taodeng/memory-continuity

Fork 0

mirror of https://github.com/dtzp555-max/memory-continuity.git synced 2026-07-21 21:15:07 +00:00

Files

T

taodeng d56506a0c9 Draft Geopolitical Turbulance Trapper development plan v1

2026-03-09 14:59:01 +10:00

13 KiB

Raw Blame History

Geopolitical Turbulance Trapper — Development Plan v1

1. Project identity

Project name: Geopolitical Turbulance Trapper

Project type: small-scale event-driven trading intelligence and derivatives decision-support system

Primary goal: Track real-time geopolitical, macro, commodity, earnings, and market information across HK, US, and AU focus markets; map those drivers into actionable short-term trading setups on target shares, indices, and derivatives.

What it should help answer:

What is the current regime: panic, rebound, chop, commodity shock, AI-infra momentum, earnings squeeze, or mixed?
Which names are most exposed or most resilient?
Which derivative type is appropriate right now: CBBC, warrant, put/call, bear/bull, options, LEAPS, or no trade?
Where is the buying zone, danger zone, take-profit zone, and do-not-chase zone?
What is the liquidity and execution risk of the proposed instrument under fast markets?

2. Why this project exists

The market backdrop is dominated by overlapping uncertainty and thematic opportunity:

Middle East and other geopolitical instability
oil and commodity shocks
AI breakthrough and infrastructure capex trends favoring shovel providers
earnings season with likely beats in selected names
elevated chop and false breaks across HK tech and global risk assets

This project is intended to convert those overlapping narratives into a structured, repeatable workflow that is more reliable than ad-hoc chat analysis.

3. Target scope

3.1 Markets

HK — first MVP priority
US — second priority
AU — later extension after HK logic is stable

3.2 Core watchlist (initial)

HK

Tencent
Alibaba
Xiaomi
HSI
HSTECH

US

Google
TSM
later candidates: NVDA, AMD, META, oil/metal-linked names

Asia ex-HK

Samsung
SK Hynix

Macro / driver instruments

Brent crude
WTI crude
gold
USD / FX proxies
volatility indicators
rates / bond-yield proxies (later)

4. Product goals

4.1 Primary system goals

User-selected primary goals already implied by prior drafts:

signal when to buy/sell derivatives
predict likely short-term direction
detect volatility spikes for risk management

4.2 Output format

Primary output should be a dashboard with visual alerts, supported by rule-based textual recommendations.

4.3 Decision support outputs

Per target / instrument, the system should output:

directional bias
volatility regime
event/risk tags
candidate derivative types
buying zone
danger zone
reduce/exit zone
liquidity risk review
execution warning
confidence / evidence level

5. Hard requirements

5.1 Facts before opinions

The system must never rely on unverified AI-generated product facts.

Examples of facts that must be independently verified before a product recommendation is considered high-confidence:

product code
underlying
issuer
call level / strike / barrier
expiry
ratio / entitlement
bid / ask / spread
volume / turnover
outstanding / open interest proxy

5.2 Bear as well as bull

The system must support:

bull tools
bear tools
paired / hedge structures
staged switch strategies (e.g. panic shield then rebound capture)

5.3 Liquidity and execution risk are first-class

The system must explicitly evaluate:

historic volume / turnover behavior
spread widening under sharp market moves
issuer quote reliability proxy
outstanding concentration risk
risk of delayed or partial order execution in fast markets

5.4 Strict execution discipline

Every recommendation should include:

entry condition
invalidation condition
stop / reduce rule
no-chase rule
special event warning (earnings, geopolitical headline, overnight gap)

6. What we learned from earlier prototypes

6.1 What is worth keeping

Earlier dashboard/system prototypes had useful ideas:

dashboard-first output
signal cards
volatility gauge / regime logic
signal breakdown panel
CBBC knock-out buffer monitoring
derivatives recommendation panel
macro/geopolitical controls
modular code layout: config / data / models / signals / backtest / dashboard

6.2 What must be changed

Earlier drafts were too weak in several areas:

derivatives facts were too easy to hardcode or hallucinate
AI was implicitly trusted as a facts layer
HK-only framing is now too narrow
strategy logic was too biased toward bullish rebound capture
liquidity/outstanding risk was not elevated enough
external data quality and verification rules were not strict enough

6.3 New design principle

AI should be the explanation layer, not the source of truth layer.

Correct order:

real data collection
product metadata verification
market regime + rule engine
risk engine
AI explanation / summarization
dashboard rendering

7. High-level system architecture

Module A — Event Radar

Track and classify relevant events:

geopolitical headlines
sanctions / conflict escalation / de-escalation
earnings and guidance
AI infra / capex headlines
commodity shocks
supply chain and policy headlines

Output:

event tag
affected names / sectors / markets
severity score
estimated duration
confidence score

Module B — Market Regime Engine

Infer current regime using price, volatility, and macro data.

