def toplobbying_command(num: int = 10, raw: bool = False):
"""Displays top lobbying firms [quiverquant.com]"""
# Debug user input
if cfg.DEBUG:
logger.debug("gov-toplobbying %s %s", num, raw)
# Retrieve Data
df_lobbying = quiverquant_model.get_government_trading(
"corporate-lobbying")
if df_lobbying.empty:
raise Exception("No corporate lobbying found")
df_lobbying["Amount"] = df_lobbying.Amount.astype(float).fillna(
0) / 100_000
lobbying_by_ticker = pd.DataFrame(
df_lobbying.groupby("Ticker")["Amount"].agg("sum")).sort_values(
by="Amount", ascending=False)
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
lobbying_by_ticker.head(num).plot(kind="bar", ax=ax)
ax.set_xlabel("Ticker")
ax.set_ylabel("Total Amount ($100k)")
ax.set_title(f"Corporate Lobbying Spent since {df_lobbying['Date'].min()}")
fig.tight_layout()
plt.savefig("ta_toplobbying.png")
imagefile = "ta_toplobbying.png"
imagefile = image_border(imagefile)
return {
"title": "Stocks: [quiverquant.com] Top Lobbying Firms",
"imagefile": imagefile,
}
def view_command(ticker=""):
"""Displays image from Finviz [Finviz]"""
# Debug
if cfg.DEBUG:
logger.debug("ta view %s", ticker)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
image_data = finviz_model.get_finviz_image(ticker)
dataBytesIO = io.BytesIO(image_data)
im = Image.open(dataBytesIO)
im = im.resize((800, 340), Image.ANTIALIAS)
imagefile = "ta_view.png"
im.save(dataBytesIO, "PNG", quality=100)
dataBytesIO.seek(0)
imagefile = image_border(imagefile, base64=dataBytesIO)
im.close()
return {
"title": f"Stocks: [Finviz] Trendlines & Data {ticker.upper()}",
"imagefile": imagefile,
}
def histcont_command(ticker=""):
"""Displays historical quarterly-contracts [quiverquant.com]"""
# Debug user input
if cfg.DEBUG:
logger.debug("gov-histcont %s", ticker)
if ticker == "":
raise Exception("A ticker is required")
# Retrieve Data
df_contracts = quiverquant_model.get_government_trading(
"quarter-contracts", ticker=ticker
)
if df_contracts.empty:
logger.debug("No quarterly government contracts found")
raise Exception("No quarterly government contracts found")
# Output Data
amounts = df_contracts.sort_values(by=["Year", "Qtr"])["Amount"].values
qtr = df_contracts.sort_values(by=["Year", "Qtr"])["Qtr"].values
year = df_contracts.sort_values(by=["Year", "Qtr"])["Year"].values
quarter_ticks = [
f"{quarter[0]}" if quarter[1] == 1 else "" for quarter in zip(year, qtr)
]
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax.plot(np.arange(0, len(amounts)), amounts / 1000, "-*", lw=2, ms=15)
ax.set_xlim([-0.5, len(amounts) - 0.5])
ax.set_xticks(np.arange(0, len(amounts)))
ax.set_xticklabels(quarter_ticks)
ax.grid()
ax.set_title(f"Historical Quarterly Government Contracts for {ticker.upper()}")
ax.set_xlabel("Date")
ax.set_ylabel("Amount ($1k)")
fig.tight_layout()
plt.savefig("gov_histcont.png")
imagefile = "gov_histcont.png"
imagefile = image_border(imagefile)
return {
"title": "Stocks: Historical Quarterly Government Contract ",
"imagefile": imagefile,
}
def contracts_command(
ticker: str = "", past_transaction_days: Union[int, str] = 10, raw: bool = False
):
"""Displays contracts associated with tickers [quiverquant.com]"""
past_transaction_days = int(past_transaction_days)
# Debug user input
if cfg.DEBUG:
logger.debug("gov-contracts %s %s %s", ticker, past_transaction_days, raw)
if ticker == "":
raise Exception("A ticker is required")
# Retrieve Data
df_contracts = quiverquant_model.get_government_trading("contracts", ticker)
if df_contracts.empty:
return {
"title": f"Stocks: [quiverquant.com] Contracts by {ticker}",
"description": f"{ticker} does not have any contracts",
}
# Output Data
df_contracts["Date"] = pd.to_datetime(df_contracts["Date"]).dt.date
df_contracts = df_contracts[
df_contracts["Date"].isin(df_contracts["Date"].unique()[:past_transaction_days])
]
df_contracts.drop_duplicates(inplace=True)
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
df_contracts.groupby("Date").sum().div(1000).plot(kind="bar", rot=0, ax=ax)
ax.set_ylabel("Amount ($1k)")
ax.set_title(f"Sum of latest government contracts to {ticker}")
fig.tight_layout()
plt.savefig("gov_contracts.png")
imagefile = "gov_contracts.png"
imagefile = image_border(imagefile)
return {
"title": f"Stocks: [quiverquant.com] Contracts by {ticker}",
"imagefile": imagefile,
}
def feargreed_command(indicator=""):
"""CNN Fear and Greed Index [CNN]"""
# Debug user input
if cfg.DEBUG:
logger.debug("econ-futures")
# Check for argument
possible_indicators = ("", "jbd", "mv", "pco", "mm", "sps", "spb", "shd")
if indicator not in possible_indicators:
raise Exception(
f"Select a valid indicator from {', '.join(possible_indicators)}" # nosec
)
# Output data
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
report, im = cnn_model.get_feargreed_report(indicator, fig)
ax.axes.xaxis.set_visible(False)
ax.axes.yaxis.set_visible(False)
if indicator:
ax.imshow(im)
imagefile = "feargreed.png"
dataBytesIO = io.BytesIO()
plt.savefig(dataBytesIO)
plt.close("all")
dataBytesIO.seek(0)
imagefile = image_border(imagefile, base64=dataBytesIO)
return {
"title": "Economy: [CNN] Fear Geed Index",
"imagefile": imagefile,
"description": report,
}
def donchian_command(ticker="",
upper_length="25",
lower_length="100",
start="",
end=""):
"""Displays chart with donchian channel [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta donchian %s %s %s %s %s",
ticker,
upper_length,
lower_length,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not upper_length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
upper_length = float(upper_length)
if not lower_length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
lower_length = float(lower_length)
ticker = ticker.upper()
df_stock = load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = volatility_model.donchian(df_stock["High"], df_stock["Low"],
upper_length, lower_length)
df_ta = df_ta.fillna(0.0)
# Output Data
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax.plot(df_stock.index, df_stock["Adj Close"].values, lw=3)
ax.plot(df_ta.index, df_ta.iloc[:, 0].values, lw=1.5, label="upper")
ax.plot(df_ta.index, df_ta.iloc[:, 1].values, lw=1.5, ls="--")
ax.plot(df_ta.index, df_ta.iloc[:, 2].values, lw=1.5, label="lower")
ax.set_title(f"{ticker} donchian")
ax.set_xlim(df_stock.index[0], df_stock.index[-1])
ax.set_xlabel("Time")
ax.set_ylabel("Price ($)")
ax.legend([ticker, df_ta.columns[0], df_ta.columns[1], df_ta.columns[2]])
ax.fill_between(
df_ta.index,
df_ta.iloc[:, 0].values,
df_ta.iloc[:, 2].values,
alpha=0.1,
)
ax.grid(b=True, which="major", color="#666666", linestyle="-")
plt.gcf().autofmt_xdate()
fig.tight_layout(pad=1)
plt.legend()
imagefile = "ta_donchian.png"
dataBytesIO = io.BytesIO()
plt.savefig(dataBytesIO)
plt.close("all")
dataBytesIO.seek(0)
imagefile = image_border(imagefile, base64=dataBytesIO)
return {
"title": f"Stocks: Donchian-Channels {ticker}",
"imagefile": imagefile,
}
def cg_command(ticker="", length="14", start="", end=""):
"""Displays chart with centre of gravity [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-cg %s %s %s %s",
ticker,
length,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
ticker = ticker.upper()
df_stock = bots.helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_close = df_stock["Adj Close"]
df_close.columns = ["values"]
df_ta = momentum_model.cg(df_close, length)
# Output Data
fig, axes = plt.subplots(2, 1, figsize=plot_autoscale(), dpi=PLOT_DPI)
ax = axes[0]
ax.set_title(f"{ticker} Centre of Gravity")
ax.plot(df_stock.index, df_stock["Adj Close"].values, "k", lw=1)
ax.set_xlim(df_stock.index[0], df_stock.index[-1])
ax.set_ylabel("Share Price ($)")
ax.grid(b=True, which="major", color="#666666", linestyle="-")
ax2 = axes[1]
ax2.plot(df_ta.index, df_ta.values, "b", lw=2, label="CG")
# shift cg 1 bar forward for signal
signal = df_ta.values
signal = np.roll(signal, 1)
ax2.plot(df_ta.index, signal, "g", lw=1, label="Signal")
ax2.set_xlim(df_stock.index[0], df_stock.index[-1])
ax2.grid(b=True, which="major", color="#666666", linestyle="-")
plt.gcf().autofmt_xdate()
fig.tight_layout(pad=1)
plt.legend()
imagefile = "ta_cg.png"
plt.savefig(imagefile)
imagefile = image_border(imagefile)
return {
"title": f"Stocks: Center-of-Gravity {ticker}",
"imagefile": imagefile,
}
def historical_command(signal: str = "", start=""):
"""Displays historical price comparison between similar companies [Yahoo Finance]"""
# Debug user input
if cfg.DEBUG:
logger.debug("scr-historical %s %s", signal, start)
# Check for argument
if signal not in so.d_signals_desc:
raise Exception("Invalid preset selected!")
