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(feat) update directional trading

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This commit is contained in:
cardosofede
2024-07-23 15:01:40 +03:00
parent fb6e843f02
commit 86675d64d0
7 changed files with 58 additions and 46 deletions
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20
pages/config/bollinger_v1/app.py
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@@ -1,18 +1,16 @@
import streamlit as st
import pandas_ta as ta # noqa: F401
import streamlit as st
from plotly.subplots import make_subplots
from frontend.components.backtesting import backtesting_section
from frontend.components.config_loader import get_default_config_loader
from frontend.components.save_config import render_save_config
from frontend.pages.config.utils import get_candles
from frontend.st_utils import initialize_st_page, get_backend_api_client
from frontend.pages.config.bollinger_v1.user_inputs import user_inputs
from plotly.subplots import make_subplots
from frontend.pages.config.utils import get_candles
from frontend.st_utils import get_backend_api_client, initialize_st_page
from frontend.visualization import theme
from frontend.visualization.backtesting import create_backtesting_figure
from frontend.visualization.backtesting_metrics import render_backtesting_metrics, render_accuracy_metrics, \
render_close_types
from frontend.visualization.backtesting_metrics import render_accuracy_metrics, render_backtesting_metrics, render_close_types
from frontend.visualization.candles import get_candlestick_trace
from frontend.visualization.indicators import get_bbands_traces, get_volume_trace
from frontend.visualization.signals import get_bollinger_v1_signal_traces
@@ -22,7 +20,6 @@ from frontend.visualization.utils import add_traces_to_fig
initialize_st_page(title="Bollinger V1", icon="📈", initial_sidebar_state="expanded")
backend_api_client = get_backend_api_client()
st.text("This tool will let you create a config for Bollinger V1 and visualize the strategy.")
get_default_config_loader("bollinger_v1")
@@ -32,7 +29,8 @@ st.session_state["default_config"].update(inputs)
st.write("### Visualizing Bollinger Bands and Trading Signals")
days_to_visualize = st.number_input("Days to Visualize", min_value=1, max_value=365, value=7)
# Load candle data
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"], interval=inputs["interval"], days=days_to_visualize)
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"],
interval=inputs["interval"], days=days_to_visualize)
# Create a subplot with 2 rows
fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
@@ -41,7 +39,9 @@ fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
add_traces_to_fig(fig, [get_candlestick_trace(candles)], row=1, col=1)
add_traces_to_fig(fig, get_bbands_traces(candles, inputs["bb_length"], inputs["bb_std"]), row=1, col=1)
add_traces_to_fig(fig, get_bollinger_v1_signal_traces(candles, inputs["bb_length"], inputs["bb_std"], inputs["bb_long_threshold"], inputs["bb_short_threshold"]), row=1, col=1)
add_traces_to_fig(fig, get_bollinger_v1_signal_traces(candles, inputs["bb_length"], inputs["bb_std"],
inputs["bb_long_threshold"], inputs["bb_short_threshold"]), row=1,
col=1)
add_traces_to_fig(fig, [get_volume_trace(candles)], row=2, col=1)
fig.update_layout(**theme.get_default_layout())

4
pages/config/bollinger_v1/user_inputs.py
View File

@@ -1,4 +1,5 @@
import streamlit as st
from frontend.components.directional_trading_general_inputs import get_directional_trading_general_inputs
from frontend.components.risk_management import get_risk_management_inputs
@@ -9,7 +10,8 @@ def user_inputs():
bb_std = default_config.get("bb_std", 2.0)
bb_long_threshold = default_config.get("bb_long_threshold", 0.0)
bb_short_threshold = default_config.get("bb_short_threshold", 1.0)
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode, candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode, \
candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
sl, tp, time_limit, ts_ap, ts_delta, take_profit_order_type = get_risk_management_inputs()
with st.expander("Bollinger Bands Configuration", expanded=True):
c1, c2, c3, c4 = st.columns(4)

