台灣壽險業自2018年起實施IFRS 9，並於2026年同步接軌IFRS 17及新一代清償能力制度（Taiwan Insurance Solvency, TIS）。在三項制度並行之背景下，壽險公司之資產配置決策同時受到IFRS 9會計分類選擇、匯率會計新制、公司流動性管理需求與TIS清償能力資本要求之多重限制，然而現有文獻較少將上述異質性制度限制整合於同一最適化架構下進行分析。
有鑑於此，本研究建構多資產隨機模型，資產端以CIR模型、幾何布朗運動模擬利率、股票與匯率之隨機動態；負債端依IFRS 17一般衡量模型建構涵蓋終身壽險、生死合險、健康險及遞延年金四類商品之評價架構，計算最佳估計負債（BEL）、風險調整（RA）與合約服務邊際（CSM）。於均值-變異數最適化架構下，以風險趨避係數λ為分析主軸，分別設計美元AC債券匯兌損益攤銷政策（S1）、公司自主流動性管理需求（S2）及TIS清償能力門檻（S3）三種制度情境，並進行TIS門檻敏感度分析。
研究結果顯示，匯率攤銷政策之效益具風險趨避門檻，僅保守型壽險公司可獲顯著配置改善效果並提升其TIS比率；流動性管理需求壓縮攤銷法效果，並使損益波動達無此需求時之兩倍以上；現行TIS監理門檻對低利率新發保單之約束效果有限，且對不同風險偏好公司之配置影響方向不同；各項制度限制存在相互壓縮之作用，個別政策效果之評估若未同時考量其他約束，將高估其實際影響。綜合而言，壽險公司資產配置策略之財務影響，並非僅取決於管理階層之風險偏好，更取決於公司所面臨之多重制度性限制，本研究所建構之整合性分析框架，可供業界於多重制度接軌下進行資產配置決策時參考。

Taiwan's life insurance industry simultaneously adopted IFRS 17 and the Taiwan Insurance Solvency (TIS) framework in 2026, alongside the existing IFRS 9. Under these three concurrent regimes, asset allocation decisions are subject to multiple constraints, including accounting classification choices, foreign exchange accounting reform, liquidity management requirements, and solvency capital requirements, yet existing literature rarely integrates them within a unified optimization framework.
This study constructs a multi-asset stochastic simulation model with CIR and GBM processes for the asset side, and an IFRS 17 General Measurement Model covering four product types for the liability side. Within a mean-variance optimization framework, three regulatory scenarios are examined: FX amortization policy (S1), liquidity constraints (S2), and TIS solvency threshold (S3).
Results show that the FX amortization benefit is risk-aversion-dependent, benefiting only conservative insurers; liquidity requirements more than double earnings volatility; the current TIS threshold has limited binding effect on new low-crediting-rate policies and exhibits asymmetric impacts across risk profiles; and regulatory constraints interact in mutually compressing ways, causing isolated policy evaluations to overstate actual effects. These findings suggest that asset allocation outcomes depend not only on risk preferences but on the full set of institutional constraints faced, and the integrated framework proposed offers practical reference for industry decision-making.

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