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November 4, 2023 03:35
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This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,59 @@ import pandas as pd from bokeh.plotting import figure, show from bokeh.models import NumeralTickFormatter, HoverTool from bokeh.models import LinearAxis, Range1d import yfinance as yf # --------------------------------------------------------------------- df = treasury_gov_pandas.update_records( 'auctions_query.pkl', 'https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query') # ---------------------------------------------------------------------- df['record_date'] = pd.to_datetime(df['record_date']) df['issue_date'] = pd.to_datetime(df['issue_date']) df['maturity_date'] = pd.to_datetime(df['maturity_date']) df['auction_date'] = pd.to_datetime(df['auction_date']) df['total_accepted'] = pd.to_numeric(df['total_accepted'], errors='coerce') df['total_accepted_neg'] = df['total_accepted'] * -1 # ---------------------------------------------------------------------- bills = df[df['security_type'] == 'Bill'] notes = df[df['security_type'] == 'Note'] bonds = df[df['security_type'] == 'Bond'] # ---------------------------------------------------------------------- freq='Q' # ---------------------------------------------------------------------- bills_issued = bills.groupby(pd.Grouper(key='issue_date', freq=freq))['total_accepted'].sum().to_frame() notes_issued = notes.groupby(pd.Grouper(key='issue_date', freq=freq))['total_accepted'].sum().to_frame() bonds_issued = bonds.groupby(pd.Grouper(key='issue_date', freq=freq))['total_accepted'].sum().to_frame() # ---------------------------------------------------------------------- bills_notes_bonds_issued = bills_issued.merge(notes_issued, how='outer', on='issue_date').merge(bonds_issued, how='outer', on='issue_date') bills_notes_bonds_issued.columns = ['bills', 'notes', 'bonds'] bills_notes_bonds_issued['bills_notes_ratio'] = bills_notes_bonds_issued['bills'] / bills_notes_bonds_issued['notes'] bills_notes_bonds_issued['bills_notes_bonds_ratio'] = bills_notes_bonds_issued['bills'] / (bills_notes_bonds_issued['notes'] + bills_notes_bonds_issued['bonds']) # ---------------------------------------------------------------------- spx = yf.Ticker('^GSPC') data = spx.history(start='1980-01-01', interval='1d') # ---------------------------------------------------------------------- p = figure(title=f'Treasury Securities Auctions Data : {freq}', sizing_mode='stretch_both', x_axis_type='datetime', x_axis_label='date', y_axis_label='', y_range=(0, 10)) p.line(x='issue_date', y='bills_notes_ratio', color='black', legend_label='Bills/Notes ratio', source=bills_notes_bonds_issued) p.extra_y_ranges = {"spx": Range1d(start=min(data['Close']), end=max(data['Close']))} p.add_layout(LinearAxis(y_range_name="spx", axis_label='SPX'), 'right') p.line(x='Date', y='Close', color='blue', legend_label='SPX', source=data, y_range_name="spx") p.legend.click_policy = 'hide' p.legend.location = 'top_left' show(p)