Τις τελευταίες δεκαετίες η υψηλή μεταβλητότητα που παρατηρείται στις χρηματοοικονομικές μεταβλητές, έχει δημιουργήσει έντονη την ανάγκη για αποτελεσματική διαχείριση του κινδύνου. Τα παράγωγα χρηματοοικονομικά προϊόντα παρέχουν τα μέσα για αντιστάθμιση του κινδύνου. Προς αυτή την κατεύθυνση έχει κατασκευασθεί ένας δείκτης που αντιπροσωπεύει την τεκμαρτή μεταβλητότητα των παραγώγων χρηματοοικονομικών προϊόντων, ο δείκτης VIX. Σκοπός της εργασίας είναι η διερεύνηση της σχέσης του δείκτη VIX με την αγορά του S&P500 και η σχέση συνολοκλήρωσης τεκμαρτής και δεσμευμένης μεταβλητότητας του S&P500. / --

Στη παρούσα εργασία θα εξετάσουμε το ζήτημα των επενδύσεων κάτω από καθεστώς αβεβαιότητας, καθώς επίσης και το πώς η μη αναστρεψιμότητα του κεφαλαίου επιδρά πάνω στη σχέση αυτή. Πιο συγκεκριμένα, θα εξετάσουμε πως η αβεβαιότητα επιδρά στην επένδυση ξεχωριστών τύπων κεφαλαίου, οι οποίοι χαρακτηρίζονται από διαφορετικό βαθμό μη αναστρεψιμότητας. / We examine the question of investment under conditions of uncertainty, and how the heterogeneity of capital affects this relationship. In particular, we will examine the impact of uncertainty on investment across types of capital, which are characterized by varying degree of irreversibility.

Cette étude démontre une nouvelle forme de synchronisation des investisseurs sur les marchés des changes qui résulte de deux phénomènes psychologiques : La forme de synchronisation examinée ici est un effet des actions spontanées et décentralisées des individus qui prennent leurs propres décisions basées sur leur compréhension interne du marché qui est, en l'occurrence, une "interprétation commune". Dans ce cas, le comportement des investisseurs n'est pas guidé par de quelconques informations « objectives » concernant le marché ni par leurs interactions sociales intentionnelles qui peuvent naturellement faciliter la synchronisation. Dans la première étude, j'ai étudié l'influence des émotions sur le choix des stratégies d'investissement qui peuvent avoir une incidence sur le schéma dominant de la politique des prix. J'ai découvert qu'il existait un effet d'interaction significative de la valence affective et de la stimulation sur le choix de la stratégie d'investissement. Les émotions positives qui occasionnent un niveau élevé d'excitation peuvent faciliter l'émergence d'une synchronisation dans une tendance haussière. Dans la deuxième étude, j'ai utilisé une combinaison de deux techniques expérimentales : des expériences avec des sujets humains et des simulations par ordinateur, pour étudier la dynamique d'une prise de décision collective dans un modèle simple de marchés financiers. Les expériences montrent à quel point l'interaction de l'historique des prix et de certains mécanismes d'apprentissage peut conduire à l'émergence de préjugés collectifs spontanés. De plus, le fait d'appliquer des simulations par ordinateur sur des données générées par des humains permet d'effectuer une prévision de la synchronisation. Les expériences et le cadre théorique suggèrent de nouvelles voies permettant d'aborder la constitution collective d'un comportement spéculatif. / This work shows a new way of synchronization of investors on exchange markets, which results from two psychological phenomena: 1) emotions and 2) cognitive mechanisms. The way of synchronization considered here is an effect of spontaneous and decentralized actions of individuals, who make their own decisions based on their internal understanding of the market which happens to be “shared interpretation”. In such case, the behavior of investors is not guided by any kind of 'objective' market information or their intentional social interactions, which may naturally facilitate synchronization. In the first study I investigated the influence of emotions on choice of investment strategies that may impact a dominant pattern of the price behavior. I found that there is a significant interaction effect of affective valence and arousal on the selection of investment strategy. Positive emotions, which cause high arousal, may facilitate emergence of synchronization in the direction of uptrend. In the second study, I used a combination of two experimental techniques: experiments with human subjects and computer simulations, to study the dynamics of collective decision-making in a simple financial markets' model. The experiments show how interplay of certain price history and learning mechanisms can lead to the emergence of spontaneous collective biases. Additionally, applying computer simulations to the data generated by the humans enables prediction of synchronization. The experiments and a theoretical framework suggest new ways to access the pathways involved in a collective formation of speculative behavior.

