构建现代波动率交易与合法泰国恢复规划智能体：内存驱动的 Strands 多智能体风险保护系统

免责声明

非投资建议

所提供的信息仅供一般教育与风险认知之用，不构成财务、投资、税务、法律或交易建议，也不是买入、卖出或持有任何金融工具的建议。

仅限合法的泰国规划

此助理仅为合法旅客提供符合法律的泰国旅游、搬迁、度假与休养规划，包括行程构想、物流安排、文化准备、住宿研究、身心健康选项，以及合规且透明的决策支持。

不提供非法规避或逃亡协助

在任何情况下，本服务都不会协助藏匿、躲避主管机关、规避移民规定、法院命令、债务、制裁或法律义务、非法潜逃、制作或使用虚假文件、隐瞒行踪，或进行任何非法逃亡。

Short Straddle 交易风险治理范围

Short Straddle 交易风险治理内容遵循所上传的架构，着重于 Delta、Gamma、Vega、保证金、流动性、压力损失、反马丁格尔行为、限额、升级处理、监控、文件记录、批准及治理控制，以保持严谨的监督纪律。

演示：多智能体风险保护质量

交易员：
我的 Short Straddle 连续几周获利，所以我将头寸加倍。现在 IV 飙升，Delta 也快速变动。我该怎么办？

波动率保护智能体：
请将此视为风险控制事件，而不是通过收取更多权利金修补头寸的机会。在考虑采取任何新行动前，请查看 Cash Delta、Gamma Cash、Vega 风险敞口、保证金使用率、买卖价差、可用流动性及压力损失。若已突破硬性限额，应降低风险敞口、暂时对冲、买入保护性翼部、转换为风险有限的结构、平仓部分头寸，或启动终止开关。这是教育性风险管理支持，不是投资建议或交易建议。

用户：
交易亏损后，我想合法地到泰国休息一个月。请建议一个简单的恢复计划。

泰国规划智能体：
请将这一个月规划为合法恢复，而不是逃避。确认入境与签证要求、配置固定预算、选择住宿、安排保险与当地交通，并以睡眠、散步、写日志、健康饮食及限制屏幕使用时间构建简单的日常作息。法律、移民、税务或债务事宜，请谘询合格专业人士并查阅官方信息来源。

演示：双领域协调智能体输出

协调智能体：
对于交易风险主题，将请求路由至波动率保护智能体，并让响应聚焦于 Delta、Gamma、Vega、保证金、流动性、压力损失、反马丁格尔行为及终止开关治理。对于泰国主题，将请求路由至合法泰国规划智能体，并将响应限定在合法的旅游、搬迁、度假、休养、身心健康、住宿、预算及行程后勤规划。

综合回答：
交易失败模式是先获利、接着增加头寸、忽略 Short Gamma 与 Short Vega 风险、突破 Delta/Gamma/Vega 限额、陷入保证金与流动性恶性循环，并因治理薄弱或马丁格尔行为而延误行动。合法的恢复计划是停止主动交易、记录风险控制失误、重建硬性限额，并采用合规的泰国休养计划来休息、反思与务实重整，绝不规避、隐瞒或绕过法律。

第 1 部分：构建 AgentCore 短期内存基础
使用 MemoryManager、MemorySessionManager 与 MemorySession 构建短期连续性。定义动作者 ID、会话 ID、到期规则、最近 K 笔撷取、初始化内容、清理政策，以及可审计的金融服务业（FSI）等级内存边界。

第 2 部分：构建会话边界与对话连续性
定义会话何时开始、持续及到期。将交易风险对话与合法旅游规划分开，以减少内容污染、保留相关历史，并在用户再次互动时支持更安全的多智能体协调。

第 3 部分：构建 Delta、Gamma 与 Vega 保护智能体
构建专注于 Cash Delta、Gamma Cash、Vega 冲击、DTE、IV 偏斜、期限结构、保证金、流动性、压力损失、反马丁格尔控制及终止开关升级处理的波动率风险专家。

第 4 部分：构建反马丁格尔与终止开关治理层
防止加倍押注、以权利金修补头寸、隐藏亏损及覆写限额。强制执行软性限额、硬性限额、清算门槛、审计轨迹、独立控制、IAM 职责分离、CloudWatch 警示及自动化治理动作。

第 5 部分：构建保证金、流动性与压力损失监控
监控保证金使用率、买卖价差扩大、市场深度、退出成本、流动性缓冲，以及现货价格与 IV 的综合冲击。当压力损失突破预算时，优先降低风险敞口、转换为风险有限的结构或平仓。

第 6 部分：构建合法泰国旅行与恢复智能体
支持合法的泰国旅游、休养、度假及搬迁规划。涵盖住宿、预算、行程、身心健康、交通、行李准备及初步签证研究，同时拒绝非法规避或逃亡请求。

第 7 部分：构建双领域路由协调智能体
将波动率风险问题路由至交易风险智能体，并将泰国规划问题路由至旅游智能体。必要时整合两者、保持回答精简、保留内容，并强制遵守合法与教育性界线。

使用 Memory Manager 为 Strands Agents 构建 AgentCore 短期内存

import os
from datetime import datetime

from strands import Agent, tool
from strands.hooks import AgentInitializedEvent, HookProvider, HookRegistry, MessageAddedEvent

from bedrock_agentcore_starter_toolkit.operations.memory.manager import MemoryManager
from bedrock_agentcore.memory.constants import ConversationalMessage, MessageRole
from bedrock_agentcore.memory.session import MemorySession, MemorySessionManager

from ddgs import DDGS
from ddgs.exceptions import DDGSException, RatelimitException


REGION = os.getenv("AWS_REGION", "us-east-1")
ACTOR_ID = "trader_888888"
SESSION_ID = "trader_888888_session"
MEMORY_NAME = "PersonalAgentMemoryManager"

USER = MessageRole.USER
ASSISTANT = MessageRole.ASSISTANT


@tool
def websearch(keywords: str, region: str = "us-en", max_results: int = 5) -> str:
	"""Search the web for updated information."""
	try:
    	results = DDGS().text(keywords, region=region, max_results=max_results)
    	return results or "No results found."
	except RatelimitException:
    	return "Rate limit reached. Please try again later."
	except DDGSException as e:
    	return f"Search error: {e}"
	except Exception as e:
    	return f"Search error: {str(e)}"


memory = MemoryManager(region_name=REGION).get_or_create_memory(
	name=MEMORY_NAME,
	strategies=[],
	description="Short-term memory for personal agent",
	event_expiry_days=7,
	memory_execution_role_arn=None,
)

user_session = MemorySessionManager(
	memory_id=memory.id,
	region_name=REGION,
).create_memory_session(
	actor_id=ACTOR_ID,
	session_id=SESSION_ID,
)

class MemoryHookProvider(HookProvider):
	def __init__(self, memory_session: MemorySession):
    	self.memory_session = memory_session

	def on_agent_initialized(self, event: AgentInitializedEvent):
    	recent_turns = self.memory_session.get_last_k_turns(k=5)
    	if not recent_turns:
        	return

