Update fine-tune notebook securities to real StockEx symbols

Replace hardcoded OPAP/MYTIL/ADMIE/etc. with actual StockEx securities
(ALPHA, PEIR, EXAE, QUEST, NBG, EUROB, AEG, INTKA, AAAK, ATTIK) and
current market prices for Colab training dataset generation.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

notebooks/ch_trader_finetune.ipynb

@@ -96,176 +96,7 @@
    "id": "dataset-gen",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# Securities traded on StockEx\n",
-    "SECURITIES = [\n",
-    "    {\"symbol\": \"ALPHA\",  \"base\": 6.00},\n",
-    "    {\"symbol\": \"PEIR\",   \"base\": 8.20},\n",
-    "    {\"symbol\": \"EXAE\",   \"base\": 6.90},\n",
-    "    {\"symbol\": \"OPAP\",   \"base\": 14.50},\n",
-    "    {\"symbol\": \"MYTIL\",  \"base\": 9.80},\n",
-    "    {\"symbol\": \"ADMIE\",  \"base\": 2.45},\n",
-    "    {\"symbol\": \"ELPE\",   \"base\": 7.60},\n",
-    "    {\"symbol\": \"MOTOR\",  \"base\": 22.30},\n",
-    "    {\"symbol\": \"OTE\",    \"base\": 15.10},\n",
-    "    {\"symbol\": \"TPEIR\",  \"base\": 1.75},\n",
-    "]\n",
-    "\n",
-    "STARTING_CAPITAL = 100_000.0\n",
-    "DAILY_OBLIGATION = 10\n",
-    "\n",
-    "\n",
-    "def gen_bbo(base_price: float) -> dict:\n",
-    "    \"\"\"Generate a realistic bid/ask spread around a base price.\"\"\"\n",
-    "    drift    = random.uniform(-0.05, 0.05)\n",
-    "    mid      = round(base_price * (1 + drift), 2)\n",
-    "    spread   = round(random.choice([0.05, 0.10, 0.15]), 2)\n",
-    "    best_bid = round(mid - spread / 2, 2)\n",
-    "    best_ask = round(mid + spread / 2, 2)\n",
-    "    return {\"best_bid\": best_bid, \"best_ask\": best_ask, \"mid\": mid}\n",
-    "\n",
-    "\n",
-    "def gen_holdings(bbos: dict) -> list:\n",
-    "    \"\"\"Randomly generate some holdings for a member.\"\"\"\n",
-    "    holdings = []\n",
-    "    n = random.randint(0, 4)  # 0–4 positions\n",
-    "    for sym in random.sample(list(bbos.keys()), min(n, len(bbos))):\n",
-    "        qty = random.randint(50, 500)\n",
-    "        mid = bbos[sym][\"mid\"]\n",
-    "        avg_cost = round(mid * random.uniform(0.92, 1.08), 2)\n",
-    "        holdings.append({\"symbol\": sym, \"quantity\": qty, \"avg_cost\": avg_cost})\n",
-    "    return holdings\n",
-    "\n",
-    "\n",
-    "def build_prompt(member_id: str, capital: float, holdings: list,\n",
-    "                 obligation_remaining: int, bbos: dict) -> str:\n",
-    "    market_lines = [\n",
-    "        f\"  {sym}: Bid {bbo['best_bid']:.2f} / Ask {bbo['best_ask']:.2f}\"\n",
-    "        for sym, bbo in sorted(bbos.items())\n",
-    "    ]\n",
-    "    holding_lines = (\n",
-    "        [f\"  {h['symbol']}: {h['quantity']} shares @ avg cost {h['avg_cost']:.2f}\"\n",
-    "         for h in holdings]\n",
-    "        if holdings else [\"  None\"]\n",
-    "    )\n",
-    "    return (\n",
-    "        f\"You are simulating clearing house member {member_id} making ONE trading decision.\\n\\n\"\n",
-    "        f\"Member state:\\n\"\n",
-    "        f\"  Available capital: EUR {capital:,.2f}\\n\"\n",
-    "        f\"  Securities obligation remaining today: {obligation_remaining} more to trade\\n\"\n",
-    "        f\"  Current holdings:\\n\" + \"\\n\".join(holding_lines) + \"\\n\\n\"\n",
-    "        f\"Current market (Bid/Ask):\\n\" + \"\\n\".join(market_lines) + \"\\n\\n\"\n",
-    "        f\"Rules:\\n\"\n",
-    "        f\"- Do not spend more than your available capital\\n\"\n",