This thesis improves our understanding of asset prices and returns as it documents a regime shift risk premium in currencies, corrects the estimation bias in the term premium of bond yields, and shows the impact of ambiguity aversion towards parameter uncertainty on equities. The thesis consists of three essays. The first essay "The Yen Risk Premiums: A Story of Regime Shifts in Bond Markets" documents a new monetary mechanism, namely the shift of monetary policies, to account for the forward premium puzzle in the USD-JPY currency pair. The shift of monetary policy regimes is modelled by a regime switching dynamic term structure model where the risk of regime shifts is priced. Our model estimation characterises two policy regimes in the Japanese bond market---a conventional monetary policy regime and an unconventional policy regime of quantitative easing. Using foreign exchange data from 1985 to 2009, we find that the shift of monetary policies generates currency risk: the yen excess return is predicted by the Japanese regime shift premium, and the emergence of the yen carry trade in the mid 1990s is associated with the transition from the conventional to the unconventional monetary policy in Japan. The second essay "Correcting Estimation Bias in Regime Switching Dynamic Term Structure Models" examines the small sample bias in the estimation of a regime switching dynamic term structure model. Using US data from 1971 to 2009, we document two regimes driven by the conditional volatility of bond yields and risk factors. In both regimes, the process of bond yields is highly persistent, which is the source of estimation bias when the sample size is small. After bias correction, the inference about expectations of future policy rates and long-maturity term premia changes dramatically in two high-volatility episodes: the 1979--1982 monetary experiment and the recent financial crisis. Empirical findings are supported by Monte Carlo simulation, which shows that correcting small sample bias leads to more accurate inference about expectations of future policy rates and term premia compared to before bias correction. The third essay "Learning about the Persistence of Recessions under Ambiguity Aversion" incorporates ambiguity aversion into the process of parameter learning and assess the asset pricing implications of the model. Ambiguity is characterised by the unknown parameter that governs the persistence of recessions, and the representative investor learns about this parameter while being ambiguity averse towards parameter uncertainty. We examine model-implied conditional moments and simulated moments of asset prices and returns, and document an uncertainty effect that characterises the difference between learning under ambiguity aversion and learning under standard recursive utility. This uncertainty effect is asymmetric across economic expansions and recessions, and this asymmetry generates in simulation a sharp increase in the equity premium at the onset of recessions, as in the recent financial crisis.