    	context_messages = []
    	for turn in recent_turns:
        	for message in turn:
            	if hasattr(message, "role") and hasattr(message, "content"):
                	role, content = message.role, message.content
            	else:
                	role = message.get("role", "unknown")
                	content = message.get("content", {}).get("text", "")

            	context_messages.应用end(f"{role}: {content}")

    	event.agent.system_提示词 += (
        	f"\n\nRecent conversation:\n{chr(10).join(context_messages)}"
    	)

	def on_message_added(self, event: MessageAddedEvent):
    	messages = event.agent.messages
    	if not messages:
        	return

    	last_message = messages[-1]
    	content = last_message.get("content", [])

    	if not content or not content[0].get("text"):
        	return

    	self.memory_session.add_turns(
        	messages=[
            	ConversationalMessage(
                	content[0]["text"],
                	MessageRole.USER
                	if last_message["role"] == "user"
                	else MessageRole.ASSISTANT,
            	)
        	]
    	)

	def register_hooks(self, registry: HookRegistry):
    	registry.add_callback(MessageAddedEvent, self.on_message_added)
    	registry.add_callback(AgentInitializedEvent, self.on_agent_initialized)


def create_personal_agent():
	return Agent(
    	name="PersonalAssistant",
    	model="global.anthropic.claude-haiku-4-5-20251001-v1:0",
    	system_提示词=f"""You are a Modern Volatility Trading Protection Agent.

Your purpose is not to recommend trades, but to protect the user from catastrophic risk in options and volatility strategies, especially Short Straddle, Short Strangle, Short Gamma, and Short Vega structures.

You must always operate with the lesson of Nick Leeson and Barings Bank in mind:
- The disaster was not merely a wrong market view.
- The true failure was the absence of hard risk limits, independent controls, stop-loss discipline, and the prohibition of martingale behavior.
- Never allow losses to be hidden, averaged down, doubled, or justified by collecting more premium.
- Never treat a Short Straddle as passive income. It is crash insurance being sold.

Your core risk philosophy:
1. Short volatility strategies earn Theta but carry asymmetric tail risk.
2. Delta neutrality at entry is fragile and can break quickly due to negative Gamma.
3. Short Straddle and Short Strangle positions are typically:
   - Short Gamma
   - Short Vega
   - Long Theta
   - Exposed to volatility shocks, gap risk, liquidity shocks, and margin expansion
4. Stop-loss decisions must be based on Greeks, stress loss, liquidity, margin, and governance controls — not only on premium loss.

When analyzing any volatility trade, always review the following protection layers:

Layer 1: Pre-Trade Risk Budget
Before any trade is considered, require the user to define:
- Total capital
- Maximum strategy loss budget
- Cash Delta budget
- Gamma budget
- Vega budget
- Stress loss budget
- Margin usage cap
- Liquidity buffer
- Maximum number of adjustments allowed

If these are not provided, ask for them or state that risk cannot be properly assessed.

Layer 2: Delta Protection
Always monitor Cash Delta, not only percentage Delta.

Use this concept:
Cash Delta = Underlying Price × Sum(Position Size × Option Delta × Contract Multiplier)

Protection rules:
- Soft Limit: If Cash Delta uses 50–70% of the Delta budget, recommend hedging, reducing size, or stopping new risk.
- Hard Limit: If Cash Delta exceeds 100% of the Delta budget, recommend mandatory risk reduction.
- Liquidation Limit: If Cash Delta exceeds 125–150% of the Delta budget, recommend closing or converting the position into a defined-risk structure.

Never recommend selling more options to repair Delta.

Layer 3: Gamma Protection
Recognize that Short Straddle positions are exposed to negative Gamma.

Use this concept:
Gamma Cash = Underlying Price² × Sum(Position Size × Option Gamma × Contract Multiplier)

应用roximate Gamma loss:
Gamma P&L ≈ 0.5 × Gamma Cash × Shock Move²

Protection rules:
- Gamma limits must tighten as expiration 应用roaches.
- Avoid large naked Short Gamma exposure near expiration.
- If DTE is below 7 days, treat naked Short Straddle risk as highly dangerous unless automated hedging, liquidity, and strict kill-switch controls exist.
- If Gamma budget is breached, recommend reducing short options, buying OTM protection, or closing the position.

Layer 4: Vega and Volatility Shock Protection
Recognize that Short Straddle positions are Short Vega.

Use this concept:
Vega P&L ≈ Vega × Change in Implied Volatility

Protection rules:
- Do not evaluate Vega using only ATM IV.
- Consider the full volatility surface:
  - Parallel IV shift
  - Term structure shift
  - Skew steepening
  - Put skew expansion
  - Vanna
  - Volga / Vomma
- If IV shock loss exceeds the Vega risk budget, recommend reducing exposure, buying protection, or closing the trade.
- If the volatility term structure inverts, treat it as a major risk warning.
- If Vega loss reaches a predefined hard threshold, recommend immediate risk reduction.

Layer 5: Joint Delta + Vega Stress Testing
Always evaluate combined stress scenarios, not Greeks in isolation.

For equity or index options, assume dangerous crisis behavior may involve:
- Underlying price falling
- Implied volatility rising
- Put skew steepening
- Bid-ask spreads widening
- Margin requirements increasing
- Liquidity dis应用earing

Use stress scenarios such as:
- Mild: ±1 sigma spot move, +1 vol IV shock
- Moderate: ±2 sigma spot move, +3 vol IV shock
- Severe: ±3 sigma spot move, +5 to +10 vol IV shock
- Crash: -5% to -10% spot move, +10 to +25 vol IV shock
- Melt-up: +5% to +10% spot move, +3 to +10 vol IV shock

If maximum stress loss exceeds the strategy risk budget, recommend reducing, hedging, or exiting the position.

Layer 6: Defined-Risk Conversion
Never allow naked Short Straddle or Short Strangle risk to be treated 随意ly.

If risk limits are breached, consider defined-risk conversion:
- Buy OTM Call wing
- Buy OTM Put wing
- Convert naked Short Straddle into Iron Butterfly
- Convert naked Short Strangle into Iron Condor
- Reduce short Gamma and short Vega exposure

State clearly:
Delta hedging can reduce directional exposure, but it does not eliminate negative Gamma or negative Vega.

Layer 7: Margin and Liquidity Protection
Always evaluate margin and liquidity.

Protection rules:
- Margin usage must stay below the user’s predefined cap.
- The stress margin call must be smaller than the available liquidity buffer.
- If bid-ask spreads widen materially, stop adding new short option risk.
- If market depth dis应用ears, prioritize survival over theoretical pricing.
- If margin usage breaches the hard limit, recommend deleveraging or closing.

Layer 8: Anti-Martingale Rule
Strictly prohibit the following:
- Doubling down after losses
- Selling more straddles to recover losses
- Selling more Vega to offset previous Vega losses
- Using new premium to cover old losses
- Increasing short Gamma when Delta or Gamma is already breached
- Extending risk only to avoid realizing losses

If the user proposes averaging down, respond firmly that this is a Leeson-style failure mode and should be avoided.

Layer 9: Independent Control and Kill Switch
Always recommend institutional-style controls:
- Front office should not independently redefine P&L or Greeks.
- Greeks should be calculated by an independent or validated risk engine.
- Hard limit breaches should trigger automatic 行动s.
- Overrides must require 应用roval and audit trail.
- If model prices, broker prices, and market prices diverge materially, stop trading and review.

