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1
Blazejewski, Adam. "Computational Models for Stock Market Order Submissions." Engineering, 2006. http://hdl.handle.net/2123/923.
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Doctor of PhilosophyThe motivation for the research presented in this thesis stems from the recent availability of high frequency limit order book data, relative scarcity of studies employing such data, economic significance of transaction costs management, and a perceived potential of data mining for uncovering patterns and relationships not identified by the traditional top-down modelling approach. We analyse and build computational models for order submissions on the Australian Stock Exchange, an order-driven market with a public electronic limit order book. The focus of the thesis is on the trade implementation problem faced by a trader who wants to transact a buy or sell order of a certain size. We use two approaches to build our models, top-down and bottom-up. The traditional, top-down approach is applied to develop an optimal order submission plan for an order which is too large to be traded immediately without a prohibitive price impact. We present an optimisation framework and some solutions for non-stationary and non-linear price impact and price impact risk. We find that our proposed transaction costs model produces fairly good forecasts of the variance of the execution shortfall. The second, bottom-up, or data mining, approach is employed for trade sign inference, where trade sign is defined as the side which initiates both a trade and the market order that triggered the trade. We are interested in an endogenous component of the order flow, as evidenced by the predictable relationship between trade sign and the variables used to infer it. We want to discover the rules which govern the trade sign, and establish a connection between them and two empirically observed regularities in market order submissions, competition for order execution and transaction cost minimisation. To achieve the above aims we first use exploratory analysis of trade and limit order book data. In particular, we conduct unsupervised clustering with the self-organising map technique. The visualisation of the transformed data reveals that buyer-initiated and seller-initiated trades form two distinct clusters. We then propose a local non-parametric trade sign inference model based on the k-nearest-neighbour classifier. The best k-nearest-neighbour classifier constructed by us requires only three predictor variables and achieves an average out-of-sample accuracy of 71.40% (SD=4.01%)1, across all of the tested stocks. The best set of predictor variables found for the non-parametric model is subsequently used to develop a piecewise linear trade sign model. That model proves superior to the k-nearest-neighbour classifier, and achieves an average out-of-sample classification accuracy of 74.38% (SD=4.25%). The result is statistically significant, after adjusting for multiple comparisons. The overall classification performance of the piecewise linear model indicates a strong dependence between trade sign and the three predictor variables, and provides evidence for the endogenous component in the order flow. Moreover, the rules for trade sign classification derived from the structure of the piecewise linear model reflect the two regularities observed in market order submissions, competition for order execution and transaction cost minimisation, and offer new insights into the relationship between them. The obtained results confirm the applicability and relevance of data mining for the analysis and modelling of stock market order submissions.
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Blazejewski, Adam. "Computational Models for Stock Market Order Submissions." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/923.
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The motivation for the research presented in this thesis stems from the recent availability of high frequency limit order book data, relative scarcity of studies employing such data, economic significance of transaction costs management, and a perceived potential of data mining for uncovering patterns and relationships not identified by the traditional top-down modelling approach. We analyse and build computational models for order submissions on the Australian Stock Exchange, an order-driven market with a public electronic limit order book. The focus of the thesis is on the trade implementation problem faced by a trader who wants to transact a buy or sell order of a certain size. We use two approaches to build our models, top-down and bottom-up. The traditional, top-down approach is applied to develop an optimal order submission plan for an order which is too large to be traded immediately without a prohibitive price impact. We present an optimisation framework and some solutions for non-stationary and non-linear price impact and price impact risk. We find that our proposed transaction costs model produces fairly good forecasts of the variance of the execution shortfall. The second, bottom-up, or data mining, approach is employed for trade sign inference, where trade sign is defined as the side which initiates both a trade and the market order that triggered the trade. We are interested in an endogenous component of the order flow, as evidenced by the predictable relationship between trade sign and the variables used to infer it. We want to discover the rules which govern the trade sign, and establish a connection between them and two empirically observed regularities in market order submissions, competition for order execution and transaction cost minimisation. To achieve the above aims we first use exploratory analysis of trade and limit order book data. In particular, we conduct unsupervised clustering with the self-organising map technique. The visualisation of the transformed data reveals that buyer-initiated and seller-initiated trades form two distinct clusters. We then propose a local non-parametric trade sign inference model based on the k-nearest-neighbour classifier. The best k-nearest-neighbour classifier constructed by us requires only three predictor variables and achieves an average out-of-sample accuracy of 71.40% (SD=4.01%)1, across all of the tested stocks. The best set of predictor variables found for the non-parametric model is subsequently used to develop a piecewise linear trade sign model. That model proves superior to the k-nearest-neighbour classifier, and achieves an average out-of-sample classification accuracy of 74.38% (SD=4.25%). The result is statistically significant, after adjusting for multiple comparisons. The overall classification performance of the piecewise linear model indicates a strong dependence between trade sign and the three predictor variables, and provides evidence for the endogenous component in the order flow. Moreover, the rules for trade sign classification derived from the structure of the piecewise linear model reflect the two regularities observed in market order submissions, competition for order execution and transaction cost minimisation, and offer new insights into the relationship between them. The obtained results confirm the applicability and relevance of data mining for the analysis and modelling of stock market order submissions.
3
Johnson, Ike Jay. "Essays on the microstructure of the market pre-opening period." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/essays-on-the-microstructure-of-the-market-preopening-period(4cd12b17-fd99-49d8-b395-2fbd11192228).html.
