Computational intelligent hybrid model for detecting disruptive trading activity

The term “disruptive trading behaviour” was first proposed by the U.S. Commodity Futures Trading Commission and is now widely used by US and EU regulation (MiFID II) to describe activities that create a misleading appearance of market liquidity or depth or an artificial price movement upward or downward according to their own purposes. Such activities, identified as a new form of financial fraud in EU regulations, damage the proper functioning and integrity of capital markets and are hence extremely harmful. While existing studies have explored this issue, they have, in most cases, either focused on empirical analysis of such cases or proposed detection models based on certain assumptions of the market. Effective methods that can analyse and detect such disruptive activities based on direct studies of trading behaviours have not been studied to date. There exists, accordingly, a knowledge gap in the literature. This paper seeks to address that gap and provides a hybrid model composed of two data-mining-based detection modules that effectively identify disruptive trading behaviours. The hybrid model is designed to work in an on-line scheme. The limit order stream is transformed, calculated and extracted as a feature stream. One detection module, “Single Order Detection,” detects disruptive behaviours by identifying abnormal patterns of every single trading order. Another module, “Order Sequence Detection,” approaches the problem by examining the contextual relationships of a sequence of trading orders using an extended hidden Markov model, which identifies whether sequential changes from the extracted features are manipulative activities (or not). Both models were evaluated using huge volumes of real tick data from the NASDAQ, which demonstrated that both are able to identify a range of disruptive trading behaviours and, furthermore, that they outperform the selected traditional benchmark models. Thus, this hybrid model is shown to make a substantial contribution to the literature on financial market surveillance and to offer a practical and effective approach for the identification of disruptive trading behaviour

Towards a Macro-Prudential Leading Indicators Framework for Monitoring Financial Vulnerability

The 1997 Asian financial crisis has revealed the limitations of the current state of monetary and financial monitoring system in most Asian countries in comprehensively addressing financial and monetary problems and issues. This paper attempts to propose a macro-prudential indicators (MPI) framework for monitoring vulnerability of financial markets. A literature survey on studies leading indicators has been presented. An illustrative and simple framework for analysis and interpretation of core set of 22 leading indicators (that were identified from 67 commonly agreed Asian Development Bank Indicators for selected Asia-Pacific countries, namely Fiji, Indonesia, the Philippines, Thailand, Viet Nam, and Taiwan, Province of China ) has been presented using annual time-series data for the afore-mentioned countries. A correlation and volatility analysis of Thailand’s annual and quarterly data (1994-2002) has also been performed in order to propose a simple methodology for constructing benchmarks for early warning signals and for developing a composite indicators. This above analysis carried out in this paper highlights the usefulness of MPIs as a tool for monitoring financial vulnerability.

Closing price manipulation and the integrity of stock exchanges

Allegations of market manipulation abound in the popular press, particularly during the recent financial turmoil. However, many aspects of manipulation are poorly understood. The purpose of this thesis is to enhance our understanding of market manipulation by providing empirical evidence on the prevalence, effects and determinants of closing price manipulation. The first issue examined in this thesis is the prevalence of closing price manipulation. This thesis uses a hand collected sample of prosecuted closing price manipulation cases from US and Canadian stock exchanges, and methods that explicitly model the incomplete and non-random detection of manipulation. The results suggest that approximately 1.1% of closing prices are manipulated. For every prosecuted closing price manipulation there are approximately 300 instances of manipulation that remain undetected or not prosecuted. Closing price manipulation is more prevalent on larger exchanges than smaller ones, but is detected at a higher rate on small exchanges. Second, this thesis examines the effects of closing price manipulation. Using a sample of prosecution cases, this thesis finds that closing price manipulation is associated with large day-end returns, subsequent return reversals, increases in day-end spreads and increases in day-end trading activity. At the broader level of market quality, this thesis provides evidence from a laboratory experiment that closing price manipulation decreases both price accuracy and liquidity. Even the mere possibility of manipulation decreases liquidity and increases trading costs. The third issue analysed in this thesis is the determinants of closing price manipulation and its detection. Estimating an empirical model of manipulation and detection, this thesis finds that the likelihood of closing price manipulation is increased by smaller regulatory budgets, greater information asymmetry, mid to low levels of liquidity, month-end days and lower volatility. Manipulation is more likely to be detected when regulatory budgets are larger and when the manipulation causes abnormal trading characteristics. Further evidence from laboratory experiments suggests that regulation helps restore price accuracy by deterring some manipulation and making remaining manipulation less aggressive. These experiments also show that regulation has an insignificant effect on liquidity because participants in regulated markets still face relatively high uncertainty about the presence of manipulators. This thesis also examines how closing price manipulation is conducted and how other market participants respond. It develops an index of closing price manipulation that can be used to study manipulation in markets or time periods in which prosecution data are not available. It also provides a tool for the detection of manipulation, which can be used by regulators in automated surveillance systems. Finally, this thesis has implications for economic efficiency and policy. Closing price manipulation is significantly more prevalent than the number of prosecution cases suggests. Further, it harms both pricing accuracy and liquidity and therefore undermines economic efficiency. The prevalence of closing price manipulation can be reduced by increasing regulatory budgets, improving the accuracy of market surveillance systems by using the detection tools developed in this thesis, structuring markets such that participants are better able to identify manipulation, and implementing closing mechanisms that are difficult to manipulate. These actions would enhance market integrity and economic efficiency