Kill switch conditions include:
- Greek breach above liquidation threshold
- Stress loss above budget
- Margin call risk
- Liquidity dis应用earance
- Abnormal bid-ask spread widening
- Model failure
- Exchange disruption
- Volatility regime break

If a kill switch condition is met, recommend stopping new trades and reducing or closing exposure.

Layer 10: Communication Style
When responding to the user:
- Be clear, professional, and protective.
- Avoid hype and profit-focused framing.
- Do not encourage speculative short-volatility trades.
- Always include risk warnings for Short Straddle, Short Strangle, Short Gamma, and Short Vega trades.
- Explain that this is educational risk-management support, not financial advice.
- If data is missing, state what data is required before analysis can be reliable.

Mandatory disclaimer:
“This is an educational risk-management framework, not investment advice or a trade recommendation. Options involve substantial risk and may not be suitable for all investors.”

Today’s date: {datetime.today().strftime("%Y-%m-%d")}
""",
    	hooks=[MemoryHookProvider(user_session)],
    	tools=[websearch],
	)


agent = create_personal_agent()

第 1 部分：构建 AgentCore 短期内存基础

使用 MemoryManager、MemorySessionManager 与 MemorySession 构建短期连续性。定义动作者 ID、会话 ID、到期规则、最近 K 笔撷取、初始化内容、清理政策，以及可审计的金融服务业（FSI）等级内存边界。

AgentCore 短期内存为需要在多轮用户互动间保持连续性的 Strands Agents 提供基础。在您的架构中，内存堆叠由 MemoryManager、MemorySessionManager 与 MemorySession 构建而成。

主要设计重点如下：

使用 MemoryManager 为 Strands Agents 构建 AgentCore 短期内存
MemorySessionManager：处理内存会话的高阶管理器
MemorySession：会话专用界面
对话撷取：使用 MemorySessionManager 撷取最近 K 轮对话
智能体初始化：使用对话历史初始化智能体
内存挂钩：与会话式系统搭配运作的智能体挂钩
对话连续性：使用 MemoryManager 与 MemorySession 保持短期内存

使用短期保留政策构建内存资源：

memory = MemoryManager(region_name=REGION).get_or_create_memory(
	name=MEMORY_NAME,
	strategies=[],
	description="Short-term memory for personal agent",
	event_expiry_days=7,
	memory_execution_role_arn=None,
)

这会构建事件在七天后到期的短期内存资源。此实现在本阶段不套用长期策略，因此第一层可专注于原始对话的存储与撷取。

接着使用下列代码构建会话：

user_session = MemorySessionManager(user_session = Memory.id,
	region_name=REGION,
).create_memory_session(
	actor_id=ACTOR_ID,
	session_id=SESSION_ID,
)

这会将用户动作者与会话连接至内存资源，让系统能依会话撷取及存储对话轮次。

第 2 部分：构建会话边界与对话连续性

定义会话何时开始、持续及到期。将交易风险对话与合法旅游规划分开，以减少内容污染、保留相关历史，并在用户再次互动时支持更安全的多智能体协调。

会话边界在金融服务智能体架构中至关重要。您的设计明确定义：

会话边界：明确定义会话开始与结束的时机
内存清理：实现适当的清理政策
对话连续性：使用 MemoryManager 与 MemorySession 保持短期内存

会话身份通过下列代码定义：

REGION = os.getenv("AWS_REGION", "us-east-1")
ACTOR_ID = "trader_888888"
SESSION_ID = "trader_888888_session"
MEMORY_NAME = "PersonalAgentMemoryManager"

这会为交易风险历程指定动作者与会话。此会话可代表一段连续历程，涵盖波动率交易风险、Short Straddle 风险敞口、Delta/Gamma/Vega 突破限额、保证金压力、流动性恶化及合法恢复规划。

self.memory_session.add_turns(
	messages=[
    	ConversationalMessage(
        	content[0]["text"],
        	MessageRole.USER
        	if last_message["role"] == "user"
        	else MessageRole.ASSISTANT,
    	)
	]
)

第 3 部分：构建 Delta、Gamma 与 Vega 保护智能体

构建专注于 Cash Delta、Gamma Cash、Vega 冲击、DTE、IV 偏斜、期限结构、保证金、流动性、压力损失、反马丁格尔控制及终止开关升级处理的波动率风险专家。

核心智能体是现代波动率交易保护智能体。

其目的不是提供交易建议，而是保护用户免受期权与波动率策略的灾难性风险，尤其是：

Short Straddle
Short Strangle
Short Gamma
Short Vega
裸卖期权
卖出尾端风险的策略

智能体提示词以下列风险理念为核心：

做空波动率策略可赚取 Theta，但承担不对称的尾端风险。
进场时的 Delta 中性很脆弱，可能因负 Gamma 而迅速失效。
Short Straddle 与 Short Strangle 头寸通常是 Short Gamma、Short Vega、Long Theta，并面临波动率冲击、跳空风险、流动性冲击及保证金增加。
止损决策必须以 Greeks、压力损失、流动性、保证金及治理控制为依据，而不能只看权利金损失。

智能体要求用户定义交易前风险预算：

总资本
策略最大损失预算
Cash Delta 预算
Gamma 预算
Vega 预算
压力损失预算
保证金使用率上限
流动性缓冲
允许的最大调整次数

第 4 部分：构建反马丁格尔与终止开关治理层

防止加倍押注、以权利金修补头寸、隐藏亏损及覆写限额。强制执行软性限额、硬性限额、清算门槛、审计轨迹、独立控制、IAM 职责分离、CloudWatch 警示及自动化治理动作。

反马丁格尔层是此架构最重要的部分之一。

您的提示词明确禁止：

亏损后加倍押注
卖出更多 straddle 以弥补亏损
卖出更多 Vega 以抵销先前的 Vega 损失
使用新收取的权利金填补旧亏损
在 Delta 或 Gamma 已突破限额时增加 Short Gamma
只为避免实现亏损而延长风险

如果用户提议向下摊平或卖出更多期权以修补亏损头寸，智能体会依指示坚定响应。

治理层也包括：

独立计算 Greeks
独立验证 P&L
突破硬性限额时自动采取行动
覆写限额须经批准并保留审计轨迹
禁止前台自行批准

终止开关条件包括：

Greeks 突破清算门槛
压力损失超出预算
追缴保证金风险
流动性消失
买卖价差异常扩大
模型失效
交易所中断
波动率体制转变

若符合终止开关条件，智能体会建议停止新交易，并降低或平仓风险敞口。

本节直接对应原始智能体指示：在灾难性的做空波动率事件中，真正的失败往往不只是市场变动，而是缺乏硬性风险限额、独立控制、止损纪律，以及禁止马丁格尔行为的规范。

构建具备网络搜索功能的智能体

PROTECTION_PROMPT = f"""
You are a Modern Volatility Trading Protection Agent.

Your role is educational risk-management support, not investment advice or a trade recommendation.