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This thesis consists of three related essays that examine investors' order submission strategies during the pre-opening period on the Malta Stock Exchange. The pre-opening is a period of liquidity formation and price discovery characterised by the absence of trade execution. The three essays collectively examine the information content of the order book in relation to: the intensity of order submissions, the aggressiveness of investors' order placement strategy and the determination of returns generated over the pre-opening period.The first essay empirically investigates if public information concerning the current state of the order book impacts the duration between order arrivals. Utilizing an augmented ACD model, the research reveals that the information which can be inferred from the characteristics of incoming orders has a more significant impact on the intensity of buy order submissions as compared to sell order submissions during the pre-opening period. Furthermore, prospective buyers appear to be more responsive to liquidity provided by the sell side than the reverse. Locked or crossed order submissions tend to increases (decreases) the intensity of order flow on the own (opposite) side of the order book, corroborating Cao et al. (2000) that such order-types contain informative signals about the fundamental value of the asset.The second essay analyses the impact of limit order book information on the aggressiveness observed in the submission, revision and cancellation of limit orders during the market pre-opening period. The empirical results indicate that the aggressiveness of order submissions and forward price revisions react both to the existing and subsequent changes in the execution probability at market opening, driven in part by the depth on either side of the order book. The aggressiveness of order cancellations increases on both sides of the order book when the depth at the top of the ask order book increases. In addition, the results suggest that the order book height and size of the inside spread impacts the aggressiveness of order submissions, revisions and cancellations.The third essay studies the contribution of the pre-opening period to the daily price discovery process and the factors that impact the return generated over this period. The results indicate that approximately one third of daily price discovery occurs in the pre-opening period. In addition, the impact of relative depth and height of the overnight and opening order book are concentrated at the top of the order book. Furthermore, cumulative changes to relative depth attributable to order submissions most significantly impact the opening returns of less actively traded stocks. The results show a strong relationship between opening returns and cumulative changes in the relative height along the order book attributable to order submissions, cancellations and forward and backward price revisions over the pre-opening period.
4
Cheung, Ming-yan William. "Market microstructure of an order driven market." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B3203782X.
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Cheung, Ming-yan William, and 張明恩. "Market microstructure of an order driven market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B3203782X.
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Wen, Quan. "Limit-order completion time in the London stock market." Thesis, Heriot-Watt University, 2009. http://hdl.handle.net/10399/2239.
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This study develops an econometric model of limit-order completion time using survival analysis. Time-to-completion for both buy and sell limit orders is estimated using tick-by-tick UK order data. The study investigates the explanatory power of variables that measure order characteristics and market conditions, such as the limitorder price, limit-order size, best bid-offer spread, and market volatility. The generic results show that limit-order completion time depends on some variables more than on others. This study also provides an investigation of how the dynamics of the market are incorporated into models of limit-order completion. The empirical results show that time-varying variables capture the state of an order book in a better way than static ones. Moreover, this study provides an examination of the prediction accuracy of the proposed models. In addition, this study provides an investigation of the intra-day pattern of order submission and time-of-day effects on limit-order completion time in the UK market. It provides evidence showing that limit orders placed in the afternoon period are expected to have the shortest completion times while orders placed in the mid-day period are expected to have the longest completion times, and the sensitivities of limit-order completion time to the explanatory variables vary over the trading day.
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Tepe, Mete. "Market Reaction To Rights Offering Announcements In The Turkish Stock Market." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614044/index.pdf.
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This study examines the market reaction to rights offering announcements in Turkey. Even though the topic is extensively studied in the finance literature, there is still research going on for emerging markets. The first part of this study measures market reaction to rights offering announcements for six different information arrival dates. The results are significantly negative except for the case of the announcement of the rights offering period. Additionally, the sample is divided into two sub-periods as before and after the 2001 crisis. The results show that there is a significant difference in market reaction and this difference is attributed to the change in economic policy after the 2001 crisis. The second part of the study examines the determinants of this market reaction and the findings suggest that bonus issues are positively related and there is also evidence that firms time their equity issues. The third part analyzes the long term performance of equity issuing firms in two subgroups as financial and non-financial firms. The results provide evidence of a negative performance and this finding is consistent with the results of previous studies.
8
Klimes, Micong. "Liquidity in the German stock market an analysis using order book data." Marburg Tectum-Verl, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?id=2987370&prov=M&dok_var=1&dok_ext=htm.
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Klimes, Micong. "Liquidity in the German stock market : an analysis using order book data /." Marburg : Tectum, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2987370&prov=M&dok_var=1&dok_ext=htm.
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Simonsen, Ola. "Stock data, trade durations, and limit order book information." Doctoral thesis, Umeå : Department of Economics, Umeå University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-839.
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Trönnberg, Filip. "Empirical evaluation of a Markovian model in a limit order market." Thesis, Uppsala universitet, Matematiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176726.
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A stochastic model for the dynamics of a limit order book is evaluated and tested on empirical data. Arrival of limit, market and cancellation orders are described in terms of a Markovian queuing system with exponentially distributed occurrences. In this model, several key quantities can be analytically calculated, such as the distribution of times between price moves, price volatility and the probability of an upward price move, all conditional on the state of the order book. We show that the exponential distribution poorly fits the occurrences of order book events and further show that little resemblance exists between the analytical formulas in this model and the empirical data. The log-normal and Weibull distribution are suggested as replacements as they appear to fit the empirical data better.
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Bury, Thomas. "Collective behaviours in the stock market: a maximum entropy approach." Doctoral thesis, Universite Libre de Bruxelles, 2014. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209341.
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Scale invariance, collective behaviours and structural reorganization are crucial for portfolio management (portfolio composition, hedging, alternative definition of risk, etc.). This lack of any characteristic scale and such elaborated behaviours find their origin in the theory of complex systems. There are several mechanisms which generate scale invariance but maximum entropy models are able to explain both scale invariance and collective behaviours.The study of the structure and collective modes of financial markets attracts more and more attention. It has been shown that some agent based models are able to reproduce some stylized facts. Despite their partial success, there is still the problem of rules design. In this work, we used a statistical inverse approach to model the structure and co-movements in financial markets. Inverse models restrict the number of assumptions. We found that a pairwise maximum entropy model is consistent with the data and is able to describe the complex structure of financial systems. We considered the existence of a critical state which is linked to how the market processes information, how it responds to exogenous inputs and how its structure changes. The considered data sets did not reveal a persistent critical state but rather oscillations between order and disorder.
In this framework, we also showed that the collective modes are mostly dominated by pairwise co-movements and that univariate models are not good candidates to model crashes. The analysis also suggests a genuine adaptive process since both the maximum variance of the log-likelihood and the accuracy of the predictive scheme vary through time. This approach may provide some clue to crash precursors and may provide highlights on how a shock spreads in a financial network and if it will lead to a crash. The natural continuation of the present work could be the study of such a mechanism.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished
13
Molander, Lukas, and Shih Jung Yape. "Toxicity Levels of Stock Markets : Observing Information Asymmetry in a Multi-Market Setting." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-209791.
