Finite-Sample Diagnostics for Multivariate Regressions with Applications to Linear Asset Pricing Models

In this paper, we propose several finite-sample specification tests for multivariate linear regressions (MLR) with applications to asset pricing models. We focus on departures from the assumption of i.i.d. errors assumption, at univariate and multivariate levels, with Gaussian and non-Gaussian (including Student t) errors. The univariate tests studied extend existing exact procedures by allowing for unspecified parameters in the error distributions (e.g., the degrees of freedom in the case of the Student t distribution). The multivariate tests are based on properly standardized multivariate residuals to ensure invariance to MLR coefficients and error covariances. We consider tests for serial correlation, tests for multivariate GARCH and sign-type tests against general dependencies and asymmetries. The procedures proposed provide exact versions of those applied in Shanken (1990) which consist in combining univariate specification tests. Specifically, we combine tests across equations using the MC test procedure to avoid Bonferroni-type bounds. Since non-Gaussian based tests are not pivotal, we apply the “maximized MC” (MMC) test method [Dufour (2002)], where the MC p-value for the tested hypothesis (which depends on nuisance parameters) is maximized (with respect to these nuisance parameters) to control the test’s significance level. The tests proposed are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995. Our empirical results reveal the following. Whereas univariate exact tests indicate significant serial correlation, asymmetries and GARCH in some equations, such effects are much less prevalent once error cross-equation covariances are accounted for. In addition, significant departures from the i.i.d. hypothesis are less evident once we allow for non-Gaussian errors.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

How the full opening of the capital account to highly liquid financial markets led Latin America to two and a half cycles of ‘mania, panic and crash’

Latin America has recently experienced three cycles of capital inflows, the first two ending in major financial crises. The first took place between 1973 and the 1982 ‘debt-crisis’. The second took place between the 1989 ‘Brady bonds’ agreement (and the beginning of the economic reforms and financial liberalisation that followed) and the Argentinian 2001/2002 crisis, and ended up with four major crises (as well as the 1997 one in East Asia) — Mexico (1994), Brazil (1999), and two in Argentina (1995 and 2001/2). Finally, the third inflow-cycle began in 2003 as soon as international financial markets felt reassured by the surprisingly neo-liberal orientation of President Lula’s government; this cycle intensified in 2004 with the beginning of a (purely speculative) commodity price-boom, and actually strengthened after a brief interlude following the 2008 global financial crash — and at the time of writing (mid-2011) this cycle is still unfolding, although already showing considerable signs of distress. The main aim of this paper is to analyse the financial crises resulting from this second cycle (both in LA and in East Asia) from the perspective of Keynesian/ Minskyian/ Kindlebergian financial economics. I will attempt to show that no matter how diversely these newly financially liberalised Developing Countries tried to deal with the absorption problem created by the subsequent surges of inflow (and they did follow different routes), they invariably ended up in a major crisis. As a result (and despite the insistence of mainstream analysis), these financial crises took place mostly due to factors that were intrinsic (or inherent) to the workings of over-liquid and under-regulated financial markets — and as such, they were both fully deserved and fairly predictable. Furthermore, these crises point not just to major market failures, but to a systemic market failure: evidence suggests that these crises were the spontaneous outcome of actions by utility-maximising agents, freely operating in friendly (‘light-touch’) regulated, over-liquid financial markets. That is, these crises are clear examples that financial markets can be driven by buyers who take little notice of underlying values — i.e., by investors who have incentives to interpret information in a biased fashion in a systematic way. Thus, ‘fat tails’ also occurred because under these circumstances there is a high likelihood of self-made disastrous events. In other words, markets are not always right — indeed, in the case of financial markets they can be seriously wrong as a whole. Also, as the recent collapse of ‘MF Global’ indicates, the capacity of ‘utility-maximising’ agents operating in (excessively) ‘friendly-regulated’ and over-liquid financial market to learn from previous mistakes seems rather limited.