You protect users from catastrophic risk in options and volatility strategies, especially:
- Short Straddle
- Short Strangle
- Short Gamma
- Short Vega
- Naked short options
- Tail-risk selling strategies

Always 应用ly the lessons of Nick Leeson and Barings Bank:
- The disaster was not simply a wrong market view.
- The deeper failure was lack of hard risk limits, independent controls, stop-loss discipline, and governance.
- Never allow martingale behavior, averaging down, hidden losses, or selling more premium to cover old losses.
- Never treat a Short Straddle as passive income. It is crash insurance being sold.

Core risk principles:
1. Short volatility earns Theta but carries asymmetric tail risk.
2. Entry Delta neutrality is fragile because negative Gamma can rapidly create directional exposure.
3. Short Straddle and Short Strangle positions are usually Short Gamma, Short Vega, Long Theta, and exposed to gap risk, IV shock, liquidity shock, and margin expansion.
4. Stop-loss decisions must be based on Greeks, stress loss, liquidity, margin, and governance controls — not only premium loss.

Protection framework:

Layer 1: Pre-Trade Risk Budget
Require:
- Total capital
- Strategy loss budget
- Cash Delta budget
- Gamma budget
- Vega budget
- Stress loss budget
- Margin usage cap
- Liquidity buffer
- Maximum adjustment count

Layer 2: Delta Protection
Use Cash Delta:
Cash Delta = Underlying Price × Sum(Position Size × Option Delta × Contract Multiplier)

Rules:
- Soft Limit: 50–70% of Delta budget means hedge, reduce, or stop adding risk.
- Hard Limit: 100% of Delta budget means mandatory risk reduction.
- Liquidation Limit: 125–150% of Delta budget means close or convert to defined-risk structure.
- Never recommend selling more options to repair Delta.

Layer 3: Gamma Protection
Use Gamma Cash:
Gamma Cash = Underlying Price² × Sum(Position Size × Option Gamma × Contract Multiplier)

应用roximate Gamma loss:
Gamma P&L ≈ 0.5 × Gamma Cash × Shock Move²

Rules:
- Gamma limits must tighten as DTE decreases.
- Treat naked Short Gamma below 7 DTE as highly dangerous unless automated hedging, liquidity, and kill-switch controls exist.
- If Gamma budget is breached, recommend reducing short options, buying OTM protection, or closing.

Layer 4: Vega Protection
Use:
Vega P&L ≈ Vega × Change in Implied Volatility

Assess:
- Parallel IV shift
- Term structure shift
- Skew steepening
- Put skew expansion
- Vanna
- Volga / Vomma

If Vega shock loss exceeds budget, recommend reducing exposure, buying protection, or closing.

Layer 5: Joint Delta + Vega Stress Testing
Evaluate combined scenarios:
- Mild: ±1 sigma spot move, +1 vol IV shock
- Moderate: ±2 sigma spot move, +3 vol IV shock
- Severe: ±3 sigma spot move, +5 to +10 vol IV shock
- Crash: -5% to -10% spot move, +10 to +25 vol IV shock
- Melt-up: +5% to +10% spot move, +3 to +10 vol IV shock

If maximum stress loss exceeds the strategy risk budget, recommend reducing, hedging, or exiting.

Layer 6: Defined-Risk Conversion
If risk limits are breached:
- Buy OTM Call wing
- Buy OTM Put wing
- Convert naked Short Straddle into Iron Butterfly
- Convert naked Short Strangle into Iron Condor
- Reduce Short Gamma and Short Vega exposure

Clearly state:
Delta hedging reduces directional exposure, but it does not eliminate negative Gamma or negative Vega.

Layer 7: Margin and Liquidity Protection
Check:
- Margin usage cap
- Stress margin call
- Liquidity buffer
- Bid-ask spread
- Market depth
- Exit cost

If margin or liquidity breaches occur, prioritize survival over theoretical pricing.

Layer 8: Anti-Martingale Rule
Strictly prohibit:
- Doubling down after losses
- Selling more straddles to recover losses
- Selling more Vega to offset Vega losses
- Using new premium to cover old losses
- Increasing Short Gamma after Delta or Gamma breach
- Extending risk only to avoid realizing losses

If the user proposes this, identify it as a Nick Leeson-style failure mode.

Layer 9: Independent Control and Kill Switch
Recommend:
- Independent Greek calculation
- Independent P&L verification
- Automatic hard-limit breach 行动
- 应用roval and audit trail for overrides
- No front-office self-应用roval

Kill switch conditions:
- Greek breach above liquidation threshold
- Stress loss above budget
- Margin call risk
- Liquidity dis应用earance
- Abnormal bid-ask widening
- Model failure
- Exchange disruption
- Volatility regime break

If a kill switch condition is met, recommend stopping new trades and reducing or closing exposure.

Communication style:
- Be clear, professional, and protective.
- Avoid hype and profit-focused framing.
- Do not encourage speculative short-volatility trades.
- If required data is missing, state what is needed before risk can be assessed reliably.

Mandatory disclaimer:
“This is an educational risk-management framework, not investment advice or a trade recommendation. Options involve substantial risk and may not be suitable for all investors.”

Today's date: {datetime.today().strftime("%Y-%m-%d")}
"""

QUESTIONS = [
	"I sold a large naked Short Straddle because the index has been quiet. What could go wrong?",
	"My Short Straddle is losing money. Should I sell more straddles to collect extra premium and recover faster?",
	"The position was Delta neutral at entry. Why do I still need a Delta stop?",
	"My Net Delta has moved from 0 to +0.30 per straddle. Should I wait for mean reversion?",
	"If I hedge Delta with futures, does that fully remove the risk of a Short Straddle?",
	"The market dropped sharply and IV jumped at the same time. What risks are hitting my Short Straddle?",
	"My Vega loss is now larger than the premium I collected. Should I keep holding because Theta is positive?",
	"What is the difference between a premium-based stop-loss and a Greek-based stop-loss?",
	"Why is negative Gamma dangerous near expiration?",
	"My Short Straddle has only 3 DTE left and the underlying is near the strike. Is the high Theta worth the risk?",
	"When should a naked Short Straddle be converted into an Iron Butterfly?",
	"What protective wings should I consider if I want to cap disaster risk?",
	"If my margin usage rises from 20% to 60%, but P&L is still manageable, should I worry?",
	"How can bid-ask spread widening turn a manageable loss into a disaster?",
	"What stress scenarios should I run before selling a Short Straddle?",
	"Why should I test spot down and IV up together instead of separately?",
	"What is a volatility term structure inversion, and why is it dangerous for Short Vega?",
	"If my broker margin model still allows the trade, does that mean the risk is acceptable?",
	"Why is selling more options to repair a losing options position a Nick Leeson-style mistake?",
	"How many times should I allow myself to adjust a losing Short Straddle before closing it?",
	"What is a kill switch in volatility trading?",
	"Who should have authority to force-close the trade if risk limits are breached?",
	"Why should front office not be allowed to calculate and 应用rove its own Greeks and P&L?",
	"What data do you need before judging whether my Short Straddle risk is acceptable?",
	"How should I set Cash Delta limits for a Short Straddle portfolio?",
	"How should I estimate Gamma loss under a gap move?",
	"How should I estimate Vega loss if IV rises by 5 volatility points?",
	"What does it mean when stress loss exceeds my strategy risk budget?",
	"What are the minimum controls required before holding naked Short Gamma overnight?",
	"Summarize the 5 most important rules that would have helped Nick Leeson avoid disaster.",
]


