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wehub-resource-sync 0249a267e1 chore: import upstream snapshot with attribution
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"# Constructing Continuous Options Series\n",
"\n",
"**Docker image**: `ml4t`\n",
"\n",
"## Purpose\n",
"\n",
"Demonstrate why a \"constant-maturity\" option series chains together different\n",
"contracts, produces phantom price jumps at every roll, and contaminates label\n",
"construction. Implement two clean alternatives: same-contract holding returns\n",
"(correct labels) and a roll-zeroed continuous reconstruction (backtestable\n",
"mark-to-market).\n",
"\n",
"## Learning Objectives\n",
"\n",
"- Detect contract rolls in a 30-day ATM straddle time series and quantify the\n",
" resulting bias against non-roll-day returns.\n",
"- Compute same-contract holding returns by looking up the entry contract's\n",
" exit price in the raw option chain.\n",
"- Build a roll-zeroed continuous price series suitable for backtesting and\n",
" compare it to naive chained returns.\n",
"- Reason about which construction belongs in label generation versus\n",
" transaction-cost accounting.\n",
"\n",
"## Book Reference\n",
"\n",
"Chapter 2 §2.2 (asset-class market data landscape — derivatives). The futures\n",
"analogue is `06_futures_continuous`; the case-study scale-up is\n",
"`case_studies/sp500_options/02_labels`.\n",
"\n",
"## Prerequisites\n",
"\n",
"- `07_sp500_options_eda` for option-chain structure.\n",
"- `08_options_greeks_computation` for theta and time decay.\n",
"- The AlgoSeek S&P 500 options EDA parquet at `$ML4T_DATA_PATH/sp500_options/`."
]
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"\"\"\"Constructing Continuous Options Series — constant-maturity roll adjustment.\"\"\"\n",
"\n",
"import plotly.graph_objects as go\n",
"import polars as pl\n",
"from plotly.subplots import make_subplots\n",
"\n",
"from data import load_sp500_options_eda"
]
},
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"tags": [
"parameters"
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"source": [
"DEMO_SYMBOL = \"AAPL\"\n",
"DEMO_YEAR = 2019"
]
},
{
"cell_type": "markdown",
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"source": [
"## 1. The Constant-Maturity Construction\n",
"\n",
"A 30-day ATM straddle is a common volatility instrument: you buy (or sell) both\n",
"an ATM call and an ATM put with ~30 days to expiration. To build a daily time\n",
"series, we select the \"best\" straddle each day — the one closest to 30 DTE and\n",
"50-delta.\n",
"\n",
"The problem: this selection is **independent** each day. The contract identity\n",
"(strike, expiration) changes whenever a new weekly/monthly option enters the\n",
"25–35 DTE window or the underlying moves enough to shift which strike is ATM."
]
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"source": [
"### 1.1 Load Raw Options for One Symbol"
]
},
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"name": "stdout",
"output_type": "stream",
"text": [
"Raw AAPL options (2019): 376,590 rows\n",
" Dates: 252\n",
" Unique (strike, expiration): 3,832\n"
]
}
],
"source": [
"raw = load_sp500_options_eda(\n",
" symbols=[DEMO_SYMBOL],\n",
" start_date=f\"{DEMO_YEAR}-01-01\",\n",
" end_date=f\"{DEMO_YEAR}-12-31\",\n",
").rename({\"timestamp\": \"date\"})\n",
"\n",
"print(f\"Raw {DEMO_SYMBOL} options ({DEMO_YEAR}): {len(raw):,} rows\")\n",
"print(f\" Dates: {raw['date'].n_unique()}\")\n",
"print(\n",
" f\" Unique (strike, expiration): {raw.select(pl.struct('strike', 'expiration')).n_unique():,}\"\n",
")"
]
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"source": [
"### 1.2 Constant-Maturity Straddle Selection\n",
"\n",
"For each trading day, select the ATM straddle closest to 30 DTE.\n",
"This replicates the logic in `materialize_options.py`."
]
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"# Selection parameters for constant-maturity straddle\n",
"DTE_WINDOW = (25, 35)\n",
"TARGET_DELTA = 0.50\n",
"DELTA_TOL = 0.15\n",
"MIN_BID = 0.01\n",
"MAX_REL_SPREAD = 0.30"
]
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"source": [
"### Straddle Selection Logic\n",
"\n",
"For each trading day, select the ATM straddle closest to 30 DTE."
