This dissertation contributes to the research in the applied market micro-structure field, aiming to investigate the impact of a specific article of the MiFID II enforced on the 3rd of January 2018: the so-called tick size regime. It is constituted by three papers that see in the market regulators and policy-makers their optimal target. The first paper evaluates the consequences of the new regulation on UK minor venues in terms of liquidity and price discovery and highlights minor unintended consequences in the implementation of the new grid. The second paper builds on these conclusions and promotes an alternative to ESMA grid, a recalibration of the tick size that might lead to a greater orderliness of UK order books. Thethirdpaperendogenouslyinvestigatesthebehaviourofthemarketparticipants in the time frame around the MiFID II enforcement, simulating liquidity breakdowns thus providing the regulators with new simple metrics to detect and monitor abnormal market participants interactions.

The tick size regime on systematic internalisers (SIs) was seen as a necessary action to level the playing field between SIs and other trading venues, with the hopes to improve the market composition and market quality in favour of regulated markets. However, the previous literature objects to the view as SIs may have gained the first-mover advantage from their previous tick size exemption. This thesis aims to examine whether the MiFID II tick size regime implementation for SIs on June 26, 2020, alters the market composition and improves the market quality at Nasdaq Stockholm. We consider 45 Swedish stocks with the highest daily average turnover to conduct difference-in-difference regressions. We find that the market quality worsens at Nasdaq Stockholm, while the market composition remains unaffected by the SI tick size regime implementation. The quoted spreads, effective spreads and price impact increase at Nasdaq Stockholm following the SI tick size regime. Impatient traders who trade on information may have rerouted their orders to Nasdaq Stockholm after the event since SIs can no longer offer the avoidance of the price-time priority. Therefore, SIs may have an important role in attracting informed traders who consume rather than supply liquidity. However, the interpretation of the results is conditioned on an inflow of traders from SIs to Nasdaq Stockholm, which we cannot explicitly measure due to the order flow not being adjusted for orders less than the standard market size.

Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: How can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly’s literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis. While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975 to 2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies: “daily return,” “lag one daily return,” and “weekly return” to alleviate the potential effect of irregular data observation. I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis. I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.

This dissertation consists of three essays in applied financial economics. The unifying theme is the use of financial regulation as quasi-experiments to understand the interrelationship between derivatives and the underlying assets. The first two essays use different quasi-experimental econometric techniques to answer the same research question: how does option listing affect the return volatility of the underlying stock? This question is difficult to answer empirically because being listed on an options exchange is not random. Volatility is one of the dimensions along which the options exchanges make their listing decisions. This selection bias confounds any causal effect that option listing may have. What is more, the options exchanges may list along unobservable dimensions. Such omitted variable bias can also confound any causal effect of option listing. My first essay overcomes these two biases by exploiting the exogenous variation in option listing that is created by the SEC-imposed option listing standards. Specifically, the SEC mandates that a stock must meet certain criteria in the underlying market before it can trade on an options exchange. For example, a stock needs to trade a total of 2.4 million shares over the previous 12 months before it can be listed. Since 2.4 million is an arbitrary number, stocks that are “just above” the 2.4 million threshold will be identical to stocks that are “just below” it, the sole difference being their probability of option listing. Accordingly, I use the 2.4 million threshold as an instrument for option listing in a fuzzy regression discontinuity design. I find that option listing causes a modest decrease in underlying volatility, a result that corroborates many previous empirical studies. My second essay attempts to estimate the effect of option listing for stocks that are “far away from” the 2.4 million threshold. I overcome the aforementioned omitted variable bias by fully exploiting the panel nature of the data. I control for the unobserved heterogeneity across stocks by implementing a two-way fixed effects model. Unlike most previous studies, I control for individual-level fixed effects at the firm level rather than at the industry level. My results show that option listing is associated with a decrease in volatility. Importantly, these results are only statistically significant in a model with firm-level fixed effects; they are insignificant with industry-level fixed effects. My third essay is a policy evaluation of the SEC’s Penny Pilot Program, a mandated decrease of the option tick size for various equity options classes. Several financial professionals claimed that this decrease would drive institutional investors out of the exchange-traded options market, channeling them into the opaque, over-the-counter (OTC) options market. I empirically test an implication of this hypothesis: if institutional investors have fled the exchange-traded options market for the OTC market, then it may take longer for information to be impounded into a stock’s price. Using the `price delay’ measure of Hou and Moskowitz (2005), I test whether stocks become less price efficient as a result of being included in the Penny Pilot Program. I perform this test using firm-level fixed effects on all classes that were included in the program. I confirm these results with synthetic control experiments for the classes included in Phase I of the Penny Pilot Program. Generally, I find no change in price efficiency of the underlying stocks, which suggests that the decrease in option tick size did not materially erode the price discovery that takes place in the exchange-traded equity options market. I also find evidence that the decrease in option tick size caused an increase in short selling for the piloted stocks. / Economics