register_matplotlib_converters()
screen = ticker.Ticker()
if signal in finviz_model.d_signals:
screen.set_filter(signal=finviz_model.d_signals[signal])
else:
preset_filter = configparser.RawConfigParser()
preset_filter.optionxform = str # type: ignore
preset_filter.read(so.presets_path + signal + ".ini")
d_general = preset_filter["General"]
d_filters = {
**preset_filter["Descriptive"],
**preset_filter["Fundamental"],
**preset_filter["Technical"],
}
d_filters = {k: v for k, v in d_filters.items() if v}
if d_general["Signal"]:
screen.set_filter(filters_dict=d_filters,
signal=d_general["Signal"])
else:
screen.set_filter(filters_dict=d_filters)
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
# Output Data
l_min = []
l_leg = []
l_stocks = screen.ScreenerView(verbose=0)
if len(l_stocks) > 10:
description = (
"\nThe limit of stocks to compare with are 10. Hence, 10 random similar stocks will be displayed."
"\nThe selected list will be: ")
random.shuffle(l_stocks)
l_stocks = sorted(l_stocks[:10])
description = description + (", ".join(l_stocks))
logger.debug(description)
plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
while l_stocks:
l_parsed_stocks = []
for symbol in l_stocks:
try:
df_similar_stock = yf.download(
symbol,
start=datetime.strftime(start, "%Y-%m-%d"),
progress=False,
threads=False,
)
if not df_similar_stock.empty:
plt.plot(
df_similar_stock.index,
df_similar_stock["Adj Close"].values,
)
l_min.append(df_similar_stock.index[0])
l_leg.append(symbol)
l_parsed_stocks.append(symbol)
except Exception as e:
error = (
f"{e}\nDisregard previous error, which is due to API Rate limits from Yahoo Finance. "
f"Because we like '{symbol}', and we won't leave without getting data from it."
)
return {
"title":
"ERROR Stocks: [Yahoo Finance] Historical Screener",
"description": error,
}
for parsed_stock in l_parsed_stocks:
l_stocks.remove(parsed_stock)
if signal:
plt.title(
f"Screener Historical Price using {finviz_model.d_signals[signal]} signal"
)
else:
plt.title(f"Screener Historical Price using {signal} preset")
plt.xlabel("Time")
plt.ylabel("Share Price ($)")
plt.legend(l_leg)
plt.grid(b=True, which="major", color="#666666", linestyle="-")
plt.minorticks_on()
plt.grid(b=True, which="minor", color="#999999", linestyle="-", alpha=0.2)
# ensures that the historical data starts from same datapoint
plt.xlim([max(l_min), df_similar_stock.index[-1]])
imagefile = "scr_historical.png"
plt.savefig(imagefile)
imagefile = image_border(imagefile)
return {
"title": "Stocks: [Yahoo Finance] Historical Screener",
"description": description,
"imagefile": imagefile,
}
def spos_command(ticker: str = ""):
"""Net short vs position [Stockgrid]"""
# Debug user input
if cfg.DEBUG:
logger.debug("dps-spos %s", ticker)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
ticker = ticker.upper()
stock = yf.download(ticker, progress=False)
if stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve data
df = stockgrid_model.get_net_short_position(ticker)
# Debug user output
if cfg.DEBUG:
logger.debug(df.to_string())
# Output data
title = f"Stocks: [Stockgrid] Net Short vs Position {ticker}"
fig = make_subplots(shared_xaxes=True, specs=[[{"secondary_y": True}]])
fig.add_trace(
go.Scatter(
name="Position ($)",
x=df["dates"].values,
y=df["dollar_dp_position"] * 1_000,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
secondary_y=True,
)
fig.add_trace(
go.Bar(
name="Net Short Vol. ($)",
x=df["dates"],
y=df["dollar_net_volume"],
opacity=1,
showlegend=False,
),
secondary_y=False,
)
# Set y-axes titles
fig.update_xaxes(dtick="M1", tickformat="%b %d\n%Y")
fig.update_yaxes(title_text="<b>Position</b> ($)", secondary_y=True)
fig.update_traces(hovertemplate="%{y:.2s}")
fig.update_layout(
margin=dict(l=0, r=10, t=40, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"Net Short Vol. vs Position for {ticker}",
title_x=0.5,
yaxis_title="<b>Net Short Vol.</b> ($)",
yaxis=dict(
side="left",
showgrid=False,
fixedrange=False,
layer="above traces",
titlefont=dict(color="#d81aea"),
tickfont=dict(color="#d81aea"),
nticks=10,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
xaxis2=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
yaxis2=dict(
side="right",
position=0.15,
fixedrange=False,
titlefont=dict(color="#fdc708"),
tickfont=dict(color="#fdc708"),
nticks=10,
),
hovermode="x unified",
)
config = dict({"scrollZoom": True})
imagefile = "dps_spos.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/spos_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/spos_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": title,
"description": plt_link,
"imagefile": imagefile,
}
def vol_command(
ticker: str = None,
expiry: str = "",
min_sp: float = None,
max_sp: float = None,
):
"""Options VOL"""
# Debug
if cfg.DEBUG:
logger.debug("opt-vol %s %s %s %s", ticker, expiry, min_sp, max_sp)
# Check for argument
if ticker is None:
raise Exception("Stock ticker is required")
dates = yfinance_model.option_expirations(ticker)
if not dates:
raise Exception("Stock ticker is invalid")
options = yfinance_model.get_option_chain(ticker, expiry)
current_price = yfinance_model.get_price(ticker)
if min_sp is None:
min_strike = 0.75 * current_price
else:
min_strike = min_sp
if max_sp is None:
max_strike = 1.25 * current_price
else:
max_strike = max_sp
calls = options.calls
puts = options.puts
call_v = calls.set_index("strike")["volume"] / 1000
put_v = puts.set_index("strike")["volume"] / 1000
df_opt = pd.merge(put_v, call_v, left_index=True, right_index=True)
dmax = df_opt.values.max()
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=call_v.index,
y=call_v.values,
name="Calls",
mode="lines+markers",
line=dict(color="green", width=3),
))
fig.add_trace(
go.Scatter(
x=put_v.index,
y=put_v.values,
name="Puts",
mode="lines+markers",
line=dict(color="red", width=3),
))
fig.add_trace(
go.Scatter(
x=[current_price, current_price],
y=[0, dmax],
mode="lines",
line=dict(color="gold", width=2),
name="Current Price",
))
fig.update_xaxes(
range=[min_strike, max_strike],
constrain="domain",
)
fig.update_layout(
margin=dict(l=0, r=0, t=60, b=20),
template=cfg.PLT_SCAT_STYLE_TEMPLATE,
title=f"Volume for {ticker.upper()} expiring {expiry}",
title_x=0.5,
legend_title="",
xaxis_title="Strike",
yaxis_title="Volume (1k)",
xaxis=dict(rangeslider=dict(visible=False), ),
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
dragmode="pan",
)
config = dict({"scrollZoom": True})
imagefile = "opt_vol.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/vol_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/vol_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Volume for {ticker.upper()} expiring {expiry}",
"description": plt_link,
"imagefile": imagefile,
}
def obv_command(ticker="", start="", end=""):
"""Displays chart with on balance volume [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-obv %s %s %s",
ticker,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
# Output Data
divisor = 1_000_000
df_vol = df_stock["Volume"].dropna()
df_vol = df_vol.values / divisor
df_ta = volume_model.obv(df_stock)
df_cal = df_ta.values
df_cal = df_cal / divisor
fig = make_subplots(
rows=3,
cols=1,
shared_xaxes=True,
vertical_spacing=0.06,
row_width=[0.2, 0.2, 0.2],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
),
row=1,
col=1,
)
colors = [
"green" if row.Open < row["Adj Close"] else "red"
for _, row in df_stock.iterrows()
]
fig.add_trace(
go.Bar(
x=df_stock.index,
y=df_vol,
name="Volume [M]",
marker_color=colors,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name="OBC [M]",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
line=dict(width=2),
opacity=1,
