{ "dashboard_title": "Paper Trading PnL", "description": "Paper trading performance tracking with PnL curves, position snapshots, order history, and trade detail drill-down.", "slug": "paper-trading-pnl", "position_json": { "HEADER_ID": {"id": "HEADER_ID", "type": "HEADER", "meta": {"text": "Paper Trading PnL"}}, "ROW-1": { "type": "ROW", "children": ["CHART-total-net-pnl-kpi", "CHART-win-rate-kpi", "CHART-total-orders-kpi", "CHART-active-positions-kpi"] }, "ROW-2": { "type": "ROW", "children": ["CHART-cumulative-pnl-timeseries", "CHART-daily-pnl-bar"] }, "ROW-3": { "type": "ROW", "children": ["CHART-pnl-by-symbol", "CHART-order-status-pie"] }, "ROW-4": { "type": "ROW", "children": ["CHART-positions-table"] }, "ROW-5": { "type": "ROW", "children": ["CHART-scorecard-table"] }, "ROW-6": { "type": "ROW", "children": ["CHART-recent-orders-table"] } }, "metadata": { "refresh_frequency": 300, "default_filters": "{}", "color_scheme": "supersetColors" }, "charts": [ { "slice_name": "Total Net PnL", "viz_type": "big_number_total", "description": "Cumulative net PnL across all paper trading activity", "datasource_type": "trino", "query": "SELECT ROUND(SUM(net_pnl), 2) AS total_net_pnl FROM lakehouse.stonks.pnl_daily WHERE execution_mode = 'paper'" }, { "slice_name": "Win Rate", "viz_type": "big_number_total", "description": "Fraction of trading days with positive net PnL", "datasource_type": "trino", "query": "SELECT ROUND(CAST(COUNT(CASE WHEN net_pnl > 0 THEN 1 END) AS DOUBLE) / NULLIF(COUNT(*), 0), 4) AS win_rate FROM lakehouse.stonks.pnl_daily WHERE execution_mode = 'paper'" }, { "slice_name": "Total Orders", "viz_type": "big_number_total", "description": "Total paper trade orders submitted", "datasource_type": "trino", "query": "SELECT COUNT(DISTINCT order_id) AS total_orders FROM lakehouse.stonks.trade_orders WHERE execution_mode = 'paper'" }, { "slice_name": "Active Positions", "viz_type": "big_number_total", "description": "Number of symbols with open positions as of the latest snapshot", "datasource_type": "trino", "query": "SELECT COUNT(DISTINCT ticker) AS active_positions FROM lakehouse.stonks.positions_daily WHERE execution_mode = 'paper' AND quantity <> 0 AND dt = (SELECT MAX(dt) FROM lakehouse.stonks.positions_daily WHERE execution_mode = 'paper')" }, { "slice_name": "Cumulative PnL Over Time", "viz_type": "echarts_timeseries_line", "description": "Running cumulative net PnL across all paper trades", "datasource_type": "trino", "query": "SELECT dt AS bucket, SUM(net_pnl) AS daily_net_pnl, SUM(SUM(net_pnl)) OVER (ORDER BY dt) AS cumulative_pnl FROM lakehouse.stonks.pnl_daily WHERE execution_mode = 'paper' GROUP BY dt ORDER BY dt" }, { "slice_name": "Daily PnL", "viz_type": "echarts_timeseries_bar", "description": "Daily net PnL for paper trading, colored by positive/negative", "datasource_type": "trino", "query": "SELECT dt AS bucket, ROUND(SUM(net_pnl), 2) AS daily_pnl, ROUND(SUM(realized_pnl), 2) AS realized, ROUND(SUM(unrealized_pnl), 2) AS unrealized FROM lakehouse.stonks.pnl_daily WHERE execution_mode = 'paper' GROUP BY dt ORDER BY dt", "params": { "x_axis": "bucket", "metrics": ["daily_pnl"] } }, { "slice_name": "PnL by Symbol", "viz_type": "echarts_timeseries_bar", "description": "Total net PnL per symbol for paper trading", "datasource_type": "trino", "query": "SELECT ticker, ROUND(SUM(net_pnl), 2) AS total_pnl, ROUND(SUM(realized_pnl), 2) AS realized_pnl, ROUND(SUM(fees), 2) AS total_fees FROM lakehouse.stonks.pnl_daily WHERE execution_mode = 'paper' GROUP BY ticker ORDER BY total_pnl DESC", "params": { "x_axis": "ticker", "metrics": ["total_pnl"] } }, { "slice_name": "Order Status Distribution", "viz_type": "pie", "description": "Breakdown of paper trade order statuses", "datasource_type": "trino", "query": "SELECT status, COUNT(*) AS count FROM lakehouse.stonks.trade_orders WHERE execution_mode = 'paper' GROUP BY status ORDER BY count DESC" }, { "slice_name": "Current Positions", "viz_type": "table", "description": "Latest position snapshot for all paper trading symbols", "datasource_type": "trino", "query": "SELECT p.ticker, p.quantity, ROUND(p.avg_entry_price, 2) AS avg_entry, ROUND(p.close_price, 2) AS close_price, ROUND(p.market_value, 2) AS market_value, ROUND(p.unrealized_pnl, 2) AS unrealized_pnl, p.snapshot_at FROM lakehouse.stonks.positions_daily p WHERE p.execution_mode = 'paper' AND p.dt = (SELECT MAX(dt) FROM lakehouse.stonks.positions_daily WHERE execution_mode = 'paper') ORDER BY ABS(p.unrealized_pnl) DESC" }, { "slice_name": "Paper Trade Scorecard", "viz_type": "table", "description": "Per-symbol paper trading scorecard with win rates, PnL, and order counts", "datasource_type": "trino", "query": "SELECT pnl.ticker, COUNT(DISTINCT pnl.dt) AS trading_days, ROUND(SUM(pnl.net_pnl), 2) AS total_net_pnl, ROUND(AVG(pnl.net_pnl), 2) AS avg_daily_pnl, ROUND(CAST(COUNT(CASE WHEN pnl.net_pnl > 0 THEN 1 END) AS DOUBLE) / NULLIF(COUNT(*), 0), 4) AS win_rate, ROUND(MIN(pnl.net_pnl), 2) AS worst_day, ROUND(MAX(pnl.net_pnl), 2) AS best_day, ROUND(SUM(pnl.fees), 2) AS total_fees, MIN(pnl.dt) AS first_trade, MAX(pnl.dt) AS last_trade FROM lakehouse.stonks.pnl_daily pnl WHERE pnl.execution_mode = 'paper' GROUP BY pnl.ticker ORDER BY total_net_pnl DESC" }, { "slice_name": "Recent Orders", "viz_type": "table", "description": "Most recent paper trade orders with fill details", "datasource_type": "trino", "query": "SELECT o.ticker, o.side, o.order_type, o.quantity, ROUND(o.limit_price, 2) AS limit_price, o.status, f.fill_price, f.fill_quantity, f.commission, o.submitted_at, f.filled_at FROM lakehouse.stonks.trade_orders o LEFT JOIN lakehouse.stonks.trade_fills f ON o.order_id = f.order_id AND o.dt = f.dt WHERE o.execution_mode = 'paper' ORDER BY o.submitted_at DESC LIMIT 50" } ] }