Taiwan Security Market is a typical order-driven market, and the business transactions are matched through the electronic trading system since 1988. In this work, we study the joint distributions of tick size changes of bid price and ask price, bid volume, and ask volume¡@for each matching order in Taiwan Stock Exchange (TSEC). Exponentially weighted moving average (EWMA) method is adopted to update the joint distribution of the incoming order variables aforementioned. Here we propose five methods to determine the update timing and consider three different initial matrices of the joint distributions. In empirical study, the daily matching data of two enterprises Uni-president Enterprises Corporation and Formosa Plastics Corporation in April, 2005 are considered. The goodness of fit for the joint distributions are determined by Chi-square Goodness of Fit Test. The results show that EWMA method provide good fit for most of the daily transaction data.

Bakgrund: En fungerande kapitalmarknad är en förutsättning för en nations innovation,vilket i sin tur är fundamentalt för att uppnå ekonomisk tillväxt. Därav blir förståelsen för hurkapitalmarknaden fungerar av största vikt. En av de vanligaste frågorna investerare ochforskare ställer sig är huruvida marknader är effektiva? Kan investerare utgå ifrån attkapitalmarknaden är effektiv och att alla handlar på samma information? Frågan är viktigeftersom kapitalmarknaden är uppbyggd på ett förtroende hos allmänheten, om dettaförtroende raseras kan det få förödande konsekvenser för nationen, utifrån svårigheter medkapitalallokeringen. Denna studie undersöker, med utgångspunkt från effektiva marknader,fenomenet kallat ex-dagseffekten. Finns det prisavvikelser på marknaden och iförekommande fall, finns det en förklaring till detta? Utifrån det undersöker studien specifiktmikrostrukturen som förklaring till den potentiella prisavvikelsen. Syfte: Syftet med studien är att undersöka, analysera, samt förklara förekomsten av exdagseffektenoch dess relation med mikrostrukturen på OMX Stockholm Large Cap,respektive Mid Cap och Small Cap. Metod: Utifrån studiens behov att sammanställa en större mängd data har en kvantitativforskningsstrategi använts. Studiens sekundärdata är insamlad för utdelande bolag noteradepå OMX Stockholm Large, Mid samt Small Cap mellan årtalen 2016 och 2019. Insamladdata har sedan sammanställts till paneldata, vilken ligger till grund för studiens t-test samtmultipla regressioner. Slutsats: Utifrån studiens t-test påvisas att ex-dagseffekten föreligger på studiens utvaldamarknad. Vidare, utifrån studiens regressioner utläses det att mikrostrukturen har en negativpåverkan på PDR. Då förekomst av mikrostrukturen påvisas kan studien inte uttala sig omhuruvida marknaden som undersökts är ineffektiv eller ej. / Background: A functioning capital market is a prerequisite for the innovation of a nation,which in turn is fundamental to achieve economic growth. Hence, the understanding of howthe capital market operates becomes of paramount importance. One of the most commonquestions investors and researchers ask themselves is whether markets are efficient? Caninvestors assume that the capital market is efficient and that everyone trades on the sameinformation? The question is important because the capital market is built upon publicconfidence, and if this trust is destroyed, it can have devastating consequences for the nation,based on difficulties with capital allocation. This study examines, based on efficient markets,the phenomenon called the ex-day effect. Are there price deviations in the market, and ifapplicable, is there an explanation for this? Based on this, the study specifically examines themicrostructure as an explanation for the potential price deviation. Purpose: The purpose of the study is to investigate, analyze, and explain the existence of theex-day effect and its relationship with the microstructure of OMX Stockholm Large Cap, MidCap and Small Cap. Method: Based on the study's need to compile a larger amount of data, a quantitativeresearch strategy has been used. The study's secondary data is collected for distributingcompanies listed on OMX Stockholm Large, Mid and Small Cap between the years 2016 and2019. Collected data has then been compiled into panel data, which is the basis for the study'st-test and multiple regressions. Conclusion: Based on the study's t-test, it is demonstrated that the ex-day effect is present inthe study's selected market. Furthermore, based on the regressions models the study used, itcan be deducted that the microstructure has an impact of PDR. Since the presence of themicrostructure is detected, the study cannot comment on whether the market examined isinefficient or not.