),
row=3,
col=1,
)
fig.update_layout(
margin=dict(l=10, r=0, t=40, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} OBV",
title_x=0.4,
yaxis_title="Stock Price ($)",
yaxis2_title="Volume [M]",
yaxis3_title="OBV [M]",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
)
config = dict({"scrollZoom": True})
imagefile = "ta_obv.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/obv_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/obv_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: On-Balance-Volume {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def gtrades_command(
ticker: str = "",
gov_type="",
past_transactions_months: int = 10,
raw: bool = False,
):
"""Displays government trades [quiverquant.com]"""
# Debug user input
if cfg.DEBUG:
logger.debug(
"gov-gtrades %s %s %s %s",
ticker,
gov_type,
past_transactions_months,
raw,
)
if ticker == "":
raise Exception("A ticker is required")
possible_args = ["congress", "senate", "house"]
if gov_type == "":
gov_type = "congress"
elif gov_type not in possible_args:
raise Exception(
"Enter a valid government argument, options are: congress, senate and house"
)
# Retrieve Data
df_gov = quiverquant_model.get_government_trading(gov_type, ticker)
if df_gov.empty:
raise Exception(f"No {gov_type} trading data found")
# Output Data
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
start_date = datetime.now() - timedelta(days=past_transactions_months * 30)
df_gov["TransactionDate"] = pd.to_datetime(df_gov["TransactionDate"])
df_gov = df_gov[df_gov["TransactionDate"] > start_date]
if df_gov.empty:
logger.debug("No recent %s trading data found", gov_type)
raise Exception(f"No recent {gov_type} trading data found")
df_gov["min"] = df_gov["Range"].apply(
lambda x: x.split("-")[0].strip("$").replace(",", "").strip()
)
df_gov["max"] = df_gov["Range"].apply(
lambda x: x.split("-")[1].replace(",", "").strip().strip("$")
if "-" in x
else x.strip("$").replace(",", "").split("\n")[0]
)
df_gov["lower"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: int(float(x["min"]))
if x["Transaction"] == "Purchase"
else -int(float(x["max"])),
axis=1,
)
df_gov["upper"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: int(float(x["max"]))
if x["Transaction"] == "Purchase"
else -1 * int(float(x["min"])),
axis=1,
)
df_gov = df_gov.sort_values("TransactionDate", ascending=True)
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax.fill_between(
df_gov["TransactionDate"].unique(),
df_gov.groupby("TransactionDate")["lower"].sum().values / 1000,
df_gov.groupby("TransactionDate")["upper"].sum().values / 1000,
)
ax.set_xlim(
[
df_gov["TransactionDate"].values[0],
df_gov["TransactionDate"].values[-1],
]
)
ax.grid()
ax.set_title(f"{gov_type.capitalize()} trading on {ticker}")
ax.set_xlabel("Date")
ax.set_ylabel("Amount ($1k)")
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter("%Y/%m/%d"))
plt.gcf().autofmt_xdate()
fig.tight_layout()
plt.savefig("gov_gtrades.png")
imagefile = "gov_gtrades.png"
imagefile = image_border(imagefile)
return {
"title": "Stocks: [quiverquant.com] Government Trades",
"imagefile": imagefile,
}
def dpotc_command(ticker: str = ""):
"""Dark pools (ATS) vs OTC data [FINRA]"""
# Debug user input
if cfg.DEBUG:
logger.debug("dps-dpotc %s", ticker)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
ticker = ticker.upper()
stock = yf.download(ticker, progress=False)
if stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve data
ats, otc = finra_model.getTickerFINRAdata(ticker)
# Debug user output
if cfg.DEBUG:
logger.debug(ats.to_string())
logger.debug(otc.to_string())
# Output data
title = f"Stocks: [FINRA] Dark Pools (ATS) vs OTC {ticker}"
if ats.empty and otc.empty:
raise Exception("Stock ticker is invalid")
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.4, 0.6],
specs=[[{
"secondary_y": True
}], [{
"secondary_y": False
}]],
)
if not ats.empty and not otc.empty:
fig.add_trace(
go.Bar(
x=ats.index,
y=(ats["totalWeeklyShareQuantity"] +
otc["totalWeeklyShareQuantity"]),
name="ATS",
opacity=0.8,
),
row=1,
col=1,
secondary_y=False,
)
fig.add_trace(
go.Bar(
x=otc.index,
y=otc["totalWeeklyShareQuantity"],
name="OTC",
opacity=0.8,
yaxis="y2",
offset=0.0001,
),
row=1,
col=1,
)
elif not ats.empty:
fig.add_trace(
go.Bar(
x=ats.index,
y=(ats["totalWeeklyShareQuantity"] +
otc["totalWeeklyShareQuantity"]),
name="ATS",
opacity=0.8,
),
row=1,
col=1,
secondary_y=False,
)
elif not otc.empty:
fig.add_trace(
go.Bar(
x=otc.index,
y=otc["totalWeeklyShareQuantity"],
name="OTC",
opacity=0.8,
yaxis="y2",
secondary_y=False,
),
row=1,
col=1,
)
if not ats.empty:
fig.add_trace(
go.Scatter(
name="ATS",
x=ats.index,
y=ats["totalWeeklyShareQuantity"] /
ats["totalWeeklyTradeCount"],
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
yaxis="y2",
),
row=2,
col=1,
)
if not otc.empty:
fig.add_trace(
go.Scatter(
name="OTC",
x=otc.index,
y=otc["totalWeeklyShareQuantity"] /
otc["totalWeeklyTradeCount"],
line=dict(color="#d81aea", width=2),
opacity=1,
showlegend=False,
),
row=2,
col=1,
)
else:
fig.add_trace(
go.Scatter(
name="OTC",
x=otc.index,
y=otc["totalWeeklyShareQuantity"] /
otc["totalWeeklyTradeCount"],
line=dict(color="#d81aea", width=2),
opacity=1,
showlegend=False,
),
row=2,
col=1,
)
fig.update_xaxes(showspikes=True, spikesnap="cursor", spikemode="across")
fig.update_yaxes(showspikes=True, spikethickness=2)
fig.update_layout(
margin=dict(l=20, r=0, t=10, b=20),
template=cfg.PLT_CANDLE_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"Dark Pools (ATS) vs OTC (Non-ATS) Data for {ticker}",
title_x=0.5,
yaxis3_title="Shares per Trade",
yaxis_title="Total Weekly Shares",
xaxis2_title="Weeks",
yaxis=dict(
fixedrange=False,
side="left",
nticks=20,
),
yaxis2=dict(
fixedrange=False,
showgrid=False,
overlaying="y",
anchor="x",
layer="above traces",
),
yaxis3=dict(
fixedrange=False,
nticks=10,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
showspikes=True,
nticks=20,
),
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
barmode="group",
bargap=0.5,
bargroupgap=0,
dragmode="pan",
hovermode="x unified",
spikedistance=1000,
hoverdistance=100,
)
config = dict({"scrollZoom": True})
imagefile = "dps_dpotc.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/dpotc_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/dpotc_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": title,
"description": plt_link,
"imagefile": imagefile,
}
def candle_command(
ticker: str = "",
interval: int = 15,
past_days: int = 1,
start="",
end="",
):
"""Shows candle plot of loaded ticker. [Source: Yahoo Finance, IEX Cloud or Alpha Vantage]
Parameters
----------
ticker: str
Ticker name
interval: int
chart mins or daily
past_days: int
Display the past * days. Default: 1(Not for Daily)
start: str
start date format YYYY-MM-DD
end: str
end date format YYYY-MM-DD
"""
logger.info("candle %s %s %s %s", ticker, interval, start, end)
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
futures = "=F" or "^"
crypto = "-USD"
if interval == 1440:
df_stock_candidate = yf.download(
ticker,
start=start,
end=end,
progress=False,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}")
df_stock_candidate.index.name = "date"
else:
s_int = str(interval) + "m"
d_granularity = {
"1m": past_days,
"5m": past_days,
"15m": past_days,
"30m": past_days,
"60m": past_days,
}
s_start_dt = datetime.utcnow() - timedelta(days=d_granularity[s_int])
s_date_start = s_start_dt.strftime("%Y-%m-%d")
df_stock_candidate = yf.download(
ticker,
start=s_date_start
if s_start_dt > start else start.strftime("%Y-%m-%d"),
progress=False,
interval=s_int,
prepost=True,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}.")
