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This study tests the ability of three one-factor, and three two-factor models in the HJM class, to explain the pricing of the Eurodollar futures options on the Chicago Mercantile Exchange from 1 January 96 to 31 December 98. The work extends the paper of Amin and Morton (1994) by introducing two-factor models, which have the advantages over the one-factor models for the yields of different maturities being imperfectly correlated. On each day, about 10.7 calls and 9.9 puts with different categories of moneyness and maturity are collected to minimise the difference of market and model prices for determining volatility parameters for each function. Three criteria are imposed for evaluating the models: (1) the ability of each model to fit option transaction prices; (2) the predictability of option prices for each model; (3) the profitability of hedging strategies for each model. The results show that the models with a combination of different sensitive volatility parameters provide smaller fitting and prediction errors than the models with a simple volatility parameter. However, volatility parameters in these models are less stable and highly correlated. We also documented that ITM options are overpriced relative to at- and OTM options. in addition, the degree of overpriced options is an increasing function of maturity. In general, two-factor models fit better for long-lived options than one-factor models, whereas there is no significant difference for both types of models for fitting shortlived options. Based on out-of-the-sample approach, those models, which have higher explanatory power in in-sample fit usually perform better, indicating volatility parameters are not unstable over time. Finally, two hedging strategies, buy-and-hold and rebalanced, are implemented to reap the findings of mispriced options. On average, the models with an exponential factor produce negative profits, as a result of overfitting the long-term options. Although this group of models fits significantly better than others, those models with flexible parameters have resulted in overfitting the biases. Although lower prediction errors are found for these models, absolute and square root models are still preferable since they can detect mispriced options by making more profits. Of these two trading strategies, the buy-and-hold strategy generates more profits for all models in most circumstances.

This study is concerned to examine the connection between signals in stock market prices and investment announcements. The intention was to establish the degree to which investment response was fully (efficiently) discounted into share prices and whether the stock market signals actually resulted in real resource consequences. This study investigated the following three questions: 1. Do companies translate high stock returns into increased investment expenditure either with or without increased access to external funds? If the answer is affirmative, then what are the time lags involved? 2. Additionally, does investment expenditure, presumably on the basis of forward looking, in response to future opportunities, influence subsequent stock market returns? In other words, are stock market returns a function of prior investment expenditure? If yes, then how long does it require to be effective? 3. Are there any significant differences across and within sectors? The existence of these relationships was examined in terms of 640 UK public companies over the period 1979-1988. Using cross section time series data, regression analysis shows that prior abnormal returns have a significant positive influence on subsequent investment expenditure. In simple regression, there is also a strong positive link between investment and abnormal returns but within a simultaneous specification the result is a small but positive feedback of investment into abnormal returns. This supports a conclusion that allocation of more resources to investment is an anticipated consequence when abnormal returns arise and secondly that there is, even then, a small positive impact when the anticipated investment occurs. As a result, the market efficiency was confirmed with 2-3% inefficiency, and the idea of market effectiveness was also confirmed. In answering the third question, a variety of issues arose. First, in terms of investment response to abnormal returns, it was observed that there are differences in the behaviour of managers and investors given the different status of firms, size, type and period of projects. Managers are more attentive to the signals from the market during the growth stage and react negatively when the firm is in a decline stage. The reaction of investors, on the other hand, is strongly negative when they anticipate that firms are in a decline stage and positive when they anticipate that firms are in a growth stage. The weaker response of investors to long-term projects compared to short-term ones supported the idea of short-termism. On the other hand, managers were found to react more strongly to abnormal returns in sectors characterized by long-term projects.

This thesis is devoted to the asset allocation and portfolio optimization with small transaction costs. Three topics are studied. The first and second topics are on asset allocation problems with purely proportional transaction cost and strictly positive transaction cost, respectively. The fundamental objective is to keep the asset portfolio close to a target portfolio and in the meantime to reduce the trading cost in doing so. For each problem, we derive the quasi-variational inequality and prove a verification theorem giving sufficient conditions for a QVI solution to be the value function. The optimal strategy is a singular control in the first topic and an impulse control in the second. Furthermore, we provide a matrix exponential representation of the QVI solution for both problems and perform asymptotic analysis to characterize the optimal no transaction region when transaction costs are sufficiently small. Additionally, for both topics, we apply the asymptotic results for the boundary points and derive an expansion for the QVI solution, the optimality of which can be shown via verification theorem (up to leading orders). The third topic is on portfolio optimization with proportional transaction cost. We construct an efficient frontier problem (EFP) of maximizing expected terminal utility and minimizing terminal CVAR. We first solve the frictionless case by duality approach and nonsmooth analysis. For three representative utility functions, we obtain numerically the optimal trading strategy, optimal expected terminal utility and optimal CVAR. Our analysis of how these three quantities change with respect to different CVAR constraints provides flexibility for an investor to balance return and risk according to her own preference. We then include transaction cost to the EFP, which is equivalent to including transaction cost to a non-smooth utility maximization problem. Asymptotic analysis gives expansions for no transaction boundaries which are then applied to EFPs with different utility functions. This topic ends by numerical analysis on impact of introducing CVAR constraint and/or transaction cost for classical utility maximization problem.