This thesis is an attempt to bridge some research gaps in the area of behavioural finance and investment through adopting the three essays scheme of PhD dissertations. There is a widespread belief that the traditional finance theory failed to provide a sufficient and plausible explanation for (1) what motivates individual investors to trade, (2) the pattern of their trading and the formation of their portfolios, (3) the determinants of cross section of expected returns other than risk. Behavioural Finance, however, offers more realistic assumptions based on two building blocks; behavioural biases of irrational investors and the limits of arbitrage that prevent the arbitrageurs from correcting mispricing and pushing prices back to fundamental values. This dissertation is structured as follows: In the first essay, the disposition effect is defined as the propensity of investors to realize gains too early while being loath to realize losses. Capital gains overhang is a measure of unrealized capital gains and losses that is associated with the disposition effect and the trading activities of behaviourally biased investors. We discover that firm characteristics can play a role in explaining variations in the capital gains overhang that is consistent with the activities of behaviourally biased and disposition investors. Specifically, we find that capital gains overhang is increasing in firm attributes that attract behaviourally biased investors, namely, earnings per share, leverage, growth and size. Capital gains overhang is also declining in market liquidity, possibly because liquidity allows behaviourally biased investors to excessively trade shares and beta and corporate earnings, probably because when high risk and inefficient firms experience losses, disposition investors experience capital losses that they are reluctant to realize. In the second essay, quantile regressions are employed to analyse the relationship between the unrealized capital gains overhang and expected returns. The ability of the disposition effect to generate momentum is also considered for the extreme expected return regions (0.05th) and (0.95th) quantiles. To do so, 450,617 observations belonging to 5176 US firms are employed, covering a time span from January 1998 to June 2015. Following the methodology of Grinblatt and Han (2005), the findings show significant differences across various quantiles in terms of signs and magnitudes. These findings indicate a nonlinear relationship between capital gains overhang and expected returns since the impact of capital gains overhang as a proxy for disposition effect on expected returns vary across the expected return distribution. More precisely, the coefficients of capital gains overhang are significantly positive and decline as the expected returns quantiles increase from the lowest to the median expected return quantiles. However, they become significantly negative and rise with the increase in expected returns quantiles above median expected returns quantiles. The findings also suggest that the disposition effect is not a good noisy proxy for momentum at the lowest expected return quantile (0.05th). However, interestingly it seems to generate contrarian in returns at the highest expected returns quantile (0.95th). In the third essays, we try to discover systematic disagreements in momentum, asymmetric volatility and the idiosyncratic risk momentum return relationship between high-tech stocks and low-tech stocks. We develop several hypotheses that suggest greater momentum profits, fainter asymmetric volatility and weaker idiosyncratic risk-momentum return relation in the high-tech stocks relative to the low tech stocks. To this end, we divide 5795 stocks that are listed in the Russell 3000 index from January 1995 to December 2015 into two samples SIC code and analysed them using the Fama French with GJR-GARCH-M term. The results show that the high-tech stocks provide greater momentum profits especially for portfolios that have holding and ranking periods of less than 12 months. In most cases momentum returns in the high-tech stocks explain a symmetric response to good and bad news while the momentum returns in the low-tech stocks show an asymmetric response. Finally, the idiosyncratic risk-momentum return relation is insignificant for high-tech stocks while it is significant and negative for low-tech stocks. That is, as idiosyncratic risk increases, momentum decreases for low-tech stocks. These findings are robust to different momentum strategies and to different breakpoints.

Cette thèse, qui revisite la perspective critique développée par l'École de Francfort, propose d'investir les transformations de l'industrie culturelle à l'ère du numérique. À partir de l'exemple du financement participatif, nous questionnons la pertinence d'idéaux normatifs structurés autour des notions d'autonomie, d'authenticité et de collaboration. Ces valeurs, constitutives de l'utopie du numérique à son origine, sont remises en avant par les porteurs de projets et les internautes qui y contribuent. Le financement participatif est présenté comme le moyen de produire et de consommer différemment de la culture. À partir des discours des acteurs, nous nous attachons à observer les mécanismes de récupération et d'incorporation de ces transformations au sein de l'industrie culturelle et d'une « forme de vie » spécifique. Ce double mécanisme de récupération des idéaux et de transformation à partir d'eux est appréhendé comme caractéristique d'une modernité hautement paradoxale (A. Honneth). Ce dispositif est saisi de manière dialectique, en s'attachant à l'étude des processus d'autonomisation au coeur même de ces paradoxes. / This dissertations, which reviews Frankfurt School Critical theory's, intends to question the cultural industry's transformations in a digital society. Through the example of crowdfunding, we question the relevance of normative ideals structured on autonomy, authenticity, independance and collaboration. This values, onces constitutives of the digital ideology, are now highlighted by the crowdfunding creators and producers. Seen as a tool which can encourage disintermediation, crowdfunding is introduced as a new way of producing and consumming culture. Based on actor's statements, we desribe how those transformations are incorporated by the cultural industry and, widely by a specific« form of life ». This dual mechanism of ideals' recuperation and transformation within them is understood as specific from a highly paradoxical modernity (A. Honneth). Crowdfunding is considered in dialectical way, and lets us see the empowerment process which appears for individuals in the heart of this paradoxes.

