Update app.py

app.py

@@ -180,17 +180,28 @@ def irr_sql(cols: List[str]) -> str:
     t_expr += " ELSE NULL END"
     y_expr = "(Interest_rate/100.0)" if has_ir else "0.0"
     return f"""
+    WITH irr_calcs AS (
+        SELECT
+            bucket,
+            Portfolio_value AS pv,
+            -- Modified Duration = Macaulay Duration / (1 + yield)
+            -- We approximate Macaulay Duration with time-to-maturity in years (t_expr)
+            ({t_expr}) / (1 + {y_expr}) AS mod_dur
+        FROM {VIEW_FQN}
+    )
     SELECT
-      bucket,
-      SUM(Portfolio_value) / 1000000.0 AS "Portfolio Value (LKR Mn)"
-    FROM {VIEW_FQN}
-    GROUP BY bucket
+        bucket,
+        SUM(pv) / 1000000.0 AS "Portfolio Value (LKR Mn)",
+        -- BPV (DV01) = SUM(Portfolio Value * Modified Duration * 0.0001)
+        SUM(pv * mod_dur * 0.0001) AS "BPV (DV01)"
+    FROM irr_calcs
+    GROUP BY bucket;
     """
 
 # =========================
 # Dashboard callback
 # =========================
-def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.DataFrame, str, pd.DataFrame]:
+def run_dashboard(scenario: str) -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.DataFrame, str, pd.DataFrame]:
     """
     Returns:
       status, as_of, a1_text, a2_text, a3_text, figure, ladder_df, irr_df,
@@ -199,6 +210,26 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
     try:
         conn = connect_md()
 
+        # --- Scenario Application ---
+        # Create a temporary view with scenario adjustments.
+        # Subsequent queries will use this stressed view.
+        stressed_view_fqn = f"{VIEW_FQN}_stressed"
+        runoff_factor = 1.0
+        rate_shock_bps = 0.0
+
+        if scenario == "Liquidity Stress: High Deposit Runoff":
+            runoff_factor = 0.8 # 20% runoff
+        elif scenario == "IRR Stress: Rate Shock (+200bps)":
+            rate_shock_bps = 200.0
+
+        scenario_sql = f"""
+        CREATE OR REPLACE TEMP VIEW {stressed_view_fqn} AS
+        SELECT *,
+            CASE WHEN lower(product) IN ('savings', 'fd', 'td', 'term_deposit') THEN Portfolio_value * {runoff_factor} ELSE Portfolio_value END AS stressed_pv
+        FROM {VIEW_FQN};
+        """
+        conn.execute(scenario_sql)
+
         # 1) Discover columns & build view
         cols = discover_columns(conn, TABLE_FQN)
         ensure_view(conn, cols)
@@ -211,20 +242,35 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
                 as_of = str(tmp["d"].iloc[0])[:10]
 
         # 3) KPIs
-        kpi = conn.execute(KPI_SQL).fetchdf()
+        # Modify queries to use the stressed view and value column
+        kpi_sql_stressed = KPI_SQL.replace(f"FROM {VIEW_FQN}", f"FROM {stressed_view_fqn}").replace("Portfolio_value", "stressed_pv")
+        kpi = conn.execute(kpi_sql_stressed).fetchdf()
         assets_t1 = safe_num(kpi["assets_t1"].iloc[0]) if not kpi.empty else 0.0
         sof_t1    = safe_num(kpi["sof_t1"].iloc[0]) if not kpi.empty else 0.0
         net_gap   = safe_num(kpi["net_gap_t1"].iloc[0]) if not kpi.empty else 0.0
 
         # 4) Ladder, IRR, and Gap Drivers
-        ladder = conn.execute(LADDER_SQL).fetchdf()
-        irr    = conn.execute(irr_sql(cols)).fetchdf()
-        drivers = conn.execute(GAP_DRIVERS_SQL).fetchdf()
+        ladder_sql_stressed = LADDER_SQL.replace(f"FROM {VIEW_FQN}", f"FROM {stressed_view_fqn}").replace("Portfolio_value", "stressed_pv")
+        drivers_sql_stressed = GAP_DRIVERS_SQL.replace(f"FROM {VIEW_FQN}", f"FROM {stressed_view_fqn}").replace("Portfolio_value", "stressed_pv")
+        irr_sql_stressed = irr_sql(cols).replace(f"FROM {VIEW_FQN}", f"FROM {stressed_view_fqn}").replace("Portfolio_value", "stressed_pv")
+
+        ladder = conn.execute(ladder_sql_stressed).fetchdf()
+        irr    = conn.execute(irr_sql_stressed).fetchdf()
+        drivers = conn.execute(drivers_sql_stressed).fetchdf()
 