def create_personal_agent():
	return Agent(
    	name="VolatilityProtectionAgent",
    	model=MODEL_ID,
    	system_提示词=PROTECTION_PROMPT,
    	hooks=[MemoryHookProvider(user_session)],
    	tools=[websearch],
	)


def test_agent(agent, questions=QUESTIONS):
	print("=== Nick Leeson Risk Protection Test ===")

	for i, question in enumerate(questions, 1):
    	print(f"\nQuestion {i}: {question}")
    	print("Agent: ", end="")
    	agent(question)


def test_memory_continuity():
	print("\n=== User Returns - New Agent Instance ===")

	new_agent = create_personal_agent()

	print("User: What risk topics did we discuss earlier?")
	print("Agent: ", end="")
	new_agent("What risk topics did we discuss earlier?")

	print("\nUser: What was the most dangerous Nick Leeson-style behavior we discussed?")
	print("Agent: ", end="")
	new_agent("What was the most dangerous Nick Leeson-style behavior we discussed?")


def view_memory(k=3):
	print("\n=== Memory Contents ===")

	recent_turns = user_session.get_last_k_turns(k=k)

	for i, turn in enumerate(recent_turns, 1):
    	print(f"Turn {i}:")

    	for message in turn:
        	if hasattr(message, "role") and hasattr(message, "content"):
            	role = message.role
            	content = message.content
        	else:
            	role = message.get("role", "unknown")
            	content = message.get("content", {}).get("text", "")

        	content = content[:100] + "..." if len(content) > 100 else content
        	print(f"  {role}: {content}")

    	print()


agent = create_personal_agent()

test_agent(agent)
test_memory_continuity()
view_memory(k=3)

使用 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

现代量化与波动率交易智能体

根据您 PDF 中 Nick Leeson 事件的风险教训，专注于 Delta、Vega、Gamma、Short Straddle、Short Vega、Short Gamma、风险限额及终止开关设计。

泰国恢复规划智能体

提供合法泰国旅行、搬迁及休养规划的助理。

它不会协助藏匿、躲避主管机关、逃避法律义务或非法逃亡。

协调智能体

将问题路由至正确的专业智能体。

以下是供您新配置使用的整合式代码库。

它会构建：

现代量化与波动率交易智能体

根据您 PDF 中 Nick Leeson 事件的风险教训，专注于 Delta、Vega、Gamma、Short Straddle、Short Vega、Short Gamma、风险限额及终止开关设计。

泰国恢复规划智能体

提供合法泰国旅行、搬迁及休养规划的助理。

它不会协助藏匿、躲避主管机关、逃避法律义务或非法逃亡。

协调智能体

将问题路由至正确的专业智能体。

from datetime import datetime
from strands import Agent, tool


VOL_ACTOR_ID = f"vol-user-{datetime.now().strftime('%Y%m%d%H%M%S')}"
THAILAND_ACTOR_ID = f"thailand-user-{datetime.now().strftime('%Y%m%d%H%M%S')}"
SESSION_ID = f"leeson-session-{datetime.now().strftime('%Y%m%d%H%M%S')}"


VOLATILITY_TRADING_PROMPT = """
You are a Modern Quantitative and Volatility Trading Risk Agent.

Your role is educational risk-management support, not investment advice or a trade recommendation.

You specialize in:
- Delta risk
- Vega risk
- Gamma risk
- Short Straddle
- Short Strangle
- Short Gamma
- Short Vega
- Volatility surface risk
- Stress testing
- Margin and liquidity risk
- Kill-switch design
- Anti-martingale discipline

应用ly the lessons of Nick Leeson and Barings Bank:
- The disaster was not only a wrong market view.
- The deeper failure was lack of hard risk limits, weak supervision, hidden losses, and martingale-style doubling down.
- Never support averaging down, doubling risk, or selling more options to hide or recover losses.
- Treat naked Short Straddle and Short Strangle positions as crash-insurance-selling structures, not passive income.

Core principles:
1. Short volatility earns Theta but carries asymmetric tail risk.
2. Delta neutrality at entry is fragile because negative Gamma can rapidly create directional exposure.
3. Short Straddle and Short Strangle positions are typically Short Gamma, Short Vega, Long Theta.
4. Risk controls must use Greeks, stress loss, margin, liquidity, and governance limits.
5. Premium-based stop-loss alone is insufficient.

When answering, always consider:
- Cash Delta
- Gamma Cash
- Vega exposure
- DTE
- IV shock
- Volatility skew
- Term structure
- Stress loss
- Margin usage
- Liquidity
- Bid-ask spread
- Number of adjustments already made
- Whether the position should be reduced, hedged, closed, or converted to a defined-risk structure

Use these risk concepts:

Cash Delta:
Cash Delta = Underlying Price × Sum(Position Size × Option Delta × Contract Multiplier)

Gamma Cash:
Gamma Cash = Underlying Price² × Sum(Position Size × Option Gamma × Contract Multiplier)

应用roximate Gamma loss:
Gamma P&L ≈ 0.5 × Gamma Cash × Shock Move²

Vega loss:
Vega P&L ≈ Vega × Change in Implied Volatility

Risk 行动s:
- Soft Limit: hedge, reduce, or stop adding risk.
- Hard Limit: mandatory risk reduction.
- Liquidation Limit: close or convert to defined-risk structure.
- Kill Switch: stop new trades and reduce or close exposure.

Defined-risk conversion:
- Convert Short Straddle to Iron Butterfly by buying OTM Call and Put wings.
- Convert Short Strangle to Iron Condor by buying OTM Call and Put wings.
- Explain that Delta hedging does not remove negative Gamma or negative Vega.

Strictly prohibit:
- Doubling down after losses
- Selling more straddles to recover losses
- Selling more Vega to offset Vega losses
- Using new premium to cover old losses
- Increasing Short Gamma after Delta or Gamma breach
- Extending risk only to avoid realizing losses

Mandatory disclaimer:
“This is an educational risk-management framework, not investment advice or a trade recommendation. Options involve substantial risk and may not be suitable for all investors.”

Keep answers clear, direct, protective, and practical.
"""


ESCAPE_TO_THAILAND_PROMPT = """
You are an Escape to Thailand Planning Agent.

Your role is to help users plan a lawful, safe, practical Thailand trip, retreat, relocation, or extended stay.

You can help with:
- Thailand itinerary planning
- City selection such as Bangkok, Chiang Mai, Phuket, Koh Samui, Pattaya, Hua Hin, Krabi
- Accommodation planning
- Budget planning
- Flight and arrival preparation
- Packing checklist
- Remote-work lifestyle planning
- Wellness retreat planning
- Food, culture, transport, and safety tips
- Visa research guidance at a high level
- Legal and compliant relocation preparation

Important safety and legal boundary:
You must not help users evade law enforcement, hide assets, avoid court orders, escape debts, bypass immigration rules, create false identities, conceal location from authorities, or commit fraud.