df_stock_candidate.index = df_stock_candidate.index.tz_localize(None)
df_stock_candidate.index.name = "date"
df_stock = df_stock_candidate
price_df = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_vwap = overlap_model.vwap(price_df, 0)
plt_title = [f"{ticker.upper()} Intraday {interval}min", "Volume"]
title = f"Intraday {interval}min Chart for {ticker.upper()}"
if interval == 1440:
plt_title = [f"{ticker.upper()} Daily", "Volume"]
title = f"Daily Chart for {ticker.upper()}"
fig = make_subplots(
shared_xaxes=True,
vertical_spacing=0.09,
subplot_titles=plt_title,
specs=[[{
"secondary_y": True
}]],
)
fig.add_trace(
go.Candlestick(
x=df_stock.index,
open=df_stock.Open,
high=df_stock.High,
low=df_stock.Low,
close=df_stock.Close,
name="OHLC",
showlegend=False,
),
secondary_y=True,
)
fig.add_trace(
go.Bar(
x=df_stock.index,
y=df_stock.Volume,
name="Volume",
yaxis="y2",
marker_color="#d81aea",
opacity=0.4,
showlegend=False,
),
secondary_y=False,
)
if interval != 1440:
fig.add_trace(
go.Scatter(
name="VWAP",
x=df_stock.index,
y=df_vwap["VWAP_D"],
opacity=0.65,
line=dict(color="#fdc708", width=2),
showlegend=True,
),
secondary_y=True,
)
fig.update_xaxes(showspikes=True, spikesnap="cursor", spikemode="across")
fig.update_yaxes(showspikes=True, spikethickness=2)
fig.update_layout(
margin=dict(l=0, r=0, t=40, b=20),
template=cfg.PLT_CANDLE_STYLE_TEMPLATE,
yaxis2_title="Price ($)",
yaxis_title="Volume",
yaxis=dict(
showgrid=False,
fixedrange=False,
side="left",
titlefont=dict(color="#d81aea"),
tickfont=dict(color="#d81aea"),
nticks=20,
),
yaxis2=dict(
side="right",
fixedrange=False,
anchor="x",
layer="above traces",
overlaying="y",
nticks=20,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
showspikes=True,
),
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
dragmode="pan",
hovermode="x unified",
spikedistance=1000,
hoverdistance=100,
)
if futures in ticker.upper():
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "sun"]),
dict(bounds=[17, 17.50], pattern="hour"),
], )
elif crypto not in ticker.upper() and interval != 1440:
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "mon"]),
dict(bounds=[20, 9.50], pattern="hour"),
], )
config = dict({"scrollZoom": True})
imagefile = "candle.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/candle_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/candle_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": title,
"description": plt_link,
"imagefile": imagefile,
}
def psi_command(ticker: str = ""):
"""Price vs short interest volume [Stockgrid]"""
# Debug user input
if cfg.DEBUG:
logger.debug("dps-psi %s", ticker)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
ticker = ticker.upper()
stock = yf.download(ticker, progress=False)
if stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve data
df, prices = stockgrid_model.get_short_interest_volume(ticker)
# Debug user output
if cfg.DEBUG:
logger.debug(df.to_string())
# Output data
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.06,
row_width=[0.3, 0.6],
specs=[[{
"secondary_y": True
}], [{
"secondary_y": False
}]],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df["date"].values,
y=prices[len(prices) - len(df):],
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
secondary_y=False,
)
fig.add_trace(
go.Bar(
x=df["date"],
y=df["total_volume"] / 1_000_000,
name="Total Volume",
yaxis="y2",
),
row=1,
col=1,
secondary_y=True,
)
fig.add_trace(
go.Bar(
x=df["date"],
y=df["short_volume"] / 1_000_000,
name="Short Volume",
yaxis="y2",
),
row=1,
col=1,
secondary_y=True,
)
fig.add_trace(
go.Scatter(
name="Short Vol. %",
x=df["date"].values,
y=100 * df["short_volume%"],
line=dict(width=2),
opacity=1,
showlegend=False,
),
row=2,
col=1,
secondary_y=False,
)
fig.update_traces(hovertemplate="%{y:.2f}")
fig.update_xaxes(showspikes=True, spikesnap="cursor", spikemode="across")
fig.update_yaxes(showspikes=True, spikethickness=2)
fig.update_layout(
margin=dict(l=10, r=0, t=40, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"Price vs Short Volume Interest for {ticker}",
title_x=0.45,
yaxis_title="Stock Price ($)",
yaxis2_title="FINRA Volume [M]",
yaxis3_title="Short Vol. %",
yaxis=dict(
side="right",
fixedrange=False,
titlefont=dict(color="#fdc708"),
tickfont=dict(color="#fdc708"),
nticks=20,
),
yaxis2=dict(
side="left",
fixedrange=False,
anchor="x",
overlaying="y",
titlefont=dict(color="#d81aea"),
tickfont=dict(color="#d81aea"),
nticks=20,
),
yaxis3=dict(
fixedrange=False,
titlefont=dict(color="#9467bd"),
tickfont=dict(color="#9467bd"),
nticks=20,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
hovermode="x unified",
spikedistance=1000,
hoverdistance=100,
)
config = dict({"scrollZoom": True})
imagefile = "dps_psi.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/psi_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/psi_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title":
f"Stocks: [Stockgrid] Price vs Short Interest Volume {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def qtrcontracts_command(num: int = 20, analysis=""):
"""Displays a look at government contracts [quiverquant.com]"""
# Debug user input
if cfg.DEBUG:
logger.debug("gov-qtrcontracts %s %s", num, analysis)
possible_args = ["total", "upmom", "downmom"]
if analysis == "":
analysis = "total"
elif analysis not in possible_args:
raise Exception(
"Enter a valid analysis argument, options are: total, upmom and downmom"
)
# Retrieve Data
df_contracts = quiverquant_model.get_government_trading(
"quarter-contracts")
if df_contracts.empty:
raise Exception("No quarterly government contracts found")
tickers = quiverquant_model.analyze_qtr_contracts(analysis, num)
# Output Data
if analysis in {"upmom", "downmom"}:
description = tickers.to_string()
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
max_amount = 0
quarter_ticks = []
for symbol in tickers:
amounts = (
df_contracts[df_contracts["Ticker"] == symbol].sort_values(
by=["Year", "Qtr"])["Amount"].values)
qtr = (df_contracts[df_contracts["Ticker"] == symbol].sort_values(
by=["Year", "Qtr"])["Qtr"].values)
year = (df_contracts[df_contracts["Ticker"] == symbol].sort_values(
by=["Year", "Qtr"])["Year"].values)
ax.plot(np.arange(0, len(amounts)),
amounts / 1_000_000,
"-*",
lw=2,
ms=15)
if len(amounts) > max_amount:
max_amount = len(amounts)
quarter_ticks = [
f"{quarter[0]} - Q{quarter[1]} "
for quarter in zip(year, qtr)
]
ax.set_xlim([-0.5, max_amount - 0.5])
ax.set_xticks(np.arange(0, max_amount))
ax.set_xticklabels(quarter_ticks)
ax.grid()
ax.legend(tickers)
titles = {
"upmom": "Highest increasing quarterly Government Contracts",
"downmom": "Highest decreasing quarterly Government Contracts",
}
ax.set_title(titles[analysis])
ax.set_xlabel("Date")
ax.set_ylabel("Amount ($1M)")
fig.tight_layout()
plt.savefig("gov_qtrcontracts.png")
imagefile = "gov_qtrcontracts.png"
imagefile = image_border(imagefile)
output = {
"title": "Stocks: [quiverquant.com] Government Contracts",
"imagefile": imagefile,
"description": description,
}
elif analysis == "total":
tickers.index = [ind + " " * (7 - len(ind)) for ind in tickers.index]
tickers[:] = [str(round(val[0] / 1e9, 2)) for val in tickers.values]
tickers.columns = ["Amount [M]"]
output = {
"title": "Stocks: [quiverquant.com] Government Contracts",
"description": tickers.to_string(),
}
return output
def vsurf_command(
ticker: str = "",
z: str = "IV",
):
"""Display vol surface
Parameters
----------
ticker: Stock Ticker
z : The variable for the Z axis
"""
# Debug
if cfg.DEBUG:
logger.debug("opt-oi %s %s", ticker, z)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
data = yfinance_model.get_iv_surface(ticker)
if data.empty:
raise Exception(f"No options data found for {ticker}.\n")
Y = data.dte
X = data.strike
if z == "IV":
Z = data.impliedVolatility
label = "Volatility"
elif z == "OI":
Z = data.openInterest
label = "Open Interest"
elif z == "LP":
Z = data.lastPrice
label = "Last Price"
points3D = np.vstack((X, Y, Z)).T
points2D = points3D[:, :2]
tri = Delaunay(points2D)
I, J, K = tri.simplices.T
lighting_effects = dict(ambient=0.5,
diffuse=0.5,
roughness=0.5,
specular=0.4,
fresnel=0.4)
fig = go.Figure(data=[
go.Mesh3d(
z=Z,
x=X,
y=Y,
i=I,
j=J,
k=K,
intensity=Z,
colorscale=cfg.PLT_3DMESH_COLORSCALE,
hovertemplate="<b>DTE</b>: %{y} <br><b>Strike</b>: %{x} <br><b>" +
z + "</b>: %{z}<extra></extra>",
showscale=False,
flatshading=True,
lighting=lighting_effects,
)