本文以日內資料研究台灣證券交易所於2005年3月1日實施股價升降單位新制後，市場交易因子與股價報酬波動率的變化；延伸討論市場參與者對新訊息之反應，進而評估實施股價升降單位新制之成效。本文首先比較四種常用來衡量報酬波動率的方法，並從中挑選出最穩健的測度方式；接著藉此分析股價日報酬波動率與市場交易因子之間的關係；最後，由於日內股價報酬波動的軌跡呈現U型曲線，為突顯波動較劇烈之時段股價報酬波動率是否亦隨股價升降單位縮小而趨緩，故著眼交易日開盤後一小時及收盤前一小時，再次檢驗上述關係。實證結果支持股價升降單位縮小使實現波動率大幅降低且交易筆數密切影響股價報酬波動率，且不論在日資料與日內資料都呈現相似結論；並發現愈接近開、收盤的時間點，股價報酬波動率降低比例亦愈大，顯示升降單位新制達成政策目的。 / In this study, we address the impact of the tick size reduction on the Taiwan Stock Exchange on March 1, 2005. We propose to investigate the variations of trading activities and return volatility, discuss investors' behaviors to the new information and evaluate the tick size reduction by analyzing intraday data. First, we select the most robust volatility measure for our study from four commonly used ones. Second, we examine the relationship between daily return volatility and trading activities. Eventually, due to the commonly observed U-shaped pattern of intraday return volatility, we re-examine the intraday relation between return volatility and trading activities. Our empirical results based on the robust realized volatility confirm that both daily and intraday return volatility decline significantly after the tick size reduction, and number of trades is a prominent trading factor in explaining realized volatility. More interestingly, we observe that the percentage decrease in realized volatility is most pronounced for trading sessions near the beginning or the ending of each trading day. Overall, our empirical findings support the arguments for tick size reduction intended by policymakers.

En utilisant des données haute-fréquence inédites, cette thèse étudie trois types de regroupements (“clusters”) présents dans le marché des changes: la concentration d'ordres sur certains prix, la concentration des transactions dans le temps et l'existence de groupes d'investisseurs prenant les mêmes décisions. Nous commençons par étudier les propriétés statistiques du carnet d'ordres EBS pour les paires de devises EUR/USD et USD/JPY et l'impact d'une réduction de la taille du tick sur sa dynamique. Une grande part des ordres limites est encore placée sur les anciens prix autorisés, entraînant l'apparition de prix-barrières, où figurent les meilleures limites la plupart du temps. Cet effet de congestion se retrouve dans la forme moyenne du carnet où des pics sont présents aux distances entières. Nous montrons que cette concentration des prix est causée par les traders manuels qui se refusent d’utiliser la nouvelle résolution de prix. Les traders automatiques prennent facilement la priorité, en postant des ordres limites un tick devant les pics de volume.Nous soulevons ensuite la question de l'aptitude des processus de Hawkes à rendre compte de la dynamique du marché. Nous analysons la précision de tels processus à mesure que l'intervalle de calibration est augmenté. Différent noyaux construits à partir de sommes d'exponentielles sont systématiquement comparés. Le marché FX qui ne ferme jamais est particulièrement adapté pour notre but, car il permet d’éviter les complications dues à la fermeture nocturne des marchés actions. Nous trouvons que la modélisation est valide selon les trois tests statistiques, si un noyau à deux exponentielles est utilisé pour fitter une heure, et deux ou trois pour une journée complète. Sur de plus longues périodes la modélisation est systématiquement rejetée par les tests à cause de la non-stationnarité du processus endogène. Les échelles de temps d'auto-excitation estimées sont relativement courtes et le facteur d'endogénéité est élevé mais sous-critique autour de 0.8. La majorité des modèles à agents suppose implicitement que les agents interagissent à travers du prix des actifs et des volumes échangés. Certains utilisent explicitement un réseau d'interaction entre traders, sur lequel des rumeurs se propagent, d'autres, un réseau qui représente des groupes prenant des décisions communes. Contrairement à d'autres types de données, de tels réseaux, s'ils existent, sont nécessairement implicites, ce qui rend leur détection compliquée. Nous étudions les transactions des clients de deux fournisseur de liquidités sur plusieurs années. En supposant que les liens entre agents sont déterminés par la synchronisation de leur activité ou inactivité, nous montrons que des réseaux d'interactions existent. De plus, nous trouvons que l'activité de certains agents entraîne systématiquement l’activité d'autres agents, définissant ainsi des relations de type “lead-lag” entre les agents. Cela implique que le flux des clients est prévisible, ce que nous vérifions à l'aide d'une méthode sophistiquée d'apprentissage statistique. / The aim of this thesis is to study three types of clustering in foreign exchange markets, namely in price, trades arrivals and investors decisions. We investigate the statistical properties of the EBS order book for the EUR/USD and USD/JPY currency pairs and the impact of a ten-fold tick size reduction on its dynamics. A large fraction of limit orders are still placed right at or halfway between the old allowed prices. This generates price barriers where the best quotes lie for much of the time, which causes the emergence of distinct peaks in the average shape of the book at round distances. Furthermore, we argue that this clustering is mainly due to manual traders who remained set to the old price resolution. Automatic traders easily take price priority by submitting limit orders one tick ahead of clusters, as shown by the prominence of buy (sell) limit orders posted with rightmost digit one (nine).The clustering of trades arrivals is well-known in financial markets and Hawkes processes are particularly suited to describe this phenomenon. We raise the question of what part of market dynamics Hawkes processes are able to account for exactly. We document the accuracy of such processes as one varies the time interval of calibration and compare the performance of various types of kernels made up of sums of exponentials. Because of their around-the-clock opening times, FX markets are ideally suited to our aim as they allow us to avoid the complications of the long daily overnight closures of equity markets. One can achieve statistical significance according to three simultaneous tests provided that one uses kernels with two exponentials for fitting an hour at a time, and two or three exponentials for full days, while longer periods could not be fitted within statistical satisfaction because of the non-stationarity of the endogenous process. Fitted timescales are relatively short and endogeneity factor is high but sub-critical at about 0.8.Most agent-based models of financial markets implicitly assume that the agents interact through asset prices and exchanged volumes. Some of them add an explicit trader-trader interaction network on which rumors propagate or that encode groups that take common decisions. Contrarily to other types of data, such networks, if they exist, are necessarily implicit, which makes their determination a more challenging task. We analyze transaction data of all the clients of two liquidity providers, encompassing several years of trading. By assuming that the links between agents are determined by systematic simultaneous activity or inactivity, we show that interaction networks do exist. In addition, we find that the (in)activity of some agents systematically triggers the (in)activity of other traders, defining lead-lag relationships between the agents. This implies that the global investment flux is predictable, which we check by using sophisticated machine learning methods.

