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Update tsmom graphs
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@rkohli3
rkohli3 committed Jul 13, 2020
1 parent 3a3c7d5 commit 9e1dfc9
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Showing 3 changed files with 65 additions and 29,129 deletions.
2 changes: 1 addition & 1 deletion YahooFinance.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ def base(self):
jsn = json.loads(txt)
try:
stk_data = jsn['context']['dispatcher']['stores']['HistoricalPriceStore']
except KeyError():
except KeyError:
raise KeyError('No data found for'.format(self.symbol))
return jsn

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29,079 changes: 0 additions & 29,079 deletions momentum.ipynb
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113 changes: 64 additions & 49 deletions tsmom.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@
import matplotlib
import YahooFinance as yf
import string
import calendar

def get_adj_close(tickers,start, end, source = 'yahoo'):
"""F: to get adjusted close columns for a list of tickers using Paython's web data dreader
Expand Down Expand Up @@ -235,7 +236,7 @@ def get_eq_line(series, data = 'returns', ret_type = 'arth', dtime = 'monthly'):

return cum_rets_prd

def get_exante_vol(series, alpha = 0.05, dtime = 'monthly', dtype = 'returns'):
def get_exante_vol(series, alpha = 0.05, dtime = 'monthly', dtype = 'returns', com = None):

"""F: that provides annualized ex ante volatility based on the method of Exponentially Weighted Average\n
This method is also know as the Risk Metrics, where the instantaneous volatility is based on past volatility\n
Expand Down Expand Up @@ -819,7 +820,9 @@ def get_monthly_heatmap(returns,
show_scale = False,
height = 600,
vmin = 0,
vmax = 255):
vmax = 255,
reversescale = False,
render = 'notebook_connected'):

"""F: to plot heatmap of monthly returns:
Expand All @@ -840,9 +843,9 @@ def get_monthly_heatmap(returns,
yr_from = returns.index[0].year
grid = empyrical.aggregate_returns(returns, convert_to = 'monthly').unstack().fillna(0).round(4) * 100
grid = grid.loc[yr_from:yr_to,:]
z = grid.as_matrix()
z = grid.values
y = grid.index.values.tolist()
x = grid.columns.values.tolist()
x = [calendar.month_abbr[i] for i in grid.columns.values.tolist()]

z = grid.values.tolist()
z.reverse()
Expand All @@ -853,7 +856,7 @@ def get_monthly_heatmap(returns,
y= y[::-1],
annotation_text= z_text,
colorscale = cscale,
reversescale = True,
reversescale = reversescale,
hoverinfo = "y+z",
showscale = show_scale,
font_colors= colors)
Expand Down Expand Up @@ -881,14 +884,22 @@ def get_monthly_heatmap(returns,
image_width = width,
image_height= 900,
filename = filename)
elif plt_type == 'show':
return fighm.show(render = render,
)
elif online == True:
return py.iplot(fighm, show_link = False, filename = filename)

def get_monthly_hist(series,
height = 400,
width = 900,
plt_type = 'iplot',
filename = None):
filename = None,
online = False,
rng = [-0.1, 0.1],
render = 'notebook_connceted'):


"""F: to plot histogram of monthly returns
params:
Expand All @@ -898,62 +909,66 @@ def get_monthly_hist(series,
returns:
plotly iplotint"""
pd.options.plotting.backend = 'plotly'
if (len(series) > 200) and (len(series) < 500):
nbins = int(len(series)/2)
elif len(series) < 200:
nbins = int(len(series))
else:
nbins = int(len(series)/4)
hist = series.iplot(kind = 'histogram',
colors = '#5f4a52',
vline = series.mean(),
bins = nbins,
asFigure= True,
layout_update = {'plot_bgcolor': 'white',
'paper_bgcolor': 'white',
'title': 'Monthly Returns Histogram for {}'.format(series.name),
'margin': dict(t = 40, pad = -40),
'width': width,
'height': height,
'xaxis' : dict(title = 'Returns',
showgrid = False,
showticklabels = True,
zeroline = True,
zerolinewidth = 3,
color = 'black',
range = [-0.06, 0.06],
hoverformat = '0.2%'
),
'yaxis' : dict(title = 'Frequency',
showgrid = False,
showticklabels = True,
zeroline = True,
zerolinewidth = 1,
color = 'black'
import plotly.express as px
hist = px.histogram(series,
nbins = 40,
title = 'Monthly Returns',
width = 700,
height = 500,

)
hist['layout'] = {'plot_bgcolor': 'white',
'paper_bgcolor': 'white',
'title': 'Monthly Returns Histogram for {}'.format(series.name),
'margin': dict(t = 40, ),#pad = -40
'xaxis' : dict(title = 'Returns',
showgrid = False,
showticklabels = True,
zeroline = True,
zerolinewidth = 3,
color = 'black',
range = rng,
hoverformat = '0.2%'
),
'shapes' : [dict(type = 'line',

x0 = series.mean(),
x1 = series.mean(),
y0 = 0,
y1 = 1,
yref = 'paper',
line = dict(dash = 'dash' + 'dot',
width = 4,
color = 'orange'),
)
],
'showlegend' : True,
'legend' : dict(x = 0.85,
y = 0.9,
bgcolor = 'white'),
})
'yaxis' : dict(title = 'Frequency',
showgrid = False,
showticklabels = True,
zeroline = True,
zerolinewidth = 1,
color = 'black'
),
'shapes' : [dict(type = 'line',

x0 = series.mean(),
x1 = series.mean(),
y0 = 0,
y1 = 1,
yref = 'paper',
line = dict(dash = 'dash' + 'dot',
width = 4,
color = 'orange'),
)
],
'showlegend' : True,
'legend' : dict(x = 0.85,
y = 0.9,
bgcolor = 'white'),
}
hist.layout.xaxis.tickformat = '0.00%'
if online == False:
if plt_type == 'iplot':
return iplot(hist, show_link= False)
elif plt_type == 'plot':
return plot(hist, show_link = False, filename = filename)
elif plt_type == 'show':
return hist.show(render = render)
elif online ==True:
py.iplot(hist, show_link = False)

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