投資者處於高物價、低利率的經濟環境下,若採取保守的儲蓄理財策略,勢必將面臨實質資產降低的風險,然存款以外的投資理財工具存在高度不確定性風險,若將資金貿然投入將導致極大風險,因此如何選擇金融商品與管理資產成為投資者關注的議題。現代投資組合理論濫觴於1952年由Markowitz所提出的平均數-變異數模型,以平均數的概念代表報酬,報酬的變異數代表風險,然相較於股價的上檔風險,投資人更加關心於股價的非預期下跌風險,故本研究將以股價的下方風險做為本研究關注的目標之一。本研究欲建立一個完整的投資流程,從篩選標的、資金配置至交易策略,希望在控制風險的情況下,獲得超越大盤的風險溢酬。建構投資組合為一連串的決策分析所組成;在選股策略中,本研究參考巴菲特基本財務指標選股策略,以毛利率、股東權益報酬率和現金流量成長率進行初步篩選,接續使用資料包絡分析法(data envelopment analysis, DEA)建構投資組合;於權重配置階段,選擇資料包絡分析法機制中的被同儕參考次數、極大化報酬與極小化風險概念之雙目標妥協解與平均-下方風險變異數三種不同邏輯之方法進行;交易策略方面採用買進持有進行操作。本研究驗證期間為2006年至2009年,使用報酬率、標準差與夏普指標衡量投資組合的績效表現,並與基金市場中的績優基金做一比較對照。其結果顯示,本研究所建構之投資組合在不同績效指標上皆有優於基金的表現。故本研究所建構之投資決策流程可供投資人在進行投資決策時加以參考運用。
Depositing money in a high inflation economic environment can’t prevent asset value from declining. Thus, how to manage personal investment properly has become a major issue nowadays. In this research, a portfolio optimization model is proposed. Decisions such as selecting stocks, locating capital and adopting trading strategies are to be determined in this model. The mean-variance model was initiated by Markowitz in 1952, which assumes that investors only care about the means and variances of their returns. However, investors usually concern the unexpected declining of stock price much more than that of rising. Thus, we concentrate on the downside risk in our study. This study consists of three stages/decisions. First of all, the fundamental financial analysis and data envelopment analysis (DEA) technique are used for selecting stocks as the candidate of final portfolio. Secondly, three different decision methods are used to determine the distribution of the total capital for investment. These methods include the reference set from DEA, the multi-objective programming technique, and the Mean-Lower Partial Movement model. Finally, the buy-and-hold trading strategy is adopted. Historical data set from January, 2006 to December, 2009 are used to measure the investing performances of the proposed model. The resulting computational results demonstrate that the proposed model (ROI, variance and Sharpe’s index) performs better than the benchmark TSEC Taiwan 50 index and other similarity benchmark funds in the market.