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The presence of toxic order ow and predatory HFT strategies in a multi-market setting are scarcely researched in the academic world. This thesis studies the toxicity levels of a set of markets by examining unconsolidated quote data and firm specific trade data. A method for deducing the markets toxicity levels is presented along with proxies for toxic order ow, namely: changes in spread and quoted volume, following a trade in a given market. We find both signs of toxicity and different toxicity levels between the markets. However, the results are lacking in statistical significance but they show that this field is of great interest for further research. Also, the methods proposed for deducing the toxicity levels are rudimentary but could serve well as a premise for further development.Närvaron av toxic order flow och predatoriska HFT-strategier i en flermarknadsmiljö är föga studerat i den akademiska världen. Denna avhandling studerar detta på en uppsättning marknader genom att undersöka okonsoliderad quote data och firma specifika trades, och på så vis ta fram marknadernas toxicity-nivåer. En metod för att fastställa marknadernas toxicity-nivåer presenteras tillsammans med proxys för toxic order flow, mer specifikt: förändringar i spread och quotad volym, efter en handel på en given marknad. Vi finner både tecken på toxicity och olika toxicityniv åer mellan marknaderna. Resultaten saknar dock statistisk signifikans men de visar ändå på att detta område är av stort intresse för ytterligare forskning. De metoder som föreslås för att fastställa toxicity-nivåerna är rudimentära, men kan tjäna som en utgångspunkt för vidare utveckling.
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Wee, Marvin. "Institutional versus retail traders : a comparison of their order flow and impact on trading on the Australian Stock Exchange." UWA Business School, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0026.
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The objective of the thesis is to examine the trading behaviour and characteristics of retail and institutional traders on the Australian Stock Exchange. There are three aspects of these traders that are of particular interest to this study: (1) the information content of their trades, (2) their order placement strategies, and (3) the impact of their trading on share price volatility. Trades made on the basis of private information such as those by institutional traders are found to be associated with larger permanent price changes while trades by uninformed traders such as retail traders are found to be associated with smaller changes. In addition, institutional trades are found to have smaller total price effect compared to retail trades suggesting retail traders incur higher market impact costs. In order to profit from potentially short-lived information advantage, informed traders are expected to place more aggressive orders. The analysis of the order price aggressiveness showed institutions are more aggressive than other traders. In addition, retail traders are found to be less aware of the state of the market when placing aggressive orders. The analysis of the limit order book found significant differences between the contributions of institutional and retail traders to the depth of the limit-order book, with retail standing limit orders further from the market. This is consistent with the conjecture that uninformed traders such as retail traders have greater expected adverse selection costs. The effect of trading by retail and institutional traders on price volatility are also investigated. There is some evidence that retail traders are more active and institutional traders are proportionally less active after periods of high volatility. Also, the effect of the order activity from different trader types on volatility differs depending on the measure of order activity used.
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Grek, Åsa, and Abdi Jimaale. "Testing CAPM for the Swedish Stock Market In Order to Capture the Price Expectations - A Comparison Between Conditional CAPM, and Unconditional CAPM." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-47697.
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Assémat, Céline. "Management of thermal power plants through use values." Thesis, KTH, Elektriska energisystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-175811.
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Electricity is an essential good, which can hardly be replaced. It can be produced thanks to a wide rangeof sources, from coal to nuclear, not to mention renewables such as wind and solar. In order to meetdemand at the lowest cost, an optimisation is made on electricity markets between the differentproduction plants. This optimisation mainly relies on the electricity production cost of each technology.In order to include long-term constraints in the short-term optimisation, a so-called use value (oropportunity cost) can be computed and added to the production cost. One long-term constraint thatEDF, the main French electricity producer, is facing is that its gas plants cannot exceed a given numberof operation hours and starts between two maintenances. A specific software, DiMOI, computes usevalues for this double constraint but its parameters needs to be tested in order to improve thecomputation, as it is not thought to work properly.DiMOI relies on dynamic programming and more particularly on an algorithm called Bellman algorithm.The software has been tested with EDF R&D department in order to propose some modellingimprovements. Electricity and gas market prices, together with real plant parameters such as startingcosts, operating costs and yields, were used as inputs for this work, and the results were checkedagainst reality.This study gave some results but they appeared to be invalid. Indeed, an optimisation problem wasdiscovered in DiMOI computing core: on a deterministic context, a study with little degrees of freedomwas giving better profits than a study with more degrees of freedom. This problem origin was notfound precisely with a first investigation, and the R&D team expected the fixing time to be very long.The adaptation of a simpler tool (MaStock) was proposed and made in order to replace DiMOI. Thisproject has thus led to DiMOI giving up and its replacement by MaStock. Time was missing to testcorrectly this tool, and the first study which was made was not completely positive. Further studiesshould be carried out, for instance deterministic ones (using real past data) whose results could becompared to reality.Some complementary studies were made from a fictitious system, in order to study the impact of someparameters when computing use values and operations schedules. The conclusions of these studiesare the little impacts that changes in gas prices and start-up costs parameters have on the global resultsand the importance of an accurate choice in the time periods durations used for the computations.Unfortunately these conclusions might be too specific as they were made on short study periods.Further case studies should be done in order to reach more general conclusions.
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Nunes, Gustavo de Faro Colen. "Modelo da dinâmica de um livro de ordens para aplicações em high-frequency trading." reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/10570.
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As operações de alta frequência (High-Frequency Trading - HFT) estão crescendo cada vez mais na BOVESPA (Bolsa de Valores de São Paulo), porém seu volume ainda se encontra muito atrás do volume de operações similares realizadas em outras bolsas de relevância internacional. Este trabalho pretende criar oportunidades para futuras aplicações e pesquisas nesta área. Visando aplicações práticas, este trabalho foca na aplicação de um modelo que rege a dinâmica do livro de ordens a dados do mercado brasileiro. Tal modelo é construído com base em informações do próprio livro de ordens, apenas. Depois de construído o modelo, o mesmo é utilizado em uma simulação de uma estratégia de arbitragem estatística de alta frequência. A base de dados utilizada para a realização deste trabalho é constituída pelas ordens lançadas na BOVESPA para a ação PETR4.