]
},
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"source": [
"def select_constant_maturity_straddle(raw_options: pl.DataFrame) -> pl.DataFrame:\n",
" \"\"\"Select the 'best' 30D ATM straddle per day from raw option chains.\"\"\"\n",
" opts = raw_options.with_columns(\n",
" pl.col(\"delta\").abs().alias(\"abs_delta\"),\n",
" ((pl.col(\"ask\") - pl.col(\"bid\")) / pl.col(\"mid_price\").clip(lower_bound=0.01)).alias(\n",
" \"rel_spread\"\n",
" ),\n",
" )\n",
" filtered = opts.filter(\n",
" pl.col(\"days_to_maturity\").is_between(DTE_WINDOW[0], DTE_WINDOW[1])\n",
" & (pl.col(\"bid\") >= MIN_BID)\n",
" & (pl.col(\"rel_spread\") <= MAX_REL_SPREAD)\n",
" & (pl.col(\"iv_convergence\") == \"Converged\")\n",
" & pl.col(\"abs_delta\").is_between(TARGET_DELTA - DELTA_TOL, TARGET_DELTA + DELTA_TOL)\n",
" )\n",
"\n",
" def _best_leg(df: pl.DataFrame, cp: str) -> pl.DataFrame:\n",
" leg = df.filter(pl.col(\"call_put\") == cp)\n",
" leg = leg.with_columns((pl.col(\"abs_delta\") - TARGET_DELTA).abs().alias(\"_dd\"))\n",
" return (\n",
" leg.with_columns(pl.col(\"_dd\").rank(\"ordinal\").over(\"date\").alias(\"_rank\"))\n",
" .filter(pl.col(\"_rank\") == 1)\n",
" .drop([\"_rank\", \"_dd\"])\n",
" )\n",
"\n",
" call_cols = [\n",
" \"date\",\n",
" \"strike\",\n",
" \"expiration\",\n",
" \"days_to_maturity\",\n",
" \"underlying_price\",\n",
" pl.col(\"mid_price\").alias(\"call_mid\"),\n",
" pl.col(\"bid\").alias(\"call_bid\"),\n",
" pl.col(\"ask\").alias(\"call_ask\"),\n",
" pl.col(\"delta\").alias(\"call_delta\"),\n",
" pl.col(\"theta\").alias(\"call_theta\"),\n",
" ]\n",
" put_cols = [\n",
" \"date\",\n",
" pl.col(\"mid_price\").alias(\"put_mid\"),\n",
" pl.col(\"bid\").alias(\"put_bid\"),\n",
" pl.col(\"ask\").alias(\"put_ask\"),\n",
" pl.col(\"delta\").alias(\"put_delta\"),\n",
" pl.col(\"theta\").alias(\"put_theta\"),\n",
" ]\n",
" calls = _best_leg(filtered, \"C\").select(call_cols)\n",
" puts = _best_leg(filtered, \"P\").select(put_cols)\n",
" return (\n",
" calls.join(puts, on=\"date\", how=\"inner\")\n",
" .with_columns(\n",
" (pl.col(\"call_mid\") + pl.col(\"put_mid\")).alias(\"instr_mid\"),\n",
" (pl.col(\"call_theta\") + pl.col(\"put_theta\")).alias(\"instr_theta\"),\n",
" (pl.col(\"call_delta\") + pl.col(\"put_delta\")).alias(\"instr_delta\"),\n",
" )\n",
" .sort(\"date\")\n",
" )"
]
},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"Constant-maturity straddle series: 252 days\n",
" Date range: 2019-01-02 to 2019-12-31\n"
]
},
{
"data": {
"text/html": [
"<div><style>\n",
".dataframe > thead > tr,\n",
".dataframe > tbody > tr {\n",
" text-align: right;\n",
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"}\n",
"</style>\n",
"<small>shape: (10, 5)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>date</th><th>strike</th><th>expiration</th><th>days_to_maturity</th><th>instr_mid</th></tr><tr><td>date</td><td>f64</td><td>date</td><td>i32</td><td>f64</td></tr></thead><tbody><tr><td>2019-01-02</td><td>160.0</td><td>2019-02-01</td><td>30</td><td>14.3</td></tr><tr><td>2019-01-03</td><td>143.0</td><td>2019-02-01</td><td>29</td><td>13.725</td></tr><tr><td>2019-01-04</td><td>149.0</td><td>2019-02-01</td><td>28</td><td>11.95</td></tr><tr><td>2019-01-07</td><td>149.0</td><td>2019-02-08</td><td>32</td><td>12.7</td></tr><tr><td>2019-01-08</td><td>152.5</td><td>2019-02-08</td><td>31</td><td>12.375</td></tr><tr><td>2019-01-09</td><td>155.0</td><td>2019-02-08</td><td>30</td><td>12.125</td></tr><tr><td>2019-01-10</td><td>155.0</td><td>2019-02-08</td><td>29</td><td>11.875</td></tr><tr><td>2019-01-11</td><td>152.5</td><td>2019-02-08</td><td>28</td><td>11.4</td></tr><tr><td>2019-01-14</td><td>150.0</td><td>2019-02-08</td><td>25</td><td>11.175</td></tr><tr><td>2019-01-15</td><td>155.0</td><td>2019-02-15</td><td>31</td><td>11.075</td></tr></tbody></table></div>"
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"shape: (10, 5)\n",
"┌────────────┬────────┬────────────┬──────────────────┬───────────┐\n",
"│ date ┆ strike ┆ expiration ┆ days_to_maturity ┆ instr_mid │\n",
"│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n",
"│ date ┆ f64 ┆ date ┆ i32 ┆ f64 │\n",
"╞════════════╪════════╪════════════╪══════════════════╪═══════════╡\n",
"│ 2019-01-02 ┆ 160.0 ┆ 2019-02-01 ┆ 30 ┆ 14.3 │\n",
"│ 2019-01-03 ┆ 143.0 ┆ 2019-02-01 ┆ 29 ┆ 13.725 │\n",
"│ 2019-01-04 ┆ 149.0 ┆ 2019-02-01 ┆ 28 ┆ 11.95 │\n",
"│ 2019-01-07 ┆ 149.0 ┆ 2019-02-08 ┆ 32 ┆ 12.7 │\n",
"│ 2019-01-08 ┆ 152.5 ┆ 2019-02-08 ┆ 31 ┆ 12.375 │\n",
"│ 2019-01-09 ┆ 155.0 ┆ 2019-02-08 ┆ 30 ┆ 12.125 │\n",
"│ 2019-01-10 ┆ 155.0 ┆ 2019-02-08 ┆ 29 ┆ 11.875 │\n",
"│ 2019-01-11 ┆ 152.5 ┆ 2019-02-08 ┆ 28 ┆ 11.4 │\n",
"│ 2019-01-14 ┆ 150.0 ┆ 2019-02-08 ┆ 25 ┆ 11.175 │\n",
"│ 2019-01-15 ┆ 155.0 ┆ 2019-02-15 ┆ 31 ┆ 11.075 │\n",
"└────────────┴────────┴────────────┴──────────────────┴───────────┘"
]
},
"execution_count": 6,
"metadata": {},
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}
],
"source": [
"cm_straddles = select_constant_maturity_straddle(raw)\n",
"print(f\"Constant-maturity straddle series: {len(cm_straddles)} days\")\n",
"print(f\" Date range: {cm_straddles['date'].min()} to {cm_straddles['date'].max()}\")\n",
"cm_straddles.select([\"date\", \"strike\", \"expiration\", \"days_to_maturity\", \"instr_mid\"]).head(10)"
]
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"source": [
"## 2. The Roll Problem\n",
"\n",
"How often does the underlying contract change?"
