選擇權是項衍生性金融商品，具備相當大的財務槓桿，其權利金一天的漲跌甚至可達數倍之多，且大部分交易的商品，到期日都在一個月之內，也就是說在相當短的期間常會有相當大的賺賠，為高報酬高風險的金融商品。操作這樣的商品時，必須相當注意市場上的變化，一般投資人在沒有能力和時間來充分盯盤的情況下，投資風險自然大增。這樣的限制，常使得部份投資人裹足不前，以致降低了市場上的成交量，這時投資人就更倚靠看盤軟體了。看盤軟體從最早期的單純報價畫面，演變至今，已增加了即時技術分析，即時新聞，線上下單等多項功能，但相對於選擇權這項高報酬高風險的新產品，看盤軟體尚須提供哪些功能呢? 本論文從智慧型代理人的角度出發，在看盤軟體內提供下列功能:依據即時資料來建立評價模型，找出合適的買賣點，以VaR及保證金最佳化為基礎來建立風險管理，並可直接進行交易。實驗證明確可有效協助散戶管理其選擇權的投資組合。
本系統的貢獻如下:

一.提出一個以Put-Call Parity為基礎，所發展出來的評價模型，來發現造成套利空間主
因的商品。
二.保證金最佳化，使投資人能夠更確實的掌握投資組合風險，並且可以更有效率的使用資
金。
三.在一般投資人環境下，以代理人架構，並整合報價軟體，完整的完成選擇權操盤代理人
系統。

Option is a derivative financial product with high risk and high payoff. The expiration dates of most trading options are often confined within a month, which implies a huge gain/loss within a very short period, or a multi-fold premium in a day. Therefore, the investors should be very careful before committing to any transactions. However, it is usually very hard if not impossible for an average investor to check each transaction manually and thoroughly. She thus tends to hesitate to increase the amount of transactions, owing to lurking risk. Software tools, which can help her to analyze arbitrage space and manage risk, are becoming more important. In fact, software tools have been improved a lot, from the very early version containing only pricing lists to the latest version with real-time analysis, market news, and Internet trading functions. In this project, we based on the function of intelligent agents to further improve the software tools. We have developed an agent which contains an arbitrage space evaluation model based on real-time transaction data to look for best-buy/best-sell pricing strategies for trading. The agent is also equipped with the capability of risk assessment based on VaR (Value at Risk) prediction and Margin optimization. It can work autonomously starting from accepting real-time quotes, arbitrage space analysis, risk control, and up to the final order placement. Our experiment shows it can correctly pinpoint arbitrage spaces and efficiently place orders subject to the user-delegated risk policy. The contributions of the work include:
1.An arbitrage space evaluation model is developed based on the Put-Call
Parity. It can find out correct arbitrage spaces.
2.A risk management module which involves margin optimization is developed.
It can help the investors to efficiently control their investments.
3.The agent is realized as a delegation system, which can seamlessly
integrate with the real-time quote applications and place orders to do
automatic program trading.

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