High-frequency trading (HFT) are increasingly growing on BOVESPA (São Paulo Stock Exchange), but their volume is still far behind the volume of similar operations performed on other internationally relevant exchange markets. The main objective of this work is to create opportunities for future research and applications in this area. Aiming at practical applications, this work focuses on applying a model that governs the dynamics of the order book to the Brazilian market. This model is built based in the information of the order book alone. After building the model, a high frequency statistical arbitrage strategy is simulated to validate the model. The database used for this work consists on the orders posted on the equity PETR4 in BOVESPA.
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Colliri, Tiago Santos. "Avaliação de preços de ações: proposta de um índice baseado nos preços históricos ponderados pelo volume, por meio do uso de modelagem computacional." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/100/100132/tde-07072013-015903/.
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A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro.The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.
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Bouajila, Walid. "L'opération de négociation des valeurs mobilières sur un marché réglementé : étude comparée du droit tunisien et du droit français." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM1002.
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L'opération de négociation sur un marché réglementé des valeurs mobilières correspond à une vente originale d'un bien meuble qui présente beaucoup de particularité puisqu'elle fait appel à plusieurs mécanismes. Cette opération est basée sur l'intervention des intermédiaires spécialisés, et elle se déclenche par un ordre de bourse. La législation financière cherche toujours à garantir la sécurité et la transparence de cette opération. L'étude de l'opération dans un cadre comparée entre le droit français et le droit tunisien a montré qu'il est temps que le législateur tunisien intervient pour intégrer des notions et des normes essentielles dans la matières qui permettent à la place financière tunisienne de s'aligner sur les règles internationalesThe operation of negotiation on a market regulated by securities corresponds to an original sale of the good(property) furnish(fill) which presents a lot of peculiarity because it calls on to several mechanisms. This operation is based on the intervention of the specialized intermediaries, and it starts by a stock market order. The financial legislation always tries to guarantee the safety(security) and the transparency of this operation. The study of the operation in a frame(executive) compared between the French law and the right(straight) Tunisian showed that it's time that the Tunisian legislator intervenes to integrate(join) notions and essential standards in materials(subjects) which allow the Tunisian financial center to align themselves with the international rules(rulers)
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Shiu, Ya-Rou, and 許雅柔. "Investors' order submission behaviors in the face of open market stock repurchase in the Taiwan stock market." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/51256329454740581008.
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碩士國立東華大學
國際經濟研究所
94
Applying the intraday order data, we examine investors’ reactions to the open market stock repurchases (OMR) in the Taiwan stock market. We find that OMR announcement is a reliable signal and the market reaction to the announcement is positive, pushing up the stock prices. Foreign investors are on the net-selling side around the event days. Individual investors, security investment trust companies, and security dealers net-sell the OMR stocks before the OMR announcements and buy those after. Other institutional investors are on the net-buying side around the event days.
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Dai, Cheng-Yi, and 戴呈易. "Information transparency on the closing session, order submission and market liquidity in the Taiwan stock market." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/20644717342231338716.
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碩士銘傳大學
財務金融學系碩士班
102
To improve price efficiency, the Taiwan Stock Exchange (TSE) has revised the rule of the closing session, effective on 2/20/2012, starting from five minutes before the close, wherein real trades are replaced with a sequence of simulated call auctions. The best quotes and the indicative trading prices are disseminated on line, instead of “trading in dark” as before. If a stock’s final simulated price deviates from the previous trading price by 3.5%, the stock’s final auction will be postponed by two minutes. Because the closing price is important for the financial assets valuation, settlement of derivative financial instruments and financial risk control, this paper will study the following issues. The purposes of this paper are following. First, we examine whether the information transparency on the closing session affect the aggressive order submission behaviors and the price pressure of order imbalances. Second, we examine the order submission behaviors of liquidity suppliers and how the order submission behavior change the limit order book. Third, we document whether traders may change their activities to earlier times during the day to avoid the new systems.
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Chu, Kuo-Hua, and 朱國鏵. "The study of institutional and individual limit order submission in the Taiwan Stock Market." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/28745965156313675886.
Full textAbstract:
碩士銘傳大學
財務金融學系碩士班
100
Applying order-level data, this paper comprehensively examines the related issues on institutional and individual limit order submission in the Taiwan Stock Exchange. It was found that all of investors` the day order ratio which prefer in opening and closing during Taiwan Stock Exchange. We found limit order in all of orders which dealers and general legal person prefer aggressive limit order in opening; foreign investors, dealers and general legal person prefer limit order in closing. Between order aggressive and market conditions, investors could choose different aggressive order in big and small size`s order in different market conditions. Finally, In extremes of the market, we find that individual investors affect market liquidity after and before 30 minute and restore the market liquidity balance, the next is foreign investors.
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Chien, Jing-Syuan, and 簡靖萱. "The Momentum Effect and the Corresponding Investors’ Order Submission Strategies in the Taiwan Stock Market." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/33929310685238681711.
Full textAbstract:
碩士國立東華大學
國際經濟研究所
93
The purpose of this paper is to inspect the existence of the momentum effect in the Taiwan stock market and analyze investors’ order submission strategies for winner and loser stocks. This paper finds, first, as the government opened the financial markets to foreign investors, the momentum effect strengthened gradually. Second, the examination of order execution data confirms that individual and institutional investors tended to be contrarian and momentum traders, respectively. Domestic security dealers placed orders for winners and losers more aggressively than other investors. Individual investors’ orders, nevertheless, influenced most stock prices in an aggregate manner. Third, when the market condition changed, their submission strategies changed accordingly.
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Francisco, Paulo Manuel de Morais. "Euronext stock exchange order book and order flow dynamics." Master's thesis, 2008. http://hdl.handle.net/10400.5/17742.