]
},
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Contract changes: 184 out of 251 days (73%)\n"
]
}
],
"source": [
"cm_straddles = cm_straddles.with_columns(\n",
" pl.col(\"expiration\").shift(1).alias(\"prev_exp\"),\n",
" pl.col(\"strike\").shift(1).alias(\"prev_strike\"),\n",
" pl.col(\"instr_mid\").shift(1).alias(\"prev_mid\"),\n",
")\n",
"\n",
"cm_straddles = cm_straddles.with_columns(\n",
" ((pl.col(\"expiration\") != pl.col(\"prev_exp\")) | (pl.col(\"strike\") != pl.col(\"prev_strike\")))\n",
" .fill_null(False)\n",
" .alias(\"is_roll\"),\n",
" ((pl.col(\"instr_mid\") - pl.col(\"prev_mid\")) / pl.col(\"prev_mid\")).alias(\"daily_return\"),\n",
")\n",
"\n",
"n_rolls = cm_straddles.filter(pl.col(\"is_roll\")).height\n",
"n_total = len(cm_straddles) - 1 # exclude first row (no return)\n",
"print(f\"Contract changes: {n_rolls} out of {n_total} days ({n_rolls / n_total:.0%})\")"
]
},
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"source": [
"### 2.1 Roll-Day vs Non-Roll-Day Returns\n",
"\n",
"If the constant-maturity series were a true continuous instrument, roll days\n",
"and non-roll days should have similar return characteristics. They don't."
]
},
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{
"data": {
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"<small>shape: (4, 4)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>metric</th><th>roll_days</th><th>non_roll_days</th><th>difference</th></tr><tr><td>str</td><td>f64</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>&quot;count&quot;</td><td>184.0</td><td>67.0</td><td>117.0</td></tr><tr><td>&quot;mean_return&quot;</td><td>0.01282</td><td>-0.008897</td><td>0.021717</td></tr><tr><td>&quot;median_return&quot;</td><td>0.0</td><td>-0.0131</td><td>0.0131</td></tr><tr><td>&quot;pct_positive&quot;</td><td>0.494565</td><td>0.298507</td><td>0.196058</td></tr></tbody></table></div>"
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"shape: (4, 4)\n",
"┌───────────────┬───────────┬───────────────┬────────────┐\n",
"│ metric ┆ roll_days ┆ non_roll_days ┆ difference │\n",
"│ --- ┆ --- ┆ --- ┆ --- │\n",
"│ str ┆ f64 ┆ f64 ┆ f64 │\n",
"╞═══════════════╪═══════════╪═══════════════╪════════════╡\n",
"│ count ┆ 184.0 ┆ 67.0 ┆ 117.0 │\n",
"│ mean_return ┆ 0.01282 ┆ -0.008897 ┆ 0.021717 │\n",
"│ median_return ┆ 0.0 ┆ -0.0131 ┆ 0.0131 │\n",
"│ pct_positive ┆ 0.494565 ┆ 0.298507 ┆ 0.196058 │\n",
"└───────────────┴───────────┴───────────────┴────────────┘"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"roll_rets = cm_straddles.filter(pl.col(\"is_roll\"))[\"daily_return\"].drop_nulls()\n",
"nonroll_rets = cm_straddles.filter(~pl.col(\"is_roll\"))[\"daily_return\"].drop_nulls()\n",
"\n",
"roll_summary = pl.DataFrame(\n",
" {\n",
" \"metric\": [\"count\", \"mean_return\", \"median_return\", \"pct_positive\"],\n",
" \"roll_days\": [\n",
" float(roll_rets.len()),\n",
" roll_rets.mean(),\n",
" roll_rets.median(),\n",
" (roll_rets > 0).mean(),\n",
" ],\n",
" \"non_roll_days\": [\n",
" float(nonroll_rets.len()),\n",
" nonroll_rets.mean(),\n",
" nonroll_rets.median(),\n",
" (nonroll_rets > 0).mean(),\n",
" ],\n",
" }\n",
")\n",
"roll_summary = roll_summary.with_columns(\n",
" (pl.col(\"roll_days\") - pl.col(\"non_roll_days\")).alias(\"difference\"),\n",
")\n",
"roll_summary"
]
},
{
"cell_type": "markdown",
"id": "d8cd527b",
"metadata": {
"papermill": {
"duration": 0.001581,
"end_time": "2026-06-13T02:33:22.884529+00:00",
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"status": "completed"
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"source": [
"The pattern is clear: roll days show systematically positive returns (~+1.3%)\n",
"while non-roll days show negative returns (~-0.9%). This is not a market signal —\n",
"it's the mechanical effect of switching from a time-decayed contract (low\n",
"premium, near expiry) to a fresh contract (high premium, further expiry).\n",
"\n",
"For a short straddle strategy, this phantom \"return\" would be interpreted as a\n",
"loss, but it's actually the cost of maintaining the constant-maturity position —\n",
"analogous to contango roll cost in futures, but much larger in magnitude."
