Behavioral Finance and Agent-Based Artificial Markets

Studying the behavior of market participants is important due to its potential impact on asset prices and the dynamics of financial markets. The idea of individual investors who are prone to biases in judgment and who use various heuristics, which might lead to anomalies on the market level, has been explored within the field of behavioral finance. In this dissertation, we analyze market-wise implications of investor behavior and their irrationalities by means of agent-based simulations of financial markets. The usefulness of agent-based artificial markets for studying the behavioral finance topics stems from their ability to relate the micro-level behavior of individual market participants (represented as agents) and the macro-level behavior of the market (artificial time-series). This micro-macro mapping of agent-based methodology is particularly useful for behavioral finance, because that link is often broken when using other methodological approaches. In this thesis, we study various biases commented in the behavioral finance literature and propose novel models for some of the behavioral phenomena. We provide mathematical definitions and computational implementations for overconfidence (miscalibration and better-than-average effect), investor sentiment (optimism and pessimism), biased self-attribution, loss aversion, and recency and primacy effects. The levels of these behavioral biases are related to the features of the market dynamics, such as the bubbles and crashes, and the excess volatility of the market price. The impact of behavioral biases on investor performance is also studied

Modeling investor optimism with fuzzy connectives

Optimism or pessimism of investors is one of the important characteristics that determine the investment behavior in financial markets. In this paper, we propose a model of investor optimism based on a fuzzy connective. The advantage of the proposed approach is that the influence of different levels of optimism can be studied by varying a single parameter. We implement our model in an artificial financial market based on the LLS model. We find that more optimistic investors create more pronounced booms and crashes in the market, when compared to the unbiased efficient market believers of the original model. In the case of extreme optimism, the optimistic investors end up dominating the market, while in the case of extreme pessimism, the market reduces to the benchmark model of rational informed investors

Behavioural biases and evolutionary dynamics in an agent-based financial market

This research is devoted to the study of financial market dynamics in a framework which combines agent-based modelling and concepts from behavioural finance. The thesis explores, in an agent-based financial market model, the interlinkage between investor heterogeneity, bounded rationality, behavioural biases and the aggregate market dynamics. We develop a dynamic equilibrium model of a financial market in the presence of heterogeneous, boundedly rational investors. The model combines a performance-driven strategy-switching mechanism of an adaptive belief system (Brock and Hommes, 1998) and an evolutionary finance model (Evstigneev, Hens and Schenk-Hopp´e, 2011). A key feature of this new model is that it contains a combination of passive and active learning dynamics. Passive learning refers to the market force by which wealth accumulates on investment strategies which have done relatively well. Active learning refers to the switching behaviour by which investors actively move their wealth into strategies which have performed well in the recent or distant past. This thesis extends the literature by examining the joint effect of passive and active learning in relation to the evolutionary dynamics of financial markets. By drawing in concepts from behavioural finance, we focus on the micro-level modelling of various heuristics and behavioural biases which may affect investors’ active learning and financial forecasting, such as overconfidence, recency bias, sentiment, etc. We quantify the macro-level market impact of these behavioural elements and study the evolutionary prospects of market dynamics. We show that the interaction between passive and active learning is crucial to understanding the market selection of dominant strategy or the survival of different strategies. Investors’ bounded rationality and behavioural biases in active learning and financial forecasting play an important role in shaping the market dynamics. Our findings point to the causes of the persistence of market inefficiencies and a variety of stylised facts of financial market. The added value of drawing together agent-based modelling and behavioural finance on the study of financial markets dynamics is demonstrated

Creating an adaptive asset allocation fund to outperform inflation in the South African financial market

Includes abstract.Includes bibliographical references (leaves 112-113).In this dissertation, I detail the process I went through to create a new asset allocation product, with the intention of beating inflation over the long term, in the South African flnancial market space. This process has been a contributor to the creation of my model for new product development in the financial market space. Simulation is at the core of this process. At the outset, I cover a brief history and contextualise absolute return funds, looking at the difference between an absolute return fund, a balanced fund and a hedge fund. The move from defined benefit to defined contribution pension funds and the impact this has had on consulting actuaries risk appetites is visited. My concern in this regard is that capital preservation is being maximised, at the expense of capital growth, without taking into account the devastating effects of inflation

Herding and feedback trading : an empirical investigation

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Stock trading and daily life : lay stock investors in Taiwan

Drawing on recent discussions of relational embeddedness and socio-technical agencement, this thesis analyses the relationship between stock trading and lay investors’ daily lives, including their social relations, activities, events, devices, places, work and ways of thinking. Taiwan’s stock market provides an appropriate location for investigation because of the dominance of lay investors in the market and the high proportion of Taiwan’s adult population who engage in stock trading. The data were obtained from three main sets of sources: in-depth interviews, document analysis and ethnographic observation. I argue that lay market actors are not only framed by the market’s mechanisms, but also by daily-life structures. The Taiwan Stock Exchange, as an electronic, anonymous financial market, has been a challenge to the embeddedness approach due to the absence of direct interaction between the parties to transactions. This study presents another aspect of socio-economic relationships in the market: the role of financial-market activity in wider social interactions. Like taking part in any popular social activity, lay investors’ social ties are maintained and expended by engaging in stock trading. Social relations and stock trading are woven together and form a largely seamless whole, part of lay investors’ daily life. The socio-technical agencements of lay investors contain distinctive features: diversity, bricolage, use of non-professional ‘devices’, action in non-financial places, everyday means of controlling market risk and association with everyday events. The differences between the agencements of lay investors and professional practitioners produce an asymmetry of calculative capabilities between market actors. Superior calculative capabilities tend to give an advantage to professional practitioners in the market, but these strengths are constrained by political and economic factors. This study sheds light on micro social factors, which are comparable with economic, institutional and psychological explanations, in accounting for lay investors’ behaviours in financial markets. The analysis also suggests the compatibility of the three important social science approaches to economic agents: Granovetter’s embeddedness, Zelizer’s relational work and Callon’s agencement

