Present value based asset pricing models are explored empirically in this thesis. Three contributions are made. First, it is shown that a market timing strategy may be implemented in an excessively volatile market such as the S&P500. The main premise of the strategy is that asset prices may revert to the present value over time. The present value is computed in real-time where the present value variables (future dividends, dividend growth and the discount factor) are forecast from simple models. The strategy works well for monthly data and when dividends are forecast from autoregressive models. The performance of the strategy relies on how discount rates are empirically defined. When discount rates are defined by the rolling and recursive historic average of realized returns, the strategy performs well. The discount rate and dividend growth can also be derived using a structural approach. Using the Campbell and Shiller log-linearized present value equation, and assuming that expected and realized dividend growth are unit related, a state space model is constructed linking the price-dividend ratio to expected returns and expected dividend growth. The model parameters are estimated from the data and, are used to derive the filtered expected returns and expected dividend growth series. The present value is computed using the filtered series. The trading rule tends to perform worse in this case. Discount rates are again found to be the major determinant of its success. Although the structural approach offers a time series of discount rates which is less volatile, it is on average higher than that of the historical mean model. The filtered expected returns is a potential predictor of realized returns. The predictive performance of expected returns is compared to that of the price-dividend ratio. It is found that expected returns is not superior to the price-dividend ratio in forecasting returns both in-sample and out-of-sample. The predictive regression included both simple Ordinary Least Squares and Vector Autoregressions. The second contribution of this thesis is the modeling of expected returns using autoregressive fractionally integrated processes. According to the work of Granger and Joyeux(1980), aggregated series which are derived from utility maximization problems follow a Beta distribution. In the time series literature, it implies that the series may have a fractional order (I(d)). Autoregressive fractionally models may have better appeal than models which explicitly posit unit roots or no unit roots. Two models are presented. The first model, which incorporates an ARFIMA(p,d,q) within the present value through the state equations, is found to be highly unstable. Small sample size may be a reason for this finding. The second model involves predicting dividend growth from simple OLS models, and sequentially netting expected returns from the present value model. Based on the previous finding that expected returns may be a long memory process, the third contribution of this thesis derives a test of long memory based on the asymptotic properties of the variance of aggregated series in the context of the Geweke Porter-Hudak (1982) semiparametric estimator. The test makes use of the fact that pure long memory process will have the same autocorrelation across observations if the observations are drawn at repeated intervals to make a new series. The test is implemented using the Sieve-AR bootstrap which accommodates long range dependence in stochastic processes. The test is relatively powerful against both linear and nonlinear specifications in large samples.

In this thesis I explore two factors that impose constraints for external finance of firms in Emerging market, the lack of property rights protection and the absence of political connections. I demonstrates that strengthening of property rights protection and sustaining tighter political connection is beneficial for firms external finance.

Cette thèse de doctorat étudie la transposition d’une méthodologie héritée de la théorie de la production, couramment appelée "méthode DEA", à l’analyse de la performance des actifs financiers. Elle souligne la pertinence de l’utilisation d’un estimateur tel que DEA, présente en détail la méthodologie qui lui est traditionnellement associée et fournit une revue de la littérature appliquant cette méthodologie à des portefeuilles d’actifs financiers. La méthodologie étudiée requiert la définition de conditions de régularité caractérisant la technologie commune à chaque entité étudiée. Elle implique donc une définition rigoureuse des intrants et produits caractérisant la technologie de production. La littérature actuelle considère implicitement un processus de génération du rendement des investissements dans des portefeuilles d’actifs par le niveau risque. Cette thèse propose un traitement différent basé sur l’idée de production jointe, également héritée de la théorie de la production et selon laquelle des intrants peuvent générer des produits indésirables et inévitables. L’approche proposée dans cette thèse considère les divers types de risque associés à l’investissement comme des produits indésirables. Cette thèse propose donc une définition d’un processus de production financier et étudie les implications théoriques d’une telle définition sur le traditionnel ensemble d’axiomes. Elle recommande également la prise en compte d’une possible préférence pour le risque là où seule l’aversion au risque est généralement supposée, et rappelle la pertinence d’inclure dans les cadres théoriques des mesures de risque associées à des préférences telles que la prudence ou la tempérance. / This doctoral thesis studies the transposition of a methodology inherited from production theory, and commonly referred to as “DEA” (Data Envelopment Analysis) only, to the study of performance of financial assets. It underlines the accuracy of using DEA as an estimator to assess the performance of financial assets, provides a detailed presentation of the methodology associated to DEA and a review of the literature that applies this methodology to the performance measurement of portfolios of financial assets.The traditional methodology requires the definition of regularity conditions that characterize the technology shared by all entities. It then implies a rigorous definition of inputs and outputs that characterize the production technology. The current literature implicitly assumes a production process that generates returns on investment in portfolios of financial assets by the level of risk taken. This thesis proposes a different treatment based on the idea of joint productions inherited from production theory and according to which inputs can generate undesirable outputs that cannot be freely disposed of. The approach proposed in this thesis then considers the various types of risk associated to the investment as undesirable outputs. This thesis proposes a definition a financial production process and studies the theoretical implications of such a definition on the traditional set of axioms. It also recommends taking into account a possible preference for risk where only risk aversion is generally assumed and reminds the importance to include in the theoretical frameworks some measures of risk associated to preferences for some risks, such as prudence or temperance.