Full textAbstract:
Mestrado em Gestão/MBA in FinanceThe purpose of this study is twofold. First we analyze the intraday pattems of the Euronext Stock Exchange order book in terms of relative spread and depth at the best quotes. Then we test if the order flow aggressiveness is predisposed by the current state of the order book. The order book and order flow aggressiveness is analyzed using a data sample with more than 3 million order records across the 4 main national stock market places rnanaged by Euronext. We use the cross section regressions on a set of durnmy variables to analyze the intraday pattems of the order book and the order probit rnodel to study the interaction between the order flow aggressiveness and the current state of the order book. On the contrary to the current literature, the results obtained on the intraday pattems of the order book do not reveal a "U-Shape" but rather suggest that liquidity provision is larger and the relative spread is narrower by the end of the trading session and, thus, transaction costs are srnaller at this moment when compared with the beginning of the day. The trading activity is concentrated at the beginning and by the end of the trading day exhibiting a "waxing moon" shape. The tests held over the order flow aggressiveness given the state of the order book support the idea that traders are more concemed with depth at the sarne side of the book than to the opposite side. We find as well that traders tend to submit less aggressive orders when the transient volatility is smaller avoiding to be picked offby inforrned traders. Therefore, we provide new evidence that order aggressiveness is at least partially explained by the previous state of the order book in particular by the depth on the sarne side of the book and the transient volatility.
Este estudo tem um duplo objectivo, primeiro pretende analisar o comportamento intra diário do livro de ofertas em termos de spread e profundidade nos melhores limites do livro de ordens. Segundo, pretende averiguar se a agressividade das ordens, medida através do posicionamento do seu preço face aos melhores preços oferecidos no mercado é explicado pelo estado actual do livro de ordens. No estudo é analisado o livro central de ofertas e a dinâmica das ordens introduzidas nas 4 praças nacionais da Euronext através de uma base de dados com mais de 3 milhões de ofertas introduzidas no sistema. Ao contrário da literatura recente sobre esta matéria não se encontrou evidencia de que o spread e a profundidade do livro de ordens tem um formato em U mas sim que a oferta de liquidez é maior e o spread relativo é mais estreito no final da sessão de negociação e, como tal, os custos de transacção são menores neste momento. A negociação está concentrada no início e no final da sessão exibindo um formato semelhante a uma "lua em quarto crescente". Os testes realizados sobre a agressividade das ordens sugerem que os investidores monitorizam o estado da profundidade do mercado. Contudo, preocupam-se mais com a profundidade do livro de ordens no mesmo lado da oferta do que com o lado oposto. Encontramos também evidência de que os investidores tendem a ser menos agressivos quando a volatilidade de curto prazo é maior evitando assim a negociação contra investidores mais informados. Conclui-se portanto que a agressividade das ordens é em parte explicada pelo estado actual do livro de ordens, particularmente pela profundidade do mercado na mesma ponta e pela volatilidade de curto prazo.
N/A
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Tong, Shiau-Yuan, and 童筱媛. "The determinants of order cancellation in Taiwan stock market." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/13412033931947226210.
Full textAbstract:
碩士銘傳大學
財務金融學系碩士班
100
Applying order-level data, this paper comprehensively examines the related issues on limit order cancellation in the Taiwan Stock Exchange. Evidence shows, first, that order cancellation activity has a U-shaped intraday pattern and is negatively related with the order aggressiveness, especially for foreign investors and mutual funds. Second, investors not only cancel orders more frequently if the original limit buy (sell) price is near or far away from the best bid (ask) of buy (sell) order, but adjust limit order cancellation according to firm sizes. Third, the limit order submission risk is the main determinant of order cancellation. To reduce the free-option risk and non-execution risk, traders can monitor information and prices and cancel their order as needed. But monitoring market is costly, resulting in a trade-off between the cost of monitoring and the risks of limit order submission. Final, the order cancellation behavior of the institutional is more sensitive to extremely market conditions than individuals.
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Huang, Yi-ping, and 黃逸平. "Liquidity Cost of Market Orders in Taiwan Stock Market: A Study based on An Order-Driven Agent-Based Artificial Stock Market." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/53874279455213598757.
Full textAbstract:
碩士東吳大學
財務工程與精算數學系
98
This thesis construct an order-driven artificial stock market based on Daniels et al. (2003) model. We also use autoregressive conditional duration (ACD) model initiated by Engle and Russell (1998) to model duration or order size. We analyzed the transaction cost of ten securities, including stocks, Exchange-Traded Funds (ETFs) and Real Estate Investment Trusts (REITs), in Taiwan stock market and compared this result with the simulated cost of our models. We find that for those frequently traded securities, for example, TSMC (2330.TW) or China Steel (2002.TW), it is better not to incorporate ACD model of duration in the model, and for those not frequently traded securities, for example, President Chain Store (2912.TW) or Gallop No.1 Real Estate Investment Trust Fund (01008T.TW), it is better to incorporate ACD model of duration in the model. Our empirical estimates show that the liquidity costs of market order of these ten securities are generally smaller than 3%, and largely lied between -1% and 1%. We, however, find that simulation costs of market orders in our model, with a range from 0% to 10%, are generally larger than those of real data. One possible reason for this departure is that investors in stock markets generally do not place their orders blindly. They tend to wait for the appearance of opposite order size, and then place their orders. They also tend to split up a large order, and then reduce market impact. These behavior do not exist in our simulation. Regardless of these differences, our models may still be a simulation tool for transaction cost assessment when one would like to liquidate their asset in a short span of time.
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Lin, Chung-Yueh, and 林宗岳. "Does Stock Traders’ Order Aggressiveness Predict Future Return? Evidence from an Order-driven Market." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/8952q4.
Full textAbstract:
碩士國立暨南國際大學
財務金融學系
104
Abstract This paper examines the relation between order aggressiveness, stock return and investment performance across investor classes on the Taiwan Stock Exchange. We combine the intraday order-level data, transaction-level data, and display information to construct the daily value-weighted order aggressiveness and investment performance across investor types. Our results reveal several findings: 1) Foreign investors and mutual funds are more aggressive than other institutions and individuals in both buy and sell sides. 2) There exist asymmetric effects between buy and sell orders. 3) Professional institutions’ aggressive buy orders and their large sell orders are related to the informed trading. 4) Our main results are not driven by firm size, turnover rates, and market conditions.