Candidate regimes:

panic sell
dead-cat bounce
high-volatility range/chop
commodity shock
earnings squeeze setup
AI infra momentum
mixed/conflicted regime

Output:

regime label
supporting evidence
derivatives suitability rules

Module C — Instrument Scanner

Scan available instruments by market.

HK

CBBC bull / bear
call / put warrants

US

options
LEAPS

Output fields per candidate:

code / contract id
underlying
type
strike / call / barrier
expiry
issuer / venue
current price
spread
volume / turnover
outstanding / OI proxy
KO buffer or moneyness
liquidity risk score

Module D — Signal / Opportunity Engine

Map:

event state
regime state
underlying price behavior
instrument characteristics into concrete setups.

Examples:

panic leg using HSI/HSTECH bear
rebound leg using Tencent / Alibaba call or deeper-buffer bull
earnings-beat volatility capture
AI-infra continuation for TSM / SK Hynix / Samsung

Module E — Risk Engine

Must evaluate:

direction risk
overnight gap risk
KO risk
IV crush / theta risk
spread/quote deterioration
outstanding crowding risk
no-fill / late-fill risk

Module F — Dashboard / UI

Main user-facing layer.

Panels:

macro / event panel
market watch panel
target name cards
derivatives action panel
liquidity and execution risk panel
alerts / watchlist / danger monitor

8. Recommended dashboard layout

Top bar

live status indicator
last refresh time
market regime badge
geo risk badge
volatility badge

Panel 1 — Macro Snapshot

Brent / WTI
gold
volatility index / proxy
FX / rates proxy
event severity highlights

Panel 2 — Target Monitor

Per target card:

latest price / move
short-term bias
earnings timing
event sensitivity
volatility regime
support / resistance / danger zone

Panel 3 — Derivatives Board

For each target:

curated candidate instruments
risk tier
liquidity tier
recommended usage (bear leg / rebound leg / hedge / avoid)
entry zone / danger zone / exit rules

Panel 4 — Signal Breakdown

Explain why a signal exists:

price action
event driver
volatility state
commodity linkage
earnings proximity
liquidity constraints

Panel 5 — Alerts

KO proximity alert
spread widening alert
geo shock alert
earnings-event alert
strategy invalidation alert

9. Data-source strategy

9.1 Principles

prioritize official or near-official sources for derivative metadata
tolerate lower-quality sources only for non-critical exploratory fields
label confidence level per field

9.2 Proposed source layers

Layer 1 — Market prices / broad data

Yahoo Finance or equivalent for fast prototyping
later upgradeable market data sources as needed

Layer 2 — HK derivatives metadata

HKEX and issuer pages as the primary truth sources
avoid trusting chat-provided product codes without verification

Layer 3 — Event/news layer

curated RSS / news APIs / official releases
event classification and severity tagging

Layer 4 — Liquidity/risk layer

live bid/ask if available
turnover and volume history
outstanding
historical spread/quote behavior if feasible

10. Strategy framework (v1)

The system should support multiple strategy families instead of one bullish mean-reversion script.

Strategy family A — Panic shield

Use broad-market or tech-index bear exposure to capture the first risk-off leg.

Strategy family B — Rebound capture

After panic exhaustion, rotate into deeper-buffer bull or call structures on high-quality rebound targets.

Strategy family C — Chop capture

In high-volatility ranges, prefer instruments and rules suited to repeated swings rather than one-direction conviction.

Strategy family D — Earnings-driven asymmetry

Focus on names likely to beat expectations but still exposed to macro risk; choose derivatives based on IV, timing, and gap risk.

Strategy family E — Theme continuation

AI infra / semiconductor / commodity-linked continuation trades in US and Asia.

11. MVP definition

11.1 MVP objective

Prove that the system can produce fact-checked, risk-aware, visually presented trade setups for HK targets under geopolitical uncertainty.

11.2 MVP market scope

HK only, first:

HSI
HSTECH
Tencent
Alibaba
Xiaomi

11.3 MVP instrument scope

HK CBBC bull / bear
HK call / put warrants

11.4 MVP deliverables

project brief
schema / data model
dashboard wireframe
regime + signal framework
derivatives verification workflow
liquidity risk framework
first working dashboard prototype

12. Suggested implementation phases

Phase 0 — Project reset and reference audit

inventory the old Claude draft and earlier dashboard concepts
identify reusable files vs files to rewrite
avoid blindly inheriting hardcoded product facts

Phase 1 — Brief + schemas

Create:

project brief
event schema
target schema
derivative schema
risk schema
alert schema

Phase 2 — HK data and verification layer

Build:

target price ingestion
macro ingestion
HK derivative metadata verification workflow
confidence labels for each field

Phase 3 — Regime + risk engine

Implement:

event tags
market regime rules
liquidity/execution risk scoring
CBBC safety buffer logic
warrant suitability rules

Phase 4 — HK dashboard MVP

Build dashboard panels with:

macro snapshot
target cards
derivatives table
risk panel
alert panel

Phase 5 — Strategy logic expansion

Add:

bear + bull + combo workflows
panic/rebound/chop playbooks
staged switching logic

Phase 6 — US extension