Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 陳郁文 | zh_TW |
dc.contributor.author | 陳穎平 | zh_TW |
dc.contributor.author | 戴天時 | zh_TW |
dc.contributor.author | Chen, Yu-Wen | en_US |
dc.contributor.author | Chen, Ying-Ping | en_US |
dc.contributor.author | Dai, Tian-Shyr | en_US |
dc.date.accessioned | 2018-01-24T07:37:02Z | - |
dc.date.available | 2018-01-24T07:37:02Z | - |
dc.date.issued | 2016 | en_US |
dc.identifier.uri | http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070356104 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/138899 | - |
dc.description.abstract | 平行運算(Parallel Computing)是指利用多個計算單元並行處理龐大但資料相依性低的資料,也就是將問題或資料拆解成多個獨立的問題或步驟,再同時分配給不同的執行單元進行處理,而達到縮短整體計算時間的目的。 近幾年高頻交易在金融市場中顯得越來越重要,也因此能夠即時處理大量金融交易資料的技術也成了其中的關鍵,而議題也促使我們使用平行運算的技術針對選擇權和期貨市場去設計交易策略以及搜索套利機會套利機會通常是來自於不合理的報價,可藉由適當的交易策略中賺取利潤而不用承擔風險,因此在高度競爭且成熟的市場中,這樣的情況除了極少出現之外,也是稍縱即逝,因此像平行運算這樣能夠高速處理大量資料藉此找出套利機會的技術非常適合於此[1][2] [3] [4]。 本研究主要是延續[5]的研究。交易策略上,我們使用蝶狀價差(Convexity Strategy)和買賣權期貨平價(Put-Call-Future Parity),並且額外增加了買賣權價差(Spread Strategy)。而原本用以離線模擬的虛擬交易所也同樣沿用至新的架構上,並且增加了在線的即時交易模式,可以透過一個 TCP 通道與遠端的伺服器進行資料的即時傳輸。 | zh_TW |
dc.description.abstract | Parallel Computing denotes a technique to simultaneously process a huge amount of data with low dependency by multiple processing units. In other words, we can divide a complex problem or a huge data set into many small independent problems or small data chunks, and reduce the overall computational time through allocating these problems to different process units in the same time. High frequency trading is becoming important in financial markets and the ability to deal a huge amount of financial trading data in real time is thus critical. This thesis apply parallel computing technique to search for arbitrage opportunities and design trading strategies for TAIEX options and futures. Usually, arbitrage opportunity comes from occasionally irrational price quotes. In highly competitive and mature markets, arbitrage opportunities are not only extremely rare but also fleeting. Therefore, the technique which can process a great number of data rapidly such as Parallel Computing is very suitable for finding arbitrage opportunity. This research revises the framework of [5]. I implement the following arbitrage strategies: convexity strategy and put-call-future parity strategy, and we have introduced spread strategy in my framework to seek arbitrage opportunities in TAIEX Exchange of Futures. Besides, the off-line framework that uses virtual exchange to simulate tradings. I add the online real-time trading mode which can receive price quotes from a remote server and send back the encoded strategies through a TCP channel. | en_US |
dc.language.iso | zh_TW | en_US |
dc.subject | 平行運算 | zh_TW |
dc.subject | 套利策略 | zh_TW |
dc.subject | Parallel Computing | en_US |
dc.subject | Arbitrage Strategy | en_US |
dc.title | 以 CUDA 架構實作在線套利交易機制平台 | zh_TW |
dc.title | Online Derivatives Arbitrage Trading Mechanism Based on CUDA Framework | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 資訊科學與工程研究所 | zh_TW |
Appears in Collections: | Thesis |