]
},
{
"cell_type": "markdown",
"id": "920232d4",
"metadata": {
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}
},
"source": [
"### 2.2 Visualizing the Sawtooth Pattern"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e81920d7",
"metadata": {
"execution": {
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}
},
"outputs": [],
"source": [
"# Prepare data for sawtooth visualization\n",
"dates = cm_straddles[\"date\"].to_list()\n",
"prices = cm_straddles[\"instr_mid\"].to_list()\n",
"dtes = cm_straddles[\"days_to_maturity\"].to_list()\n",
"rolls = cm_straddles[\"is_roll\"].to_list()\n",
"\n",
"roll_dates = [d for d, r in zip(dates, rolls, strict=False) if r]\n",
"roll_prices = [p for p, r in zip(prices, rolls, strict=False) if r]\n",
"nonroll_dates = [d for d, r in zip(dates, rolls, strict=False) if not r]\n",
"nonroll_prices = [p for p, r in zip(prices, rolls, strict=False) if not r]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "9fce88c0",
"metadata": {
"execution": {
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"shell.execute_reply": "2026-06-13T02:33:23.698109Z"
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"status": "completed"
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"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Build both panels in a single cell so the inline backend does not flush\n",
"# the figure mid-construction.\n",
"fig = make_subplots(\n",
" rows=2,\n",
" cols=1,\n",
" shared_xaxes=True,\n",
" subplot_titles=[\n",
" f\"{DEMO_SYMBOL} Constant-Maturity Straddle Price\",\n",
" \"Days to Expiration (DTE)\",\n",
" ],\n",
" vertical_spacing=0.08,\n",
")\n",
"\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=nonroll_dates,\n",
" y=nonroll_prices,\n",
" mode=\"markers\",\n",
" name=\"Same contract\",\n",
" marker=dict(size=4, color=\"#3498db\"),\n",
" opacity=0.7,\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=roll_dates,\n",
" y=roll_prices,\n",
" mode=\"markers\",\n",
" name=\"Contract switch\",\n",
" marker=dict(size=6, color=\"#e74c3c\", symbol=\"diamond\"),\n",
" opacity=0.9,\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=dates,\n",
" y=prices,\n",
" mode=\"lines\",\n",
" name=\"Price\",\n",
" line=dict(width=1, color=\"#95a5a6\"),\n",
" showlegend=False,\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=dates,\n",
" y=dtes,\n",
" mode=\"lines+markers\",\n",
" name=\"DTE\",\n",
" marker=dict(size=3, color=\"#2ecc71\"),\n",
" line=dict(width=1),\n",
" ),\n",
" row=2,\n",
" col=1,\n",
")\n",
"\n",
"fig.update_yaxes(title_text=\"Straddle Mid ($)\", row=1, col=1)\n",
"fig.update_yaxes(title_text=\"DTE\", row=2, col=1)\n",
"fig.update_xaxes(title_text=\"Date\", row=2, col=1)\n",
"fig.update_layout(template=\"plotly_white\", height=600, legend=dict(x=0.01, y=0.99))\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "e55d2195",
"metadata": {
"papermill": {
"duration": 0.002827,
"end_time": "2026-06-13T02:33:23.707195+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.704368+00:00",
"status": "completed"
}
},
"source": [
"The sawtooth pattern is visible: price decays for a few days (theta eats the\n",
"premium), then jumps up when a new contract with more time value is selected.\n",
"The DTE panel confirms: DTE drops from ~35 to ~25, then jumps back when the\n",
"contract rolls. **Every price jump at a roll is a phantom return.**"
]
},
{
"cell_type": "markdown",
"id": "5a04b775",
"metadata": {
"papermill": {
"duration": 0.002776,
"end_time": "2026-06-13T02:33:23.712791+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.710015+00:00",
"status": "completed"
}
},
"source": [
"## 3. Same-Contract Holding Returns\n",
"\n",
"The correct return for a straddle trade is: enter a specific contract at mid on\n",
"day $t$, exit the **same contract** at mid on day $t + h$. This requires\n",
"looking up that specific contract in the raw option chain $h$ days later.\n",
"\n",
"$$r_{same} = \\frac{P_{entry}^{mid}(K, T) - P_{exit}^{mid}(K, T)}{P_{entry}^{mid}(K, T)}$$\n",
"\n",
"where $(K, T)$ identifies the specific strike and expiration."
]
},
{
"cell_type": "markdown",
"id": "2e0b508b",
"metadata": {
"papermill": {
"duration": 0.002775,
"end_time": "2026-06-13T02:33:23.718369+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.715594+00:00",
"status": "completed"
}
},
"source": [
"### 3.1 Build Exit Price Lookup from Raw Chain"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "8010aaf9",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.724648Z",
"iopub.status.busy": "2026-06-13T02:33:23.724541Z",
"iopub.status.idle": "2026-06-13T02:33:23.726665Z",
"shell.execute_reply": "2026-06-13T02:33:23.726385Z"
},
"papermill": {
"duration": 0.005684,
"end_time": "2026-06-13T02:33:23.726862+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.721178+00:00",
"status": "completed"
}
},
"outputs": [],
"source": [
"HOLDING_PERIOD = 10 # days\n",
"\n",
"\n",
"def build_exit_lookup(raw_options: pl.DataFrame) -> pl.DataFrame:\n",
" \"\"\"Build a lookup table: (date, strike, expiration, call_put) → mid_price.\n",
"\n",
" Used to find the exit price of a specific contract h days after entry.\n",
" \"\"\"\n",
" return raw_options.filter(\n",
" pl.col(\"bid\") >= MIN_BID,\n",
" pl.col(\"iv_convergence\") == \"Converged\",\n",
" ).select(\n",
" [\n",
" \"date\",\n",
" \"strike\",\n",
" \"expiration\",\n",
" \"call_put\",\n",
" \"mid_price\",\n",
" \"bid\",\n",
" \"ask\",\n",
" \"delta\",\n",
" \"theta\",\n",
" \"days_to_maturity\",\n",