-    "        f\"- Do not sell more shares than you hold\\n\"\n",
-    "        f\"- If you have no holdings, you must BUY\\n\"\n",
-    "        f\"- Choose a realistic price close to the BBO mid-price\\n\"\n",
-    "        f\"- Quantity should be between 10 and 200\\n\\n\"\n",
-    "        f\"Respond ONLY with valid JSON, no other text:\\n\"\n",
-    "        f'Example: {{\"symbol\": \"ALPHA\", \"side\": \"BUY\", \"quantity\": 50, \"price\": 5.95}}'\n",
-    "    )\n",
-    "\n",
-    "\n",
-    "def gen_decision(capital: float, holdings: list, bbos: dict) -> dict:\n",
-    "    \"\"\"Generate a rule-valid trading decision for the given state.\"\"\"\n",
-    "    has_holdings = len(holdings) > 0\n",
-    "\n",
-    "    # Decide side: BUY if no holdings or randomly; SELL if heavy positions\n",
-    "    holdings_value = sum(\n",
-    "        h[\"quantity\"] * bbos.get(h[\"symbol\"], {}).get(\"mid\", h[\"avg_cost\"])\n",
-    "        for h in holdings\n",
-    "    )\n",
-    "    net_worth = capital + holdings_value\n",
-    "    holdings_ratio = holdings_value / net_worth if net_worth > 0 else 0\n",
-    "\n",
-    "    if not has_holdings:\n",
-    "        side = \"BUY\"\n",
-    "    elif holdings_ratio > 0.6:\n",
-    "        side = random.choices([\"SELL\", \"BUY\"], weights=[0.7, 0.3])[0]\n",
-    "    else:\n",
-    "        side = random.choices([\"BUY\", \"SELL\"], weights=[0.55, 0.45])[0]\n",
-    "\n",
-    "    if side == \"BUY\":\n",
-    "        # Pick a random affordable symbol\n",
-    "        affordable = [\n",
-    "            sym for sym, bbo in bbos.items()\n",
-    "            if 10 * bbo[\"best_ask\"] <= capital\n",
-    "        ]\n",
-    "        if not affordable:\n",
-    "            # Fall back to cheapest\n",
-    "            sym = min(bbos, key=lambda s: bbos[s][\"best_ask\"])\n",
-    "        else:\n",
-    "            # Weight toward securities we already hold (adding to position)\n",
-    "            held_syms = [h[\"symbol\"] for h in holdings]\n",
-    "            weights = [3 if s in held_syms else 1 for s in affordable]\n",
-    "            sym = random.choices(affordable, weights=weights)[0]\n",
-    "        ask = bbos[sym][\"best_ask\"]\n",
-    "        max_qty = min(200, int(capital / ask))\n",
-    "        qty = random.randint(10, max(10, max_qty))\n",
-    "        price = round(bbos[sym][\"mid\"] + random.uniform(-0.05, 0.05), 2)\n",
-    "        price = max(bbos[sym][\"best_bid\"], min(price, ask))\n",
-    "        return {\"symbol\": sym, \"side\": \"BUY\", \"quantity\": qty, \"price\": round(price, 2)}\n",
-    "    else:\n",
-    "        # Sell from existing holdings\n",
-    "        h = random.choice(holdings)\n",
-    "        sym = h[\"symbol\"]\n",
-    "        bbo = bbos[sym]\n",
-    "        qty = random.randint(10, min(200, h[\"quantity\"]))\n",
-    "        price = round(bbo[\"mid\"] + random.uniform(-0.05, 0.05), 2)\n",
-    "        price = max(bbo[\"best_bid\"] - 0.05, min(price, bbo[\"best_ask\"]))\n",
-    "        return {\"symbol\": sym, \"side\": \"SELL\", \"quantity\": qty, \"price\": round(price, 2)}\n",
-    "\n",
-    "\n",
-    "def generate_dataset(n: int) -> list:\n",
-    "    examples = []\n",
-    "    member_ids = [f\"USR{i:02d}\" for i in range(1, 11)]\n",
-    "\n",
-    "    scenarios = [\n",
-    "        # (capital_range, obligation_range, description)\n",
-    "        ((80_000, 100_000), (5, 10), \"fresh_member\"),     # new, must trade a lot\n",