No description available.

The Treasury's report "Institutional Investment in the United Kingdom: A Review" (the Myners Review) suggested in 2001 that various sectors of the UK equity market may be suitable for active investment management, tacitly assuming that some sectors are efficient whilst others are not. The validity of this assumption is tested against 29 industrial sector indices within the FTSE All Share index. Sector efficiency is, taken to be that index values reflect information correctly (strong efficient) or to the point where benefits do not exceed costs (weakly efficient). Existence of a sector index following a random walk is used to identify strong efficiency with the subsequent conclusion that passive management would be appropriate. Where the time series is not random, forecasting gains less than the management costs of active trading indicate weak efficiency with the corollary that passive management is still applicable. Industrial sectors where the index can be forecast with gains in excess of costs are not efficient and are appropriate for active management. The indices are tested for stationarity: none are stationary in levels but all reject the Dickey Fuller null hypothesis of a unit root in their first difference, the logarithmic return. Tests for randomness are based on pure random walks and random walks with drift and/or trend. Non-random time series are examined for maintained regressions based on AR, MA and ARMA. Where appropriate, ARCH is applied to the variance, utilising GARCH, Threshold GARCH, GARCH-in mean, Exponential GARCH and Component GARCH. Additionally there is a test for cointegration. All potential data generating processes' residuals are tested for independent identical distributions using the BDS test. If the maintained regression produces residuals that are III) then that series is assumed to be explained. The results show that four indices are strong efficient and five are weak; giving nine sectors that should be managed passively. Only one sector is found where there is scope for active management to make an abnormal gain in excess of costs. Nineteen of the indices had GARCH, which indicated a possible lack of efficiency but no decision on management style. One index was unexplained. Thus the Myners review's suggestion of active management where appropriate was valid, but limited solely to the Personal Care & Household Products sector.

This thesis is an application of Random Matrix Theory (RMT) to portfolio management and financial networks. From a portfolio management perspective, we apply the RMT approach to clean measurement noise from correlation matrices constructed for large portfolios of stocks of the FTSE 100. We apply this methodology to a number of correlation estimators, i.e., the sample correlation matrix, the Constant Conditional Correlation Model (CCC) of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) Model of Engle (2002) and the Regime-Switching Beta CAPM Correlation Model, based on Ang and Bekaert (2004). For these estimators, we find that the RMT- filtering delivers portfolios with the lowest realised risk, the best prediction accuracy and also the highest cumulated returns and Sharpe Ratios. The gains from using the RMT-filtering, in terms of cumulated wealth, range from 65%, for the sample correlation matrix to 30%, for the regime-dependent correlation estimator. In the case of regime switching CAPM models, we find that the regime switching correlation matrices, in the high volatility regime are found to be a good filter which makes further RMT- filtering to be redundant. This establishes the validity of using regime sensitive portfolio management to deal with asymmetric asset correlations during high and low volatility regimes. From a financial network perspective, we assess the stability of a global banking network built from bilateral exposures of 18 BIS reporting banking systems to net debtor countries. For this, we applied the eigen-pair method of Markose (2012), which is based on the work of May (1972, 1974) for random networks. We use a stability condition based on the maximum eigenvalue (λmax) of a matrix of net bilateral exposures relative to equity capital as a systemic risk index (SRI). We provide evidence of the early warning capabilities of λmax, when this surpasses a prespecified threshold. We use the right and left associated eigenvectors as a gauge for systemic importance and systemic vulnerability, respectively. The λmax SRI was found to be superior in terms of early warning when compared to the standard SRIs based on market price data, viz. the DCC-MES of Acharya et al. (2010), the SRISK of Acharya et al. (2012) and the DCC-ΔCoVaR of Adrian and Brunnermeier (2011).

Two main methods have been used in mutual funds evaluation. One is portfolio evaluation, and the other is data envelopment analysis (DEA). The history of portfolio evaluation dates from the 1960s with emphasis on both expected return and risk. However, there are many criticisms of traditional portfolio analysis which focus on their sensitivity to chosen benchmarks. Imperfections in portfolio analysis models have led to the exploration of other methodologies to evaluate fund performance, in particular data envelopment analysis (DEA). DEA is a non-parametric methodology for measuring relative performance based on mathematical programming. Based on the unique characteristics of investment trusts, Morey and Morey (1999) developed a mutual funds efficiency measure in a traditional mean-variance model. It was based on Markowitz portfolio theory and related the non-parametric methodologies to the foundations of traditional performance measurement in mean-variance space. The first application in this thesis is to apply the non-linear programming calculation of the efficient frontier in mean variance space outlined in Morey and Morey (1999) to a new modern data set comprising a multi-year sample of investment funds. One limitation of DEA is the absence of sampling error from the methodology. Therefore the second innovation in this thesis extends Morey and Morey (1999) model by the application of bootstrapped probability density functions in order to develop confidence intervals for the relative performance indicators. This has not previously been achieved for the DEA frontier in mean variance space so that the DEA efficiency scores obtained through Morey and Morey (1999) model have not hitherto been tested for statistical significance. The third application in this thesis is to examine the efficiency of investment trusts in order to analyze the factors contributing to investment trusts' performance and detect the determinants of inefficiency. Robust-OLS regression, Tobit models and Papke-Wooldridge (PW) models are conducted and compared to evaluate contextual variables affecting the performance of investment funds. From the thesis, new and original Matlab codes designed for Morey and Morey (1999) models are presented. With the Matlab codes, not only the results are obtained, but also how this quadratic model is programming could be very clearly seen, with all the details revealed.

