2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr)

27-28 March 2014

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  • [Front cover]

    Publication Year: 2014, Page(s):1 - 2
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  • General chair welcome message

    Publication Year: 2014, Page(s): 1
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  • Organizing Committees

    Publication Year: 2014, Page(s):1 - 3
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  • Speakers

    Publication Year: 2014, Page(s): 1
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    Provides an abstract for each of the presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • Best Paper Awards

    Publication Year: 2014, Page(s): 1
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  • Contents

    Publication Year: 2014, Page(s):i - v
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  • 2014 CIFEr opening address

    Publication Year: 2014, Page(s): vii
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    Alex Lipton is Managing Director, Quantitative Solutions Executive at Bank of America and a Visiting Professor of Quantitative Finance at University of Oxford. Prior to his current role, he was Managing Director, Co-Head of the Global Quantitative Group at Bank of America Merrill Lynch, and a Visiting Professor of Mathematics at Imperial College London. Previously, he was Managing Director and Hea... View full abstract»

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  • Systemic risk identification, modelling, analysis, and monitoring: An integrated approach

    Publication Year: 2014, Page(s): viii
    Cited by:  Papers (1)
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    Over the last fifteen years, computational intelligence applications have proliferated solutions to financial engineering problems, bringing a new fertile area of collaboration between professional engineering and financial communities. Computational systems based on machine learning techniques have become indispensable in virtually all financial applications, from portfolio selection to proprieta... View full abstract»

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  • Dynamic stochastic programming tools for individual asset liability management

    Publication Year: 2014, Page(s): ix
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    Summary form only given. Recent times have seen the transfer of risks to individual households as the unintended consequences of pension reforms and new rules for regulation of financial advisory companies. We present new theory and technology for individual Asset Liability Management (iALM) which addresses these critical issues for individuals. The iALM tool uses a cutting edge dynamic stochastic... View full abstract»

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  • The resolution of failing banks: Bail-out or bail-in?

    Publication Year: 2014, Page(s): x
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    Summary form only given. Prior to the Lehman failure, most large failing banks were rescued by an encouraged merger with a stronger bank. That route has now become more difficult. Because of the dangers of liquidating any large bank, the aim will be to recapitalise them. In the past this has been done by bail-out. This has led to many objections, on grounds of moral hazard, unfairness to taxpayers... View full abstract»

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  • A World of financial data at your fingertips, functional, strongly tooled and strongly typed

    Publication Year: 2014, Page(s): xi
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    Modern financial programming and modelling is highly information rich, but our programming tools are often information sparse, especially our strongly typed ones. This leads to an impasse where improvements in programming to aid accuracy and clarity of financial software implementation such as units-of-measure analysis or typed functional programming can't be rolled out to industry. The F# program... View full abstract»

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  • An analysis of price impact functions of individual trades on the London Stock Exchange

    Publication Year: 2014, Page(s):1 - 8
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    Studying price impact is important in finance and previous work examines the relationship between trade size and price impact on a number of equity markets. In this study, using recent order book data from the London Stock Exchange, we examine the price impact function for six highly-liquid stocks and novelly investigate whether the function displays time-of-day effects. The results show that pric... View full abstract»

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  • Survival models for the duration of bid-ask spread deviations

    Publication Year: 2014, Page(s):9 - 16
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    Many commonly used liquidity measures are based on snapshots of the state of the limit order book (LOB) and can thus only provide information about instantaneous liquidity, and not regarding the local liquidity regime. However, trading in the LOB is characterised by many intra-day liquidity shocks, where the LOB generally recovers after a short period of time. In this paper, we capture this dynami... View full abstract»

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  • An agent-based model for market impact

    Publication Year: 2014, Page(s):17 - 24
    Cited by:  Papers (4)
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    Based on recent theoretical and empirical developments this paper proposes an agent-based model for market impact. Three types of agents are present on the market: Liquidity consumers, liquidity providers and noise traders. The first group creates large orders based on portfolio considerations. When they submit an order to the market they split it up into smaller parts to evade price impact costs.... View full abstract»

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  • Time series prediction with a non-causal neural network

    Publication Year: 2014, Page(s):25 - 31
    Cited by:  Papers (1)
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    Neural networks have been widely applied to time series prediction over past few decades. Generally, applications of them restrict to causal models where current values are dependent on past values. In contrast, a non-causal neural network is proposed in this paper to deal with time series prediction by allowing dependence on future values. Both past and future values are used together for trainin... View full abstract»

