$YZJ Shipbldg SGD (BS6.SG)$ Not sure why this fellow drops again.

$YZJ Shipbldg SGD (BS6.SG)$ To quantitatively assess the probability of the USTR proposal being implemented, Bayesian analysis can be used in conjunction with Historical Data, political environment, and Industry impact for an Algo estimate.

1. Analysis of key influencing factors.
(1) Historical Approval Rate (𝑃(Pass Policy | Submit Proposal))
• Based on Historical Data, trade sanction proposals involving China usually have a low overall implementation rate, but some measures may be enforced:
o 2018 Trump Tariffs (Section 301): Some high tariff policies were successfully implemented.
o 2023 Electric Vehicles Subsidy Investigation: The USA's subsidies for Chinese electric vehicles are still under discussion and have not yet formed a comprehensive ban.
In 2024, the USA's Marine Transportation review of China is currently in the investigation phase, and sanctions have not been implemented immediately.
• Assumed base probability: 30% (that is, there is a 30% chance that past similar sanction policies have been partially implemented).
(2) Political & Economic Environment (𝑃(policy approval | political pressure))
• In the 2024 USA election year, the Democratic government tends to take a hardline approach towards China to secure votes.
• The escalation of the trade war may lead to inverse costs:
o It affects USA importers and shipping companies, which may face strong opposition from the Industry.
o Inflation risk: Additional port fees may lead to a decline in the competitiveness of USA product exports, and Congress may adjust policies.
• Adjustment probability: 25% (i.e., the political impact may lower the probability of policy implementation).
(3) Industry Reaction (𝑃(Policy Approval|Industry Impact))
• Global shipping...