])
fig.update_layout(scene=dict(
xaxis=dict(
title="Strike",
tickfont=dict(size=11),
titlefont=dict(size=12),
),
yaxis=dict(title="DTE", ),
zaxis=dict(title=z, ),
), )
fig.update_layout(
margin=dict(l=0, r=0, t=40, b=20),
template=cfg.PLT_3DMESH_STYLE_TEMPLATE,
title=f"{label} Surface for {ticker.upper()}",
title_x=0.5,
hoverlabel=cfg.PLT_3DMESH_HOVERLABEL,
scene_camera=dict(
up=dict(x=0, y=0, z=2),
center=dict(x=0, y=0, z=-0.3),
eye=dict(x=1.25, y=1.25, z=0.69),
),
scene=cfg.PLT_3DMESH_SCENE,
)
config = dict({"scrollZoom": True})
imagefile = "opt-vsurf.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/vsurf_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/vsurf_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"{label} Surface for {ticker.upper()}",
"description": plt_link,
"imagefile": imagefile,
}
def cc_hist_command(ticker: str = None,
expiry: str = "",
strike: float = 10,
opt_type: str = ""):
"""Plot historical option prices
Parameters
----------
ticker: str
Stock ticker
expiry: str
expiration date
strike: float
Option strike price
put: bool
Calls for call
Puts for put
"""
# Debug
if cfg.DEBUG:
print(f"opt-hist {ticker} {strike} {opt_type} {expiry}")
# Check for argument
if ticker is None:
raise Exception("Stock ticker is required")
yf_ticker = yf.Ticker(ticker)
dates = list(yf_ticker.options)
if not dates:
raise Exception("Stock ticker is invalid")
options = yf.Ticker(ticker).option_chain(expiry)
if opt_type == "Calls":
options = options.calls
if opt_type == "Puts":
options = options.puts
chain_id = options.loc[options.strike == strike,
"contractSymbol"].values[0]
df_hist = yf.download(chain_id)
df_hist.index.name = "date"
plt_title = [
f"\n{ticker.upper()} {strike} {opt_type} expiring {expiry} Historical",
"Volume",
]
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.06,
subplot_titles=plt_title,
row_width=[0.2, 0.7],
)
fig.add_trace(
go.Candlestick(
x=df_hist.index,
open=df_hist.Open,
high=df_hist.High,
low=df_hist.Low,
close=df_hist.Close,
name="OHLC",
),
row=1,
col=1,
)
colors = [
"green" if row.Open < row["Close"] else "red"
for _, row in df_hist.iterrows()
] # pylint: disable=E1120
fig.add_trace(
go.Bar(
x=df_hist.index,
y=df_hist.Volume,
name="Volume",
marker_color=colors,
),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=0, t=25, b=5),
template=cfg.PLT_CANDLE_STYLE_TEMPLATE,
showlegend=False,
yaxis_title="Premium",
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
)
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "mon"]),
], )
config = dict({"scrollZoom": True})
rand = np.random.randint(70000)
imagefile = f"opt_hist{rand}.png"
fig.write_image(imagefile)
imagefile = image_border(imagefile)
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
fig.write_html(f"in/cc_hist_{rand}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/cc_hist_{rand}.html)"
return {
"title":
f"{ticker.upper()} {strike} {opt_type} expiring {expiry} Historical",
"description": plt_link,
"imagefile": imagefile,
}
def macd_command(ticker="",
fast="12",
slow="26",
signal="9",
start="",
end=""):
"""Displays chart with moving average convergence/divergence [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
# pylint: disable=logging-too-many-args
logger.debug(
"ta-macd %s %s %s %s %s %s",
ticker,
fast,
slow,
signal,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not fast.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
fast = float(fast)
if not slow.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
slow = float(slow)
if not signal.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
signal = float(signal)
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = momentum_model.macd(df_stock["Adj Close"], fast, slow, signal)
trace_name = df_ta.columns[0].replace("_", " ")
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.5, 0.6],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
)
fig.add_trace(
go.Bar(
name="MACD Histogram",
x=df_ta.index,
y=df_ta.iloc[:, 1].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
mode="lines",
name="MACD Line",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
mode="lines",
name="Signal Line",
x=df_ta.index,
y=df_ta.iloc[:, 2].values,
opacity=1,
),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=20, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} {trace_name}",
title_x=0.3,
yaxis_title="Stock Price ($)",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
)
config = dict({"scrollZoom": True})
imagefile = "ta_macd.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/macd_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/macd_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Moving-Average-Convergence-Divergence {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def rsi_command(ticker="",
length="14",
scalar="100",
drift="1",
start="",
end=""):
"""Displays chart with relative strength index [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
# pylint: disable=logging-too-many-args
logger.debug(
"ta-rsi %s %s %s %s %s %s",
ticker,
length,
scalar,
drift,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
if not scalar.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
scalar = float(scalar)
if not drift.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
drift = float(drift)
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = momentum_model.rsi(df_stock["Adj Close"], length, scalar, drift)
# Output Data
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.5, 0.6],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
)
for i in range(0, df_ta.shape[1]):
trace_name = df_ta.columns[i].replace("_", " ")
fig.add_trace(
go.Scatter(
name=trace_name,
x=df_ta.index,
y=df_ta.iloc[:, i],
opacity=1,
),
row=2,
col=1,
)
fig.add_hrect(
y0=70,
y1=100,
fillcolor="red",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hrect(
y0=0,
y1=30,
fillcolor="green",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hline(
y=70,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="red", dash="dash"),
row=2,
col=1,
)
fig.add_hline(
y=30,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="green", dash="dash"),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=20, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} {trace_name}",
title_x=0.5,
yaxis_title="Stock Price ($)",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_rsi.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/rsi_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/rsi_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Relative-Strength-Index {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def ftd_command(ticker: str = "", start="", end=""):
"""Fails-to-deliver data [SEC]"""
# Debug user input
if cfg.DEBUG:
logger.debug("dps-ftd %s %s %s", ticker, start, end)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
ticker = ticker.upper()
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
# Retrieve data
ftds_data = sec_model.get_fails_to_deliver(ticker, start, end, 0)
# Debug user output
if cfg.DEBUG:
logger.debug(ftds_data.to_string())
stock = helpers.load(ticker, start)
stock_ftd = stock[stock.index > start]
stock_ftd = stock_ftd[stock_ftd.index < end]
# Output data
fig = make_subplots(shared_xaxes=True, specs=[[{"secondary_y": True}]])
fig.add_trace(
go.Scatter(
name=ticker,
x=stock_ftd.index,
y=stock_ftd["Adj Close"],
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
secondary_y=False,
)
fig.add_trace(
go.Bar(
name="FTDs",
x=ftds_data["SETTLEMENT DATE"],
y=ftds_data["QUANTITY (FAILS)"] / 1000,
opacity=1,
),
secondary_y=True,
)
# Set y-axes titles
fig.update_yaxes(title_text="<b>Shares</b> [K]", secondary_y=True)
fig.update_layout(
margin=dict(l=0, r=20, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker}",
title_x=0.5,
yaxis_title="<b>Stock Price</b> ($)",
yaxis=dict(
side="right",
fixedrange=False,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
xaxis2=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
yaxis2=dict(
side="left",
position=0.15,
fixedrange=False,
),
hovermode="x unified",
)
config = dict({"scrollZoom": True})
imagefile = "dps_ftd.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/ftds_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/ftds_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: [SEC] Failure-to-deliver {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def cci_command(ticker="", length="14", scalar="0.015", start="", end=""):