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  • A comparison of forecasting approaches for capital markets

    Publication Year: 2014, Page(s):32 - 39
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    In recent years, machine learning algorithms have become increasingly popular in financial forecasting. Their flexible, data-driven nature makes them ideal candidates for dealing with complex financial data. This paper investigates the effectiveness of a number of machine learning algorithms, and combinations of these algorithms, at generating one-step ahead forecasts of a number of financial time... View full abstract»

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  • Exchange rate forecasting using echo state networks for trading strategies

    Publication Year: 2014, Page(s):40 - 47
    Cited by:  Papers (2)
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    Because of the diversity of portfolios based on assets throughout international markets, exchange rate prediction plays an important role in risk management, asset allocation, and trading strategies. This paper aims to investigate the use of a recent paradigm of recurrent neural networks, echo state networks (ESNs), applied to forecasting and trading currency exchange rates. It does so by benchmar... View full abstract»

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  • From text to bank interrelation maps

    Publication Year: 2014, Page(s):48 - 54
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    In the wake of the ongoing global financial crisis, interdependencies among banks have come into focus in trying to assess systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discussion. Co-occurrences of bank names are turned into a network, which can be visual... View full abstract»

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  • An empirical study of the financial community network on Twitter

    Publication Year: 2014, Page(s):55 - 62
    Cited by:  Papers (2)
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    Twitter, one of the several major social media platforms, has been identified as an influential factor to financial markets by multiple academic and professional publications in recent years. The motivation of this study hinges on the growing popularity of the use of social media and the increasing prevalence of its influence among the financial investment community. This paper presents an empiric... View full abstract»

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  • Twitter financial community modeling using agent based simulation

    Publication Year: 2014, Page(s):63 - 70
    Cited by:  Papers (3)
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    With the empirical evidence that Twitter influences the financial market, there is a need for a bottom-up approach focusing on individual Twitter users and their message propagation among a selected Twitter community with regard to the financial market. This paper presents an agent-based simulation framework to model the Twitter network growth and message propagation mechanism in the Twitter finan... View full abstract»

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  • Do dark pools stabilize markets and reduce market impacts? Investigations using multi-agent simulations

    Publication Year: 2014, Page(s):71 - 76
    Cited by:  Papers (4)
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    In financial stock markets, dark pools, which never provide any order books and quotes, are becoming widely used. It is said that dark pools may lead to stabilization of markets. However, an increased use of dark pools does raise regulatory concerns as it may ultimately affect the quality of the price discovery mechanism. In this study, we built an artificial market model, multi-agent simulation, ... View full abstract»

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  • Detecting price manipulation in the financial market

    Publication Year: 2014, Page(s):77 - 84
    Cited by:  Papers (4)
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    Market abuse has attracted much attention from financial regulators around the world but it is difficult to fully prevent. One of the reasons is the lack of thoroughly studies of the market abuse strategies and the corresponding effective market abuse approaches. In this paper, the strategies of reported price manipulation cases are analysed as well as the related empirical studies. A transformati... View full abstract»

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  • Detecting wash trade in the financial market

    Publication Year: 2014, Page(s):85 - 91
    Cited by:  Papers (1)
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    Wash trade refers to the activities of traders who utilise deliberately designed collusive transactions to increase the trading volumes for creating active market impression. Wash trade can be damaging to the proper functioning and integrity of capital markets. Existing work focuses on collusive clique detections based on certain assumptions of trading behaviours. Effective approaches for analysin... View full abstract»

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  • Improving portfolio risk profile with threshold accepting

    Publication Year: 2014, Page(s):92 - 99
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    The application of the Threshold Accepting (TA) algorithm in portfolio optimisation can reduce portfolio risk compared with a Trust-Region local search algorithm. In a benchmark comparison of several different objective functions combined with different optimisation routines, we show that the TA search algorithm applied to a Conditional Value at Risk (CVaR) objective function yields the lowest Bas... View full abstract»

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  • Multi-period asset allocation with lower partial moments criteria and affine policies

    Publication Year: 2014, Page(s):100 - 106
    Cited by:  Papers (1)
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    This paper discusses a computational methodology for solving multi-period dynamic asset allocation problems using empirical asymmetric measures of risk. Three features distinguish the proposed approach from the mainstream ones. First, our approach is nonparametric, in the sense that it does not require explicit estimation of a statistical model for the returns distribution. Second, it employs affi... View full abstract»

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