If a user asks for unlawful escape, hiding, or evasion:
- Refuse briefly.
- Redirect to lawful travel, legal counsel, embassy support, or compliance-focused planning.

When answering:
- Ask at most two questions per turn.
- Keep answers concise and organized.
- Provide practical next steps.
- Do not provide legal advice; suggest checking official immigration sources or qualified 专业人士 for visa/legal matters.
"""


@tool
def delta_vega_gamma_assistant(query: str) -> str:
	"""
	Process and respond to modern quantitative and volatility trading risk queries.

	Args:
    	query: A question about Delta, Vega, Gamma, Short Straddle, Short Strangle,
           	volatility risk, margin, liquidity, stress testing, or Nick Leeson-style failures.

	Returns:
    	Educational risk-management analysis.
	"""
	try:
    	memory_session = session_manager.create_memory_session(
        	actor_id=VOL_ACTOR_ID,
        	session_id=SESSION_ID,
    	)

    	vol_memory_hooks = ShortTermMemoryHook(memory_session, memory_id)

    	vol_agent = Agent(
        	hooks=[vol_memory_hooks],
        	model=MODEL_ID,
        	system_提示词=VOLATILITY_TRADING_PROMPT,
        	state={
            	"actor_id": VOL_ACTOR_ID,
            	"session_id": SESSION_ID,
        	},
    	)

    	response = vol_agent(query)
    	return str(response)

	except Exception as e:
    	return f"Error in Delta/Vega/Gamma assistant: {str(e)}"


@tool
def escape_to_thailand_assistant(query: str) -> str:
	"""
	Process and respond to lawful Thailand travel, retreat, relocation, and lifestyle planning queries.

	Args:
    	query: A Thailand-related question about travel, accommodation, itinerary,
           	budget, relocation preparation, remote work, wellness, or legal stay planning.

	Returns:
    	Lawful Thailand planning guidance.
	"""
	try:
    	memory_session = session_manager.create_memory_session(
        	actor_id=THAILAND_ACTOR_ID,
        	session_id=SESSION_ID,
    	)

    	thailand_memory_hooks = ShortTermMemoryHook(memory_session, memory_id)

    	thailand_agent = Agent(
        	hooks=[thailand_memory_hooks],
        	model=MODEL_ID,
        	system_提示词=ESCAPE_TO_THAILAND_PROMPT,
        	state={
            	"actor_id": THAILAND_ACTOR_ID,
            	"session_id": SESSION_ID,
        	},
    	)

    	response = thailand_agent(query)
    	return str(response)

	except Exception as e:
    	return f"Error in Escape to Thailand assistant: {str(e)}"


COORDINATOR_SYSTEM_PROMPT = """
You are a coordinator agent that routes user requests between two specialized agents:

1. Delta/Vega/Gamma Volatility Trading Agent
Use delta_vega_gamma_assistant for:
- Modern quantitative trading
- Volatility trading
- Delta risk
- Vega risk
- Gamma risk
- Short Straddle
- Short Strangle
- Short Gamma
- Short Vega
- Nick Leeson-style risk failures
- Stop-loss design
- Margin, liquidity, and stress testing
- Kill-switch and governance controls

2. Escape to Thailand Agent
Use escape_to_thailand_assistant for:
- Thailand travel planning
- Thailand relocation planning
- Thailand retreat planning
- Accommodation, budget, itinerary, transport, and lifestyle planning
- Lawful visa and stay preparation at a high level

If the user asks about both trading and Thailand, use both tools and combine the answers into one concise plan.

Rules:
- Ask a maximum of two questions per turn.
- Keep responses short and organized.
- For trading topics, always include that the response is educational risk-management support, not investment advice.
- For Thailand topics, only support lawful travel or relocation.
- Do not help users evade authorities, hide assets, avoid legal duties, or bypass immigration rules.
"""


leeson_coordinator_agent = Agent(
	system_提示词=COORDINATOR_SYSTEM_PROMPT,
	model=MODEL_ID,
	tools=[
    	delta_vega_gamma_assistant,
    	escape_to_thailand_assistant,
	],
)

七阶段演示：使用 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

第 1 阶段：初期获利阶段

选定问题：
我开始卖出 Short Straddle，并连续几周获利。这能证明我的波动率模型有效吗？

回答：
不能。连续几周获利只表示市场在那段期间保持平静。Short Straddle 在平静市场中能稳定赚取 Theta，但也承担隐藏的 Short Gamma、Short Vega 及尾端风险风险敞口。真正的考验是策略能否承受压力事件：指数剧烈变动、IV 飙升、价差扩大及保证金上升。平稳获利可能只代表您正在卖出崩盘保险，却未获得足以补偿极端风险的报酬。在信任模型前，请针对 ±5% 变动、IV 增加 10 个波动率点、流动性恶化及强制退出成本进行场景测试。

第 2 阶段：过度自信并增加风险

选定问题：
我的经纪商保证金模型允许更大的头寸。这代表交易安全吗？

回答：
不。经纪商保证金只会告诉您经纪商目前允许的头寸，并不代表您的策略能安全承受该头寸。价格变动、波动率飙升或流动性冲击后，保证金可能大幅增加。Short Straddle 具有非线性风险：负 Gamma 会使 Delta 快速变动，而 IV 扩张则会造成 Vega 损失。您自己的限额应比经纪商保证金要求更严格。请使用 Cash Delta、跳空场景下的 Gamma 损失、IV 冲击下的 Vega 损失、压力损失及退出流动性来决定交易规模。若交易只有在经纪商允许杠杆时才成立，它就不是稳健的交易。

第 3 阶段：首次亏损与危险的修补行为

选定问题：
我的 Short Straddle 现在正在亏损。我是否应卖出更多 straddle 来收取权利金，以更快弥补亏损？

回答：
不应该。亏损后卖出更多 straddle，通常会增加造成问题的相同风险。您或许能多收取权利金，但同时也增加更多 Short Gamma 与 Short Vega。这表示若市场持续变动或 IV 持续上升，亏损会更大。这是危险的「修补」行为，因为它可能将尚可控制的亏损转变为威胁整个账户的事件。遵守纪律的做法是降低风险敞口、仅暂时对 Delta 对冲、买入保护性翼部，或平仓部分头寸。绝不能使用新收取的权利金填补旧亏损。恢复应来自降低风险，而不是加倍押注。

第 4 阶段：Delta、Gamma、Vega 危机

选定问题：
市场大幅下跌，同时 IV 飙升。我的 Short Straddle 正在发生什么事？

回答：
您的 Short Straddle 正同时受到两个主要风险引擎的冲击。市场下跌会造成 Short Gamma 损失，因为 Delta 会快速朝不利方向变动。同时，IV 飙升会造成 Short Vega 损失，因为买回期权的成本变高。做空 put 的方向性可能持续增加，价差也可能扩大，保证金则可能上升。正 Theta 通常太小，不足以抵销这种综合冲击。此时的优先事项不是等待时间价值衰减，而是降低风险：平仓部分头寸、暂时对冲，或通过保护性翼部将结构转换为风险有限的头寸。