Cette thèse est composée de quatre chapitres qui contribuent à une meilleure connaissance des comportements d’échange des investisseurs individuels et de leur performance. Dans le premier chapitre, nous réalisons la première étude consacrée aux performances de portefeuille des investisseurs individuels français. A partir d’une base de données de plus de 8 millions de transactions réalisées par 56 723 investisseurs, nous montrons que les investisseurs français affichent des rentabilités ajustées au risque négatives sur leurs portefeuilles et font des choix d’investissement pénalisants. De plus, nous mettons en évidence que les investisseurs les plus sophistiqués ne sont pas plus performants que leurs pairs.Dans le second chapitre, nous montrons que l’aspiration individuelle constitue un déterminant clé pour expliquer l’hétérogénéité des performances de portefeuille. Nous définissons les aspirations selon la Théorie Comportementale du Portefeuille. Les investisseurs qui ont de fortes aspirations détiennent des portefeuilles plus risqués, échangent plus fréquemment et diversifient moins que les investisseurs ayant de faibles aspirations. En contrôlant de la fréquence des échanges, de la diversification et des facteurs de risque habituels, nous montrons que les investisseurs ayant de fortes aspirations sous-performent les investisseurs ayant de faibles aspirations.Dans le troisième chapitre nous analysons les performances des investisseurs individuels via des mesures adaptées à leurs préférences. Lorsque leurs performances sont évaluées avec ces mesures plutôt qu’avec le ratio de Sharpe, une plus grande part des investisseurs bat l’indice de marché. Cette observation jette un regard nouveau sur les capacités de gestion des investisseurs individuels. Cependant, nous montrons que l’amélioration des performances est liée à la skewness des portefeuilles plutôt qu’à une sélection de titres pertinente.Dans le dernier chapitre, nous explorons les comportements de rachat des investisseurs individuels. Nous montrons que les investisseurs préfèrent racheter (1) les titres pour lesquels ils ont réalisé une plus-value lors de la vente (2) les titres dont le prix a diminué depuis la vente. Nos tests excluent les explications rationnelles et confirment que l’évitement du regret est à l’origine de tels comportements. Sur la base d’une analyse de survie, nous montrons que les investisseurs sophistiqués sont moins sujets à ces préférences. / This dissertation is composed of four chapters that make a substantial contribution to existing knowledge of the trading behavior and performance of individual investors. The first chapter provides the most extensive study of the trading performance of French individual investors to date. Based on a large database of nearly 8 million trades realized by56,723 investors, we show that French investors exhibit negative risk-adjusted returns on their portfolios, and make penalizing choices in their trades. We find that more sophisticated investors do not perform better than their peers, and we conclude that investors would gain more from applying a passive strategy. In the second chapter, we evidence that individual aspiration is a key determinant of existing heterogeneity in portfolio performance. We define aspirations according to the Behavioral Portfolio Theory. Investors who have high aspirations hold riskier portfolios, trade more frequently and diversify less than investors who have low aspirations. After controlling for turnover, diversification and usual risk factors, we find that investors with high aspirations underperform investors with low aspirations.In the third chapter we highlight alternative measures of performance that efficiently convey the real preferences of investors. When they are evaluated with these alternative measures rather than with the Sharpe ratio, a higher proportion of investors beat the market index. This observation challenges the global evidence that individual investors are poor portfolio managers. However, our evidence suggests that the improvement of an investor’s performance is linked to portfolio skewness rather than relevant stock selection.In the last chapter, we explore the repurchase behavior of individual investors. We find that French investors prefer to repurchase (1) stocks that have been sold for a gain and (2) stocks that have lost value since their sale. Our tests exclude rational explanations for these preferences and confirm our hypothesis that such patterns can be traced to the avoidance of regret in trades. We use survival analysis to demonstrate that sophisticated investors suffer less from there purchase preferences.

In this thesis a mathematical description and analysis of the Cumulative Prospect Theory is presented. Conditions that ensure well-posedness of the problem are provided, as well as existence results concerning optimal policies for discrete-time incomplete market models and for a family of diffusion market models. A brief outline of how this work is organised follows. In Chapter 2 important results on weak convergence and discrete time finance models are described, these facts form the main background to introduce in Chapter 3 the problem of optimal investment under the CPT theorem in a discrete time setting. We describe our model, present some assumptions and main results are derived. The second part of this work comprises the description of the martingale problem formulation of diffusion processes in Chapter 4. A key result on the limits and topological properties of the set of laws of a class of Itô processes is described in Chapter 5. Finally, we introduce a factor model that includes a class of stochastic volatility models, possibly with path-depending coefficients. Under this model, the problem of optimal investment with a behavioural investor is analysed and our main results on well-posedness and existence of optimal strategies are described under the framework of weak solutions. Further research and challenges when applying the techniques developed in this work are described.