Forecasting financial markets using linear, nonlinear & model combination methods

In this thesis we investigate the question of asset price predictability. The two major themes that we focus on are firstly; whether machine learning and statistical modelling techniques, which impose less restrictive assumptions on asset price dynamics than do classical linear methods, can be used to forecast and trade financial markets to a degree greater than that which traditional asset pricing models would lead us to expect and secondly; to what extent model combination/ensemble strategies can add value in this pursuit. The approaches used include support vector regression (SVR), k-nearest neighbours (KNN), trading rules, linear regression (LR) and the random subspace ensemble method. We investigate these two themes using inherently data-driven models across datasets of sufficient size to render statistically meaningful results in three self-contained contexts. The first piece of empirical work compares the relative forecasting performance of SVR, KNN and LR models when applied to predicting daily returns of 58 UK stocks in the FTSE 100 over 4000 days. Bootstrap simulations are used to shed further statistical light on model performance. Secondly, we investigate the extent to which model combinations can improve forecasting performance with the use of the random subspace ensemble method for constructing ensembles of linear regression models to predict the returns of a portfolio of FTSE 100 stocks. The primary ensemble consists of 62500 component models estimated by randomly sampling subsets of the feature set and the final result combined via a majority vote. Lastly, we conduct an in-depth study of the channel break-out trading rule over a portfolio of 37 futures markets. We borrow a page from the book of modern portfolio theory where it is the performance of individual markets in the context of a portfolio that is ultimately of interest rather than on an individual basis. This approach is rarely used in the literature but is able to shed more light on the question of trading rule efficacy. Bootstrap resampling is employed to derive robust performance statistics. Our results show the Sharpe Ratio of the portfolio to be three times greater than of individual markets as a result of diversification in addition to being greater than that of S&P500 benchmark. We did not set out in an attempt to refute the weak form of Fama's (1970) classic taxonomy of information sets or, colloquially, "to beat the market"; nonetheless, some of our results suggest economically significant returns

What happens when it all goes wrong? A study into the impacts of personal financial shocks

This thesis examines the impact on individuals who suffer from significant financial loss. It also highlights broader environmental issues relating to financial provision for individuals, particularly in retirement. Such issues include regulation, financial literacy, the significant choice available, and the need for professional financial advice. These are particularly significant in the Australian context where financial self-sufficiency is promoted as a desired option in retirement. The collapse of Queensland-based Storm Financial is used as a casestudy to investigate these matters. A qualitative approach was taken with elements of grounded theory and narrative inquiry utilised when engaging with the available data. Available data from a 2009 Parliamentary Inquiry includes 823 pages of public hearing transcripts and 2879 pages of written submissions. Interviews with 15 different parties were also carried out, giving rise to 33 hours of recorded conversation. To mitigate issues of researcher and participant bias and a reliance on qualitative interpretation as the primary tool of analysis, various procedures including triangulation and member checking were adopted. It is apparent that sudden and significant financial loss is devastating. An individual's emotional wellbeing is a primary casualty, and one's mental health is also vulnerable. An individual's social world is also impacted, including relationships with family and friends, how one engages in community activities, and the ability to partake in familial and cultural roles. Financial victims also perceive a sense of judgement from society at large about their losses. A loss of trust may be the epitome of financial loss. Any financial promise requires trust in institutions, professional service providers, government via licensing and regulation, and others including oneself. Trust in all of these entities is impacted when loss occurs, and is highly dependent on not just the size but also the circumstances of those losses. The loss of trust and the loss of financial means leads in turn to a lack of control over one's life. Many of these impacts are reflected in other traumatic circumstances, and some are seen to be particularly exacerbated in the specific case of Storm. These impacts demonstrate that vulnerability exists when encouraging self-sufficiency in retirement. Greater individualisation in financial provision introduces risks that current regulation may not be equipped to mitigate, particularly in the areas of licensing and disclosure. Information asymmetry between informed and non-informed participants exacerbates these risks. This highlights the importance of ethical disposition when dealing with financial affairs. The current retirement 'pillars' of the age pension, superannuation and other savings describe 'mechanisms' of income, but an alternative pillared system of government, other institutions, and oneself is offered to highlight the underlying sources of trust. Storm's collapse highlights that money matters but not for its own sake - it is the subsequent loss of control and options that is tangibly impacted. Significant financial loss is therefore anything but trivial, and a strong dependence of overall wellbeing on financial wellbeing is highlighted. Any system which allows unnecessary risks upon the attainment of such financial wellbeing for individuals should therefore be subjected to critical scrutiny