-    "        ((50_000, 80_000),  (0, 5),  \"active_member\"),    # mid-session, nearly done\n",
-    "        ((20_000, 50_000),  (0, 2),  \"low_capital\"),      # low cash, mostly holdings\n",
-    "        ((5_000,  20_000),  (0, 10), \"very_low_capital\"), # near margin, careful\n",
-    "        ((90_000, 100_000), (10, 10),\"start_of_day\"),     # just started\n",
-    "    ]\n",
-    "\n",
-    "    for _ in range(n):\n",
-    "        cap_range, obl_range, _ = random.choice(scenarios)\n",
-    "        capital    = round(random.uniform(*cap_range), 2)\n",
-    "        obligation = random.randint(*obl_range)\n",
-    "        member_id  = random.choice(member_ids)\n",
-    "\n",
-    "        # Generate market state\n",
-    "        bbos = {s[\"symbol\"]: gen_bbo(s[\"base\"]) for s in SECURITIES}\n",
-    "\n",
-    "        # Generate holdings consistent with remaining capital\n",
-    "        holdings = gen_holdings(bbos)\n",
-    "\n",
-    "        # Ensure capital consistency: if holdings are expensive, reduce capital\n",
-    "        holdings_cost = sum(h[\"quantity\"] * h[\"avg_cost\"] for h in holdings)\n",
-    "        if holdings_cost > STARTING_CAPITAL - capital:\n",
-    "            # Scale down holdings to fit\n",
-    "            scale = (STARTING_CAPITAL - capital) / max(holdings_cost, 1)\n",
-    "            for h in holdings:\n",
-    "                h[\"quantity\"] = max(10, int(h[\"quantity\"] * scale))\n",
-    "\n",
-    "        prompt   = build_prompt(member_id, capital, holdings, obligation, bbos)\n",
-    "        decision = gen_decision(capital, holdings, bbos)\n",
-    "\n",
-    "        examples.append({\n",
-    "            \"prompt\": prompt,\n",
-    "            \"completion\": json.dumps(decision),\n",
-    "        })\n",
-    "\n",
-    "    return examples\n",
-    "\n",
-    "\n",
-    "print(f\"Generating {DATASET_SIZE} training examples...\")\n",
-    "raw_data = generate_dataset(DATASET_SIZE)\n",
-    "print(f\"Done. Example:\")\n",
-    "print(\"PROMPT:\\n\", raw_data[0][\"prompt\"])\n",
-    "print(\"\\nCOMPLETION:\", raw_data[0][\"completion\"])"
-   ]
+   "source": "# Securities from shared_data/securities.txt  (symbol, start_price, current_price)\nSECURITIES = [\n    {\"symbol\": \"ALPHA\", \"base\": 5.65},\n    {\"symbol\": \"PEIR\",  \"base\": 8.35},\n    {\"symbol\": \"EXAE\",  \"base\": 6.90},\n    {\"symbol\": \"QUEST\", \"base\": 13.35},\n    {\"symbol\": \"NBG\",   \"base\": 8.00},\n    {\"symbol\": \"EUROB\", \"base\": 3.45},\n    {\"symbol\": \"AEG\",   \"base\": 4.75},\n    {\"symbol\": \"INTKA\", \"base\": 7.35},\n    {\"symbol\": \"AAAK\",  \"base\": 2.75},\n    {\"symbol\": \"ATTIK\", \"base\": 4.90},\n]\n\nSTARTING_CAPITAL = 100_000.0\nDAILY_OBLIGATION = 10\n\n\ndef gen_bbo(base_price: float) -> dict:\n    \"\"\"Generate a realistic bid/ask spread around a base price.\"\"\"\n    drift    = random.uniform(-0.05, 0.05)\n    mid      = round(base_price * (1 + drift), 2)\n    spread   = round(random.choice([0.05, 0.10, 0.15]), 2)\n    best_bid = round(mid - spread / 2, 2)\n    best_ask = round(mid + spread / 2, 2)\n    return {\"best_bid\": best_bid, \"best_ask\": best_ask, \"mid\": mid}\n\n\ndef gen_holdings(bbos: dict) -> list:\n    \"\"\"Randomly generate some holdings for a member.