Many econometric analyses of commodity futures over the years have been performed using spot or front month contract prices. Using such daily prices without the consideration of the associated contract traded volumes is slightly erroneous because, in reality, traders will typically trade the ‘most liquid’ contract, that is, the contract with the largest average daily volume (ADV). The reason for this is in order to gain the best price when buying or selling. If this ‘true’ time series is to be considered, a mapping procedure is required to account for the price jumps at the time when a trader trades out of the expiring contract and enters the new front month contract. A key finding was that this effect was significant, irrespective of the size of the price jump, sometimes referred to as basis or roll and also due to the accumulated roll over a number of years corresponding to multiple contracts. It was also found that the mapping procedure has a significant effect on the time series and should hence always be employed if the realistic traded time series is to be considered. Given this phenomenon, algorithmically-traded commodities futures must necessarily employ such time series when creating metrics or considering an econometric analysis. The key findings include the importance of diversification in algorithmically-traded portfolios, utilising the AOM and PSI metrics. The mapping of data sets to create realistic ‘live-traded’ time series was found to be significant, while the optimal day of roll over prior to contract expiry was found to be related to the trading volumes for certain commodities. Other key findings include the causalities and spillovers within the metals sector where various relationships are evident once the results were processed and analysed, both pre and post mapping. Interestingly, the key relationships including bidirectional volatility and shock spillovers between the four key metals existed when the unmapped data was used however, many of the feedbacks within these relationships was lost when the mapped data sets were considered. A significant finding was therefore the consistent differences in findings between mapped and unmapped data sets attributed to the optimisation or favourability of the models (whether econometric or algorithmic). This is due to the unmapped data including roll or basis (which the models are fitted to) taking into account the roll or basis and utilising them in finding relationships between data sets. In the mapped data set (the time series seen by traders) the roll or basis is accounted for and hence the relationships found stand in real-time trading situations. The differences in the results show how the effect of mapping can be significant with unmapped data sets displaying results which will not exist in a real time traded time series.

Cette thèse cherche à lier les cycles économiques et la gestion de portefeuille. Le premier chapitre construit un cadre théorique entre les cycles économiques et les primes de risques. Il met en évidence l’importance des points de retournement du cycle de croissance, plus connu sous le nom d’écart de production. Les deux chapitres suivants ont pour objectif de détecter en temps réel ces points de retournement. La première approche se concentre sur une méthode non paramétrique d’apprentissage automatique simple et facilement compréhensible appelée quantification vectorielle adaptative. La seconde approche utilise des méthodes plus complexes d’apprentissage automatique, dites ensemblistes : les forêts aléatoires et le boosting. Les deux démarches permettent de créer des stratégies d’investissement performantes en temps réel. Enfin, le dernier chapitre élabore une méthode d’allocation d’actifs à partir de différents algorithmes de regroupement hiérarchique. Les résultats empiriques démontrent l’intérêt de cette tentative : les portefeuilles créés sont robustes, diversifiés et lucratifs. / A well-worked theory of macro-based investment decision is introduced. The theoretical influence of economic cycles on time-varying risk premiums is explained and exhibited. The importance of the turning points of the growth cycle, better known as the output gap, is outlined. To quickly and accurately detect economic turning points, probabilistic indicators are first created from a simple and transparent machine-learning algorithm known as Learning Vector Quantization. Those indicators are robust, interpretable and preserve economic consistency. A more complex approach is then evaluated: ensemble machine learning algorithms, referred to as random forest and as boosting, are applied. The two key features of those algorithms are their abilities to entertain a large number of predictors and to perform estimation and variable selection simultaneously. With both approaches investment strategies based on the models achieve impressive risk-adjusted returns: timing the market is thus possible. At last, exploring a new way of capital allocation, a hierarchical clustering based asset allocation method is introduced. The empirical results indicate that hierarchical clustering based portfolios are robust, truly diversified and achieve statistically better risk-adjusted performances than commonly used portfolio optimization techniques.