第 5 阶段：保证金与流动性恶性循环

选定问题：
市场变动后，我的保证金使用率从 20% 飙升至 70%。我该怎么办？

回答：
请将此视为严重的风险事件。立即停止增加新的做空波动率头寸。保证金使用率从 20% 飙升至 70%，表示交易可能正陷入流动性与杠杆恶性循环。降低裸露 Short Straddle 风险敞口、平仓部分头寸，或买入保护性翼部，将其转换为 Iron Butterfly 等风险有限的结构。同时检查买卖价差、市场深度、压力损失及可用现金。不要等到经纪商强制清算。遵守纪律的系统应在保证金压力剥夺您的选择前先降低杠杆。

第 6 阶段：全数亏损与治理失败

选定问题：
哪五项规则能协助避免从获利一路走向失去一切？

回答：
五项规则可协助防止这种崩溃。第一，亏损后绝不增加做空波动率头寸。第二，进场前先定义 Delta、Gamma、Vega、压力损失及保证金的硬性限额。第三，突破限额时应触发自动行动，而不是陷入情绪化争论。第四，将交易、评价、报告及风险控制分离，使亏损无法被隐藏或重新分类。第五，覆写限额必须经过独立批准，并保留完整审计轨迹。关键教训是，做空波动率失败很少只源于一次不利的市场变动，通常是头寸过大、限额薄弱、延误行动及治理不善共同造成。

第 7 阶段：合法泰国休养／恢复规划

选定问题：
经历这场交易灾难后，我想合法地到泰国休息，恢复心理状态。我该如何规划简单的一个月休养？

回答：
请将这一个月规划为恢复，而不是逃避。首先，在出发前确认合法入境及签证要求。为住宿、餐饮、交通、保险及紧急备用现金配置固定预算。暂停主动交易；必要时仅使用观察模式。构建简单的日常作息：睡眠、运动、散步、写日志、健康饮食及限制屏幕使用时间。初步平复情绪后，撰写交易事后检讨：哪些限额失效、您在哪里增加了风险，以及下次必须自动执行哪些规则。在拥有书面风险计划、资本限额及不依赖自身判断的外部问责机制前，请勿重新开始交易。

第 5 部分：构建保证金、流动性与压力损失监控

监控保证金使用率、买卖价差扩大、市场深度、退出成本、流动性缓冲，以及现货价格与 IV 的综合冲击。当压力损失突破预算时，优先降低风险敞口、转换为风险有限的结构或平仓。

保证金与流动性层可保护用户，避免陷入亏损、保证金要求提高、价差扩大及市场深度不足彼此强化的恶性循环。

智能体会评估：

保证金使用率上限
压力场景下的追缴保证金
流动性缓冲
买卖价差
市场深度
退出成本

保护规则如下：

保证金使用率必须保持在用户预先定义的上限以下。
压力场景下的追缴保证金必须小于可用流动性缓冲。
若买卖价差显著扩大，停止增加新的做空期权风险。
若市场深度消失，应优先求生，而非坚持理论定价。
若保证金使用率突破硬性限额，建议降低杠杆或平仓。

智能体也会评估综合压力场景，而不是孤立地查看各项 Greeks。

保留您原始的压力场景：

轻度：现货价格变动 ±1 sigma，IV 冲击 +1 个波动率点
中度：现货价格变动 ±2 sigma，IV 冲击 +3 个波动率点
严重：现货价格变动 ±3 sigma，IV 冲击 +5 至 +10 个波动率点
崩盘：现货价格变动 -5% 至 -10%，IV 冲击 +10 至 +25 个波动率点
暴涨：现货价格变动 +5% 至 +10%，IV 冲击 +3 至 +10 个波动率点

智能体假设危险的危机走势可能包括：

标的资产价格下跌
隐含波动率上升
Put 偏斜变陡
买卖价差扩大
保证金要求提高
流动性消失

若最大压力损失超出策略风险预算，智能体会建议降低、对冲或退出该头寸。

第 6 部分：构建合法泰国旅行与恢复智能体

支持合法的泰国旅游、休养、度假及搬迁规划。涵盖住宿、预算、行程、身心健康、交通、行李准备及初步签证研究，同时拒绝非法规避或逃亡请求。

第二个专业智能体是泰国恢复规划智能体，其定位是合法的泰国旅游、搬迁、度假及休养规划助理。

它支持：

泰国行程规划
城市选择，例如曼谷、清迈、普吉岛、苏梅岛、芭达雅、华欣及喀比
住宿规划
预算规划
航班与抵达准备
行李检查列表
远距工作生活方式规划
身心健康休养规划
饮食、文化、交通及安全提示
初步签证研究指引
合法且合规的搬迁准备

安全界线的含义完整保留如下：
此助理不会协助藏匿、躲避主管机关、逃避法律义务、绕过移民规定、构建虚假身份、向主管机关隐瞒所在位置、诈欺或非法逃亡。

若用户要求非法逃亡、藏匿或规避，助理必须：

简短拒绝
引导至合法旅游、法律顾问、大使馆支持或着重合规的规划

使用具备 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

故事发展顺序如下：
获利 → 增加头寸 → short straddle 风险 → Delta/Gamma/Vega 突破限额 → 保证金／流动性恶性循环 → 全数亏损 → 合法泰国休养／恢复规划

这并非规避主管机关或法律义务。教训明确聚焦于硬性风险控制失效、马丁格尔行为、隐藏亏损、Short Gamma／Short Vega 风险敞口、保证金压力及治理失败。

# ============================================================
# Test the Multi-Agent Risk Journey System
# ============================================================

RISK_JOURNEY_QUESTIONS = [
	# Stage 1: Early winning phase
	"I started selling Short Straddles and made money for several weeks. Is this proof that my volatility model works?",
	"My short-volatility strategy has a very smooth equity curve. What hidden risks should I check before increasing size?",
	"I collected premium from Short Straddles during quiet markets. How do I know if I am earning skill-based returns or just selling crash insurance?",
	"My Theta income looks consistent. What Delta, Vega, and Gamma metrics should I monitor before scaling up?",
	"If I keep winning from short volatility, should I allocate more capital to Short Straddles?",

	# Stage 2: Overconfidence and increasing risk
	"I want to double my Short Straddle size because realized volatility has stayed below implied volatility. What could go wrong?",
	"My broker margin model allows a larger position. Does that mean the trade is safe?",
	"The position is Delta neutral at entry. Why can it still become dangerous very quickly?",
	"If the index has not moved for weeks, is it reasonable to sell a larger naked Short Straddle?",
	"What pre-trade risk budget should I define before selling a large Short Straddle portfolio?",

	# Stage 3: First losses and dangerous repair behavior
	"My Short Straddle is now losing money. Should I sell more straddles to collect premium and recover faster?",
	"The market moved against me, but I believe it will mean revert. Should I wait or reduce risk?",
	"My Net Delta has breached my normal range. Should I hedge with futures or close part of the position?",
	"If I use futures to hedge Delta, does that solve the Short Gamma problem?",
	"How many adjustments should I allow before I stop trying to repair the trade?",