" ]\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "73c7a095",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.733258Z",
"iopub.status.busy": "2026-06-13T02:33:23.733164Z",
"iopub.status.idle": "2026-06-13T02:33:23.750315Z",
"shell.execute_reply": "2026-06-13T02:33:23.749920Z"
},
"papermill": {
"duration": 0.021019,
"end_time": "2026-06-13T02:33:23.750729+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.729710+00:00",
"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Exit price lookup: 232,944 rows\n",
" Unique contracts: 6,413\n"
]
}
],
"source": [
"# Build lookup from the raw chain\n",
"lookup = build_exit_lookup(raw)\n",
"print(f\"Exit price lookup: {len(lookup):,} rows\")\n",
"print(\n",
" f\" Unique contracts: {lookup.select(pl.struct('strike', 'expiration', 'call_put')).n_unique():,}\"\n",
")"
]
},
{
"cell_type": "markdown",
"id": "79b7cc8e",
"metadata": {
"papermill": {
"duration": 0.002936,
"end_time": "2026-06-13T02:33:23.756868+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.753932+00:00",
"status": "completed"
}
},
"source": [
"### 3.2 Compute Same-Contract Returns\n",
"\n",
"For each day's constant-maturity straddle, find the same contract's price\n",
"$h$ trading days later in the raw chain."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "8cf02d64",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.763385Z",
"iopub.status.busy": "2026-06-13T02:33:23.763291Z",
"iopub.status.idle": "2026-06-13T02:33:23.767212Z",
"shell.execute_reply": "2026-06-13T02:33:23.766890Z"
},
"papermill": {
"duration": 0.007967,
"end_time": "2026-06-13T02:33:23.767676+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.759709+00:00",
"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Entry-exit pairs to look up: 242\n"
]
}
],
"source": [
"# Get the trading calendar (ordered dates)\n",
"trading_dates = cm_straddles[\"date\"].unique().sort().to_list()\n",
"date_to_idx = {d: i for i, d in enumerate(trading_dates)}\n",
"\n",
"\n",
"def get_exit_date(entry_date, h: int, cal: list):\n",
" \"\"\"Get the trading date h business days after entry_date.\"\"\"\n",
" idx = date_to_idx.get(entry_date)\n",
" if idx is None or idx + h >= len(cal):\n",
" return None\n",
" return cal[idx + h]\n",
"\n",
"\n",
"# Build entry-exit pairs\n",
"entries = cm_straddles.select(\n",
" [\n",
" \"date\",\n",
" \"strike\",\n",
" \"expiration\",\n",
" \"instr_mid\",\n",
" \"call_mid\",\n",
" \"put_mid\",\n",
" \"instr_delta\",\n",
" \"is_roll\",\n",
" ]\n",
").rename({\"date\": \"entry_date\", \"instr_mid\": \"entry_mid\"})\n",
"\n",
"# Add exit dates\n",
"exit_dates = [\n",
" get_exit_date(d, HOLDING_PERIOD, trading_dates) for d in entries[\"entry_date\"].to_list()\n",
"]\n",
"entries = entries.with_columns(pl.Series(\"exit_date\", exit_dates).cast(pl.Date))\n",
"\n",
"# Drop entries where exit date is beyond our data\n",
"entries = entries.filter(pl.col(\"exit_date\").is_not_null())\n",
"print(f\"Entry-exit pairs to look up: {len(entries):,}\")"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "d270b655",
"metadata": {
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"exception": false,
"start_time": "2026-06-13T02:33:23.770680+00:00",
"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Exit prices found: 222 / 242 (91.7%)\n"
]
}
],
"source": [
"# Look up call exit price\n",
"call_exit = lookup.filter(pl.col(\"call_put\") == \"C\").select(\n",
" [\n",
" pl.col(\"date\").alias(\"exit_date\"),\n",
" \"strike\",\n",
" \"expiration\",\n",
" pl.col(\"mid_price\").alias(\"call_exit_mid\"),\n",
" ]\n",
")\n",
"\n",
"# Look up put exit price\n",
"put_exit = lookup.filter(pl.col(\"call_put\") == \"P\").select(\n",
" [\n",
" pl.col(\"date\").alias(\"exit_date\"),\n",
" \"strike\",\n",
" \"expiration\",\n",
" pl.col(\"mid_price\").alias(\"put_exit_mid\"),\n",
" ]\n",
")\n",
"\n",
"# Join: entry contract → exit prices for same (strike, expiration)\n",
"same_contract = entries.join(call_exit, on=[\"exit_date\", \"strike\", \"expiration\"], how=\"left\").join(\n",
" put_exit, on=[\"exit_date\", \"strike\", \"expiration\"], how=\"left\"\n",
")\n",
"\n",
"# Compute same-contract straddle exit mid\n",
"same_contract = same_contract.with_columns(\n",
" (pl.col(\"call_exit_mid\") + pl.col(\"put_exit_mid\")).alias(\"exit_mid\"),\n",
")\n",
"\n",
"# Same-contract return (short straddle: positive = profitable)\n",
"same_contract = same_contract.with_columns(\n",
" ((pl.col(\"entry_mid\") - pl.col(\"exit_mid\")) / pl.col(\"entry_mid\")).alias(\"same_contract_ret\"),\n",
")\n",
"\n",
"# How many lookups succeeded?\n",
"found = same_contract.filter(pl.col(\"exit_mid\").is_not_null()).height\n",
"print(f\"Exit prices found: {found} / {len(same_contract)} ({found / len(same_contract):.1%})\")"
]
},
{
"cell_type": "markdown",
"id": "574aace1",
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}
},
"source": [
"### 3.3 Compare Naive vs Same-Contract Returns"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "f0813c5d",
"metadata": {
"execution": {
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"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Paired observations: 221\n",
"Correlation(naive, same-contract) = 0.093\n"
]
},
{
"data": {
"text/html": [
"<div><style>\n",
".dataframe > thead > tr,\n",
".dataframe > tbody > tr {\n",
" text-align: right;\n",
" white-space: pre-wrap;\n",
"}\n",
"</style>\n",