+        # Create display copies of dataframes and format them for the UI
+        ladder_display = ladder.copy()
         if "Amount (LKR Mn)" in ladder.columns:
-            ladder["Amount (LKR Mn)"] = ladder["Amount (LKR Mn)"].map('{:,.2f}'.format)
-        if "Portfolio Value (LKR Mn)" in irr.columns:
-            irr["Portfolio Value (LKR Mn)"] = irr["Portfolio Value (LKR Mn)"].map('{:,.2f}'.format)
+            ladder_display["Amount (LKR Mn)"] = ladder_display["Amount (LKR Mn)"].map('{:,.2f}'.format)
+        else:
+            ladder_display = pd.DataFrame()
+
+        # Format IRR table
+        irr_display = irr.copy()
+        if not irr_display.empty:
+            irr_display["Portfolio Value (LKR Mn)"] = irr_display["Portfolio Value (LKR Mn)"].map('{:,.2f}'.format)
+            irr_display["BPV (DV01)"] = irr_display["BPV (DV01)"].map('{:,.2f}'.format)
+
         if "Amount (LKR Mn)" in drivers.columns:
             drivers_display = drivers.copy()
             drivers_display["Amount (LKR Mn)"] = drivers_display["Amount (LKR Mn)"].map('{:,.2f}'.format)
@@ -264,6 +310,14 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
         # Note: The data source does not contain features for seasonal analysis (e.g., day_of_week, is_month_end).
         explain_text += "*   **Seasonal Pattern:** Analysis not possible without relevant time-series features in the source data."
 
+        # Add scenario explanation for IRR stress
+        if scenario == "IRR Stress: Rate Shock (+200bps)" and not irr.empty:
+            net_bpv = irr["BPV (DV01)"].sum()
+            eve_impact = net_bpv * rate_shock_bps
+            eve_impact_mn = eve_impact / 1_000_000
+            explain_text += f"\n\n### IRR Stress Scenario Impact\n*   A **+{rate_shock_bps:.0f} bps** rate shock is projected to change the portfolio's Economic Value by **LKR {eve_impact_mn:,.2f} Mn**."
+
+
         status = f"✅ OK (as of {pd.Timestamp.now().strftime('%Y-%m-%d %H:%M:%S')})"
         return (
             status,
@@ -272,8 +326,8 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
             a2_text,
             a3_text,
             fig,
-            ladder,
-            irr,
+            ladder_display,
+            irr_display,
             explain_text,
             drivers_display,
         )
@@ -305,6 +359,18 @@ with gr.Blocks(title=APP_TITLE) as demo:
 
     with gr.Row():
         refresh_btn = gr.Button("🔄 Refresh", variant="primary")
+        theme_btn = gr.Button("🌗 Toggle Theme")
+        theme_btn.click(
+            None,
+            None,
+            _js="() => { document.querySelector('html').classList.toggle('dark'); }"
+        )
+
+    scenario_dd = gr.Dropdown(
+        label="Select Stress Scenario",
+        choices=["Baseline", "Liquidity Stress: High Deposit Runoff", "IRR Stress: Rate Shock (+200bps)"],
+        value="Baseline"
+    )
 
     with gr.Row():
         as_of = gr.Textbox(label="As of date", interactive=False)
@@ -317,7 +383,10 @@ with gr.Blocks(title=APP_TITLE) as demo:
         with gr.Column(scale=2):
             chart = gr.Plot(label="Maturity Ladder")
             ladder_df = gr.Dataframe(label="Ladder Detail")
-            irr_df = gr.Dataframe(label="Interest-Rate Risk (approx)")
+            irr_df = gr.Dataframe(
+                label="Interest-Rate Risk (BPV/DV01)",
+                headers=["Bucket", "Portfolio Value (LKR Mn)", "BPV (DV01)"]
+            )
         with gr.Column(scale=1):
             explain_text = gr.Markdown("Analysis of the T+1 gap will appear here...")
             drivers_df = gr.Dataframe(
@@ -327,6 +396,7 @@ with gr.Blocks(title=APP_TITLE) as demo:
 
     refresh_btn.click(
         fn=run_dashboard,
+        inputs=[scenario_dd],
         outputs=[status, as_of, a1, a2, a3, chart, ladder_df, irr_df, explain_text, drivers_df],
     )