\"\"\"\n    holdings = []\n    n = random.randint(0, 4)\n    for sym in random.sample(list(bbos.keys()), min(n, len(bbos))):\n        qty = random.randint(50, 500)\n        mid = bbos[sym][\"mid\"]\n        avg_cost = round(mid * random.uniform(0.92, 1.08), 2)\n        holdings.append({\"symbol\": sym, \"quantity\": qty, \"avg_cost\": avg_cost})\n    return holdings\n\n\ndef build_prompt(member_id: str, capital: float, holdings: list,\n                 obligation_remaining: int, bbos: dict) -> str:\n    market_lines = [\n        f\"  {sym}: Bid {bbo['best_bid']:.2f} / Ask {bbo['best_ask']:.2f}\"\n        for sym, bbo in sorted(bbos.items())\n    ]\n    holding_lines = (\n        [f\"  {h['symbol']}: {h['quantity']} shares @ avg cost {h['avg_cost']:.2f}\"\n         for h in holdings]\n        if holdings else [\"  None\"]\n    )\n    return (\n        f\"You are simulating clearing house member {member_id} making ONE trading decision.\\n\\n\"\n        f\"Member state:\\n\"\n        f\"  Available capital: EUR {capital:,.2f}\\n\"\n        f\"  Securities obligation remaining today: {obligation_remaining} more to trade\\n\"\n        f\"  Current holdings:\\n\" + \"\\n\".join(holding_lines) + \"\\n\\n\"\n        f\"Current market (Bid/Ask):\\n\" + \"\\n\".join(market_lines) + \"\\n\\n\"\n        f\"Rules:\\n\"\n        f\"- Do not spend more than your available capital\\n\"\n        f\"- Do not sell more shares than you hold\\n\"\n        f\"- If you have no holdings, you must BUY\\n\"\n        f\"- Choose a realistic price close to the BBO mid-price\\n\"\n        f\"- Quantity should be between 10 and 200\\n\\n\"\n        f\"Respond ONLY with valid JSON, no other text:\\n\"\n        f'Example: {{\"symbol\": \"ALPHA\", \"side\": \"BUY\", \"quantity\": 50, \"price\": 5.65}}'\n    )\n\n\ndef gen_decision(capital: float, holdings: list, bbos: dict) -> dict:\n    \"\"\"Generate a rule-valid trading decision for the given state.\"\"\"\n    holdings_value = sum(\n        h[\"quantity\"] * bbos.get(h[\"symbol\"], {}).get(\"mid\", h[\"avg_cost\"])\n        for h in holdings\n    )\n    net_worth = capital + holdings_value\n    holdings_ratio = holdings_value / net_worth if net_worth > 0 else 0\n\n    if not holdings:\n        side = \"BUY\"\n    elif holdings_ratio > 0.6:\n        side = random.choices([\"SELL\", \"BUY\"], weights=[0.7, 0.3])[0]\n    else:\n        side = random.choices([\"BUY\", \"SELL\"], weights=[0.55, 0.45])[0]\n\n    if side == \"BUY\":\n        affordable = [sym for sym, bbo in bbos.items() if 10 * bbo[\"best_ask\"] <= capital]\n        if not affordable:\n            sym = min(bbos, key=lambda s: bbos[s][\"best_ask\"])\n        else:\n            held_syms = [h[\"symbol\"] for h in holdings]\n            weights = [3 if s in held_syms else 1 for s in affordable]\n            sym = random.choices(affordable, weights=weights)[0]\n        ask = bbos[sym][\"best_ask\"]\n        max_qty = min(200, int(capital / ask))\n        qty = random.randint(10, max(10, max_qty))\n        price = round(bbos[sym][\"mid\"] + random.uniform(-0.05, 0.05), 2)\n        price = max(bbos[sym][\"best_bid\"], min(price, ask))\n        return {\"symbol\": sym, \"side\": \"BUY\", \"quantity\": qty, \"price\": round(price, 2)}\n    else:\n        h = random.choice(holdings)\n        sym = h[\"symbol\"]\n        bbo = bbos[sym]\n        qty = random.randint(10, min(200, h[\"quantity\"]))\n        price = round(bbo[\"mid\"] + random.uniform(-0.05, 0.05), 2)\n        price = max(bbo[\"best_bid\"] - 0.05, min(price, bbo[\"best_ask\"]))\n        return {\"symbol\": sym, \"side\": \"SELL\", \"quantity\": qty, \"price\": round(price, 