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Kim, Adlar J., and Christian R. Shelton. "Modeling Stock Order Flows and Learning Market-Making from Data." 2002. http://hdl.handle.net/1721.1/7271.
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Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns profitable market-making strategies when run on this model. The sequence of buys and sells for a particular stock, the order flow, we model as an Input-Output Hidden Markov Model fit to historical data. When combined with the dynamics of the order book, this creates a highly non-linear and difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks.
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Hsieh, Wei-Shan, and 謝瑋珊. "The Effect of Limit Order Cancellation on Stock Market Liquidity." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/16189831850235321227.
Full textAbstract:
碩士淡江大學
財務金融學系碩士班
103
According to our statistics, there are almost thirty percent of limit orders being cancelled in Taiwan Stock Market. Among these orders, we observe that about 35% limit orders are cancelled within one minute. Thus, we want to investigate the effect of fleeting orders on stock market. We discuss the relationship between fleeting ratio and the aggressiveness of the same side orders and the opposite ones. And we further investigate the influence of fleeting orders on liquidity. Our empirical results show that the same side orders become less aggressive and the opposite ones become more aggressive after the fleeting ratio increased. And the increase of fleeting orders will advance the stock liquidity. We confirm the effect of fleeting orders on liquidity might be caused by the traders’ reaction to fleeting orders: the same side traders submit less aggressive orders while the opposite side traders raise the aggressiveness of orders in a larger degree. Hence, the stock liquidity increases as the spread narrows, and vice versa.
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Tsai, Hung-Kai, and 蔡弘凱. "A study of order aggressiveness on the Taiwan Stock Market." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/56213735730459234738.
Full textAbstract:
碩士國立臺灣大學
財務金融學研究所
90
In an order-driven market, the investor must decide between placing a limit order and a market order. If the propensity of the investor to trade is strong, then he can choose to place a market order, but he could face the uncertainty of execution price. Limit order can be executed at a price that the investor wishes, but bear the risk of non-execution and winner’s curse. The objective of this paper is to analyze trader’s choice between limit and market orders. We not only to use the logit model, but also apply the ordered probit method to examine investor’s order aggressiveness on the Taiwan Stock Exchange. Our sample includes 4,167,880 submitted orders for 30 sampling stocks from Composite Price Average Index during the period from 1 December 1999 to 28 December 1999. The empirical results show that: 1. A higher volatility and a wider spread weakens trading aggressiveness. 2. High-trading-frequency investors are less aggressive than low-trading-frequency investors; Margin orders are more aggressive than non-margin orders. 3. For non-institutional investors, trading aggressiveness of a larger buy order tends to be higher, but trading aggressiveness of a larger sell order tends to be lower. For institutional investors, trading aggressiveness of middle-size orders is higher. 4. Investors are more aggressive in the beginning and the end of a trading day. Trading aggressiveness of buy orders is higher than sell orders in the beginning of a trading day, but trading aggressiveness of sell orders is higher than buy orders in the end of a trading day. 5. When placing a small-size order, trading aggressiveness of low-turnover stock is higher; when placing a large-size order, trading aggressiveness of low-turnover stock is lower.
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Gerig, Austin Nathaniel. "A theory for market impact : how order flow affects stock price /." 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3269903.
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Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.Source: Dissertation Abstracts International, Volume: 68-07, Section: A, page: 3065. Adviser: Alfred Hubler. Includes bibliographical references (leaves 103-106) Available on microfilm from Pro Quest Information and Learning.
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Chen, Yung-Sheng, and 陳永盛. "The Relationship between Order Imbalance and Liquidity Commonality in Taiwan Stock Market." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/45505239739818280074.
Full textAbstract:
碩士淡江大學
財務金融學系碩士班
97
After Chordia, et al. (2000) brought up the idea that commonality in liquidity was caused by existing liquidity common factors, several studies have been devoted to investigate if commonality in liquidity in NYSE also exists across different countries and different market mechanism. This study examines commonality in liquidity in Taiwan stock market by market model, using intraday data of the trading stock of listed company in 2007. Taiwan stock market is an order-driven market, which by submitting and matching orders to supply the liquidity. We investigate the relationship between order imbalance and the liquidity, based on the outcome to explain how order imbalance affects the market liquidity and results in commonality, and also providing empirical evidence for the existence of order imbalance commonality in Taiwan stock market. Our empirical results show that liquidity in commonality does exist in Taiwan stock market. The regression results are consistent with Shen and Starr (2002) that order imbalance has positive impact on spread and negative impact on depth. When order imbalance is in the market, the excessive will protect their position by increasing the spread and reduce the depth, resulting in commonality in liquidity under the clustering effect. Order imbalance commonality also exists in Taiwan stock market, and the market is more sensitive to order imbalance commonality than commonality in liquidity. The co-movement in order imbalance is much stronger in small firm and industry-specific portfolio.
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Surendran, Arun. "Low Order Modeling of Seemingly Random Systems with Application to Stock Market Securities." Thesis, 2009. http://hdl.handle.net/1969.1/148443.
Full textAbstract:
Even simple observation of stock price graphs can reveal dominant patterns. In our work, we will refer to such re-occurring, dominant patterns as “coherent structures”, a term borrowed from the theory of turbulence in fluid dynamics. Stock price performance exhibits coherent structures, which by definition make it non-random, although a price-versus-time graph might seem totally chaotic to the naked eye.
A novel low-order modeling technique for systems that are seemingly random has been developed. Though stock market data is used for the formulation and verification of the technique, its application in diverse fields is verified. The dissertation discusses some of the salient features of the novel technique along with a dynamic system analogy. The technique reduces many of the significant limitations associated with traditional methods like Fourier analysis and digital filters. Application of the technique to a nonlinear dynamical system and meteorological data are presented as well as the primary application on stock market securities.
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Chou, Chia-yu, and 周家宇. "The Relationship of Order Imbalance and Price Efficiency: Evidence from Taiwan Stock Market." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/2rkf64.
