
27 -4.047889e-06
28 -4.839084e-06
29 -5.208106e-06
...
1410 4.856951e-06
1411 6.075773e-06
1412 9.159968e-06
1413 9.985022e-06
1414 1.069234e-05
1415 1.140865e-05
1416 1.136520e-05
1417 1.156541e-05
1418 1.065633e-05
1419 9.176497e-06
1420 9.275813e-06
1421 8.254755e-06
1422 7.583274e-06
1423 7.301820e-06
1424 6.959007e-06
1425 6.292826e-06
1426 8.411427e-06
1427 8.746155e-06
1428 1.112640e-05
1429 1.299290e-05
1430 1.398810e-05
1431 1.441297e-05
1432 1.509612e-05
1433 1.462091e-05
1434 1.436198e-05
1435 1.390849e-05
1436 1.419959e-05
1437 1.554140e-05
1438 1.884861e-05
1439 2.163656e-05
Name: macd, Length: 1440, dtype: float64
347
Visualizing the MACD in Python with Plotly Chart the price as a Candlestick visualization similar to the chart seen above; Chart the MACD and Signal lines in a second chart, below the Candlestick; Chart the Convergence/Divergence series as a Histogram overlaying our signal lines.
The strategy is to buy – or close a short position – when the MACD crosses above the zero line, and sell – or close a long position – when the MACD crosses below the zero line. This method should be used carefully, as the delayed nature means that fast, choppy markets would often see the signals issued too late.
The standard setting for MACD is the difference between the 12- and 26-period EMAs. Chartists looking for more sensitivity may try a shorter short-term moving average and a longer long-term moving average. MACD(5,35,5) is more sensitive than MACD(12,26,9) and might be better suited for weekly charts.
The Indicator The periods used to calculate the MACD can be easily customized to fit any strategy, but traders will commonly rely on the default settings of 12- and 26-day periods. A positive MACD value, created when the short-term average is above the longer-term average, is used to signal increasing upward momentum.
Here you go, with explanation in comments.
import pandas as pd
from stockstats import StockDataFrame as Sdf
data = pd.read_csv('data.csv')
stock = Sdf.retype(data)
signal = stock['macds'] # Your signal line
macd = stock['macd'] # The MACD that need to cross the signal line
# to give you a Buy/Sell signal
listLongShort = ["No data"] # Since you need at least two days in the for loop
for i in range(1, len(signal)):
# # If the MACD crosses the signal line upward
if macd[i] > signal[i] and macd[i - 1] <= signal[i - 1]:
listLongShort.append("BUY")
# # The other way around
elif macd[i] < signal[i] and macd[i - 1] >= signal[i - 1]:
listLongShort.append("SELL")
# # Do nothing if not crossed
else:
listLongShort.append("HOLD")
stock['Advice'] = listLongShort
# The advice column means "Buy/Sell/Hold" at the end of this day or
# at the beginning of the next day, since the market will be closed
print(stock['Advice'])
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