2)}\n\n\ndef generate_dataset(n: int) -> list:\n    examples = []\n    member_ids = [f\"USR{i:02d}\" for i in range(1, 11)]\n    scenarios = [\n        ((80_000, 100_000), (5, 10), \"fresh_member\"),\n        ((50_000, 80_000),  (0, 5),  \"active_member\"),\n        ((20_000, 50_000),  (0, 2),  \"low_capital\"),\n        ((5_000,  20_000),  (0, 10), \"very_low_capital\"),\n        ((90_000, 100_000), (10, 10),\"start_of_day\"),\n    ]\n    for _ in range(n):\n        cap_range, obl_range, _ = random.choice(scenarios)\n        capital    = round(random.uniform(*cap_range), 2)\n        obligation = random.randint(*obl_range)\n        member_id  = random.choice(member_ids)\n        bbos       = {s[\"symbol\"]: gen_bbo(s[\"base\"]) for s in SECURITIES}\n        holdings   = gen_holdings(bbos)\n        holdings_cost = sum(h[\"quantity\"] * h[\"avg_cost\"] for h in holdings)\n        if holdings_cost > STARTING_CAPITAL - capital:\n            scale = (STARTING_CAPITAL - capital) / max(holdings_cost, 1)\n            for h in holdings:\n                h[\"quantity\"] = max(10, int(h[\"quantity\"] * scale))\n        prompt   = build_prompt(member_id, capital, holdings, obligation, bbos)\n        decision = gen_decision(capital, holdings, bbos)\n        examples.append({\"prompt\": prompt, \"completion\": json.dumps(decision)})\n    return examples\n\n\nprint(f\"Generating {DATASET_SIZE} training examples...\")\nraw_data = generate_dataset(DATASET_SIZE)\nprint(f\"Done. Example:\")\nprint(\"PROMPT:\\n\", raw_data[0][\"prompt\"])\nprint(\"\\nCOMPLETION:\", raw_data[0][\"completion\"])"
   },
   {
    "cell_type": "code",
@@ -478,83 +309,7 @@
    "id": "inference-test",
    "metadata": {},
    "outputs": [],
-   "source": [
-    "import re\n",
-    "from transformers import pipeline\n",
-    "\n",
-    "pipe = pipeline(\n",
-    "    \"text-generation\",\n",
-    "    model=merged_model,\n",
-    "    tokenizer=tokenizer,\n",
-    "    device_map=\"auto\",\n",
-    ")\n",
-    "\n",
-    "# Test scenarios\n",
-    "test_cases = [\n",
-    "    {\n",
-    "        \"desc\": \"New member, no holdings, must trade\",\n",
-    "        \"capital\": 100_000.0,\n",
-    "        \"holdings\": [],\n",
-    "        \"obligation\": 10,\n",
-    "    },\n",
-    "    {\n",
-    "        \"desc\": \"Experienced member with holdings, low obligation\",\n",
-    "        \"capital\": 65_000.0,\n",
-    "        \"holdings\": [\n",
-    "            {\"symbol\": \"ALPHA\", \"quantity\": 300, \"avg_cost\": 5.90},\n",
-    "            {\"symbol\": \"OPAP\",  \"quantity\": 150, \"avg_cost\": 14.20},\n",
-    "        ],\n",
-    "        \"obligation\": 2,\n",
-    "    },\n",
-    "    {\n",
-    "        \"desc\": \"Low capital, large holdings\",\n",
-    "        \"capital\": 8_000.0,\n",
-    "        \"holdings\": [\n",
-    "            {\"symbol\": \"PEIR\",  \"quantity\": 500, \"avg_cost\": 8.10},\n",
-    "            {\"symbol\": \"MYTIL\", \"quantity\": 200, \"avg_cost\": 9.50},\n",
-    "        ],\n",
-    "        \"obligation\": 5,\n",
-    "    },\n",
-    "]\n",
-    "\n",
-    "test_bbos = {s[\"symbol\"]: gen_bbo(s[\"base\"]) for s in SECURITIES}\n",
-    "\n",
-    "print(\"=\" * 70)\n",
-    "for tc in test_cases:\n",
-    "    print(f\"\\nSCENARIO: {tc['desc']}\")\n",
-    "    prompt = build_prompt(\n",
-    "        \"USR01\", tc[\"capital\"], tc[\"holdings\"], tc[\"obligation\"], test_bbos\n",
-    "    )\n",