"""Displays chart with commodity channel index [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-cci %s %s %s %s %s",
ticker,
length,
scalar,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
# pylint
try:
length = int(length)
except ValueError as e:
raise Exception("Length has to be an integer") from e
try:
scalar = float(scalar)
except ValueError as e:
raise Exception("Scalar has to be an integer") from e
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = momentum_model.cci(
df_stock["High"], df_stock["Low"], df_stock["Adj Close"], length, scalar
)
dmin = df_ta.values.min()
dmax = df_ta.values.max()
# Output Data
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.5, 0.6],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
)
fig.add_trace(
go.Scatter(
showlegend=False,
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_hrect(
y0=100,
y1=dmax,
fillcolor="red",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hrect(
y0=-100,
y1=dmin,
fillcolor="green",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hline(
y=-100,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="green", dash="dash"),
row=2,
col=1,
)
fig.add_hline(
y=100,
fillcolor="red",
opacity=1,
layer="below",
line_width=3,
line=dict(color="red", dash="dash"),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=20, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} CCI",
title_x=0.5,
yaxis_title="Stock Price ($)",
yaxis=dict(
fixedrange=False,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_cci.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/cci_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/cci_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Commodity-Channel-Index {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def topsells_command(
gov_type="",
past_transactions_months: int = 5,
num: int = 10,
raw: bool = False,
):
"""Displays most sold stocks by the congress/senate/house [quiverquant.com]"""
# Debug user input
if cfg.DEBUG:
logger.debug(
"gov-topsells %s %s %s %s",
gov_type,
past_transactions_months,
num,
raw,
)
possible_args = ["congress", "senate", "house"]
if gov_type == "":
gov_type = "congress"
elif gov_type not in possible_args:
raise Exception(
"Enter a valid government argument, options are: congress, senate and house"
)
# Retrieve Data
df_gov = quiverquant_model.get_government_trading(gov_type)
# Output Data
if df_gov.empty:
raise Exception(f"No {gov_type} trading data found\n")
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
start_date = datetime.now() - timedelta(days=past_transactions_months * 30)
df_gov["TransactionDate"] = pd.to_datetime(df_gov["TransactionDate"])
df_gov = df_gov[df_gov["TransactionDate"] > start_date].dropna()
df_gov["Range"] = df_gov["Range"].apply(lambda x: "$5,000,001-$5,000,001"
if x == ">$5,000,000" else x)
df_gov["min"] = df_gov["Range"].apply(lambda x: x.split("-")[0].strip(
"$").replace(",", "").strip().replace(">$", "").strip())
df_gov["max"] = df_gov["Range"].apply(
lambda x: x.split("-")[1].replace(",", "").strip().strip("$").replace(
">$", "").strip() if "-" in x else x.strip("$").replace(
",", "").replace(">$", "").strip())
df_gov["lower"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["min"])
if x["Transaction"] == "Purchase" else -float(x["max"]),
axis=1,
)
df_gov["upper"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["max"])
if x["Transaction"] == "Purchase" else -float(x["min"]),
axis=1,
)
description = None
df_gov = df_gov.sort_values("TransactionDate", ascending=True)
if raw:
df = pd.DataFrame(
df_gov.groupby("Ticker")["upper"].sum().div(1000).sort_values(
ascending=True).abs().head(n=num))
description = "```" + df.to_string() + "```"
fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
df_gov.groupby("Ticker")["upper"].sum().div(1000).sort_values().abs().head(
n=num).plot(kind="bar", rot=0, ax=ax)
ax.set_ylabel("Amount ($1k)")
ax.set_title(
f"{num} most sold stocks over last {past_transactions_months} months"
f" (upper bound) for {gov_type}")
plt.gcf().axes[0].yaxis.get_major_formatter().set_scientific(False)
fig.tight_layout()
plt.savefig("gov_topsells.png")
imagefile = "gov_topsells.png"
imagefile = image_border(imagefile)
return {
"title": f"Stocks: [quiverquant.com] Top sells for {gov_type.upper()}",
"imagefile": imagefile,
"description": description,
}
def aroon_command(ticker="", length="25", scalar="100", start="", end=""):
"""Displays chart with aroon indicator [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-aroon %s %s %s %s %s",
ticker,
length,
scalar,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = int(length)
if not scalar.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
scalar = float(scalar)
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = trend_indicators_model.aroon(
df_stock["High"], df_stock["Low"], length, scalar
)
# Output Data
aadown = df_ta.columns[0].replace("_", " ")
aaup = df_ta.columns[1].replace("_", " ")
aaosc = df_ta.columns[2].replace("_", " ")
fig = make_subplots(
rows=3,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.2, 0.2, 0.2],
)
fig.add_trace(
go.Scatter(
name=ticker,
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"Aroon DOWN ({aadown})",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"Aroon UP ({aaup})",
x=df_ta.index,
y=df_ta.iloc[:, 1].values,
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"Aroon OSC ({aaosc})",
x=df_ta.index,
y=df_ta.iloc[:, 2].values,
opacity=1,
),
row=3,
col=1,
)
fig.add_hline(
y=50,
fillcolor="grey",
opacity=1,
layer="below",
line_width=3,
line=dict(color="grey", dash="dash"),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=20, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"Aroon on {ticker}",
title_x=0.5,
yaxis_title="Stock Price ($)",
yaxis=dict(
fixedrange=False,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_aroon.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/aroon_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/aroon_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Aroon-Indicator {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def fib_command(ticker="", start="", end=""):
"""Displays chart with fibonacci retracement [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-fib %s %s %s",
ticker,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
f_start = None
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
f_start = start
if end == "":
end = datetime.now()
f_end = None
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
f_end = None
ticker = ticker.upper()
df_stock = bots.helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
start = start.strftime("%Y-%m-%d")
end = end.strftime("%Y-%m-%d")
(
df_fib,
min_date,
max_date,
min_pr,
max_pr,
) = custom_indicators_model.calculate_fib_levels(df_stock, 120, f_start, f_end)
levels = df_fib.Price
fig, ax = plt.subplots(figsize=(plot_autoscale()), dpi=cfp.PLOT_DPI)
ax.plot(df_stock["Adj Close"], "b")
ax.plot([min_date, max_date], [min_pr, max_pr], c="k")
for i in levels:
ax.axhline(y=i, c="g", alpha=0.5)
for i in range(5):
ax.fill_between(df_stock.index, levels[i], levels[i + 1], alpha=0.6)
ax.set_ylabel("Price")
ax.set_title(f"Fibonacci Support for {ticker.upper()}")
ax.set_xlim(df_stock.index[0], df_stock.index[-1])
ax1 = ax.twinx()
ax1.set_ylim(ax.get_ylim())
ax1.set_yticks(levels)
ax1.set_yticklabels([0, 0.235, 0.382, 0.5, 0.618, 1])
plt.gcf().autofmt_xdate()
fig.tight_layout(pad=1)
imagefile = "ta_fib.png"
plt.savefig(imagefile)
imagefile = image_border(imagefile)
return {
"title": f"Stocks: Fibonacci-Retracement-Levels {ticker}",
"imagefile": imagefile,
}
def bbands_command(ticker="",
length="5",
n_std="2",
mamode="sma",
start="",
end=""):
"""Displays chart with bollinger bands [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
# pylint: disable=logging-too-many-args
logger.debug(
"ta-bbands %s %s %s %s %s %s",
ticker,
length,
n_std,
mamode,
start,
end,
)
# Check for argument
possible_ma = [
"dema",
"ema",
"fwma",
"hma",
"linreg",
"midpoint",
"pwma",
"rma",
"sinwma",
"sma",
"swma",
"t3",
"tema",
"trima",
"vidya",
"wma",
"zlma",
]
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not length.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
length = float(length)
if not n_std.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
n_std = float(n_std)
if mamode not in possible_ma:
raise Exception("Invalid ma entered")
