Abstract A stochastic model for orderbook dynamics is proposed in Cont et al.(2010) and empirically evaluated in thisthesis. Arrival rates of limit, marketand cancellation orders are described interms of a Markov chain where thearrival rates are exponentiallydistributed. The model not onlyconsiders the best bid and ask queuesbut also additional price levels of theorder book. Methods for computingseveral quantities important to highfrequency trading are proposed usingLaplace transforms and continuedfractions. These quantities includeconditional probabilities such as theprobability of a price increasedepending on the profile of the orderbook. Computing these probabilities aresupposed to be easy enough to computeanalytically. However this was not thecase. We failed in the inversion of theLaplace transform methods and the mainreason is that the instructions in Contet al. (2010) are not adequate when itcomes to perform the inversion. Hence wedraw the conclusion that the method isno good for predicting short termbehavior of limit order books. For longterm applications the model can be usedto simulate the order book with goodresults.

"On a stock exchange, trading activity has an impact on stock prices. Market agents place limit orders, which come in the form of bids and asks. These orders wait in the market to be executed when another agent agrees to fulfill the transaction. We examine an "inventory-based" quoting strategy model developed by Marco Avellaneda and Sasha Stoikov. We expand on their work by developing a method to calibrate the model to market data using limit order data provided by Morgan Stanley. We consider solving a least squares problem which fits the model to the data using a sensitivity parameter."

We analyse the steady-state behaviour of two different models with collaborating queues: that is, models in which 'customers' can be served by many types of 'servers', and 'servers' can process many types of 'customers'. The first example is a large-scale service system, such as a call centre. Collaboration is the result of cross-trained staff attending to several different types of incoming calls. We first examine a load-balancing policy, which aims to keep servers in different pools equally busy. Although the policy behaves order-optimally over fixed time horizons, we show that the steady-state distribution may fail to be tight on the diffusion scale. That is, in a family of ever-larger networks whose arrival rates grow as O(r) (where r is a scaling parameter growing to infinity), the sequence of steady-state deviations from equilibrium scaled down by sqrt(r) is not tight. We then propose a different policy, for which we show that the sequence of invariant distributions is tight on the r (1/2+epsilon) scale, for any epsilon > 0. For this policy we conjecture that tightness holds on the diffusion scale as well. The second example models a limit order book, a pricing mechanism for a single-commodity market in which buyers (respectively sellers) are prepared to wait for the price to drop (respectively rise). We analyse the behaviour of a simplified model, in which the arrival events are independent of each other and the state of the limit order book. The system can be represented by a queueing model, with 'customers' and 'servers' corresponding to bids and asks; the roles of customers and servers are symmetric. We show that, with probability 1, the price interval breaks up into three regions. At small (respectively large) prices, only finitely many bid (respectively ask) orders ever get fulfilled, while in the middle region all orders eventually clear. We derive equations which define the boundaries between these regions, and solve them explicitly in the case of iid uniform arrivals to obtain numeric values of the thresholds. We derive a heuristic for the distribution of the highest bid (respectively lowest ask), and present simulation data confirming it.

Title: Volatility bursts and order book dynamics Author: Jana Plačková Department: Department of Probability and Mathematical Statistics Supervisor: Dr. Jan M. Swart Supervisor's e-mail address: swart@utia.cas.cz Abstract: The presented paper studies the dynamics of supply and demand through the electronic order book. We describe and define the basic rules of the order book and its dynamics. We also define limit and market orders and describe the differences between them and how they influenced the evolution of ask, bid price and spread. Next part of the paper is dedicated to the de- scription and definition of volatility and its basic models. The brief overview about volatility clustering and its modeling by economists and physicists can be found in the following part. In the last part we introduce a simple model of order book in which we observe ask, bid price and spread. Then we study the empirical distribution of spread and try to find its probability distribu- tion. The volatility clustering is then observed through the relative returns of spread. In the last part we introduce some possible improvement of the model. Keywords: volatility clustering, order book, limit orders, market orders 1

Doctor of Philosophy / This dissertation presents the results of three empirical studies on price formation and liquidity in financial futures markets. The research entails three related areas: the effect of taxes on the prices of Australian stock index futures; the efficiency of the information transmission mechanism between the cash and futures markets; and the price and liquidity impact of large trades in interest rate and equity index futures markets. An overview of previous research identifies some important gaps in the existing literature that this dissertation aims to resolve for the benefit of arbitrageurs, investment managers, brokers and regulators.

Doctor of Philosophy / This dissertation presents the results of three empirical studies on price formation and liquidity in financial futures markets. The research entails three related areas: the effect of taxes on the prices of Australian stock index futures; the efficiency of the information transmission mechanism between the cash and futures markets; and the price and liquidity impact of large trades in interest rate and equity index futures markets. An overview of previous research identifies some important gaps in the existing literature that this dissertation aims to resolve for the benefit of arbitrageurs, investment managers, brokers and regulators.