40
pages/config/kalman_filter_v1/app.py
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@@ -1,13 +1,14 @@
import streamlit as st
import pandas as pd
import plotly.graph_objects as go
import streamlit as st
import yaml
from hummingbot.connector.connector_base import OrderType
from plotly.subplots import make_subplots
from pykalman import KalmanFilter
from CONFIG import BACKEND_API_HOST, BACKEND_API_PORT
from backend.services.backend_api_client import BackendAPIClient
from frontend.st_utils import initialize_st_page, get_backend_api_client
from CONFIG import BACKEND_API_HOST, BACKEND_API_PORT
from frontend.st_utils import get_backend_api_client, initialize_st_page
# Initialize the Streamlit page
initialize_st_page(title="Kalman Filter V1", icon="📈", initial_sidebar_state="expanded")
@@ -18,6 +19,7 @@ def get_candles(connector_name="binance", trading_pair="BTC-USDT", interval="1m"
backend_client = BackendAPIClient(BACKEND_API_HOST, BACKEND_API_PORT)
return backend_client.get_real_time_candles(connector_name, trading_pair, interval, max_records)
@st.cache_data
def add_indicators(df, observation_covariance=1, transition_covariance=0.01, initial_state_covariance=0.001):
# Add Bollinger Bands
@@ -61,7 +63,6 @@ with c3:
with c4:
max_records = st.number_input("Max Records", min_value=100, max_value=10000, value=1000)
st.write("## Positions Configuration")
c1, c2, c3, c4 = st.columns(4)
with c1:
@@ -87,28 +88,25 @@ with c1:
with c2:
transition_covariance = st.number_input("Transition Covariance", value=0.001, step=0.0001, format="%.4f")
# Load candle data
candle_data = get_candles(connector_name=candles_connector, trading_pair=candles_trading_pair, interval=interval, max_records=max_records)
candle_data = get_candles(connector_name=candles_connector, trading_pair=candles_trading_pair, interval=interval,
max_records=max_records)
df = pd.DataFrame(candle_data)
df.index = pd.to_datetime(df['timestamp'], unit='s')
candles_processed = add_indicators(df, observation_covariance, transition_covariance)
# Prepare data for signals
signals = candles_processed[candles_processed['signal'] != 0]
buy_signals = signals[signals['signal'] == 1]
sell_signals = signals[signals['signal'] == -1]
from plotly.subplots import make_subplots
# Define your color palette
tech_colors = {
'upper_band': '#4682B4', # Steel Blue for the Upper Bollinger Band
'upper_band': '#4682B4', # Steel Blue for the Upper Bollinger Band
'middle_band': '#FFD700', # Gold for the Middle Bollinger Band
'lower_band': '#32CD32', # Green for the Lower Bollinger Band
'buy_signal': '#1E90FF', # Dodger Blue for Buy Signals
'lower_band': '#32CD32', # Green for the Lower Bollinger Band
'buy_signal': '#1E90FF', # Dodger Blue for Buy Signals
'sell_signal': '#FF0000', # Red for Sell Signals
}
@@ -127,9 +125,15 @@ fig.add_trace(go.Candlestick(x=candles_processed.index,
row=1, col=1)
# Bollinger Bands
fig.add_trace(go.Scatter(x=candles_processed.index, y=candles_processed['kf_upper'], line=dict(color=tech_colors['upper_band']), name='Upper Band'), row=1, col=1)
fig.add_trace(go.Scatter(x=candles_processed.index, y=candles_processed['kf'], line=dict(color=tech_colors['middle_band']), name='Middle Band'), row=1, col=1)
fig.add_trace(go.Scatter(x=candles_processed.index, y=candles_processed['kf_lower'], line=dict(color=tech_colors['lower_band']), name='Lower Band'), row=1, col=1)
fig.add_trace(
go.Scatter(x=candles_processed.index, y=candles_processed['kf_upper'], line=dict(color=tech_colors['upper_band']),
name='Upper Band'), row=1, col=1)
fig.add_trace(
go.Scatter(x=candles_processed.index, y=candles_processed['kf'], line=dict(color=tech_colors['middle_band']),
name='Middle Band'), row=1, col=1)
fig.add_trace(
go.Scatter(x=candles_processed.index, y=candles_processed['kf_lower'], line=dict(color=tech_colors['lower_band']),
name='Lower Band'), row=1, col=1)
# Signals plot
fig.add_trace(go.Scatter(x=buy_signals.index, y=buy_signals['close'], mode='markers',
@@ -140,7 +144,8 @@ fig.add_trace(go.Scatter(x=sell_signals.index, y=sell_signals['close'], mode='ma
name='Sell Signal'), row=1, col=1)
fig.add_trace(go.Scatter(x=signals.index, y=signals['signal'], mode='markers',
marker=dict(color=signals['signal'].map({1: tech_colors['buy_signal'], -1: tech_colors['sell_signal']}), size=10),
marker=dict(color=signals['signal'].map(
{1: tech_colors['buy_signal'], -1: tech_colors['sell_signal']}), size=10),
showlegend=False), row=2, col=1)
# Update layout
@@ -218,8 +223,7 @@ with c3:
)
upload_config_to_backend = st.button("Upload Config to BackendAPI")
if upload_config_to_backend:
backend_api_client = get_backend_api_client()
backend_api_client.add_controller_config(config)
st.success("Config uploaded successfully!")
st.success("Config uploaded successfully!")

