臺灣博碩士論文加值系統

在金融領域中, 風險和報酬間的關係一直是備受矚目的議題．根據過往的經驗，選擇權的波動率中隱含著市場對風險的預期．然而，由於風險中立評價理論的成功，我們卻難以用選擇權價格預測市場對未來報酬的看法。S. Ross 在2011年提出的回復理論，提供了一個較為直覺的方式，從選擇權價格中成功的將市場對風險的偏好與對報酬的預期區分出來．本篇論文著重於使用Ross的回復理論做指數選擇權的實證研究，並將回復理論應用於Black-Litterman最佳化資產組合的模型上．

Relationship between risk and return is the most important concern in finance. It is well known that market expectations of risk are embedded in option prices. However, due to the success of risk-neutral pricing theory, option prices are silent in predicting natural probability of return. Therefore, S. Ross proposes an intuitive method, Recovery Theorem, to recover the natural probability distribution under a discrete-time setting. This work aims to conduct empirical test of index options based on Ross’s Recovery Theorem, and applies Recovery Theorem in Black-Litterman portfolio optimization model.

Abstract i
摘要 ii
誌謝 iii
Content iv
List of Figures v
List of Table vi
Chapter 1 Introduction 1
Chapter 2 Ross Recovery Theorem 3
2.1 Discrete-time Model 3
2.2 Continuous-time Model 7
Chapter 3 Implementation of Recovery Theorem 13
3.1 Step 1: From Market Option Prices to Current State Price Matrix 14
3.2 Step 2: From Current State Price Matrix to Transition State Price Matrix 19
3.3 Step 3: From Transition State Price Matrix to Natural Transition Probability…..23
Chapter 4 Application to Black-Litterman Model 24
4.1 Introduction to Portfolio Optimization Theory 24
4.2 Implementation of Black-Litterman Model 26
Chapter 5 Conclusion 32
Reference 33

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