Main goal of this thesis is improvement of an order book model so that it behaved more realistically, based on a model developed by J. Plačková in her diploma thesis in 2011. We consider this simple model for evolution of order book in which limit orders of unit size arrive according to independent Poisson processes. Frequency of buy limit orders below resp. sell limit orders above a given price level is described by demand and supply functions. Buy (resp. sell) limit orders that arrive with price above (resp. below) the current ask (resp. bid) price are converted into market orders and cancellation of orders is not allowed. We extend this model by introducing market makers who place at the same time one buy and one sell limit order with current bid and ask prices. We show how introducing market makers reduces the spread that in the original model was unrealistically large and also show a method of calculating the precise rate of market makers needed to reduce the spread to zero. 1

Using NASDAQ high frequency trading (HFT) and minute-by-minute Limit Order Book (LOB) data over 120 sample stocks in 10 weeks between 2008-2010, including the week of the Lehman Brothers crisis, we study how trading activities of HFTs, NHFTs (Non-HFTs) and their order placements interact, and affect overall market quality. We capture order placements via the depth (step) and the height (price) dimensions along the LOB. We first document that HFTs are active not only at the top of the LOB, but their orders are placed along the LOB with an average around the 5th step, slightly ahead of NHFTs who on average are close to the 6th step. Generally, both HFTs and NHFTs are more aggressive in order placement with large stocks and hidden orders and HFT orders are further ahead during the crisis week, though price-wise they all back off somewhat with more conservative placements by NHFTs. In market turmoil, whenever HFTs see NHFTs trade among themselves, they become less aggressive in order placement. However, when HFTs trade, other HFT orders become more aggressive by moving ahead. On the contrary, NHFTs generally become more aggressive when other NHFTs supply liquidity in trading, and more conservative when HFTs are the supplier. We find mixed results on the impact of HFTs order placements and trading activities on market quality by different measures, but aggressive orders by HFTs and NHFTs both are related with decreases in short-term market volatility. Our findings highlight the importance of not only studying HFTs and NHFTs activities along the LOB, but also in both depth and height dimensions, instead of only at the market inside quotes.

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Cette thèse est composée de deux parties reliées, le premier sur le carnet d'ordre et le deuxième sur les effets de valeur de tick. Dans la première partie, nous présentons notre cadre de modélisation de carnet. Le modèle queue-réactive est d'abord introduit, dans laquelle nous révisons l'approche zéro intelligence traditionnelle en ajoutant dépendance envers l'État de carnet. Une étude empirique montre que ce modèle est très réaliste et reproduit de nombreuses fonctionnalités intéressantes microscopiques de l'actif sous-jacent comme la distribution du carnet de commandes. Nous démontrons également qu'il peut être utilisé comme un simulateur de marché efficace, ce qui permet l'évaluation de la tactique de placement complexes. Nous étendons ensuite le modèle de queue-réactive à un cadre markovien général. Conditions de Ergodicité sont discutés en détail dans ce paramètre. Dans la deuxième partie de cette thèse, nous sommes intéressés à étudier le rôle joué par la valeur de la tique à deux échelles microscopiques et macroscopiques. Tout d'abord, une étude empirique sur les conséquences d'un changement de la valeur de tick est effectuée à l'aide des données du programme pilote de réduction de la taille 2014 tick japonais. Une formule de prédiction pour les effets d'un changement de valeur de tique sur les coûts de transactions est dérivé. Ensuite, un modèle multi-agent est introduit afin d'expliquer les relations entre le volume du marché, la dynamique des prix, spread bid-ask, la valeur de la tique et de l'état du carnet d'ordres d'équilibre. / This thesis is made of two connected parts, the first one about limit order book modeling and the second one about tick value effects. In the first part, we present our framework for Markovian order book modeling. The queue-reactive model is first introduced, in which we revise the traditional zero-intelligence approach by adding state dependency in the order arrival processes. An empirical study shows that this model is very realistic and reproduces many interesting microscopic features of the underlying asset such as the distribution of the order book. We also demonstrate that it can be used as an efficient market simulator, allowing for the assessment of complex placement tactics. We then extend the queue-reactive model to a general Markovian framework for order book modeling. Ergodicity conditions are discussed in details in this setting. Under some rather weak assumptions, we prove the convergence of the order book state towards an invariant distribution and that of the rescaled price process to a standard Brownian motion. In the second part of this thesis, we are interested in studying the role played by the tick value at both microscopic and macroscopic scales. First, an empirical study of the consequences of a tick value change is conducted using data from the 2014 Japanese tick size reduction pilot program. A prediction formula for the effects of a tick value change on the trading costs is derived and successfully tested. Then, an agent-based model is introduced in order to explain the relationships between market volume, price dynamics, bid-ask spread, tick value and the equilibrium order book state.