How the full opening of the capital account to highly liquid financial markets led Latin America to two and a half cycles of ‘mania, panic and crash’

Latin America has recently experienced three cycles of capital inflows, the first two ending in major financial crises. The first took place between 1973 and the 1982 ‘debt-crisis’. The second took place between the 1989 ‘Brady bonds’ agreement (and the beginning of the economic reforms and financial liberalisation that followed) and the Argentinian 2001/2002 crisis, and ended up with four major crises (as well as the 1997 one in East Asia) — Mexico (1994), Brazil (1999), and two in Argentina (1995 and 2001/2). Finally, the third inflow-cycle began in 2003 as soon as international financial markets felt reassured by the surprisingly neo-liberal orientation of President Lula’s government; this cycle intensified in 2004 with the beginning of a (purely speculative) commodity price-boom, and actually strengthened after a brief interlude following the 2008 global financial crash — and at the time of writing (mid-2011) this cycle is still unfolding, although already showing considerable signs of distress. The main aim of this paper is to analyse the financial crises resulting from this second cycle (both in LA and in East Asia) from the perspective of Keynesian/ Minskyian/ Kindlebergian financial economics. I will attempt to show that no matter how diversely these newly financially liberalised Developing Countries tried to deal with the absorption problem created by the subsequent surges of inflow (and they did follow different routes), they invariably ended up in a major crisis. As a result (and despite the insistence of mainstream analysis), these financial crises took place mostly due to factors that were intrinsic (or inherent) to the workings of over-liquid and under-regulated financial markets — and as such, they were both fully deserved and fairly predictable. Furthermore, these crises point not just to major market failures, but to a systemic market failure: evidence suggests that these crises were the spontaneous outcome of actions by utility-maximising agents, freely operating in friendly (light-touched) regulated, over-liquid financial markets. That is, these crises are clear examples that financial markets can be driven by buyers who take little notice of underlying values — investors have incentives to interpret information in a biased fashion in a systematic way. ‘Fat tails’ also occurred because under these circumstances there is a high likelihood of self-made disastrous events. In other words, markets are not always right — indeed, in the case of financial markets they can be seriously wrong as a whole. Also, as the recent collapse of ‘MF Global’ indicates, the capacity of ‘utility-maximising’ agents operating in unregulated and over-liquid financial market to learn from previous mistakes seems rather limited.

The role of politicians in inciting financial markets to attack the eurozone. EuropEos Commentary No. 4, 21 June 2010

While acknowledging that the sustainability of sovereign debt is a serious issue that must be confronted, this EuropEos Commentary finds that financial markets have blown the problem completely out of proportion, leading to a full-scale confidence crisis. The authors present evidence suggesting that politicians’ public disagreements and careless statements at critical junctures may have added oil to incipient fire. By creating the impression that domestic political interests would take precedence over orderly management of the Greek debt crisis, they raised broader doubts about their ability to address fundamental economic divergences within the area, which are the real source of debt sustainability problems in the medium term.

Financial markets--preliminary observations on the October 1987 crash : report to congressional requesters /

"GAO/GGD-88-38."

Tool for discovering sequential patterns in financial markets

The goal of this thesis is the study of a tool that can help analysts in finding sequential patterns. This tool will have a focus on financial markets. A study will be made on how new and relevant knowledge can be mined from real life information, potentially giving investors, market analysts, and economists new basis to make informed decisions. The Ramex Forum algorithm will be used as a basis for the tool, due to its ability to find sequential patterns in financial data. So that it further adapts to the needs of the thesis, a study of relevant improvements to the algorithm will be made. Another important aspect of this algorithm is the way that it displays the patterns found, even with good results it is difficult to find relevant patterns among all the studied samples without a proper result visualization component. As such, different combinations of parameterizations and ways to visualize data will be evaluated and their influence in the analysis of those patterns will be discussed. In order to properly evaluate the utility of this tool, case studies will be performed as a final test. Real information will be used to produce results and those will be evaluated in regards to their accuracy, interest, and relevance.

