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This dissertation investigates the effects of frictions that emerge from financial markets on business-cycle fluctuations. The purpose of Chapter 1 is to situate my work in the literature and to stress its contributions. In Chapter 2, I reassess the role of financial frictions in amplifying the impacts of productivity shocks using a framework in which a fraction of firms are borrowing-constrained and land is a collateral asset. A first finding is that amplification effects are much lower when land is supplied elastically. However, financial shocks that affect the maximum allowable ratio of loans to collateral have greater effects on output. Another result pertains to the role of the elasticity of substitution between land and capital in responses to financial shocks: lower values generate greater output responses. While Chapter 2's environment is set up to be in a closed-economy, the last two chapters involve two-country settings. Chapter 3 still intersects with Chapter 2 on some dimensions, in particular, land dynamics and financial frictions that feature borrowing-constrained firms. The borrowing mechanism brings about a distortion in labour markets that interacts with a class of preferences that are non-separable between consumption and leisure. Technology shocks contribute to explain international co-movements, whereas financial shocks allow the model to replicate the lack of international risk sharing that is characterized by the quantity anomaly and the Backus-Smith puzzle. In Chapter 4, I apply Chari, Kehoe and McGrattan’s (2007) business cycle accounting method to a two-country, two-good real business cycle model. Using their approach, I measure the same closed-economy time-varying wedges and I introduce an international wedge that accounts for discrepancies between the growth in real exchange rates and in the stochastic discount factors ratio. In fact, the effects of financial frictions embedded in Chapter 3's framework can be retrieved from a combination of labour and investment wedges. The volatility of the international wedge corresponds to a metric of bilateral risk sharing. An important finding is that, from a non-separable preferences specification of the baseline model, the investment wedge partly accounts for the Backus-Smith puzzle. This suggests that distortions in national capital markets are important to consider for international risk sharing. / Thesis (Ph.D, Economics) -- Queen's University, 2013-04-29 22:56:23.03

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.

In this thesis, we study random bridges of a certain class of Lévy processes and their applications to credit risky asset pricing. In the first part, we construct the compound random bridges(CLRBs) and analyze some tools and properties that make them suitable models for information processes. We focus on the Markov property, dynamic consistency, measure changes and increment distributions. Thereafter, we consider applications in credit risky asset pricing. We generalize the information based credit risky asset pricing framework to incorporate prematurity default possibilities. Lastly we derive closed-form expressions for default trends and intensities for credit risky bonds with CLRB as the background partial information process. We obtain analytical expressions for specific CLRBs. The second part looks at application of stochastic filtering in the current information based asset pricing framework. First, we formulate credit risky asset pricing in the information-based framework as a filtering problem under incomplete information. We derive the Kalman-Bucy filter in one dimension for bridges of Lévy processes with a given finite variance.

Three distinct but interrelated studies with their foundations in recent developments in the South African capital markets are presented in this thesis. The first study presents an empirical analysis of the systemic risk exposures and contributions of 125 financial institutions between 2003 and 2018. Using two popular measures of systemic risk, the marginal expected shortfall (MES) and conditional capital shortfall (SRISK), it is shown that banking institutions are collectively the largest contributors to systemic risk in the financial system. Surprisingly, further analysis reveals that despite the high levels of market concentration and interconnectedness, SRISK increases are not propagated across sectors. Notwithstanding the foregoing, the results provide support for previous empirical findings of the systemic importance of banking institutions. In addition, causality analysis of the relationship between SRISK in the banking sector and the prime lending rate provides new evidence that complements previous theories of systemic risk spillovers into the real economy, specifically through lending activity. Overall, the results illustrate the potential for the use of market based measures in supporting macroprudential oversight and informing policy decisions. The second essay addresses questions related to misconduct contagion and crowding. Crowding is a form of clustering in which the behaviour of market participants leads to congestion on one side of the market, otherwise known as crowded trades. We propose a measure of crowding, based on intraday trade data and use the measure to study changes in the trading environment following allegations of misconduct. Evidence of coincidental and significant changes in crowding and trade volumes is reported in the first set of empirical results, consistent with the notion of information contagion and how firm-specific developments may have significance for other firms. More importantly, the study demonstrates empirically, that crowding increases exposure to adverse spillover effects and deteriorates liquidity in the equity market. We further contributes to the literature, by documenting novel evidence of the asymmetric effects of intraday volatility and trade volume on MES and quoted spreads, respectively, that is dependent on the crowd direction. Relative to buy-crowds, sellcrowds amplify the effect volatility has on MES and reduce the effect trade volume has on quoted spreads. In the third study, the aim is to investigate the implications of domestic crosslistings for the market quality of twenty-six firms that cross-listed between April 2018 and April 2020, following a series of amendments to legislation. Evidence of significant improvements in market quality in the six months after a cross limited, even after adjusting for market quality changes of firms that do not cross-list. Additionally, our results offer no support for the hypothesis that there is a significant difference in market quality changes observed for high and low liquidity firms, in contrast to previous cross-listing studies. Lastly, by consolidating order books across exchanges, it is shown that the price dimension of execution quality can be improved across all venues, even after controlling for liquidity characteristics. We conclude that interoperability between venues can be effective in reducing the cost of trading, and is therefore necessary for a domestic cross-listing to be worthwhile. Collectively, the findings contribute to the ongoing debate around best execution standards and inter-market competition in South Africa's equity market.

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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