Closing price manipulation and the integrity of stock exchanges

Allegations of market manipulation abound in the popular press, particularly during the recent financial turmoil. However, many aspects of manipulation are poorly understood. The purpose of this thesis is to enhance our understanding of market manipulation by providing empirical evidence on the prevalence, effects and determinants of closing price manipulation. The first issue examined in this thesis is the prevalence of closing price manipulation. This thesis uses a hand collected sample of prosecuted closing price manipulation cases from US and Canadian stock exchanges, and methods that explicitly model the incomplete and non-random detection of manipulation. The results suggest that approximately 1.1% of closing prices are manipulated. For every prosecuted closing price manipulation there are approximately 300 instances of manipulation that remain undetected or not prosecuted. Closing price manipulation is more prevalent on larger exchanges than smaller ones, but is detected at a higher rate on small exchanges. Second, this thesis examines the effects of closing price manipulation. Using a sample of prosecution cases, this thesis finds that closing price manipulation is associated with large day-end returns, subsequent return reversals, increases in day-end spreads and increases in day-end trading activity. At the broader level of market quality, this thesis provides evidence from a laboratory experiment that closing price manipulation decreases both price accuracy and liquidity. Even the mere possibility of manipulation decreases liquidity and increases trading costs. The third issue analysed in this thesis is the determinants of closing price manipulation and its detection. Estimating an empirical model of manipulation and detection, this thesis finds that the likelihood of closing price manipulation is increased by smaller regulatory budgets, greater information asymmetry, mid to low levels of liquidity, month-end days and lower volatility. Manipulation is more likely to be detected when regulatory budgets are larger and when the manipulation causes abnormal trading characteristics. Further evidence from laboratory experiments suggests that regulation helps restore price accuracy by deterring some manipulation and making remaining manipulation less aggressive. These experiments also show that regulation has an insignificant effect on liquidity because participants in regulated markets still face relatively high uncertainty about the presence of manipulators. This thesis also examines how closing price manipulation is conducted and how other market participants respond. It develops an index of closing price manipulation that can be used to study manipulation in markets or time periods in which prosecution data are not available. It also provides a tool for the detection of manipulation, which can be used by regulators in automated surveillance systems. Finally, this thesis has implications for economic efficiency and policy. Closing price manipulation is significantly more prevalent than the number of prosecution cases suggests. Further, it harms both pricing accuracy and liquidity and therefore undermines economic efficiency. The prevalence of closing price manipulation can be reduced by increasing regulatory budgets, improving the accuracy of market surveillance systems by using the detection tools developed in this thesis, structuring markets such that participants are better able to identify manipulation, and implementing closing mechanisms that are difficult to manipulate. These actions would enhance market integrity and economic efficiency