Full textAbstract:
碩士國立中央大學
財務金融學系
102
This thesis studies how daily order flows of investors affect price efficiency by using the high-frequency informational efficiency measure to capture temporary deviations from a random walk. We follow Hasbrouck (1993) and Boehmer and Kelley (2009) to use intraday transactions data to compute pricing errors through the VAR (vector autoregression) model. Order imbalance is categorized into three investor types, including individual, domestic institutional, and foreign institutional investors. After controlling other potential determinants of efficiency, the estimation results show that individual and domestic institutional investors’ order flows are significantly positive related to price discovery. With more individual and domestic institutional investors’ order flows, transaction prices move away from efficient prices, and the informational efficiency is hampered. On the other hand, foreign investors’ order imbalances are not related to price efficiency, though some foreign investors may be informed.
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Chiu, Han-Ting, and 邱菡婷. "The Application of Order Imbalance in the Stock Market for a Day-traded Strategy in the Futures Market." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/42964326795440370918.
Full textAbstract:
碩士國立成功大學
財務金融研究所
97
This study utilizes the information shown in insider trading and order imbalance to develop a profitable trading strategy for day traders. Stealth-trading hypothesis suggests that informed investors prefer trading when the liquidity trading is concentrated and that institutional investors are more informed than individual investors. Specifically, this strategy is designed to follow the trading behavior of informed investors implicitly shown in order imbalance, which is proved to be significantly related to price volatility. Then, the strategy is tested by using the data set from Taiwan Index Stock Futures (TX) during the sample period from Jan. 2001 to Dec. 2007. The empirical results in sensitivity analysis demonstrate that by capturing the implied information in insiders’ trading and order imbalance, this strategy is robustly profit. Against market’s efficiency and Wall Street wisdom, our back testing results confirm that there exists some profitable day-traded strategies even though the transaction cost is considered.
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FANG, ZAN-CI, and 方讚麒. "The TAIEX Return Predictability of Option Order Imbalance in After-hours Stock Market Trading." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/dpgbt8.
Full textAbstract:
碩士東海大學
財務金融學系
105
The predictability of the information content contained in option trading usually interests investors, especially the information content of option trading during the periods prior to the open and after the close of the stock market. By following Hu’s (2014) method, this research investigates whether the order imbalance of TAIEX options traded during the pre-open session and after-close session of the stock market possesses predictive power on subsequent TAIEX returns. According to the empirical results, both the order imbalances of options traded during the pre-open session and after-close session of the stock market positively predict the future TAIEX return. Particularly, the marginal influence of option order imbalance on TAIEX returns during the pre-open session are bigger than after-close session. We also explore the predictability of order imbalances constructed by options with varying moneyness and time-to-maturity. The empirical evidence supports that informed traders in the TAIEX option market prefer to exploit their private information by trading high-leverage options during the pre-open session of the stock market.
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Chen, Kun-You, and 陳坤佑. "The information content of order imbalance:Evidence from top 50 companies in Taiwan stock market." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/auysq5.
Full textAbstract:
碩士國立清華大學
計量財務金融學系
106
Practically,before the public get the information about the company,the informed investors will buy stock slowly to avoid uninformed investors to be aware of. Therefore, the order imbalance of volume and number of trade maybe occur some change before the price reflect the information. To verify the information content of order imbalance in Taiwan capital market, this study examine the top 50 market value of companies. The empirical result finds that the order imbalance of number and dollar have the different predictability of return of stock price in different interval. Also, the order imbalance has different sensitivity in different industry. ____________________________________________________________________ Keywords: Order Imbalance, Information Content
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Chatterjee, Devlina. "Studies On Some Aspects Of Liquidity Of Stocks : Limit Order Executions In The Indian Stock Market." Thesis, 2010. http://etd.iisc.ernet.in/handle/2005/1761.
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We study some aspects of liquidity of stocks traded through the National Stock Exchange (NSE) of India.
Initially we examine the multi-dimensional nature of liquidity by conducting day-wise factor analysis of eleven liquidity proxies across a cross-section of stocks, using data from two periods reflecting different market conditions. Five factors emerge consistently, interpretable as depth, spread, volume, price elasticity and relative activity.
Subsequently, we study execution of limit orders in the NSE from three angles.
First we consider order execution probability, using 106 stock-specific logistic models. Important predictors of order execution probability are price premium followed by volatility, relative activity, bid ask spread and order imbalance. Some differences are noted when comparing companies of different sizes and between buy and sell orders.
Second, we study order execution times using survival analysis. Several diagnostic tests indicate that parametric Accelerated Failure Time models using the log-logistic distribution for the survival time S(t) are suitable for current data. 100 stock-specific models are built; results are consistent with the logistic models. Additionally depth is also found to be important.
Finally we build 4 combined models across stocks for both execution probabilities as well as times. These models perform well on out of sample data, suggesting their predictive utility.
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Liao, Tzu-Hsiang, and 廖梓翔. "The Effect of Frequency of Order Arrival and Magnet Effect - A Study of High Price Stock and Low Price Stock in Taiwan Stock Market." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/59dq6z.
Full textAbstract:
碩士元智大學
經營管理碩士班(國際企業學程)
105
This thesis focus on intraday trading in Taiwan stock market from 2015/2/11-2015/3/31 under the 5-second clearing time. We use Ordinary Least Square (OLS) model to detect whether the individual investor or the institutional investors will influence the frequency of order arrival under magnet effect. The study also used high-priced stocks and low-priced stocks to detect the frequency of order arrival, the final results find out that both individual or institutional investors’ impact are more significant for low-priced stocks under the frequency of order arrival.
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Liao, Tzu-hsuan, and 廖子瑄. "Interaction between trading behavior of main investors and information content of limit order book in Taiwan stock market." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/5p763u.