-    "    messages = [\n",
-    "        {\"role\": \"system\",\"content\": SYSTEM_PROMPT},\n",
-    "        {\"role\": \"user\",  \"content\": prompt},\n",
-    "    ]\n",
-    "    output = pipe(\n",
-    "        messages,\n",
-    "        max_new_tokens=60,\n",
-    "        temperature=0.3,\n",
-    "        do_sample=True,\n",
-    "        pad_token_id=tokenizer.eos_token_id,\n",
-    "    )\n",
-    "    response = output[0][\"generated_text\"][-1][\"content\"].strip()\n",
-    "    print(f\"RESPONSE: {response}\")\n",
-    "\n",
-    "    # Validate JSON\n",
-    "    try:\n",
-    "        m = re.search(r\"\\{[^}]+\\}\", response)\n",
-    "        if m:\n",
-    "            d = json.loads(m.group())\n",
-    "            assert d[\"side\"] in (\"BUY\", \"SELL\")\n",
-    "            assert d[\"symbol\"] in [s[\"symbol\"] for s in SECURITIES]\n",
-    "            assert d[\"quantity\"] > 0\n",
-    "            assert d[\"price\"] > 0\n",
-    "            print(f\"✓ Valid JSON: {d}\")\n",
-    "        else:\n",
-    "            print(\"✗ No JSON found in response\")\n",
-    "    except Exception as e:\n",
-    "        print(f\"✗ Invalid: {e}\")\n",
-    "    print(\"-\" * 70)"
-   ]
+   "source": "import re\nfrom transformers import pipeline\n\npipe = pipeline(\n    \"text-generation\",\n    model=merged_model,\n    tokenizer=tokenizer,\n    device_map=\"auto\",\n)\n\ntest_cases = [\n    {\n        \"desc\": \"New member, no holdings, must trade\",\n        \"capital\": 100_000.0,\n        \"holdings\": [],\n        \"obligation\": 10,\n    },\n    {\n        \"desc\": \"Experienced member with holdings, low obligation\",\n        \"capital\": 65_000.0,\n        \"holdings\": [\n            {\"symbol\": \"ALPHA\", \"quantity\": 300, \"avg_cost\": 5.60},\n            {\"symbol\": \"QUEST\", \"quantity\": 150, \"avg_cost\": 13.20},\n        ],\n        \"obligation\": 2,\n    },\n    {\n        \"desc\": \"Low capital, large holdings\",\n        \"capital\": 8_000.0,\n        \"holdings\": [\n            {\"symbol\": \"PEIR\",  \"quantity\": 500, \"avg_cost\": 8.30},\n            {\"symbol\": \"NBG\",   \"quantity\": 200, \"avg_cost\": 7.95},\n        ],\n        \"obligation\": 5,\n    },\n]\n\ntest_bbos = {s[\"symbol\"]: gen_bbo(s[\"base\"]) for s in SECURITIES}\n\nprint(\"=\" * 70)\nfor tc in test_cases:\n    print(f\"\\nSCENARIO: {tc['desc']}\")\n    prompt = build_prompt(\"USR01\", tc[\"capital\"], tc[\"holdings\"], tc[\"obligation\"], test_bbos)\n    messages = [\n        {\"role\": \"system\", \"content\": SYSTEM_PROMPT},\n        {\"role\": \"user\",   \"content\": prompt},\n    ]\n    output = pipe(\n        messages,\n        max_new_tokens=60,\n        temperature=0.3,\n        do_sample=True,\n        pad_token_id=tokenizer.eos_token_id,\n    )\n    response = output[0][\"generated_text\"][-1][\"content\"].strip()\n    print(f\"RESPONSE: {response}\")\n    try:\n        m = re.search(r\"\\{[^}]+\\}\", response)\n        if m:\n            d = json.loads(m.group())\n            assert d[\"side\"] in (\"BUY\", \"SELL\")\n            assert d[\"symbol\"] in [s[\"symbol\"] for s in SECURITIES]\n            assert d[\"quantity\"] > 0\n            assert d[\"price\"] > 0\n            print(f\"✓ Valid JSON: {d}\")\n        else:\n            print(\"✗ No JSON found in response\")\n    except Exception as e:\n        print(f\"✗ Invalid: {e}\")\n    print(\"-\" * 70)"
   },
   {
    "cell_type": "markdown",