"<small>shape: (4, 3)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>metric</th><th>naive_chained</th><th>same_contract</th></tr><tr><td>str</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>&quot;mean_return&quot;</td><td>-0.025303</td><td>0.009765</td></tr><tr><td>&quot;std&quot;</td><td>0.18246</td><td>0.26816</td></tr><tr><td>&quot;median_return&quot;</td><td>-0.005435</td><td>0.070293</td></tr><tr><td>&quot;pct_positive_short&quot;</td><td>0.488688</td><td>0.633484</td></tr></tbody></table></div>"
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"text/plain": [
"shape: (4, 3)\n",
"┌────────────────────┬───────────────┬───────────────┐\n",
"│ metric ┆ naive_chained ┆ same_contract │\n",
"│ --- ┆ --- ┆ --- │\n",
"│ str ┆ f64 ┆ f64 │\n",
"╞════════════════════╪═══════════════╪═══════════════╡\n",
"│ mean_return ┆ -0.025303 ┆ 0.009765 │\n",
"│ std ┆ 0.18246 ┆ 0.26816 │\n",
"│ median_return ┆ -0.005435 ┆ 0.070293 │\n",
"│ pct_positive_short ┆ 0.488688 ┆ 0.633484 │\n",
"└────────────────────┴───────────────┴───────────────┘"
]
},
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Naive return: shift-based on constant-maturity series (what 02_labels.py did)\n",
"naive_rets = cm_straddles.with_columns(\n",
" pl.col(\"instr_mid\").shift(-1).alias(\"naive_entry\"),\n",
" pl.col(\"instr_mid\").shift(-(1 + HOLDING_PERIOD)).alias(\"naive_exit\"),\n",
").with_columns(\n",
" ((pl.col(\"naive_entry\") - pl.col(\"naive_exit\")) / pl.col(\"naive_entry\")).alias(\"naive_ret\"),\n",
")\n",
"\n",
"# Align for comparison\n",
"comparison = (\n",
" same_contract.filter(pl.col(\"same_contract_ret\").is_not_null())\n",
" .select([\"entry_date\", \"same_contract_ret\"])\n",
" .join(\n",
" naive_rets.select([pl.col(\"date\").alias(\"entry_date\"), \"naive_ret\"]).drop_nulls(),\n",
" on=\"entry_date\",\n",
" how=\"inner\",\n",
" )\n",
")\n",
"\n",
"print(f\"Paired observations: {len(comparison):,}\")\n",
"\n",
"naive_vs_same = pl.DataFrame(\n",
" {\n",
" \"metric\": [\"mean_return\", \"std\", \"median_return\", \"pct_positive_short\"],\n",
" \"naive_chained\": [\n",
" comparison[\"naive_ret\"].mean(),\n",
" comparison[\"naive_ret\"].std(),\n",
" comparison[\"naive_ret\"].median(),\n",
" (comparison[\"naive_ret\"] > 0).mean(),\n",
" ],\n",
" \"same_contract\": [\n",
" comparison[\"same_contract_ret\"].mean(),\n",
" comparison[\"same_contract_ret\"].std(),\n",
" comparison[\"same_contract_ret\"].median(),\n",
" (comparison[\"same_contract_ret\"] > 0).mean(),\n",
" ],\n",
" }\n",
")\n",
"corr = comparison.select(pl.corr(\"naive_ret\", \"same_contract_ret\").alias(\"correlation\")).item()\n",
"print(f\"Correlation(naive, same-contract) = {corr:.3f}\")\n",
"naive_vs_same"
]
},
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"cell_type": "markdown",
"id": "03c31d4e",
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"end_time": "2026-06-13T02:33:23.812079+00:00",
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},
"source": [
"The naive chained returns systematically differ from same-contract returns.\n",
"The correlation tells us how much of the naive signal is genuine vs artifact.\n",
"Any label or model trained on naive returns is learning a mix of actual\n",
"straddle P&L and roll mechanics."
]
},
{
"cell_type": "code",
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"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Scatter plot: naive vs same-contract\n",
"fig = go.Figure()\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=comparison[\"naive_ret\"].to_list(),\n",
" y=comparison[\"same_contract_ret\"].to_list(),\n",
" mode=\"markers\",\n",
" marker=dict(size=3, color=\"#3498db\", opacity=0.4),\n",
" name=\"Returns\",\n",
" )\n",
")\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=[-0.5, 0.5],\n",
" y=[-0.5, 0.5],\n",
" mode=\"lines\",\n",
" line=dict(dash=\"dash\", color=\"gray\"),\n",
" name=\"45° line\",\n",
" )\n",
")\n",
"fig.update_layout(\n",
" template=\"plotly_white\",\n",
" title=f\"{DEMO_SYMBOL}: Naive vs Same-Contract {HOLDING_PERIOD}d Returns\",\n",
" xaxis_title=\"Naive (chained constant-maturity)\",\n",
" yaxis_title=\"Same-contract holding return\",\n",
" width=600,\n",
" height=500,\n",
")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "1c750f17",
"metadata": {
"lines_to_next_cell": 2,
"papermill": {
"duration": 0.003941,
"end_time": "2026-06-13T02:33:23.881099+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.877158+00:00",
"status": "completed"
}
},
"source": [
"## 4. Building a Continuous Series for Backtesting\n",
"\n",
"For backtesting, we need a continuous price series where daily returns reflect\n",
"actual P&L — no phantom jumps at rolls. Unlike futures (which roll quarterly\n",
"and suit Panama adjustment), straddles roll almost daily, so we use a\n",
"**return-based reconstruction**:\n",
"\n",
"1. On non-roll days: daily return = genuine within-contract P&L\n",
"2. On roll days: set return to 0 (the roll is a transaction, not a return)\n",
"3. Reconstruct prices: $P_{adj,t} = P_0 \\prod_{i=1}^{t} (1 + r_i)$\n",
"\n",
"Roll costs (bid-ask at roll) are modeled separately as transaction costs in\n",
"Chapter 18."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "b5c0d3bf",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.889585Z",
"iopub.status.busy": "2026-06-13T02:33:23.889485Z",
"iopub.status.idle": "2026-06-13T02:33:23.892101Z",
"shell.execute_reply": "2026-06-13T02:33:23.891776Z"
},
"papermill": {
"duration": 0.007659,
"end_time": "2026-06-13T02:33:23.892600+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.884941+00:00",
"status": "completed"
}
},
"outputs": [],
"source": [
"def build_continuous_straddle_series(cm_series: pl.DataFrame) -> pl.DataFrame:\n",