Three essays on the psychology of investment and financial markets

Préface My thesis consists of three essays where I consider equilibrium asset prices and investment strategies when the market is likely to experience crashes and possibly sharp windfalls. Although each part is written as an independent and self contained article, the papers share a common behavioral approach in representing investors preferences regarding to extremal returns. Investors utility is defined over their relative performance rather than over their final wealth position, a method first proposed by Markowitz (1952b) and by Kahneman and Tversky (1979), that I extend to incorporate preferences over extremal outcomes. With the failure of the traditional expected utility models in reproducing the observed stylized features of financial markets, the Prospect theory of Kahneman and Tversky (1979) offered the first significant alternative to the expected utility paradigm by considering that people focus on gains and losses rather than on final positions. Under this setting, Barberis, Huang, and Santos (2000) and McQueen and Vorkink (2004) were able to build a representative agent optimization model which solution reproduced some of the observed risk premium and excess volatility. The research in behavioral finance is relatively new and its potential still to explore. The three essays composing my thesis propose to use and extend this setting to study investors behavior and investment strategies in a market where crashes and sharp windfalls are likely to occur. In the first paper, the preferences of a representative agent, relative to time varying positive and negative extremal thresholds are modelled and estimated. A new utility function that conciliates between expected utility maximization and tail-related performance measures is proposed. The model estimation shows that the representative agent preferences reveals a significant level of crash aversion and lottery-pursuit. Assuming a single risky asset economy the proposed specification is able to reproduce some of the distributional features exhibited by financial return series. The second part proposes and illustrates a preference-based asset allocation model taking into account investors crash aversion. Using the skewed t distribution, optimal allocations are characterized as a resulting tradeoff between the distribution four moments. The specification highlights the preference for odd moments and the aversion for even moments. Qualitatively, optimal portfolios are analyzed in terms of firm characteristics and in a setting that reflects real-time asset allocation, a systematic over-performance is obtained compared to the aggregate stock market. Finally, in my third article, dynamic option-based investment strategies are derived and illustrated for investors presenting downside loss aversion. The problem is solved in closed form when the stock market exhibits stochastic volatility and jumps. The specification of downside loss averse utility functions allows corresponding terminal wealth profiles to be expressed as options on the stochastic discount factor contingent on the loss aversion level. Therefore dynamic strategies reduce to the replicating portfolio using exchange traded and well selected options, and the risky stock.

Random diffusion and leverage effect in financial markets

We prove that Brownian market models with random diffusion coefficients provide an exact measure of the leverage effect [J-P. Bouchaud et al., Phys. Rev. Lett. 87, 228701 (2001)]. This empirical fact asserts that past returns are anticorrelated with future diffusion coefficient. Several models with random diffusion have been suggested but without a quantitative study of the leverage effect. Our analysis lets us to fully estimate all parameters involved and allows a deeper study of correlated random diffusion models that may have practical implications for many aspects of financial markets.

Information, learning, and risk in financial markets

Cette thèse comprend trois essais qui abordent l'information le processus d'ap-prentissage ainsi que le risque dans les marchés finances. Elle se concentre d'abord sur les implications à l'équilibre de l'hétérogénéité des agents à travers un processus d'apprentissage comprtemental et de mise à jour de l'information. De plus, elle examine les effets du partage des risques dans un reseau entreprise-fournisseur. Le premier chapitre étudie les effets du biais de disponibili sur l'évaluation des actifs. Ce biais décrit le fait que les agents surestiment l'importance de l'information acquise via l'expérience personnelle. L'hétérogénéité restante des différentes perceptions individuelles amène à une volonté d'échanges. Conformé¬ment aux données empiriques, les jeunes agents échangent plus mais en même temps souffrent d'une performance inférieure. Le deuxième chapitre se penche sur l'impact qu'ont les différences de modelisation entre les agents sur leurs percevons individuelles du processus de prix, dans le contexte des projections de modèles. Les agents sujets à un biais de projection pensent être représentatifs et interprètent les opinions des autres agents comme du bruit. Les agents, avec des modèles plus persistants, perçoivent que les prix réagissent de façon excessive lors des périodes de turbulence. Le troisième chapitre analyse l'impact du partage des risques dans la relation entreprise-fournisseur sur la décision optimale de financement de l'entreprise. Il étudie l'impact sur l'optimisation de la structure du capital ainsi que sur le coût du capital. Les résultats indiquent en particulier qu'un fournisseur avec un effet de levier faible est utile pour le financement d'un nouveau projet d'investissement. Pour des projets très rentables et des fournisseurs à faible effet de levier, le coût des capitaux propres de l'entreprise peut diminuer.

Stock and Bond Market Integration: Evidence from Russian Financial Markets

Minimizing the risks of an investment portfolio but not in the favour of expected returns is one of the key interests of an investor. Typically, portfolio diversification is achieved using two main strategies: investing in different classes of assets thought to have little or negative correlations or investing in similar classes of assets in multiple markets through international diversification. This study investigates integration of the Russian financial markets in the time period of January 1, 2003 to December 28, 2007 using daily data. The aim is to test the intra-country and cross-country integration of the Russian stock and bond markets between seven countries. Our test methodology for the short-run dynamics testing is the vector autoregressive model (VAR) and for the long-run cointegration testing we use the Johansen cointegration test which is an extension to VAR. The empirical results of this study show that the Russian stock and bond markets are not integrated in the long-run either at intra-country or cross-country level which means that the markets are relatively segmented. The short-run dynamics are also relatively low. This implies a presence of potential gains from diversification.