This thesis examines the performance of currency-only portfolios with different strategies, in out-of-sample analysis. I first examine a number of passive portfolio strategies into currency market in out-of-sample analysis. The strategies I applied in this chapter include sample-based mean-variance portfolio and its extension, minimum variance portfolio, and equally-weighted risk contribution model. Moreover, I consider GDP portfolio and Trade portfolio as market value portfolio for currency market. With naïve portfolio, there are 12 different asset allocation models. In my out-of-sample analysis, naïve portfolio performs reasonably well among all 12 portfolios, and transaction cost does not seriously affect the results prior to transaction cost analysis. The results are robust across different estimation windows and perspectives of investors from different countries. Next, more portfolio strategies are examined to compare with naïve portfolio in currency market. The first portfolio strategy called ‘optimal constrained portfolio’ in this chapter is derived from the idea of maximising the quadratic utility function. In addition, the timing strategies, a set of simple active portfolio strategies, are also considered. In my out-of-sample analysis with rolling sample approach, naïve portfolio can be beaten by all the strategies discussed in this chapter. In chapter six, the characteristics of currency are exploited to construct a currency only portfolio. Firstly, the pre-sample test proves that the characteristics, both fundamental and financial, are relevant to the portfolio construction. I then examine the performance of parametric portfolio policies. The results show that while fundamental characteristics can bring investor benefits of active portfolio management, financial characteristics cannot. Moreover, I find the relationship between characteristics of currency and weights of optimal portfolio. The overall results show that currencies can be thought of as an asset in their own right to construct optimal portfolios, which have better performance than naïve portfolio, if suitable strategies are used. In addition, ‘lesser’ currencies, indeed, bring significant benefits to the investors.

Ma thèse aboutit à un programme de recherche qui étudie l'investissement (et l'épargne) sous trois angles différents. Il renseigne sur 1) le comportement d'épargne des pays riches en pétrole, 2) la formation des prix et la dynamique de l'investissement sur le marché pétrolier, et 3) le rôle des rachats d'actions dans l'inhibition de l'effet positif d'une politique monétaire accommodante sur l'investissement au niveau des entreprises. Le point commun sous-jacent de ces trois axes de travail est la compréhension des facteurs qui influencent les décisions d'investissement au niveau de l'entreprise, de l'industrie ou du pays. Le premier chapitre de ma thèse, External Saving and Exhaustible Resource Extraction, aborde précisément la question de la gestion épuisable des ressources face à l'incertitude. En reliant le comportement d'extraction et d'économie dans un cadre théorique cohérent, ce chapitre contribue à deux veines de la littérature qui se sont développées séparément jusqu'à plus récemment. Le deuxième chapitre, L'effet retardateur du stockage sur l'investissement : Les données du secteur pétrolier américain continuent d'explorer le rôle de l'incertitude, mais cette fois-ci, elles analysent à la fois la dynamique des prix et celle des investissements lorsque les décisions d'investissement sont irréversibles. Le dernier chapitre de cette thèse, Rachat d'actions, politique monétaire et coût de la dette, porte sur une étude empirique des déterminants de l'investissement. Partant de la structure du capital des entreprises, cette partie de ma thèse porte sur le rôle des rachats dans le détournement de la dette à faible coût des investissements et de l'emploi. / My thesis culminates into a research program that studies investment (and saving) from three different perspectives. It informs on 1) the saving behaviour of oil-rich countries, on 2) price formation and investment dynamics in the oil market, and on 3) the role of share buybacks in muting the positive effect of accommodative monetary policy on firm-level investment. The underlying common thread among these three work streams is understanding factors that mediate the investment decisions at the firm, industry, or country level. The first chapter of my thesis, External Saving and Exhaustible Resource Extraction, addresses precisely the issue of exhaustible resource management in the face of uncertainty. In linking the extraction and saving behavior under a coherent theoretical framework, this chapter contributes to two veins of the literature that have developed separately until more recently. The second chapter, The Delaying Effect of Storage on Investment: Evidence from the US Oil Sector, continues to explore the role of uncertainty but this time analyses both price and investment dynamics when investment decisions are irreversible. The last chapter of this thesis, Share Buybacks, Monetary Policy and the Cost of Debt, turns it attention to an empirical investigation of the determinants of investment. Starting from the capital structure of firms, this part of my thesis focuses on the role of repurchases in diverting low-cost debt away from investment and employment.

No abstract available / Industrial and Organisational Psychology / D. Com. (Consulting Psychology)