Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/112360
題名: 利用Quantopian交易平台設計演算法交易策略
Design algorithmic trading strategy by Quantopian trading platform
作者: 吳雅岩
Wu, Ya Yen
貢獻者: 謝明華
吳雅岩
Wu, Ya Yen
關鍵詞: 演算法交易
金融科技
因子投資
績效指標
權重策略
投資組合
Algorithmic trading
FinTech
Factor investing
Performance index
Weight
Portfolio
日期: 2017
上傳時間: 31-Aug-2017
摘要: 本文以全球第一個演算法交易雲端平台-Quantopian進行研究,藉由平台社群討論區內公開之演算法交易策略,透過交易策略篩選和初步優化,以演算法交易策略為投資標的,搭配不同權重策略建構投資組合。權重策略部分,本文提出適用於組合式交易策略的績效指標加權 (Performance Index Weighted) 法,應用因子投資的觀念,融合排序相關性較低、不同面向之績效指標作為報酬率驅動因子,並參考Asness et al. (2013) 以因子排序作為權重計算依據,提供了簡單直覺、非最適化求解而且穩健的加權方式,更直接地將交易策略各面向績效的優劣反應在權重上。\n 根據數值分析,發現組合式交易策略長期而言,整體績效表現平均優於個別演算法交易策略,最小變異、績效指標加權和均等權重投資組合的風險亦明顯低於個別交易策略,且最小變異、績效指標加權和均等權重投資組合在降低投資組合風險的同時,並未犧牲過多報酬,風險調整後績效表現優於個別交易策略。而績效指標加權投資組合之年化報酬率、風險衡量和風險調整後績效表現皆優於最小變異、平均數-變異數、均等權重的加權投資組合,此種權重策略可使投資組合之夏普比率 (Sharpe ratio) 顯著提升,且投資組合的風險大幅降低,最大跌幅 (Max drawdown) 在四年半的實驗區間內降至10%以下的水準,風險調整後績效優異。\n 透過Quantopian社群演算法交易平台,個人投資者也能站在巨人的肩膀上學習,集合眾人的力量,憑藉量化交易創造出和機構法人一樣具有競爭力的投資組合。如Chan (2009) 所言,個人投資者也能憑藉量化交易,設計一套演算法交易策略。
Quantopian is a crowd-sourced hedge fund which allows members on the platform to develop their own algorithmic strategies and even get capital allocations from Quantopian. In this paper, we constructed portfolios by Quantopian trading platform and proposed Performance Index Weighted method which generate consistently profit in our study. First, we filtered algorithmic trading strategies shared on the Quantopian community and improved the performance slightly. Second, we combined multiple algorithmic strategies with varied portfolio weight method, such as minimize-variance, performance index weighted, mean-variance, and equal weighed method to construct a portfolio.\n To elaborate, Performance Index Weighted portfolio is actually an application of factor investing, in which the portfolio weight depends on the ranking of performance index (factors), and these index measure returns, risk, and also risk-adjusted returns, which truly reflects how well the algorithmic strategy is. As a result, we used the performance index as a return driver and invested more in well-ranked strategies directly. Performance index weighted is a simple, robust, and fully intuitively way to construct a portfolio.\n In numerical analysis, we found that using multiple strategies to construct a portfolio could generate better performance than a single algorithm strategy on average. Moreover, the annual returns, risk measure, and risk-adjusted returns of Performance Index Weighted portfolio turn out to be better than minimize-variance portfolio, mean-variance portfolio, and equal weighted portfolio. As a result, Performance Index Weighted portfolio has significantly higher Sharpe ratio and lower Max Drawdown (lower than 10% in our out-of-sample test) than other portfolios, which shows excellent risk-adjusted performance.\n Most important of all, retail traders could learn more precisely by standing on the shoulders of giants through Quantopian trading platform. Also, by collecting wisdom from the crowd, we create an opportunity for retail traders to construct competitive portfolios just as institutional investors do.
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描述: 碩士
國立政治大學
風險管理與保險學系
104358016
資料來源: http://thesis.lib.nccu.edu.tw/record/#G0104358016
資料類型: thesis
Appears in Collections:學位論文

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