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = volatility_model.bbands(df_stock["Adj Close"], length, n_std,
mamode)
# Output Data
bbu = df_ta.columns[2].replace("_", " ")
bbm = df_ta.columns[1].replace("_", " ")
bbl = df_ta.columns[0].replace("_", " ")
fig = go.Figure()
fig.add_trace(
go.Scatter(
name=f"{bbu}",
x=df_ta.index,
y=df_ta.iloc[:, 2].values,
opacity=1,
mode="lines",
line_color="indigo",
), )
fig.add_trace(
go.Scatter(
name=f"{bbl}",
x=df_ta.index,
y=df_ta.iloc[:, 0].values,
opacity=1,
mode="lines",
line_color="indigo",
fill="tonexty",
fillcolor="rgba(74, 0, 128, 0.2)",
), )
fig.add_trace(
go.Scatter(
name=f"{bbm}",
x=df_ta.index,
y=df_ta.iloc[:, 1].values,
opacity=1,
line=dict(
width=1.5,
dash="dash",
),
), )
fig.add_trace(
go.Scatter(
name=f"{ticker}",
x=df_stock.index,
y=df_stock["Adj Close"],
line=dict(color="#fdc708", width=2),
opacity=1,
), )
fig.update_layout(
margin=dict(l=0, r=0, t=50, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} Bollinger Bands ({mamode.upper()})",
title_x=0.5,
yaxis_title="Stock Price ($)",
xaxis_title="Time",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_bbands.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/bbands_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/bbands_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Bollinger-Bands {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def sma_command(ticker="", window="", offset="", start="", end=""):
"""Displays chart with simple moving average [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-sma %s %s %s %s %s",
ticker,
window,
offset,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
l_legend = [ticker]
if window == "":
window = [20, 50]
else:
window_temp = list()
for wind in window.split(","):
try:
window_temp.append(float(wind))
except Exception as e:
raise Exception("Window needs to be a float") from e
window = window_temp
ticker = ticker.upper()
stock = helpers.load(ticker, start)
if stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
price_df = pd.DataFrame(stock["Adj Close"].values,
columns=["Price"],
index=stock.index)
i = 1
for win in window:
sma_data = overlap_model.sma(values=stock["Adj Close"],
length=win,
offset=offset)
price_df = price_df.join(sma_data)
l_legend.append(f"SMA {win}")
i += 1
# Output Data
start = start.strftime("%Y-%m-%d")
end = end.strftime("%Y-%m-%d")
price_df = price_df.loc[(price_df.index >= start) & (price_df.index < end)]
fig = go.Figure()
fig.add_trace(
go.Scatter(
name=f"{ticker}",
x=price_df.index,
y=price_df["Price"],
line=dict(color="#fdc708", width=2),
opacity=1,
), )
for i in range(1, price_df.shape[1]):
trace_name = price_df.columns[i].replace("_", " ")
fig.add_trace(
go.Scatter(
name=trace_name,
x=price_df.index,
y=price_df.iloc[:, i],
opacity=1,
), )
fig.update_layout(
margin=dict(l=0, r=0, t=50, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"{ticker} SMA",
title_x=0.5,
yaxis_title="Stock Price ($)",
xaxis_title="Time",
yaxis=dict(fixedrange=False, ),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_sma.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/sma_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/sma_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Simple-Moving-Average {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def stoch_command(ticker="", fast_k="14", slow_d="3", slow_k="3", start="", end=""):
"""Displays chart with stochastic relative strength average [Yahoo Finance]"""
# Debug
if cfg.DEBUG:
logger.debug(
"ta-stoch %s %s %s %s %s %s",
ticker,
fast_k,
slow_k,
slow_d,
start,
end,
)
# Check for argument
if ticker == "":
raise Exception("Stock ticker is required")
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
if not fast_k.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
fast_k = int(fast_k)
if not slow_k.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
slow_k = int(slow_k)
if not slow_d.lstrip("-").isnumeric():
raise Exception("Number has to be an integer")
slow_d = int(slow_d)
ticker = ticker.upper()
df_stock = helpers.load(ticker, start)
if df_stock.empty:
raise Exception("Stock ticker is invalid")
# Retrieve Data
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_ta = momentum_model.stoch(
df_stock["High"],
df_stock["Low"],
df_stock["Adj Close"],
fast_k,
slow_d,
slow_k,
)
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.07,
row_width=[0.5, 0.7],
)
fig.add_trace(
go.Scatter(
x=df_stock.index,
y=df_stock["Adj Close"].values,
line=dict(color="#fdc708", width=2),
opacity=1,
showlegend=False,
),
row=1,
col=1,
)
K = df_ta.columns[0].replace("_", " ")
D = df_ta.columns[1].replace("_", " ")
fig.add_trace(
go.Scatter(
name=f"%K {K}",
x=df_stock.index,
y=df_ta.iloc[:, 0].values,
line=dict(width=1.8),
opacity=1,
),
row=2,
col=1,
)
fig.add_trace(
go.Scatter(
name=f"%D {D}",
x=df_stock.index,
y=df_ta.iloc[:, 1].values,
line=dict(width=1.8, dash="dash"),
opacity=1,
),
row=2,
col=1,
)
fig.add_hrect(
y0=80,
y1=100,
fillcolor="red",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hrect(
y0=0,
y1=20,
fillcolor="green",
opacity=0.2,
layer="below",
line_width=0,
row=2,
col=1,
)
fig.add_hline(
y=80,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="red", dash="dash"),
row=2,
col=1,
)
fig.add_hline(
y=20,
fillcolor="green",
opacity=1,
layer="below",
line_width=3,
line=dict(color="green", dash="dash"),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=0, t=40, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=f"Stochastic Relative Strength Index (STOCH RSI) on {ticker}",
title_x=0.5,
yaxis_title="Stock Price ($)",
yaxis=dict(
fixedrange=False,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
),
dragmode="pan",
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
)
config = dict({"scrollZoom": True})
imagefile = "ta_stoch.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/stoch_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/stoch_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": f"Stocks: Stochastic-Relative-Strength-Index {ticker}",
"description": plt_link,
"imagefile": imagefile,
}
def hist_command(
ticker: str = None,
expiry: str = "",
strike: float = 10,
opt_type: str = "",
greek: str = "",
):
"""Plot historical option prices
Parameters
----------
ticker: str
Stock ticker
expiry: str
expiration date
strike: float
Option strike price
put: bool
Calls for call
Puts for put
"""
# Debug
if cfg.DEBUG:
print(f"opt-hist {ticker} {strike} {opt_type} {expiry} {greek}")
# Check for argument
if ticker is None:
raise Exception("Stock ticker is required")
if opt_type == "Puts":
put = bool(True)
if opt_type == "Calls":
put = bool(False)
chain_id = ""
df_hist = syncretism_model.get_historical_greeks(ticker, expiry, chain_id,
strike, put)
title = f"\n{ticker.upper()} {strike} {opt_type} expiring {expiry} Historical {greek.upper()}"
# Output data
fig = make_subplots(shared_xaxes=True, specs=[[{"secondary_y": True}]])
fig.add_trace(
go.Scatter(
name=ticker.upper(),
x=df_hist.index,
y=df_hist.price,
line=dict(color="#fdc708", width=2),
opacity=1,
), )
fig.add_trace(
go.Scatter(
name="Premium",
x=df_hist.index,
y=df_hist["premium"],
opacity=1,
yaxis="y2",
), )
if greek:
fig.add_trace(
go.Scatter(
name=f"{greek.upper()}",
x=df_hist.index,
y=df_hist[greek],
opacity=1,
yaxis="y3",
), )
fig.update_layout(
margin=dict(l=10, r=10, t=30, b=20),
template=cfg.PLT_TA_STYLE_TEMPLATE,
colorway=cfg.PLT_TA_COLORWAY,
title=title,
title_x=0.03,
yaxis_title="<b>Stock Price</b> ($)",
yaxis=dict(
side="right",
fixedrange=False,
titlefont=dict(color="#fdc708"),
tickfont=dict(color="#fdc708"),
position=0.02,
nticks=20,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
domain=[0.037, 1],
),
xaxis2=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
xaxis3=dict(
rangeslider=dict(visible=False),
type="date",
fixedrange=False,
),
dragmode="pan",
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
yaxis2=dict(
side="left",
fixedrange=False,
anchor="x",
overlaying="y",
titlefont=dict(color="#d81aea"),
tickfont=dict(color="#d81aea"),
nticks=20,
),
yaxis3=dict(
side="left",
position=0,
fixedrange=False,
overlaying="y",
titlefont=dict(color="#00e6c3"),
tickfont=dict(color="#00e6c3"),
nticks=20,
),
hovermode="x unified",
)
config = dict({"scrollZoom": True})
imagefile = "opt_hist.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/hist_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/hist_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title":