19
pages/config/macd_bb_v1/app.py
View File

@@ -6,11 +6,10 @@ from frontend.components.config_loader import get_default_config_loader
from frontend.components.save_config import render_save_config
from frontend.pages.config.macd_bb_v1.user_inputs import user_inputs
from frontend.pages.config.utils import get_candles
from frontend.st_utils import initialize_st_page, get_backend_api_client
from frontend.st_utils import get_backend_api_client, initialize_st_page
from frontend.visualization import theme
from frontend.visualization.backtesting import create_backtesting_figure
from frontend.visualization.backtesting_metrics import render_backtesting_metrics, render_accuracy_metrics, \
render_close_types
from frontend.visualization.backtesting_metrics import render_accuracy_metrics, render_backtesting_metrics, render_close_types
from frontend.visualization.candles import get_candlestick_trace
from frontend.visualization.indicators import get_bbands_traces, get_macd_traces
from frontend.visualization.signals import get_macdbb_v1_signal_traces
@@ -25,11 +24,11 @@ get_default_config_loader("macd_bb_v1")
inputs = user_inputs()
st.session_state["default_config"].update(inputs)
st.write("### Visualizing MACD Bollinger Trading Signals")
days_to_visualize = st.number_input("Days to Visualize", min_value=1, max_value=365, value=7)
# Load candle data
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"], interval=inputs["interval"], days=days_to_visualize)
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"],
interval=inputs["interval"], days=days_to_visualize)
# Create a subplot with 2 rows
fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
@@ -38,9 +37,12 @@ fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
add_traces_to_fig(fig, [get_candlestick_trace(candles)], row=1, col=1)
add_traces_to_fig(fig, get_bbands_traces(candles, inputs["bb_length"], inputs["bb_std"]), row=1, col=1)
add_traces_to_fig(fig, get_macdbb_v1_signal_traces(df=candles, bb_length=inputs["bb_length"], bb_std=inputs["bb_std"],
bb_long_threshold=inputs["bb_long_threshold"], bb_short_threshold=inputs["bb_short_threshold"],
macd_fast=inputs["macd_fast"], macd_slow=inputs["macd_slow"], macd_signal=inputs["macd_signal"]), row=1, col=1)
add_traces_to_fig(fig, get_macd_traces(df=candles, macd_fast=inputs["macd_fast"], macd_slow=inputs["macd_slow"], macd_signal=inputs["macd_signal"]), row=2, col=1)
bb_long_threshold=inputs["bb_long_threshold"],
bb_short_threshold=inputs["bb_short_threshold"],
macd_fast=inputs["macd_fast"], macd_slow=inputs["macd_slow"],
macd_signal=inputs["macd_signal"]), row=1, col=1)
add_traces_to_fig(fig, get_macd_traces(df=candles, macd_fast=inputs["macd_fast"], macd_slow=inputs["macd_slow"],
macd_signal=inputs["macd_signal"]), row=2, col=1)
fig.update_layout(**theme.get_default_layout())
# Use Streamlit's functionality to display the plot
@@ -61,4 +63,3 @@ if bt_results:
render_close_types(bt_results["results"])
st.write("---")
render_save_config(st.session_state["default_config"]["id"], st.session_state["default_config"])