" \"\"\"Build a continuous straddle price series from within-contract returns.\n",
"\n",
" On roll days, the return is set to 0 (roll is a transaction, not a return).\n",
" The resulting series has no phantom jumps and its returns reflect actual P&L.\n",
" \"\"\"\n",
" df = cm_series.with_columns(\n",
" ((pl.col(\"instr_mid\") - pl.col(\"instr_mid\").shift(1)) / pl.col(\"instr_mid\").shift(1)).alias(\n",
" \"raw_daily_ret\"\n",
" ),\n",
" )\n",
"\n",
" # On roll days, set return to 0\n",
" df = df.with_columns(\n",
" pl.when(pl.col(\"is_roll\"))\n",
" .then(0.0)\n",
" .otherwise(pl.col(\"raw_daily_ret\"))\n",
" .alias(\"clean_daily_ret\"),\n",
" )\n",
"\n",
" # Reconstruct price from cumulative returns, starting at the first observed price\n",
" start_price = cm_series[\"instr_mid\"][0]\n",
" cum_rets = df[\"clean_daily_ret\"].fill_null(0.0).to_list()\n",
"\n",
" adj_prices = [start_price]\n",
" for r in cum_rets[1:]:\n",
" adj_prices.append(adj_prices[-1] * (1.0 + r))\n",
"\n",
" return df.with_columns(pl.Series(\"price_adjusted\", adj_prices))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "e631df61",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.903221Z",
"iopub.status.busy": "2026-06-13T02:33:23.903131Z",
"iopub.status.idle": "2026-06-13T02:33:23.907338Z",
"shell.execute_reply": "2026-06-13T02:33:23.907060Z"
},
"papermill": {
"duration": 0.009018,
"end_time": "2026-06-13T02:33:23.907746+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.898728+00:00",
"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Roll-day bias removed: raw roll mean was +0.0128, now 0.0000\n"
]
},
{
"data": {
"text/html": [
"<div><style>\n",
".dataframe > thead > tr,\n",
".dataframe > tbody > tr {\n",
" text-align: right;\n",
" white-space: pre-wrap;\n",
"}\n",
"</style>\n",
"<small>shape: (2, 3)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>metric</th><th>roll_days</th><th>non_roll_days</th></tr><tr><td>str</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>&quot;raw_mean&quot;</td><td>0.01282</td><td>-0.008897</td></tr><tr><td>&quot;clean_mean&quot;</td><td>0.0</td><td>-0.008897</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (2, 3)\n",
"┌────────────┬───────────┬───────────────┐\n",
"│ metric ┆ roll_days ┆ non_roll_days │\n",
"│ --- ┆ --- ┆ --- │\n",
"│ str ┆ f64 ┆ f64 │\n",
"╞════════════╪═══════════╪═══════════════╡\n",
"│ raw_mean ┆ 0.01282 ┆ -0.008897 │\n",
"│ clean_mean ┆ 0.0 ┆ -0.008897 │\n",
"└────────────┴───────────┴───────────────┘"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"adjusted = build_continuous_straddle_series(cm_straddles)\n",
"\n",
"# Compare roll-day returns: raw vs cleaned\n",
"adj_roll = adjusted.filter(pl.col(\"is_roll\"))\n",
"adj_nonroll = adjusted.filter(~pl.col(\"is_roll\"))\n",
"\n",
"raw_vs_clean = pl.DataFrame(\n",
" {\n",
" \"metric\": [\"raw_mean\", \"clean_mean\"],\n",
" \"roll_days\": [\n",
" adj_roll[\"raw_daily_ret\"].mean(),\n",
" adj_roll[\"clean_daily_ret\"].mean(),\n",
" ],\n",
" \"non_roll_days\": [\n",
" adj_nonroll[\"raw_daily_ret\"].mean(),\n",
" adj_nonroll[\"clean_daily_ret\"].mean(),\n",
" ],\n",
" }\n",
")\n",
"print(\n",
" f\"Roll-day bias removed: raw roll mean was {adj_roll['raw_daily_ret'].mean():+.4f}, now 0.0000\"\n",
")\n",
"raw_vs_clean"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "1e1386a9",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.916323Z",
"iopub.status.busy": "2026-06-13T02:33:23.916215Z",
"iopub.status.idle": "2026-06-13T02:33:23.966114Z",
"shell.execute_reply": "2026-06-13T02:33:23.965769Z"
},
"papermill": {
"duration": 0.054909,
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"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Visualize raw vs adjusted price series\n",
"fig = make_subplots(\n",
" rows=2,\n",
" cols=1,\n",
" shared_xaxes=True,\n",
" subplot_titles=[\"Raw Constant-Maturity Series (sawtooth)\", \"Continuous (roll-zeroed)\"],\n",
" vertical_spacing=0.08,\n",
")\n",
"\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=adjusted[\"date\"].to_list(),\n",
" y=adjusted[\"instr_mid\"].to_list(),\n",
" mode=\"lines\",\n",
" name=\"Raw\",\n",
" line=dict(color=\"#e74c3c\", width=1.5),\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"fig.add_trace(\n",
" go.Scatter(\n",
" x=adjusted[\"date\"].to_list(),\n",
" y=adjusted[\"price_adjusted\"].to_list(),\n",
" mode=\"lines\",\n",
" name=\"Adjusted\",\n",
" line=dict(color=\"#3498db\", width=1.5),\n",
" ),\n",
" row=2,\n",
" col=1,\n",
")\n",
"\n",
"fig.update_yaxes(title_text=\"Straddle Mid ($)\", row=1, col=1)\n",
"fig.update_yaxes(title_text=\"Adjusted Price ($)\", row=2, col=1)\n",
"fig.update_layout(\n",
" template=\"plotly_white\",\n",
" height=500,\n",
" title=f\"{DEMO_SYMBOL} Straddle: Raw vs Continuous (Roll-Adjusted)\",\n",
")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "1cd3b286",
"metadata": {
"papermill": {
"duration": 0.0049,
"end_time": "2026-06-13T02:33:23.976739+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.971839+00:00",
"status": "completed"
}
},
"source": [
"The adjusted series shows steady theta decay without the sawtooth jumps.\n",
"This is the series suitable for backtesting — roll costs should be modeled\n",
"separately as transaction costs (Chapter 18).\n",
"\n",
"**Note**: This continuous series approximates the actual P&L but is not exact.\n",
"The precise approach — same-contract holding returns (Section 3 above) — is\n",
"what the case study uses for label construction."
