Magíster en Ciencias de la Ingeniería, Mención Matemáticas Aplicadas / Ingeniero Civil Matemático / Se desarrolla un modelo dinámico a tiempo contínuo que permite el comercio de múltiples mercados financieros interconectados, organizados como limit order markets, en el cual agentes endógenamente toman decisiones óptimas para maximizar el valor esperado de sus ganacias. Los agentes toman sus decisiones considerando incentivos propios, condiciones de mercado, potenciales decisiones de negociación futuras y diferentes estrategias adoptadas por otros agentes. Se concentra el estudio al análisis de divulgación de profundidad y la fragmentación en el contexto de múltiples mercados. Se prueban tres escenarios principales: (i) un único mercado Transparente, (ii) un único mercado Opaco y (iii) un mercado múltiple interconectado entre una bolsa Transparente y una Opaca que comercian el mismo activo. Los resultados principales indican que, en el contexto de un único mercado, la divulgación de profundidad genera una competencia que incrementa el suministro de liquidez y, en consecuencia, reduce el spread, el ruido de mercado e incrementa la profundidad en los precios más competitivos y en el volumen total del libro. Los agentes con una valoración privada absoluta positiva del activo incrementan sus ganancias a costa de los agentes sin valoración privada, al disminuir sus costos de espera y aumentar sus ganancias por transacción. Estos beneficios son amplificados en el contexto de múltiples mercados debido a las restricciones para transar que generan una competencia más agresiva. Se encuentra que hay un flujo de liquidez hacia la componente Transparente debido a los agentes multi mercados proveedores de liquidez, lo cual reduce el spread e incrementa las profundidades. Para mantenerse atractivos, los agentes en la Bolsa Opaca también entran en competencia, lo cual reduce el spread y ruido de mercado en esta bolsa de similar manera. Los agentes multi mercados demandantes de liquidez son los que presentan el mejor rendimiento de todos, principalmente al reducir significativamente los tiempos de sus ejecuciones. / We develop a dynamic model in continuous time to simulate multi markets trading. Traders make endogenously sequential optimal decision to maximize their expected payoffs across different limit order markets, taking into account intrinsic incentives, markets conditions, potential future trading decisions and different strategies adopted by other agents. We focus our study in depth disclosure and lit fragmentation, and test three main scenarios: (i) a single Lit Market, (ii) a single Opaque Market and (iii) Multi Markets interconnected with both Lit and Opaque venues trading a single common asset. Our main results indicate that, in a single market environment, depth disclosure generates a competition that increments liquidity supply and as a consequence, reduces spread, microstructure noise and increases depth at best quotes and total depth of the book. Agents with a positive absolute private valuation of the asset increases their benefits at the expense of agents without a private valuation, by decreasing their waiting costs and increasing their money transfer. These benefits are amplified in a multi market environment due to trading restrictions that generates more aggressive competition. We find a liquidity flow to the Lit venue given by multi market liquidity suppliers, that reduces the spread and increases depths. To stay in competence agents in the Opaque Venue enter the competition as well, reducing spread and microstructure noise in that exchange too. Multi market liquidity demanders with the possibility to trade in both venues have the best performance of all agents, due to a significant reduction in their execution time.

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.

Moderne statistische und ökonometrische Methoden behandeln erfolgreich stilisierte Fakten auf den Finanzmärkten. Die vorgestellten Techniken erstreben die Dynamik von Finanzmarktdaten genauer als traditionelle Ansätze zu verstehen. Wirtschaftliche und finanzielle Vorteile sind erzielbar. Die Ergebnisse werden hier in praktischen Beispielen ausgewertet, die sich vor allem auf die Prognose von Finanzmarktdaten fokussieren. Unsere Anwendungen umfassen: (i) die Modellierung und die Vorhersage des Liquiditätsangebotes, (ii) die Lokalisierung des ’Multiplicative Error Model’ und (iii) die Erbringung von Evidenz für den empirischen Zustandsfaktorparadox über Landern. / Modern methods in statistics and econometrics successfully deal with stylized facts observed on financial markets. The presented techniques aim to understand the dynamics of financial market data more accurate than traditional approaches. Economic and financial benefits are achievable. The results are here evaluated in practical examples that mainly focus on forecasting of financial data. Our applications include: (i) modelling and forecasting of liquidity supply, (ii) localizing multiplicative error models and (iii) providing evidence for the empirical pricing kernel paradox across countries.

Stochastic fluctuations can have profound impacts on engineered systems. Nonetheless, we can achieve significant benefits such as cost reduction based upon expanding our fundamental knowledge of stochastic systems. The primary goal of this thesis is to contribute to our understanding by developing and analyzing stochastic models for specific types of engineered systems. The knowledge gained can help management to optimize decision making under uncertainty. This thesis has three parts. In Part I, we study many-server queues that model large-scale service systems such as call centers. We focus on the positive recurrence of piecewise Ornstein-Uhlenbeck (OU) processes and the validity of using these processes to predict the steady-state performance of the corresponding many-server queues. In Part II, we investigate diffusion processes constrained to the positive orthant under infinitesimal changes in the drift. This sensitivity analysis on the drift helps us understand how changes in service capacities at individual stations in a stochastic network would affect the steady-state queue-length distributions. In Part III, we study the trading mechanism known as limit order book. We are motivated by a desire to better understand the interplay among order flow rates, liquidity fluctuation, and optimal executions. The goal is to characterize the temporal evolution of order book shape on the “macroscopic” time scale.

The intention of this thesis is to provide a primitive mathematical model for a financial market in which tradings affect the asset prices. Currently, the idea of a price-volume relationship is typically used in the form of empirical models for specific cases. Among the theoretical models that have been used in stock markets, few included the volume parameter. The thesis provides a general theoretical model with the volume parameter for the intention of a broader use. The core of the model is the correlation between trading volume and stock price, indicating that volume should be a function of the stock price and time. This function between price and time was made visible by the use of the trading volume process, also known as the Limit Order book. The development of this model may be of some use to investors, who could build their wealth process based on the dynamics of the process found through a Limit Order Book. This wealth process can help them build an optimal trading strategy design.

High Frequency Trading (HFT) algorithms are automated feedback systems interacting with markets to maximize returns on investments. These systems have the potential to read different resolutions of market information at any given time, where Level I information is the minimal information about an equity--essentially its price--and Level II information is the full order book at that time for that equity. This paper presents a study of using Recurrent Neural Network (RNN) models to predict the spread of the DOW Industrial 30 index traded on NASDAQ, using Level I and Level II data as inputs. The results show that Level II data does not significantly improve the prediction of spread when predicting less than 100 millisecond into the future, while it is increasingly informative for spread predictions further into the future. This suggests that HFT algorithms should not attempt to make use of Level II information, and instead reallocate that computation power for improved trading performance, while slower trading algorithms may very well benefit from processing the complete order book.

We study optimal order placement in a limit order book. By modelling the limit order book dynamics as a Markov chain, we can frame the purchase of a single share as a Markov Decision Process. Within the framework of the model, we can estimate optimal decision policies numerically. The trade rate is varied using a running cost control variable. The optimal policy is found to result in a lower cost of trading as a function of the trade rate compared to a market order only strategy. / Vi studerar optimal orderläggning i en limit orderbok. Genom att modellera dynamiken av inkommande ordrar som en Markov kedja så kan vi formula optimal orderläggning som en Markov Decision Process. Inom ramverket av modellen så kan vi skatta optimala strategier numeriskt. En löpande kostnad används som en kontrollvariabel för handelstakten av den optimala strategin. Vi finner att den optimala strategin resulterar i en lägre handelskostnad som funktion av deltagande jämfört med en marknadsorder strategi.

Diese Arbeit enthält vier Aufsätze über die Beziehungen zwischen Handelsstrategien auf Aktienmärkten und dem Zustand des Marktes. Es werden ökonometrische Methoden angewendet um den Markteinfluss von limit order Platzierungen, die Eigenschaften von limit ordern sowie die Verwendung von versteckten ordern zu analysieren. Im Kapitel 1 quantifizieren wir die Effekte der limit order Platzierung auf Preisquotierungen am Börsenplatzes Euronext. Wir zeigen, dass eine limit order signifikante Informationen enthält und illustrieren inwieweit ihr Einfluss auf den Markt von ihren Charakteristika und dem Zustand des Orderbuchs abhängt. Das Kapitel 2 enthält empirische Resultate über die limit order Aktivität und den Markteinfluss von limit orders an der New Yorker NASDAQ Börse. Wir dokumentieren, dass Marktteilnehmer die Platzierung von limit orders mit kleinen Volumina präferieren, diese aber sofort nach ihrem Einsatz wieder löschen. Basierend auf der geschätzten Marktauswirkung einer limit order schlagen wir eine Methode zur Prognose ihres optimalen Volumens vor. Im Kapitel 3 werden die limit order-Strategien von Marktteilnehmern in intransparenten Märkten untersucht. Wir zeigen, dass die Position der sogenannten versteckten Liquidität im Orderbuch von diversen Variablen abhängt, die den Zustand des Marktes beschreiben. Die Daten suggerieren, dass Händler die Platzierung sogenannter hidden orders im Hinblick auf günstige Liquidität am Markt und dem "picking-off"-Risiko ausbalancieren. Im letzten Kapitel 4 präsentieren wir ein Softwaresystem zur Rekonstruktion von Orderbüchern und zur Extrahierung von Orderflussinformationen aus message stream Daten. Die Basismodule des Systems basieren auf allgemeinen Orderbuch-Ereignissen. Sie sind abstrakt gehalten und können so einfach auf beliebige Märkte mit elektronischen Orderbüchern angewendet werden. / In four essays, this thesis examines the interaction between traders'' strategies and the state of market by the econometric analysis of maket impact of limit order submission, the typical properties of order flow and the traders'' usage of hidden orders. Chapter 1 quantifies short-term and long-term effects of limit order submissions on quotes in Euronext. We show that limit orders have significant information content and the maginitude of their impact on the quotes depends on both the order''s characteritics and the state of limit order books (LOBs). Chapter 2 provides new empirical evidence on order submission activities and market impacts of limit orders at NASDAQ. We find that traders dominantly submit small size limit orders and cancell most of them immediately after submission. Based on the estimated market impact of orders, we propose a method to predict the optimal size of a limit order conditional on its position in the LOB and the desired impact. Chapter 3 analyzes traders'' decisions on using undisclosed orders in opaque markets. Our empirical findings show that market conditions affect traders'' order submission strategies and suggest that traders balance their hidden order placements to compete for the provision of liquidity and protect themselves against picking-off risk. Chapter 4 presents a program framework for reconstructing LOBs as well as extracting order flow information from message stream data. We design the basic modules of the system in an abstract layer based on common order events in limit order markets, so that it can be easily adapted to data at any limit order markets.

Neste trabalho, apresentamos um conjunto de fatos empíricos e propriedades estatística de negociações em alta frequência, e discutimos algumas questões gerais comuns a dados de alta frequência tais: como discretização, espaçamento temporal irregular, durações correlacionadas, periodicidade diária, correlações temporais e as propriedades estatísticas dos fluxos de ordens. Logo apresentamos dois modelos da literatura,estilizados para a dinâmica do limit order book. No primeiro modelo os fluxo de ordens é descrito por processos de Poisson independentes, propomos para ele uma forma alternativa da prova de ergodicidade basejada em funções de Lyapunov. O segundo modelo é um modelo reduzido que toma em consideração dinâmicas tipo difusão para os tamanhos do bid e ask, e se foca só nas ordens como melhores preços, e modela explicitamente as cotações do bid e ask na presença de liquidez oculta. E por ultimo, propomos um modelo alternativo para a dinâmica do preço e do spread no limit order book, estudamos o comportamento assintótico do modelo e estabelecemos condições de ergodicidade e transitoridade. Além disso, consideramos a uma família de cadeias de Markov definidos nas sequências de caracteres (strings, ou palavras) com infinito alfabeto e para alguns exemplos inspirados nos modelos de negociações em alta frequência, obtemos condições para ergodicidade, transitoriedade e recorrência nula, para a qual usamos as técnicas de construção de funções Lyapunov. / In this work, we present a set of empirical facts and statistical properties of negotiations at high frequency and discuss some general issues common to high-frequency data such: as discretization, irregular spacing, correlated durations, daily periodicity, temporal correlations and the statistical properties of flows orders. Soon we present two models stylized in the literature for the dynamic limit order book. In the first model the order flow described by separate Poisson processes and we propose it to an alternative form of test ergodicity based on Lyapunov function. The second model is a reduced model that takes into consideration diffusion-type dynamics for the sizes of the bid and ask, and focus only on orders as best price and model explicitly quotes the bid and ask in the presence of hidden liquidity. And finally, we propose an alternative model for the price dynamics and spread in the limit order book, we study the asymptotic behavior of the model and established conditions of ergodicity. Furthermore, we consider the a family of Markov chains defined on the sequences of characters (strings, or words) with infinite alphabet. For some examples inspired by the models of high frequency trading we obtain a conditions for ergodicity, transience and null-recurrence. In order to prove this we use the construction of Lyapunov functions techniques.