f"{ticker.upper()} {strike} {opt_type} expiring {expiry} Historical",
"description": plt_link,
"imagefile": imagefile,
}
def overview_command(
ticker: str = None,
expiry: str = None,
min_sp: float = None,
max_sp: float = None,
):
"""Options Overview"""
# Debug
if cfg.DEBUG:
logger.debug("opt-overview %s %s %s %s", ticker, expiry, min_sp, max_sp)
# Check for argument
if ticker is None:
raise Exception("Stock ticker is required")
# Get options info/dates, Look for logo_url
df = get_options_info(ticker) # Barchart Options IV Overview
dates = yfinance_model.option_expirations(ticker) # Expiration dates
tup = f"{ticker.upper()}"
url = yf.Ticker(tup).info["logo_url"]
url += "?raw=true" if url else ""
if not dates:
raise Exception("Stock ticker is invalid")
options = yfinance_model.get_option_chain(ticker, str(expiry))
calls = options.calls.fillna(0)
puts = options.puts.fillna(0)
current_price = yfinance_model.get_price(ticker)
min_strike2 = np.percentile(calls["strike"], 1)
max_strike2 = np.percentile(calls["strike"], 100)
min_strike = 0.75 * current_price
max_strike = 1.95 * current_price
if len(calls) > 40:
min_strike = 0.75 * current_price
max_strike = 1.25 * current_price
if min_sp:
min_strike = min_sp
min_strike2 = min_sp
if max_sp:
max_strike = max_sp
max_strike2 = max_sp
if min_sp > max_sp: # type: ignore
min_sp, max_sp = max_strike2, min_strike2
call_oi = calls.set_index("strike")["openInterest"] / 1000
put_oi = puts.set_index("strike")["openInterest"] / 1000
df_opt = pd.merge(call_oi, put_oi, left_index=True, right_index=True)
df_opt = df_opt.rename(
columns={"openInterest_x": "OI_call", "openInterest_y": "OI_put"}
)
max_pain = op_helpers.calculate_max_pain(df_opt)
fig = go.Figure()
dmax = df_opt[["OI_call", "OI_put"]].values.max()
dmin = df_opt[["OI_call", "OI_put"]].values.min()
fig.add_trace(
go.Scatter(
x=df_opt.index,
y=df_opt["OI_call"],
name="Calls",
mode="lines+markers",
line=dict(color="green", width=3),
)
)
fig.add_trace(
go.Scatter(
x=df_opt.index,
y=df_opt["OI_put"],
name="Puts",
mode="lines+markers",
line=dict(color="red", width=3),
)
)
fig.add_trace(
go.Scatter(
x=[current_price, current_price],
y=[dmin, dmax],
mode="lines",
line=dict(color="gold", width=2),
name="Current Price",
)
)
fig.add_trace(
go.Scatter(
x=[max_pain, max_pain],
y=[dmin, dmax],
mode="lines",
line=dict(color="grey", width=3, dash="dash"),
name=f"Max Pain: {max_pain}",
)
)
fig.update_xaxes(
range=[min_strike, max_strike],
constrain="domain",
)
fig.update_layout(
margin=dict(l=0, r=0, t=60, b=20),
template=cfg.PLT_SCAT_STYLE_TEMPLATE,
title=f"Open Interest for {ticker.upper()} expiring {expiry}",
title_x=0.5,
legend_title="",
xaxis_title="Strike",
yaxis_title="Open Interest (1k)",
xaxis=dict(
rangeslider=dict(visible=False),
),
legend=dict(yanchor="top", y=0.99, xanchor="left", x=0.01),
dragmode="pan",
)
config = dict({"scrollZoom": True})
imagefile = "opt_oi.png"
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/oi_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/oi_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
uploaded_image_oi = gst_imgur.upload_image(imagefile, title="something")
image_link_oi = uploaded_image_oi.link
os.remove(imagefile)
column_map = {"openInterest": "oi", "volume": "vol", "impliedVolatility": "iv"}
columns = [
"strike",
"bid",
"ask",
"volume",
"openInterest",
"impliedVolatility",
]
calls_df = calls[columns].rename(columns=column_map)
puts_df = puts[columns].rename(columns=column_map)
calls_df = calls_df[calls_df["strike"] >= min_strike2]
calls_df = calls_df[calls_df["strike"] <= max_strike2]
puts_df = puts_df[puts_df["strike"] >= min_strike2]
puts_df = puts_df[puts_df["strike"] <= max_strike2]
calls_df["iv"] = pd.to_numeric(calls_df["iv"].astype(float))
puts_df["iv"] = pd.to_numeric(puts_df["iv"].astype(float))
formats = {"iv": "{:.2f}"}
for col, f in formats.items():
calls_df[col] = calls_df[col].map(
lambda x: f.format(x) # pylint: disable=W0640
)
puts_df[col] = puts_df[col].map(lambda x: f.format(x)) # pylint: disable=W0640
calls_df.set_index("strike", inplace=True)
puts_df.set_index("strike", inplace=True)
if "-" in df.iloc[0, 1]:
iv = f"```diff\n- {df.iloc[0, 1]}\n```"
else:
iv = f"```yaml\n {df.iloc[0, 1]}\n```"
pfix, sfix = f"{ticker.upper()} ", f" expiring {expiry}"
if expiry == dates[0]:
pfix = f"{ticker.upper()} Weekly "
sfix = ""
titles = [f"{ticker.upper()} Overview", f"{pfix}Open Interest{sfix}"]
embeds = [
disnake.Embed(
title=f"{ticker.upper()} Overview",
color=cfg.COLOR,
),
disnake.Embed(
title=f"{pfix}Open Interest{sfix}",
description=plt_link,
colour=cfg.COLOR,
),
]
choices = [
disnake.SelectOption(label=f"{ticker.upper()} Overview", value="0", emoji="🟢"),
disnake.SelectOption(label=f"{pfix}Open Interest{sfix}", value="1", emoji="🟢"),
]
embeds_img = []
i, i2, end = 0, 0, 20
df_calls = []
dindex = len(calls_df.index)
while i <= dindex:
df_calls = calls_df.iloc[i:end]
df_calls.append(df_calls)
figc = df2img.plot_dataframe(
df_calls,
fig_size=(1000, (40 + (40 * 20))),
col_width=[3, 3, 3, 3],
tbl_cells=cfg.PLT_TBL_CELLS,
font=cfg.PLT_TBL_FONT,
template=cfg.PLT_TBL_STYLE_TEMPLATE,
paper_bgcolor="rgba(0, 0, 0, 0)",
)
imagefile = helpers.save_image("opt-calls.png", figc)
uploaded_image = gst_imgur.upload_image(imagefile, title="something")
image_link = uploaded_image.link
embeds_img.append(
f"{image_link}",
)
titles.append(f"{pfix}Calls{sfix}")
embeds.append(
disnake.Embed(
title=f"{pfix}Calls{sfix}",
colour=cfg.COLOR,
),
)
i2 += 1
i += 20
end += 20
os.remove(imagefile)
# Add Calls page field
i, page, puts_page = 2, 0, 3
i3 = i2 + 2
choices.append(
disnake.SelectOption(label="Calls Page 1", value="2", emoji="🟢"),
)
for i in range(2, i3):
page += 1
puts_page += 1
embeds[i].add_field(name=f"Calls Page {page}", value="_ _", inline=True)
# Puts Pages
i, end = 0, 20
df_puts = []
dindex = len(puts_df.index)
while i <= dindex:
df_puts = puts_df.iloc[i:end]
df_puts.append(df_puts)
figp = df2img.plot_dataframe(
df_puts,
fig_size=(1000, (40 + (40 * 20))),
col_width=[3, 3, 3, 3],
tbl_cells=cfg.PLT_TBL_CELLS,
font=cfg.PLT_TBL_FONT,
template=cfg.PLT_TBL_STYLE_TEMPLATE,
paper_bgcolor="rgba(0, 0, 0, 0)",
)
imagefile = helpers.save_image("opt-puts.png", figp)
uploaded_image = gst_imgur.upload_image(imagefile, title="something")
image_link = uploaded_image.link
embeds_img.append(
f"{image_link}",
)
titles.append(f"{pfix}Puts{sfix}")
embeds.append(
disnake.Embed(
title=f"{pfix}Puts{sfix}",
colour=cfg.COLOR,
),
)
i2 += 1
i += 20
end += 20
os.remove(imagefile)
# Add Puts page field
i, page = 0, 0
puts_page -= 1
i2 += 2
choices.append(
disnake.SelectOption(label="Puts Page 1", value=f"{puts_page}", emoji="🟢"),
)
for i in range(puts_page, i2):
page += 1
embeds[i].add_field(name=f"Puts Page {page}", value="_ _", inline=True)
# Author/Footer
for i in range(0, i2):
embeds[i].set_author(
name=cfg.AUTHOR_NAME,
url=cfg.AUTHOR_URL,
icon_url=cfg.AUTHOR_ICON_URL,
)
embeds[i].set_footer(
text=cfg.AUTHOR_NAME,
icon_url=cfg.AUTHOR_ICON_URL,
)
# Set images to Pages
i = 0
img_i = 0
embeds[1].set_image(url=image_link_oi)
for i in range(2, i2):
embeds[i].set_image(url=embeds_img[img_i])
img_i += 1
i += 1
if url:
embeds[0].set_thumbnail(url=f"{url}")
else:
embeds[0].set_thumbnail(url=cfg.AUTHOR_ICON_URL)
# Overview Section
embeds[0].add_field(name=f"{df.iloc[0, 0]}", value=iv, inline=False)
embeds[0].add_field(
name=f"•{df.iloc[1, 0]}", value=f"```css\n{df.iloc[1, 1]}\n```", inline=True
)
for N in range(2, 6):
embeds[0].add_field(
name=f"_ _ _ _ _ _ _ _ _ _ •{df.iloc[N, 0]}",
value=f"```css\n{df.iloc[N, 1]}\n```",
inline=True,
)
embeds[0].add_field(name="_ _", value="_ _", inline=False)
for N in range(6, 8):
embeds[0].add_field(
name=f"_ _ _ _ _ _ _ _ _ _ •{df.iloc[N, 0]}",
value=f"```css\n{df.iloc[N, 1]}\n```",
inline=True,
)
embeds[0].add_field(name="_ _", value="_ _", inline=False)
for N in range(8, 10):
embeds[0].add_field(
name=f"_ _ _ _ _ _ _ _ _ _ •{df.iloc[N, 0]}",
value=f"```css\n{df.iloc[N, 1]}\n```",
inline=True,
)
embeds[0].add_field(name="_ _", value="_ _", inline=False)
for N in range(10, 12):
embeds[0].add_field(
name=f"_ _ _ _ _ _ _ _ _ _ •{df.iloc[N, 0]}",
value=f"```css\n{df.iloc[N, 1]}\n```",
inline=True,
)
embeds[0].set_footer(text=f"Page 1 of {len(embeds)}")
os.remove(imagefile)
return {
"view": Menu,
"titles": titles,
"embed": embeds,
"choices": choices,
"embeds_img": embeds_img,
}