]
},
{
"cell_type": "markdown",
"id": "8d2b3a68",
"metadata": {
"papermill": {
"duration": 0.004907,
"end_time": "2026-06-13T02:33:23.986654+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.981747+00:00",
"status": "completed"
}
},
"source": [
"## 5. Summary: Three Approaches Compared\n",
"\n",
"| Approach | Mechanism | Suitable For |\n",
"|----------|-----------|--------------|\n",
"| Naive (chained) | `shift(-h)` on constant-maturity series | **Nothing** — contaminates labels |\n",
"| Same-contract | Look up entry contract's price h days later | **Labels** — correct per-trade P&L |\n",
"| Continuous (roll-zeroed) | Zero out roll-day returns, rebuild prices | **Backtesting** — smooth mark-to-market |\n",
"\n",
"The same-contract approach (Section 3) requires the raw option chains to\n",
"look up exit prices. The continuous approach (Section 4) only needs the\n",
"constant-maturity series but must detect rolls and zero out their returns."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "f480de27",
"metadata": {
"execution": {
"iopub.execute_input": "2026-06-13T02:33:23.997124Z",
"iopub.status.busy": "2026-06-13T02:33:23.997024Z",
"iopub.status.idle": "2026-06-13T02:33:24.002000Z",
"shell.execute_reply": "2026-06-13T02:33:24.001682Z"
},
"papermill": {
"duration": 0.010919,
"end_time": "2026-06-13T02:33:24.002464+00:00",
"exception": false,
"start_time": "2026-06-13T02:33:23.991545+00:00",
"status": "completed"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Paired observations: 221\n"
]
},
{
"data": {
"text/html": [
"<div><style>\n",
".dataframe > thead > tr,\n",
".dataframe > tbody > tr {\n",
" text-align: right;\n",
" white-space: pre-wrap;\n",
"}\n",
"</style>\n",
"<small>shape: (3, 4)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>metric</th><th>naive</th><th>continuous</th><th>same_contract</th></tr><tr><td>str</td><td>f64</td><td>f64</td><td>f64</td></tr></thead><tbody><tr><td>&quot;mean&quot;</td><td>-0.025303</td><td>0.025918</td><td>0.009765</td></tr><tr><td>&quot;std&quot;</td><td>0.18246</td><td>0.088039</td><td>0.26816</td></tr><tr><td>&quot;corr_with_same_contract&quot;</td><td>0.09325</td><td>0.120107</td><td>1.0</td></tr></tbody></table></div>"
],
"text/plain": [
"shape: (3, 4)\n",
"┌─────────────────────────┬───────────┬────────────┬───────────────┐\n",
"│ metric ┆ naive ┆ continuous ┆ same_contract │\n",
"│ --- ┆ --- ┆ --- ┆ --- │\n",
"│ str ┆ f64 ┆ f64 ┆ f64 │\n",
"╞═════════════════════════╪═══════════╪════════════╪═══════════════╡\n",
"│ mean ┆ -0.025303 ┆ 0.025918 ┆ 0.009765 │\n",
"│ std ┆ 0.18246 ┆ 0.088039 ┆ 0.26816 │\n",
"│ corr_with_same_contract ┆ 0.09325 ┆ 0.120107 ┆ 1.0 │\n",
"└─────────────────────────┴───────────┴────────────┴───────────────┘"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Final comparison: all three 10d forward return approaches\n",
"# Naive\n",
"adjusted = adjusted.with_columns(\n",
" pl.col(\"instr_mid\").shift(-1).alias(\"raw_entry\"),\n",
" pl.col(\"instr_mid\").shift(-(1 + HOLDING_PERIOD)).alias(\"raw_exit\"),\n",
").with_columns(\n",
" ((pl.col(\"raw_entry\") - pl.col(\"raw_exit\")) / pl.col(\"raw_entry\")).alias(\"naive_fwd_ret\"),\n",
")\n",
"\n",
"# Continuous-adjusted\n",
"adjusted = adjusted.with_columns(\n",
" pl.col(\"price_adjusted\").shift(-1).alias(\"adj_entry\"),\n",
" pl.col(\"price_adjusted\").shift(-(1 + HOLDING_PERIOD)).alias(\"adj_exit\"),\n",
").with_columns(\n",
" ((pl.col(\"adj_entry\") - pl.col(\"adj_exit\")) / pl.col(\"adj_entry\")).alias(\"cont_fwd_ret\"),\n",
")\n",
"\n",
"# Merge with same-contract returns\n",
"comparison_all = (\n",
" adjusted.select([pl.col(\"date\").alias(\"entry_date\"), \"naive_fwd_ret\", \"cont_fwd_ret\"])\n",
" .join(\n",
" same_contract.select([\"entry_date\", \"same_contract_ret\"]),\n",
" on=\"entry_date\",\n",
" how=\"left\",\n",
" )\n",
" .drop_nulls()\n",
")\n",
"\n",
"print(f\"Paired observations: {len(comparison_all):,}\")\n",
"\n",
"three_way = pl.DataFrame(\n",
" {\n",
" \"metric\": [\"mean\", \"std\", \"corr_with_same_contract\"],\n",
" \"naive\": [\n",
" comparison_all[\"naive_fwd_ret\"].mean(),\n",
" comparison_all[\"naive_fwd_ret\"].std(),\n",
" comparison_all.select(pl.corr(\"naive_fwd_ret\", \"same_contract_ret\")).item(),\n",
" ],\n",
" \"continuous\": [\n",
" comparison_all[\"cont_fwd_ret\"].mean(),\n",
" comparison_all[\"cont_fwd_ret\"].std(),\n",
" comparison_all.select(pl.corr(\"cont_fwd_ret\", \"same_contract_ret\")).item(),\n",
" ],\n",
" \"same_contract\": [\n",
" comparison_all[\"same_contract_ret\"].mean(),\n",
" comparison_all[\"same_contract_ret\"].std(),\n",
" 1.0,\n",
" ],\n",
" }\n",
")\n",
"three_way"
]
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"## Key Takeaways\n",
"\n",
"1. **Constant-maturity option series chain different contracts**: The \"best\"\n",
" 30D ATM straddle changes every 1-2 days on average. Each switch creates a\n",
" phantom price jump from time-value reset.\n",
"\n",
"2. **Roll contamination is systematic**: Roll-day returns average +1.3% vs\n",
" -0.9% on non-roll days. This 2.2pp bias compounds over ~184 roll days/year\n",
" because options decay faster and roll more frequently than futures.\n",
"\n",
"3. **Same-contract returns are the correct label**: Looking up the entry\n",
" contract's price h days later in the raw option chain gives the actual\n",
" holding P&L. The raw chain data makes this feasible.\n",
"\n",
"4. **Roll-zeroed reconstruction creates a backtestable series**: Setting\n",
" roll-day returns to zero and rebuilding prices removes phantom jumps while\n",
" preserving genuine within-contract P&L on non-roll days.\n",
"\n",
"5. **Roll costs are transaction costs, not returns**: The cost of maintaining\n",
" a constant-maturity position (closing old, opening new) should be modeled\n",
" as execution cost in Chapter 18, not embedded in the price series.\n",
"\n",
"## Next\n",
"\n",
"The S&P 500 options case study\n",
"([`02_labels`](../case_studies/sp500_options/02_labels.ipynb)) applies the\n",
"same-contract and roll-zeroed constructions at panel scale across the full\n",
"universe and multi-year sample."
]
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