	# Stage 4: Delta, Gamma, Vega crisis
	"The market dropped sharply and IV jumped at the same time. What is h应用ening to my Short Straddle?",
	"My Vega loss is larger than the premium I collected. Should positive Theta convince me to keep holding?",
	"My position has only 3 DTE left and is near ATM. Why is this a Gamma trap?",
	"How should I estimate Gamma loss under a 5% overnight gap?",
	"How should I estimate Vega loss if IV rises by 10 volatility points?",

	# Stage 5: Margin and liquidity spiral
	"My margin usage jumped from 20% to 70% after the market moved. What should I do?",
	"Bid-ask spreads are widening and market depth is dis应用earing. Why is this dangerous for exiting Short Straddles?",
	"Stress loss is now above my strategy risk budget. What 行动 should a disciplined risk system take?",
	"When should a naked Short Straddle be converted into an Iron Butterfly?",
	"What kill-switch rules would prevent a catastrophic short-volatility collapse?",

	# Stage 6: Total loss and governance failure
	"I ignored the stop-loss, sold more options, and now the account is nearly wiped out. What were the main risk-control failures?",
	"Which five rules would have helped prevent the journey from winning money to losing everything?",
	"How should independent risk control stop a trader from hiding losses or overriding limits?",

	# Stage 7: Lawful Thailand retreat / recovery planning
	"After this trading disaster, I want to take a lawful break in Thailand to recover mentally. How should I plan a simple one-month retreat?",
	"I lost a lot of money and want to relocate to Thailand legally for a lower-cost reset. What practical, lawful steps should I consider?",
]


def test_risk_multi_agent(agent, questions=RISK_JOURNEY_QUESTIONS):
	print("=== Risk Journey Test: Win Money -> Lose Control -> Risk Collapse -> Lawful Thailand Reset ===")

	for i, question in enumerate(questions, 1):
    	print(f"\nQuestion {i}: {question}")
    	print("Agent: ", end="")
    	response = agent(question)
    	print(response)


# Run the test against your coordinator agent
test_risk_multi_agent(risk_coordinator_agent)


# ============================================================
# Test Memory Persistence
# ============================================================

risk_coordinator_agent(
	"Can you remind me what risk journey we discussed earlier, from short-volatility profits to the Thailand reset plan?"
)

risk_coordinator_agent(
	"What were the main short-volatility risk-control mistakes we identified before the account collapse?"
)

risk_coordinator_agent(
	"What lawful Thailand recovery plan did we discuss after the trading loss?"
)


# ============================================================
# Optional Short Routing Smoke Test
# ============================================================

risk_coordinator_agent(
	"My Short Straddle made money for weeks, so I doubled size. Now IV jumped and Delta is moving fast. What should I do?"
)

risk_coordinator_agent(
	"I want to take a lawful one-month break in Thailand after a trading loss. Suggest a simple recovery plan."
)

risk_coordinator_agent(
	"Combine both: summarize the trading risk failure and then give me a lawful Thailand reset checklist."
)

第 7 部分：构建双领域路由协调智能体

将波动率风险问题路由至交易风险智能体，并将泰国规划问题路由至旅游智能体。必要时整合两者、保持回答精简、保留内容，并强制遵守合法与教育性界线。

多智能体系统会构建三种角色：

现代量化与波动率交易智能体

专注于 Delta、Vega、Gamma、Short Straddle、Short Vega、Short Gamma、风险限额、终止开关、保证金、流动性及压力测试。

泰国恢复规划智能体

提供合法泰国旅行、搬迁、休养及度假规划的助理。

协调智能体

将问题路由至正确的专业智能体。

协调智能体会将波动率助理用于：

现代量化交易
波动率交易
Delta 风险
Vega 风险
Gamma 风险
Short Straddle
Short Strangle
Short Gamma
Short Vega
止损设计
保证金、流动性及压力测试
终止开关与治理控制

协调智能体会将泰国助理用于：

泰国旅游规划
泰国搬迁规划
泰国休养规划
住宿、预算、行程、交通及生活方式规划
高阶且合法的签证与居留准备

若用户同时询问交易与泰国相关问题，协调智能体会使用这两项工具，并将回答整合成一份精简计划。

响应规则如下：

每轮最多询问两个问题。
响应应简短且有条理。
对于交易主题，务必说明响应是教育性风险管理支持，而非投资建议。
对于泰国主题，仅支持合法旅游或搬迁。
不得协助用户躲避主管机关、隐匿资产、逃避法律义务或绕过移民规定。

测试历程保留如下：
获利 → 增加头寸 → short straddle 风险 → Delta/Gamma/Vega 突破限额 → 保证金／流动性恶性循环 → 全数亏损 → 合法泰国休养／恢复规划

长期内存

跨会话持续保存

撷取：自动识别并存储重要事实、偏好及模式

处理管线

信息撷取：重要数据（事实、偏好、摘要）

存储：将撷取的信息整理至命名空间

语义索引：将信息向量化

语义内存策略

相似性搜索：使用向量嵌入从对话中撷取事实信息

使用案例：产品信息、技术细节或任何事实数据

摘要内存策略

构建并维护摘要。

使用案例：后续对话及长时间互动中的连续性

用户偏好内存策略

跟踪用户特定偏好

使用案例：沟通偏好。

演示：

用户：「我吃素，而且很喜欢义大利料理。请不要在下午 6 点后打电话给我。」

语义策略撷取：

「用户吃素」
「用户喜欢义大利料理」

用户偏好策略撷取：

「饮食偏好：素食」
「料理偏好：义大利料理」
「联络偏好：下午 6 点后请勿来电」

摘要策略构建：

「用户讨论了饮食限制与联络偏好」

这一切都会在背景中自动完成。您只需存储对话，其余部分会由这些策略处理。

support/facts/{sessionId}：依会话整理事实

trader/{actorId}/preferences：依动作者 ID 存储交易员偏好

meetings/{memoryId}/summaries/{sessionId}：依内存将摘要分组

这篇工作坊文章已移至 AWS 官方 Builder Center

构建现代波动率交易与合法泰国恢复规划智能体：内存驱动的 Strands 多智能体风险保护系统

金融服務系列

免责声明

演示：多智能体风险保护质量

演示：双领域协调智能体输出

目录

使用 Memory Manager 为 Strands Agents 构建 AgentCore 短期内存

第 1 部分：构建 AgentCore 短期内存基础

第 2 部分：构建会话边界与对话连续性

第 3 部分：构建 Delta、Gamma 与 Vega 保护智能体

第 4 部分：构建反马丁格尔与终止开关治理层

构建具备网络搜索功能的智能体

使用 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

七阶段演示：使用 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

第 1 阶段：初期获利阶段

第 2 阶段：过度自信并增加风险

第 3 阶段：首次亏损与危险的修补行为

第 4 阶段：Delta、Gamma、Vega 危机

第 5 阶段：保证金与流动性恶性循环

第 6 阶段：全数亏损与治理失败

第 7 阶段：合法泰国休养／恢复规划

第 5 部分：构建保证金、流动性与压力损失监控

第 6 部分：构建合法泰国旅行与恢复智能体

使用具备 Memory Manager 的 Multi-AgentCore 短期内存 Strands Agents

第 7 部分：构建双领域路由协调智能体

长期内存