Synced repo using 'sync_with_huggingface' Github Action

page/complete_backtest.py

@@ -61,13 +61,22 @@ def complete_backtest():
         st.success(f"Analysis finished in {round(time.time()-start, 2)} seconds")
 
     if "results" in st.session_state:
-        st.write("⬇️ Select a row in index column to get detailed information of the respective stock run.")
+        # st.write("⬇️ Select a row in index column to get detailed information of the respective stock run.")
+        st.markdown(f"""
+                    ### :orange[Nifty50 stocks backtest result by using {strategy}]
+                     ⬇️ Select a row in index column to get detailed information of the respective stock run.
+                    """)
         cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades', 'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]']
         df = st.dataframe(st.session_state.results, hide_index=True, column_order=cols, on_select="rerun", selection_mode="single-row")
         df.selection.rows = 1
         if df.selection.rows:
             row = df.selection.rows
+            ticker = st.session_state.results['stock'].values[row]
             plot = st.session_state.results['plot'].values[row]
+            color = "green" if st.session_state.results['Return [%]'].values[row][0] > 0 else "red"
+            st.markdown(f"""
+            ### :{color}[{ticker[0]} backtest plot] 📊
+            """)
             components.html(plot[0], height=1067)
 
 complete_backtest()

page/single_backtest.py

@@ -7,7 +7,7 @@ from bokeh.plotting import figure
 from streamlit.components import v1 as components
 
 from indicators import SMC
-from utils import fetch, smc_plot_backtest, smc_ema_plot_backtest, smc_structure_plot_backtest
+from utils import fetch, run_strategy
 
 def use_file_for_bokeh(chart: figure, chart_height=1067):
     # Function used to replace st.boken_chart, because streamlit doesn't support bokeh v3
@@ -73,6 +73,8 @@ def algorithmic_trading_dashboard():
             ema2 = st.number_input("Slow EMA Length", min_value=1, value=21)
         with c3:
             cross_close = st.checkbox("Close trade on EMA crossover", value=False)
+    else:
+        ema1, ema2, cross_close = None, None, None
 
     # Button to run the analysis
     if st.button("Run"):
@@ -95,18 +97,26 @@ def algorithmic_trading_dashboard():
             )
 
         # Generate backtest plot
-        if strategy == "Order Block":
-            backtest_plot = smc_plot_backtest(data, 'test.html', swing_hl)
-        elif strategy == "Order Block with EMA":
-            backtest_plot = smc_ema_plot_backtest(data, 'test.html', ema1, ema2, cross_close)
-        elif strategy == "Structure trading":
-            backtest_plot = smc_structure_plot_backtest(data, 'test.html', swing_hl)
+        # if strategy == "Order Block":
+        #     backtest_plot = smc_plot_backtest(data, 'test.html', swing_hl)
+        # elif strategy == "Order Block with EMA":
+        #     backtest_plot = smc_ema_plot_backtest(data, 'test.html', ema1, ema2, cross_close)
+        # elif strategy == "Structure trading":
+        #     backtest_plot = smc_structure_plot_backtest(data, 'test.html', swing_hl)
+
+        backtest_results = run_strategy(ticker, strategy, period, interval, swing_hl=swing_hl, ema1=ema1, ema2=ema2, cross_close=cross_close)
 
         # Display plots
         st.write("### Signal Plot")
         st.plotly_chart(signal_plot, width=1200)
 
-        st.write("### Backtesting Plot")
-        st.bokeh_chart(backtest_plot)
+        st.write('### Backtest Results')
+        cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades',
+                'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]']
+        st.dataframe(backtest_results, hide_index=True, column_order=cols)
+
+        st.write("### Backtest Plot")
+        plot = backtest_results['plot']
+        components.html(plot[0], height=1067)
 
 algorithmic_trading_dashboard()

utils.py

@@ -14,21 +14,6 @@ def fetch(symbol, period, interval):
     df.columns =df.columns.get_level_values(0)
     return df
 
-def smc_plot_backtest(data, filename, swing_hl, **kwargs):
-    bt = Backtest(data, SMC_test, **kwargs)
-    bt.run(swing_window=swing_hl)
-    return bt.plot(filename=filename, open_browser=False)
-
-def smc_ema_plot_backtest(data, filename, ema1, ema2, closecross, **kwargs):
-    bt = Backtest(data, SMC_ema, **kwargs)
-    bt.run(ema1=ema1, ema2=ema2, close_on_crossover=closecross)
-    return bt.plot(filename=filename, open_browser=False)
-
-def smc_structure_plot_backtest(data, filename, swing_hl, **kwargs):
-    bt = Backtest(data, SMCStructure, **kwargs)
-    bt.run(swing_window=swing_hl)
-    return bt.plot(filename=filename, open_browser=False)
-
 def smc_backtest(data, filename, swing_hl, **kwargs):
     bt = Backtest(data, SMC_test, **kwargs)
     results = bt.run(swing_window=swing_hl)
@@ -47,7 +32,7 @@ def smc_structure_backtest(data, filename, swing_hl, **kwargs):
     bt.plot(filename=filename, open_browser=False)
     return results
 
-def run_strategy(ticker_symbol, strategy, period, interval, kwargs):
+def run_strategy(ticker_symbol, strategy, period, interval, **kwargs):
     # Fetching ohlc of random ticker_symbol.
     retries = 3
     for i in range(retries):
@@ -87,8 +72,6 @@ def run_strategy(ticker_symbol, strategy, period, interval, kwargs):
     backtest_results['plot'] = plot
 
     # Reordering columns.
-    # cols = df.columns.tolist()
-    # cols = cols[-1:] + cols[:-1]
     cols = ['stock', 'Start', 'End', 'Return [%]', 'Equity Final [$]', 'Buy & Hold Return [%]', '# Trades',
             'Win Rate [%]', 'Best Trade [%]', 'Worst Trade [%]', 'Avg. Trade [%]', 'plot']
     backtest_results = backtest_results[cols]