Stock price manipulation:Prevalence and determinants

We empirically analyze the prevalence and economic underpinnings of closing price manipulation and its detection. We estimate that ∼1% of closing prices are manipulated, of which only a small fraction is detected and prosecuted. We find that stocks with high levels of information asymmetry and mid to low levels of liquidity are most likely to be manipulated. A significant proportion of manipulation occurs on month/quarter-end days. Manipulation on these days is more likely in stocks with high levels of institutional ownership. Government regulatory budget has a strong effect on both manipulation and detection

The Growth and Limits of Arbitrage: Evidence from Short Interest

We develop a novel methodology to infer the amount of capital allocated to quantitative equity arbitrage strategies. Using this methodology, which exploits time-variation in the cross section of short interest, we document that the amount of capital devoted to value and momentum strategies has grown significantly since the late 1980s. We provide evidence that this increase in capital has resulted in lower strategy returns. However, consistent with theories of limited arbitrage, we show that strategy-level capital flows are influenced by past strategy returns as well as strategy return volatility, and that arbitrage capital is most limited during times when strategies perform best. This suggests that the growth of arbitrage capital may not completely eliminate returns to these strategies

Decision Support Systems for Financial Market Surveillance

Entscheidungsunterstützungssysteme in der Finanzwirtschaft sind nicht nur für die Wis-senschaft, sondern auch für die Praxis von großem Interesse. Um die Finanzmarktüber-wachung zu gewährleisten, sehen sich die Finanzaufsichtsbehörden auf der einen Seite, mit der steigenden Anzahl von onlineverfügbaren Informationen, wie z.B. den Finanz-Blogs und -Nachrichten konfrontiert. Auf der anderen Seite stellen schnell aufkommen-de Trends, wie z.B. die stetig wachsende Menge an online verfügbaren Daten sowie die Entwicklung von Data-Mining-Methoden, Herausforderungen für die Wissenschaft dar. Entscheidungsunterstützungssysteme in der Finanzwirtschaft bieten die Möglichkeit rechtzeitig relevante Informationen für Finanzaufsichtsbehörden und Compliance-Beauftragte von Finanzinstituten zur Verfügung zu stellen. In dieser Arbeit werden IT-Artefakte vorgestellt, welche die Entscheidungsfindung der Finanzmarktüberwachung unterstützen. Darüber hinaus wird eine erklärende Designtheorie vorgestellt, welche die Anforderungen der Regulierungsbehörden und der Compliance-Beauftragten in Finan-zinstituten aufgreift

An empirical investigation of bubble and contagion effects in the Thai stock market

This thesis examines stock price bubbles in the Stock Exchange of Thailand (SET) from its establishment in April 1975 until December 2012 using regime-switching bubble models, on the main aggregated market index, called the SET Index, and several disaggregated stock indices by industrial sector. The results suggest some evidence of bubble-like behaviour in these indices, most especially when a structural break is included at July 1997, the date when Thailand switched to adopting a managed floating exchange rate system. Given the limitations of published stock price indices in Thailand a new, consistent index was computed the K-NI. The econometric test results using this new index indicate strong evidence of stock price bubbles in several industrial sectors and at least some evidence of bubbles in all industry groups in the SET. Finally, the standard model is extended to study the transmission of bubbles between industry groups. The results indicate some levels of contagion in the Technology sector, as well as, in several other industry groups, while the Resources sector seems to be relatively isolated

How successful is the G7 in managing exchange rates?

The paper assesses the extent to which the Group of Seven (G7) has been successful in its management of major currencies since the 1970s. Using an event-study approach, the paper finds evidence that the G7 has been overall effective in moving the US dollar, yen and euro in the intended direction at horizons of up to three months after G7 meetings, but not at longer horizons. While the success of the G7 is partly dependent on the market environment, it is also to a significant degree endogenous to the policy process itself. The findings indicate that the reputation and credibility of the G7, as well as its ability to form and communicate a consensus among individual G7 members, are important determinants for the G7’s ability to manage major currencies. The paper concludes by analyzing the factors that help the G7 build reputation and consensus, and by discussing the implications for global economic governance. JEL Classification: F31, F33, F50adjustment, communication, euro, event-study methodology, exchange rate, G7, Group of Seven, policy, success, US dollar, yen