本篇論文基於市場上所存在的一些交易機制，探討漲跌停前後之股價行為。因為證券市場上存在一些交易規則，例如漲跌停限制、買賣價差、最小升降單位限制、競價制度等，這些交易規則，具有法定的效力，理所當然地會影響投資人的行為。這種以各種交易機制的存在，探討價格形成的過程，就是市場微結構理論之研究範疇。 本篇引用Hausman, Lo, and MacKinlay (1992)所建立之Ordered Probit模型來分析漲跌停前後之股價行為，以個股逐筆交易的價格變動為因變數，而建立因變數為間斷型之分析模型，並以等待撮合時間、交易量、落後期交易價格、買賣價差等經濟變數，來探討個股逐筆交易價格變動的成因。在此同時，鑑於以往研究多假定價量關係為線性，本研究引入非線性的概念，檢定價量之間是否存有非線線性之關係；最後，為使模型更具解釋力，我們引入異質性變異數。 第一章 緒論……………………………………………………………..1 第一節 研究動機……………………………………………..1 第二節 研究目的……………………………………………..7 第三節 研究範圍與限制……………………………………..7 第四節 研究架構與內容……………………………………..8 第二章 文獻回顧……………………………………………………….10 第一節 非同時交易………………………………………….10 第二節 最小升降單位……………………………………….11 第三節 買賣價差…………………………………………….14 第四節 漲跌停限制………………………………………….15 第五節 重要模型回顧…………………………………….…18 2.5.1 Chou(1996)……………………………………..18 2.5.2 Hausman, Lo, and MacKinlay(1992)…………..20 第三章 實證模型設定………………………………………………….25 第一節 資料來源…………………………………………….25 第二節 樣本選取…………………………………………….25 第三節 模型設定…………………………………………….26 3.3.1 價格的變動區間……………………………….26 3.3.2 解釋變數……………………………………….29 3.3.3 條件變異數的型式…………………………….32 3.3.4 價格與成交量之間非線性關係的檢定……….32 第四節 資料處理…………………………………………….33 第四章 實證分析……………………………………………………….36 第一節 模型基本統計分析………………………………….36 第二節 價量非線性關係的檢定…………………………….39 第三節 Ordered Probit模型實證分析……………………….40 第五章 結論與建議……………………………………………………..48 第一節 結論…………………………………………………..48 第二節 建議…………………………………………………..49 參考文獻…………………………………………………………………..50 / This thesis is an application of the market microstructure theory’. In light of some trading mechanisms in our stock market, such as price limit, bid-asked spread, tick size, and auction system, those trading rules would influence the behavior of investors. We want to study the process and outcomes of stock price under those explicit trading rules. We use the Ordered Probit model (Hausman, Lo, and MacKinlay, 1992) to investigate the stock behaviors when it hits price limits. We also use price change as the discrete dependent variable, and time elapsed, trading volume, lag price changes, bid-asked spread as explanatory variables. In order to make the model more explainable, heterogeneity is applied. Moreover, we also want to find out if there is any nonlinear relationship between price change and trading volume.