市場輪廓理論與金融物理學於台灣金融市場之實證

Abstract

投資人往往過度自信以致於對風險忽視，造成龐大的損失。考量風險控制的資金管理便是非常重要的解決方法。本研究提出根據時空環境變化的主動調整投資組合避險策略降低系統及非系統性風險，並使投資人能夠保本與獲利。 本研究以金融物理學計算市場輪廓的擺動因子力量衡量市場的方向，整合固定比例投資組合保險策略與時間無關投資組合保護策略組成主動式混合型投資組合保本策略。接著，利用基因演算法求解兼顧報酬與風險的多目標解答空間，以找到滿意的投資組合權重及槓桿乘數集合。最後，以臺灣50指數成分股為實證對象衡量本模型之信度與效度。 實驗結果顯示，混合型投資組合保險策略主動根據市場方向選擇CPPI與TIPP策略其報酬與風險績效優於只使用CPPI或TIPP的傳統投資組合保險策略。再者，隨著不同的保本底線，單目標(報酬率)的投資組合及多目標(Sharpe Ratio)的投資組合會有不同的適合使用情境。最後，根據模型績效提供資金管理策略建議。

Investors are always overconfidence about their decision and neglect risks with enormous losses. Money management with risk control is an important solution. This study was proposed a portfolio insurance policy based on market changes that could reduce both system risk and non-systematic risk, and make profits for investors.

This research measured market trend with rotation factor of market profile that calculate by finance physics. It integrated CPPI and TIPP to develop an active hybrid portfolio insurance policy. Furthermore, this model found a set of portfolio weights and multiplier for solving multi-objective problem with returns and risks by using genetic algorithm. The reliability and validity of models was experimentally by trading FTSE TWSE Taiwan 50 Index.

The result showed the returns and risk control of hybrid portfolio insurance policy was better than CPPI or TIPP. In conclusion, single-objective (returns) portfolio and multi-objective (Sharpe Ratio) portfolio suit different scenarios with different floor.