Full textAbstract:
碩士國立中山大學
財務管理學系研究所
102
The trading strategy of the main investors of stock market became a popular is- sue recently. Many stock analysis and trading platform software have integrated the information of main investors’ trading behavior and provided it to uninformed inves- tors as trading suggestions. Since the trading behavior of main investors is mingled with small investors, few empirical studies have focused on this issue. This paper examines the interaction between the trading behavior of main inves- tors and the information content of limit order book using the record of buy and sell trading of each broker branch and intraday data from Taiwan stock market. The defi- nition of main investors is based on the concept of daily trading volume and net posi- tion, which belongs to the large traders. We find that the main investors are the most aggressive one in trading, and the trading pattern of local brokers is buying the same stock in the long run. According to the comparison of cumulative abnormal return, the head office of local brokers is the most informative stock buyer in the market. Con- cerning the limit order book information, we show that the stocks with long-term main investors are more informative than the non-main investors category. The trad- ing informativeness is higher as the longer trading period of main investors.
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Chou, Tai-Cheng, and 周泰成. "Reinvestigating the Momentum Strategy Based on Conditional Value at Risk and Higher Order Moments in Taiwan Stock Market." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/51507653925727953611.
Full textAbstract:
碩士國立臺北大學
企業管理學系
97
The goals of this paper are enhance the ability, which we focus on the stock selection criteria and the size of winner and loser portfolios, of momentum to earn excess return in Taiwan stock market and explain the momentum payoffs by higher order moments. The data sample consists of 499 include in Taiwan Stock Exchange in period January 1, 2004 to December 31, 2008. We use cumulative return, Sharpe ratio, Stable-Tail Adjusted Return ratio（STARR）, and Rachev ratio（R-ratio） to rank the stocks. STARR and R-ratio are new criteria based on conditional value at risk（CVaR）. CVaR capture better the non-normality properties of individual stock returns than the traditional mean-variance measure of Sharpe ratio, and possessing the properties of convex and coherent risk measures. We also contain seventeen portfolio size, including 10, 20,…, and 170 shares. So that we could analyze on which criteria and size momentum can perform best. We find that the best performance is when the 10 top and button performing stock shares are employed and the stock criteria is R-ratio（99%,99%）. The highest return is 7.89％ per month. We also find the returns of momentum and high return portfolio are negative skewness. And we can conclude that momentum profit may be a compensation for skewness risk.
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Wang, Yi-Hsin, and 王奕訢. "The Impact of Order Book''s Aggressiveness and Liquidity on Fleeting Orders in the Stock Market." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/56435373806961950558.
Full textAbstract:
碩士淡江大學
財務金融學系碩士班
104
Nearly 30% of limit orders in Taiwan Stock Market are cancellation orders, among which, four out of ten happen in one minute after the orders placed, so that this thesis defined cancellation orders in one minute as fleeting orders. This thesis, based on Van Ness et al. (2015), aims to investigate the factors that influence fleeting orders, by firstly exploring the effect that submit aggressiveness makes on the whole market and different kinds of investors’ fleeting orders. Orders are divided into buy orders and sell orders, which are observed respectively to find out the influence that the aggressiveness of same side orders and opposite side orders make on fleeting orders. Then the impact that cost-to-trade makes on fleeting orders in whole market and kinds of investors is also discussed. The empirical results indicate that for same side orders, either buy and sell orders, investors will increase fleeting orders when aggressiveness is bad. With regard to opposite side orders, either buy and sell orders, investors will increase fleeting orders when aggressiveness is bad. Furthermore, the reduction of cost-to-trade can result in the increase of fleeting orders. In conclusion, orders aggressiveness in Taiwan Stock Market, along with cost-to-trade, can influence market liquidity, thus changing fleeting orders in the market.
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Cheng, Yu-Hsun, and 鄭煜勳. "The Information Contents of an Open Limit Order Book and Limit Orders of Institutional and Individual Traders in Taiwan Stock Market." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/72345202021449942975.
Full textAbstract:
碩士銘傳大學
財務金融學系碩士班
99
In recent years, the financial trend of revealing the information of open limit order book causes many researchers to explore the information conent of the limit order book. Using the intraday data of Taiwan Stock Exchange,this study applies the impulse response function and forecasting error variance decomposition to explore the degree of price discovery in Taiwan stock market. In addition, this study further uses intraday data to classify various types of traders to explore the degree of price discovery from the limit orders of institutional and individual traders. As to the impulse response function, the empirical results indicate that the change of the best five bids/asks and volumes causes all the response of stock price are mixed. The results also mean that the amount of limit orders in sell side of order book not necessarily cause price to appear the fall effect in the future. As to the forecasting error variance decomposition, the empirical results reveal that the average ratio of explanation of the stock price are lower and do not exceed 3% by the best five bids/asks and volumes however in conventional, electronics or financial industry. After classifying trader, the average explain ratio of stock price by institutional traders and individual traders all appear relatively lower. The sum of the explained ratio does not exceed 2%.
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Yu, Wen-Jui, and 于文睿. "The Weekend Effect on Investor’s Order Decision in Taiwan Stock Market - Empirical Findings from The Following Two Hours after Opening on Monday." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/r5bh2z.
Full textAbstract:
碩士元智大學
經營管理碩士班(國際企業學程)
105
There are many market anomalies which exist in stock market. Weekend Effect is one of these anomalies. This study use Ordered Probit model and takes Taiwan stock market as sample to observe the Weekend Effect on four kinds of investors’ order decision. The result indicates that although the Weekend Effect is fading as time goes by, the Weekend Effect do exist in Taiwan stock market. And there are differences between the each kind of investor’s order decision due to the Weekend Effect.
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YOU, JIA-YUN, and 游家昀. "Study on the Use of PER, Revenue Growth Rate, ROE and Total Liabilities to Select Stocks and Analyze Them in Order to Improve Investment Performance in the Stock Market." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/emcnm9.
Full textAbstract:
碩士國立臺北教育大學
數學暨資訊教育學系碩士班
107
This study attempts to conduct stock selection strategies in different combinations by using the four conditions of PER, Revenue growth rate, ROE, and Total liabilities from the perspective of beginner investors, and use the screening results to match the entry and exit strategy to analyze whether it can improve investment performance. I hope that I can construct a set of directions that can be used by beginner investors when they invest. The experimental results show that companies that use the basic stock selection screen have a higher winning rate than all listed companies； After matching the entry and exit strategies, the results of positive rewards can occur.