Equity culture is underdeveloped in Central and Eastern Europe. The corporate sector's dependence on debt as an external source of capital, scarce and illiquid capital markets and distrust in corporate sharing are the reasons for this. Yet, according to a number of surveys, fIrms are dissatisfied with the existing forms of debt driven external capital. The barriers of access to capital and the cost of capital are high resulting in unattractive and inflexible financing options. However, the availability of capital is a necessity for corporate existence and economic growth. The question of the viability of equity financing development as an alternative to the traditional debt financing in the transition economies of Central and Eastern Europe puzzles many. National policymakers as well as domestic and foreign investors need this question answered so that time and effort is not wasted on pursuing unviable strategies and creating unrealistic investment plans. The development of an equity culture in the CEECs is the main focus of this study. We develop a theory-bridging conceptual framework through which we attempt to demonstrate what factors contribute to its formation. We maintain that fIrms seeking equity finance are the main drivers for equity culture development in a country. This demand is affected by the size of transaction costs these finns incur in the process of searching for, establishing and co-ordinating contractual relationships with equity providers. We establish that the size of transaction costs is detennined by a set of conditions stemming from internal (managerial) and external (macro-economic and institutional) environments impacting the firm. The conceptual framework is empirically tested using quantitative data on ten Central and Eastern European countries (CEECs) (EU member countries since 2004 and 2007) for a continuous period of thirteen years (1996-2008). Firstly, a relatively new graphical display method - the Co-Plot method - is applied to cluster the gathered data. This method facilitates benchmarking against two representatives of the equity oriented financial system (UK and USA) and two representatives of the bank (debt) oriented financial system (Germany and Japan). The outcome of this analysis is the identification of three separate groups within our sample ofCEECs (Leaders, Potentials, Laggards) in terms of the potential for equity culture development they exhibit. Secondly, a regression analysis follows. It determines causal relationships between the demand-based dependent variables and independent variables represented by equity culture supportive conditions. Regressions are performed while controlling for different finn sizes (Large finns, SMEs, Micro firms and the total number of firms) to detennine the driving factors of equity culture development for each firm size individually as differing effects are expected. Furthermore, we carry out the regression analysis while controlling for the groups of Leaders, Potentials, and Laggards on a case by case basis. Finally, a qualitative comparative analysis for three CEECs, Slovakia, Hungary and Bulgaria, (each being a representative for a group with different potential for equity culture development) is provided. Our findings suggest that CEECs belonging to the group of Leaders have the macroeconomic and institutional conditions necessary for the development of an equity culture in place and that it is the equity-oriented financial institutions and the managerial capabilities which require further attention so that equity culture can be fully developed. By contrast, countries from the Potentials group have the macroeconomic performance required for the development of an advanced equity-based fmancial system, however the conditions stemming from the institutional (including both quality as weil as adequacy of equityiii r I .1 oriented financial intermediaries) and the managerial environment need improving. The results for the group of Laggards indicate that in order for an equity culture to be able to develop, a complex set of macro-economic, institutional and managerial conditions requires attention. Furthermore, we establish that large firms do not necessarily require the presence of adequate managerial conditions for them to become the drivers of equity culture development. In the case of SMEs we fmd that it i& primarily the presence of appropriate institutional rather than macro-economic and managerial conditions that have to be satisfied in order for these finns to opt for equity finance. Finally. our results for micro firms imply that although the presence of adequate macro-economic and institutional conditions is important, however, it is not sufficient. It is the presence of appropriate managerial conditions which motivate micro firms to consider equity finance. Our study contributes to the existing literature in several ways. Firstly, it contributes to theory by providing a Dew conceptual perspective on the financial system development and finn financing options in transition economies typical for their limited experience with equity financing and an underdeveloped equity culture, such as the CEECs. Secondly, it provides contributions to practice by proposing managerial and policy recommendations, how to identify best investment targets, and how to support equity culture development should it be desired.

