µL

The thesis deals with two kinds of double auction - with the continuous auction and a sequence of call auctions. We explain their rules and we define their models. We present results of simulations of the both kinds of double auction - the aim is to look for the call auction with such parameters that the prices and the traded volume of the continuous auction are approximated best. Finally, in a theoretical part, we characterize the dis- tribution of the order book in the continuous auction and then we specify the joint distribution of the price and the traded volume in the call auction (the distribution of bid, ask and the traded volume given by the continuous auction may be immediately devised from the distribution of the order book).

This report aimed to develop algorithms for solving the optimization problem of matchingbuy and sell orders in call auctions while minimizing the number of transactions. The developed algorithms were evaluated based on their execution time and solution accuracy.The study found that the problem was more difficult to solve than initially anticipated, and commercial solvers were inadequate for the task. The data’s characteristics werecritical to the algorithms’ performance, and the lack of specifications for instruments andexchange posed a challenge. The algorithms were tested on a broad range of datasets with different characteristics, as well as real trades of stocks from the Stockholm Stock Exchange. Evaluating the best-performing algorithm became a trade-off between time and accuracy, where the quickest algorithm did not have the highest solution accuracy. Therefore, the importance of these factors should be considered before deciding which algorithm to implement. Eight algorithms were evaluated: four greedy algorithms and four clusteralgorithms capable of identifying 2-1 and 3-1 matches. If execution time is the single most crucial factor, the Unsorted Greedy Algorithm should be considered. However, if accuracyi s a priority, the Cluster 3-1 & 1-3 Algorithm should be considered, even though it takes longer to find a solution. Ultimately, the report concluded that while no single algorithm can be definitively la-beled as the best, the Cluster 2-1 Algorithm strikes the most effective balance between execution time and solution accuracy, while also remaining relatively stable in perfor-mance for all test cases. The recommendation was based on the fact that the Cluster 2-1 Algorithm proved to be the quickest of the developed cluster algorithms, and that cluster algorithms were able to find the best solutions for all tested data sets. This study successfully addressed its purpose by developing eight algorithms that solved the given problem and suggested an appropriate algorithm that strikes a balance between execution time and solution quality.

高頻率交易在近年已漸成為全球趨勢，在世界各主要交易所的交易型態中都占有相當的比例。高頻率交易雖因係非僅有單一策略型態的套利行為，而目前尚未有明確之定義，然簡言之，其係指於毫秒等級的微小時間內，利用複雜的計算機運算系統挾帶速度優勢來進行迅速探測出市場上股票或期貨微小的價格差異並從中套利之交易模式。高頻率交易的特性是「交易頻繁，但每次獲利微薄」，且通常是當沖交易。然而，此種立基於快速撮合的逐筆交易制度以及資訊軟硬體設備進步而生之新型交易模式，除能帶來增加交易市場流動性、促進市場活絡等優點以外，亦藏有使股市因無意向成交而產生劇烈波動或造成市場秩序不公平等風險，如著名的美國2010年閃電崩盤即為一例。 我國證券市場的交易制度幾經更迭，現行所採之集合競價的撮合間隔時間一路從20秒降至現行的5秒，然仍遲未採行各國趨勢之逐筆交易制度。現任證交所董事長施俊吉對此也於2016年12月13日受訪時指出，集合競價交易方式已屬老式且落伍，逐筆交易已水到渠成，運作尚有賴券商業者大力配合。只要券商準備好即可隨時啟動。 證券交易市場首重公平性，此於我國證券交易法立法目的即可觀之。我國雖因未採行逐筆交易制度，目前尚未面臨高頻率交易之挑戰，然於可預見之未來，我國實施逐筆交易制度後，高頻率交易的產生以及比重無可避免地將有隨之增加之可能。此時我國證券交易市場所將面臨的，即高頻率交易究竟有無促進市場效率、抑或破壞市場公平性；以及我們又該如何將之規範以兼顧市場整體利益與投資人保護等考驗。 本論文以現行我國交易制度的發展動向為脈絡，並以未雨綢繆之角度初探高頻率交易此一議題，藉參考他國就此交易模式之制度與規範方向，自我國現行證券交易法之制度下進行檢視及討論，藉此試提出於我國推行逐筆交易後，發生高頻率交易時之相關配套建議以及對投資人的保護措施，做為我國日後實際推行逐筆交易制度與高頻率交易時之參考依據。 / High-frequency trading (HFT) has become a global trend in recent years. It accounts for a considerable proportion in the world's major exchanges. HFT is not only a single strategy for the type of arbitrage behavior; hence, there is still no clear definition of it. But in short, it refers to a type of algorithmic trading characterized by "frequent transactions with minute profit". Despite the benefit of increasing the liquidity of market and promoting market activity, it also has some disadvantages such as interfering the market order and the risk of unfairness. The well-known case, Flash Crash, of America in 2010 is so one example of HFT. The securities market trading system of Taiwan, Call Auction, has changed several times. The interval of the auction collecting and matching time has been all the way from 20 seconds down to the 5 seconds in current. But the final goal, Trade by Trade Matching transaction, has not yet been adopted so far. In December of 2016, the current chairman of Taiwan Stock Exchange said that Call Auction transaction is now old-fashioned and outdated, Trade by Trade Matching transaction has become a matter of course. Trade by Trade Matching transaction is just right around the corner, and it’s ready to launch as long as the brokers are ready. Fairness is the first priority in securities market. While Taiwan has not yet adopted the Trade by Trade Matching transaction and has not yet faced the challenges of HFT, Taiwan will no doubt implement it in the foreseeable future, and therefore the possibility of the appearance and the proportion of HFT in our market will be increasing. At the same time, HFT will be faced with whether it will promote market efficiency or undermine the fairness of the market. How should we regulate it and how to protect the interests of investors and the overall benefit of our market will also become our tests. This thesis takes the development trend of current trading system in Taiwan as a starting point and probes into the issue of HFT from the view of precaution. By referring to the trading system and regulations toward HFT of other countries, this thesis try to propose relevant suggestions and protection measures for investors and appropriate regulations of market after the implementation of Trade by Trade Matching transaction and the embracement of HFT in Taiwan.