4
pages/config/macd_bb_v1/user_inputs.py
View File

@@ -1,4 +1,5 @@
import streamlit as st
from frontend.components.directional_trading_general_inputs import get_directional_trading_general_inputs
from frontend.components.risk_management import get_risk_management_inputs
@@ -12,7 +13,8 @@ def user_inputs():
macd_fast = default_config.get("macd_fast", 21)
macd_slow = default_config.get("macd_slow", 42)
macd_signal = default_config.get("macd_signal", 9)
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode, candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode,\
candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
sl, tp, time_limit, ts_ap, ts_delta, take_profit_order_type = get_risk_management_inputs()
with st.expander("MACD Bollinger Configuration", expanded=True):
c1, c2, c3, c4, c5, c6, c7 = st.columns(7)

13
pages/config/supertrend_v1/app.py
View File

@@ -6,13 +6,12 @@ from frontend.components.config_loader import get_default_config_loader
from frontend.components.save_config import render_save_config
from frontend.pages.config.supertrend_v1.user_inputs import user_inputs
from frontend.pages.config.utils import get_candles
from frontend.st_utils import initialize_st_page, get_backend_api_client
from frontend.st_utils import get_backend_api_client, initialize_st_page
from frontend.visualization import theme
from frontend.visualization.backtesting import create_backtesting_figure
from frontend.visualization.backtesting_metrics import render_backtesting_metrics, render_accuracy_metrics, \
render_close_types
from frontend.visualization.backtesting_metrics import render_accuracy_metrics, render_backtesting_metrics, render_close_types
from frontend.visualization.candles import get_candlestick_trace
from frontend.visualization.indicators import get_volume_trace, get_supertrend_traces
from frontend.visualization.indicators import get_supertrend_traces, get_volume_trace
from frontend.visualization.signals import get_supertrend_v1_signal_traces
from frontend.visualization.utils import add_traces_to_fig
@@ -28,7 +27,8 @@ st.session_state["default_config"].update(inputs)
st.write("### Visualizing Supertrend Trading Signals")
days_to_visualize = st.number_input("Days to Visualize", min_value=1, max_value=365, value=7)
# Load candle data
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"], interval=inputs["interval"], days=days_to_visualize)
candles = get_candles(connector_name=inputs["candles_connector"], trading_pair=inputs["candles_trading_pair"],
interval=inputs["interval"], days=days_to_visualize)
# Create a subplot with 2 rows
fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
@@ -36,7 +36,8 @@ fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
row_heights=[0.8, 0.2])
add_traces_to_fig(fig, [get_candlestick_trace(candles)], row=1, col=1)
add_traces_to_fig(fig, get_supertrend_traces(candles, inputs["length"], inputs["multiplier"]), row=1, col=1)
add_traces_to_fig(fig, get_supertrend_v1_signal_traces(candles, inputs["length"], inputs["multiplier"], inputs["percentage_threshold"]), row=1, col=1)
add_traces_to_fig(fig, get_supertrend_v1_signal_traces(candles, inputs["length"], inputs["multiplier"],
inputs["percentage_threshold"]), row=1, col=1)
add_traces_to_fig(fig, [get_volume_trace(candles)], row=2, col=1)
layout_settings = theme.get_default_layout()

4
pages/config/supertrend_v1/user_inputs.py
View File

@@ -1,4 +1,5 @@
import streamlit as st
from frontend.components.directional_trading_general_inputs import get_directional_trading_general_inputs
from frontend.components.risk_management import get_risk_management_inputs
@@ -8,7 +9,8 @@ def user_inputs():
length = default_config.get("length", 20)
multiplier = default_config.get("multiplier", 3.0)
percentage_threshold = default_config.get("percentage_threshold", 0.5)
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode, candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
connector_name, trading_pair, leverage, total_amount_quote, max_executors_per_side, cooldown_time, position_mode, \
candles_connector_name, candles_trading_pair, interval = get_directional_trading_general_inputs()
sl, tp, time_limit, ts_ap, ts_delta, take_profit_order_type = get_risk_management_inputs()
with st.expander("SuperTrend Configuration", expanded=True):