In this thesis we develop dynamic cooperative investment schemes in discrete and continuous time. Instead of investing individually, several agents may invest joint capital into a commonly agreed trading strategy, and then split the uncertain outcome of the investment according to the pre-agreed scheme, based on their individual risk-reward preferences. As a result of cooperation, each investor is able to get a share, which cannot be replicated with the available market instruments, and because of this, cooperative investment is usually strictly profitable for all participants, when compared with an optimal individual strategy. We describe cooperative investment strategies which are Pareto optimal, and then propose a method to choose the most ‘fair’ Pareto optimal strategy based on equilibrium theory. In some cases, uniqueness and stability for the equilibrium are justified. We study a cooperative investment problem, for investors with different risk preferences, coming from expected utility theory, mean-variance theory, mean-deviation theory, prospect theory, etc. The developed strategies are time-consistent; that is the group of investors have no reasons to change their mind in the middle of the investment process. This is ensured by either using a dynamic programming approach, by applying the utility model based on the compound independence axiom. For numerical experiments, we use a scenario generation algorithm and stochastic programming model for generating appropriate scenario tree components of the S&P 100 index. The algorithm uses historical data simulation as well as a GARCH model.

This thesis, which is divided into 3 papers, investigates the relationship between weather and individuals’ trading behaviour in the spread-trading market. The spread-trading market offers the opportunity of examining individuals’ trading records, and thus enables the exploration of the impact of weather on individuals’ financial decision-making behaviours. The first paper investigates the effect of a range of weather variables on individual spread traders’ hourly trading volumes and their propensity to buy or sell (bullish/bearish trading sentiment). The findings suggest that a range of weather factors appear to influence the trading volume, but have less effect on trading sentiment. Importantly, the weather effects were different in the winter and the summer, and often in opposite directions. The neglect of this important seasonal effect could be why previous studies have produced ambiguous results concerning the effect of weather on trader behaviour. The second paper examines the relationship between weather and the most widely reported behavioural bias in financial markets, the ‘disposition effect’ (DE); whereby, traders tend to sell positions which are in profit rather than those that are in loss. Previous research suggests that weather can influence individuals’ mood. In addition, system 1 thinking is more associated with emotional rather than logical thought, whereby investors rely more on their intuition, rather than on rational analysis. Therefore, via its impact on mood, it is postulated in paper 2 that weather could influence the degree of system 1 thinking in which investors engage and that this in turn could influence the incidence of the DE. Indeed, the results reported in paper 2 indicate that weather does significantly influence individuals’ DE. In addition, in line with the affect infusion model (AIM: Forgas, 1995), the biased decisions (i.e. DE) of less (cf. more) informed traders are more affected by weather factors. This study is the first to link weather conditions to the occurrence of the degree of the DE and, therefore, contributes to the literature exploring the origins of the DE. The third paper tests the impact of weather changes on individuals’ risk-taking decisions. Previous literature suggests that changes in weather can influence people’s psychology and physiology. In addition, humans possess the ability to maintain thermal homeostasis via both biological mechanisms and behaviours. Therefore, sudden changes in weather may have a greater effect on mood and behaviour than the general weather conditions. It might, therefore, be expected that individuals’ trading behaviour will be influenced not only by the current weather conditions, but also changes in those conditions. In addition, I control for current weather conditions and potential seasonal differences in the effects of weather factors. The results suggest that a range of weather changes that might be associated with greater relative personal discomfort (e.g. precipitation increases and air pressure decreases in winter and temperature increases in summer months) induce risk-taking behaviours. The results confirm the importance of taking account of weather changes when communicating risk-related messages and for those designing effective means of managing risk.

Portfolio managers have access to large amounts of financial time series data, which is rich in structure and information. Such structure, at varying time horizons and frequencies, exhibits different characteristics, such as momentum and mean reversion to mention two. The key challenge in building a smart portfolio is to first, identify and model the relevant data regimes operating at different time frames and then convert them into an investment model targeting each regime separately. Regimes in financial time series can change over a period of time, i.e. they are heterogeneous. This has implications for a model, as it may stop being profitable once the regime it is targeting has stopped or evolved into another one over a period of time. Changing regimes or those evolving into other regimes is one of the key reasons why we should have several independent models targeting relevant regimes at a particular point in time. In this thesis we present a smart portfolio management approach that advances existing methods and one that beats the Sharpe ratio of other methods, including the efficient frontier. Our smart portfolio is a two-tier framework. In the first tier we build four quantitative investment models, with each model targeting a pattern at different time horizon. We build two market neutral models using the pairs methodology and the other two models use the momentum approach in the equity market. In the second tier we build a set of meta models that allocate capital to tier one, using Kelly Criterion, to build a meta portfolio of quantitative investment models. Our approach is smart at several levels. Firstly, we target patterns that occur in financial data at different time horizons and create high probability investment models. Hence we make better use of data. Secondly, we calculate the optimal bet size using Kelly at each time step to maximise returns. Finally we avoid making investments in loss making models and hence make smarter allocation of capital.