A few days ago I watched a video about the relationship between the Commitments of Trader’s commercials net position and detecting bottoms in a commodity futures market. Commercial traders are traders that actually provide a commodity or instrument to the market or have bought a contract to take delivery of it. Commercials are usually net short in their commodity, and in the few times they get net long we can suspect that the commodity is strongly undervalued.
I will look for net long positions in the Soybean Oil market:
import quandl import pandas as pd import matplotlib.pyplot as plt bo_cot_legacy = quandl.get("CFTC/BO_F_L_ALL") bo_1 = quandl.get("CHRIS/CME_BO1", authtoken="YOURQUANDLTOKEN", start_date="2000-01-01", end_date="2017-05-11") bo_1_cot = pd.merge(bo_1, bo_cot_legacy, how='outer',left_index=True, right_index=True).fillna(method='ffill') fig, ax1 = plt.subplots() plt.title('Soybean Oil & Commercials net long') ax1.plot(bo_1_cot.Settle, 'b-') net_long=bo_1_cot['Commercial Long']-bo_1_cot['Commercial Short']>0 ax1.plot(bo_1_cot.Settle[net_long],'g^') fig.autofmt_xdate()
And here is the answer: