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A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in the Faculty of Science, School of Computer Science and Applied Mathematics University of the Witwatersrand. October 2016. / Automated algorithmic trade execution is a central problem in modern financial markets, however finding and navigating optimal trajectories in this system is a non-trivial task. Many authors have developed exact analytical solutions by making simplifying assumptions regarding governing dynamics, however for practical feasibility and robustness, a more dynamic approach is needed to capture the spatial and temporal system complexity and adapt as intraday regimes change. This thesis aims to consolidate four key ideas: 1) the financial market as a complex adaptive system, where purposeful agents with varying system visibility collectively and simultaneously create and perceive their environment as they interact with it; 2) spin glass models as a tractable formalism to model phenomena in this complex system; 3) the multivariate Hawkes process as a candidate governing process for limit order book events; and 4) reinforcement learning as a framework for online, adaptive learning. Combined with the data and computational challenges of developing an efficient, machine-scale trading algorithm, we present a feasible scheme which systematically encodes these ideas. We first determine the efficacy of the proposed learning framework, under the conjecture of approximate Markovian dynamics in the equity market. We find that a simple lookup table Q-learning algorithm, with discrete state attributes and discrete actions, is able to improve post-trade implementation shortfall by adapting a typical static arrival-price volume trajectory with respect to prevailing market microstructure features streaming from the limit order book. To enumerate a scale-specific state space whilst avoiding the curse of dimensionality, we propose a novel approach to detect the intraday temporal financial market state at each decision point in the Q-learning algorithm, inspired by the complex adaptive system paradigm. A physical analogy to the ferromagnetic Potts model at thermal equilibrium is used to develop a high-speed maximum likelihood clustering algorithm, appropriate for measuring critical or near-critical temporal states in the financial system. State features are studied to extract time-scale-specific state signature vectors, which serve as low-dimensional state descriptors and enable online state detection. To assess the impact of agent interactions on the system, a multivariate Hawkes process is used to measure the resiliency of the limit order book with respect to liquidity-demand events of varying size. By studying the branching ratios associated with key quote replenishment intensities following trades, we ensure that the limit order book is expected to be resilient with respect to the maximum permissible trade executed by the agent. Finally we present a feasible scheme for unsupervised state discovery, state detection and online learning for high-frequency quantitative trading agents faced with a multifeatured, asynchronous market data feed. We provide a technique for enumerating the state space at the scale at which the agent interacts with the system, incorporating the effects of a live trading agent on limit order book dynamics into the market data feed, and hence the perceived state evolution. / LG2017

Boston University. University Professors Program Senior theses. / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / 2031-01-02

A dissertation submitted in fulfillment of the requirements of the degree of Master of Science in the School of Computer Science and Applied Mathematics March 22, 2017 / Agent-based models, particularly those applied to financial markets, demonstrate the ability to produce realistic, simulated system dynamics, comparable to those observed in empirical investigations. Despite this, they remain fairly difficult to calibrate due to their tendency to be computationally expensive, even with recent advances in technology. For this reason, financial agent-based models are frequently validated by demonstrating an ability to reproduce well-known log return time series and central limit order book stylized facts, as opposed to being rigorously calibrated to transaction data. We thus apply an established financial agent-based model calibration framework to a number of intraday agent-based models employing realistic order matching procedures and demonstrate that while the parameters of these models rooted in market microstructure can indeed be meaningfully calibrated, those exclusively related to agent behaviors and incentives remain problematic, due to the presence of parameter degeneracies not identified by stylized fact-centric validation. We further argue that the observed parameter degeneracies are likely a consequence of the realistic matching processes employed in these models, which suggests that alternative approaches to linking data, phenomenology and market structure may be necessary and that the stylized fact-centric validation of intraday agent-based models is insufficient. / MT 2017

This thesis consists of three papers addressing different aspects of financial markets and macroeconomic activities. Firm Risks, Credit, and Labor Market Fluctuations studies the effect of changes in firm risks on the cyclical properties of the labor market. I develop a general equilibrium model in which the adjustment of employment is costly. Financial frictions arise from the limited liability property of the contract between lenders and firms. The changes in firm risks alter the amount of debt that firms can borrow to finance their working capital. This mechanism amplifies labor market fluctuations and displays a countercyclical external finance premium, consistent with the empirical evidence. Shadow Banks and Stabilization Policies studies the interaction between commercial banks and shadow banks and the effect of stabilization policies. I develop a general equilibrium model in which the shadow banks obtain loans from commercial banks in the form of short-term collateralized debt. The moral hazard creates volatile leverage of shadow banks, which makes the economy more vulnerable to economic shocks. Upon an aggregate disturbance, a stabilization policy in the form of direct lending is relatively more efficient than policies aimed at the shadow-banking sector. Bank Capital and Lending: An Analysis of Commercial Banks in the United States empirically evaluates the impact of bank capital on lending patterns of commercial banks in the United States. Using two different measures of capital, namely the capital adequacy ratio and tier 1 ratio, we find a moderate relationship between bank equity and lending. We also use an innovative instrumental variables methodology that helps us overcome the endogeneity issues that are common in such analyses.

This article examines the liberalization and cross-border integration of European financial markets from a political-economic perspective. Three features particularly come to the fore: First, national liberalization and European integration have been two sides of one integrated political process that owes its specific dynamics to the conflicts of interest between different groups of actors. Second, not only effective liberalization, but also market integration relies on an extension and formalization of public financial market regulation – and thus seemingly on ‘more state’. Third, the established distinction between ‘state’ and ‘market’ and their respective roles is insufficient for a proper understanding for the politics of financial market regulation.

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Insider dealing has been in the public eye for many years now. The impact of Big Bang and the growth of financial conglomerates has, however, propelled the practice to the very forefront of regulatory concern. Regulators are faced with a dilemma: financial conglomerates bring with them many economic benefits, but they also accentuate the problem of insider dealing, in that the greater availability of inside information within these open ended financial houses, increases the scope for its misuse. Regulators must ensure that the regulation imposed does not overly impede the benefits to be gained from conglomeration; yet they must ensure that regulation is sufficiently stringent to provide a fair market place. The Chinese Wall - a self-styled mechanism consisting of policies procedures designed to stop the flow of inside information within financial conglomerates - is singled out for special treatment. The legal and policy problems associated with the use of the mechansim are reviewed. These revolve around two main issues: (i) Is the Wall an effective policy device to rebut allegations of insider dealing in a financial conglomerate where Arm A is dealing in shares in Company X while arm B has information pertaining to Company X. (ii) If the Chinese Wall actually works, does the operation of the mechanism give rise to breach of fiduciary obligations ie. to what extent does the operation of the Chinese Wall in conglomerates modify traditional fiduciary law. The conclusion reached is that the Chinese Wall offers regulators the best solution to the problem of conflicts of interest and obligation in fully fledged financial conglomerates. The Wall must, however, be 'strengthened' to prevent, for example, a coroprate fiduciary dealing for its own account where another department within the conglomerate has a material interest in the transaction. At common law, the courts ought to, and probably would, accept this approach. However in an action brought under the SIB rulebook, and the rulebooks made thereunder, it would seem that the courts are bound to accept a Wall per se (ie. without being strengthened) as valid. To the extent that this differs from what ought to be the position at common law, the SIB rulebook should be modified. A tentative import of economic analysis is used to complement the largely legal analysis. In this way it is hoped to gain a better grasp of the policy issues under study.