Factor analysis in the stock market: An application to statistical arbitrage

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Statistical arbitrage on commodities

Questa tesi è incentrata sull'analisi dell'arbitraggio statistico, strategia di trading che cerca di trarre profitto dalle fluttuazioni statistiche di prezzo di uno o più asset sulla base del loro valore atteso. In generale, si creano opportunità di arbitraggio statistico quando si riescono ad individuare delle componenti sistematiche nelle dinamiche dei prezzi di alcuni asset che si muovono con regolarità persistenti e prevalenti. Perturbazioni casuali della domanda e dell’offerta nei mercati possono causare divergenze nei prezzi, dando luogo a opportunità di intermarket spread, ossia simultanei acquisto e vendita di commodities correlate tra loro. Vengono approfonditi vari test econometrici, i test unit root utilizzati per verificare se una serie storica possa essere modellizzata con un processo random walk. Infine viene costruita una strategia di trading basata sull'arbitraggio statistico e applicata numericamente alle serie storiche dal 2010 al 2014 di due titoli azionari sul petrolio: Brent e WTI.

Enhancing and implementing a pairs trading strategy

This paper designs a pairs trading model with the intent to identify existing profitable market opportunities to invest, i.e. traditionally strong correlated stocks that have diverged from its historical norm. It comprises a broad literature review on this strategy whose relevant findings (strategy improvements) are contemplated in the model. The authors combine the statistical results of the model with a backtesting analysis in order to provide guidance on the best investment opportunities.

Pairs Trading -strategia Suomen osakemarkkinoilla

Tutkielman tavoitteena on selvittää soveltuvatko suomalaiset osakkeet parikaupankäyntiin ja voidaanko niillä luoda tuottavia kaupankäyntistrategioita. Tutkielmassa tarkastellaan pystytäänkö suomalaisista osakkeista muodostamaan parikaupankäynnin kannalta toimivia osakepareja. Aineisto koostuu kaikkiaan 53 tutkitusta yrityksestä, joiden joukosta valitaan paras osakepari kultakin viideltä toimialalta. Tutkimusperiodi käsittää vuodet 2004–2007, eli se sisältää noin 1000 kaupankäyntipäivää per osa-ke. Viittä valittua osakeparia tutkitaan tarkemmin tilastollisilla ja teknisillä analyysimenetelmillä. Empiiristen tulosten perusteella suomalaiset osakkeet soveltuvat hyvin parikaupankäyntiin. Jokaisella viidellä tutkitulla osakeparilla ilmeni selvää hintojen erkaantumista ja konvergoitumista, joten niillä olisi tutkimuspe-riodin aikana pystynyt käymään menestyksekästä parikauppaa.

Pairs trading profitability in the Finnish stock market: A comparison between three methods

Pairs trading is an algorithmic trading strategy that is based on the historical co-movement of two separate assets and trades are executed on the basis of degree of relative mispricing. The purpose of this study is to explore one new and alternative copula-based method for pairs trading. The objective is to find out whether the copula method generates more trading opportunities and higher profits than the more traditional distance and cointegration methods applied extensively in previous empirical studies. Methods are compared by selecting top five pairs from stocks of the large and medium-sized companies in the Finnish stock market. The research period includes years 2006-2015. All the methods are proven to be profitable and the Finnish stock market suitable for pairs trading. However, copula method doesn’t generate more trading opportunities or higher profits than the other methods. It seems that the limitations of the more traditional methods are not too restrictive for this particular sample data.

Modelación estocástica y trading algorítmico del spread entre acciones mediante procesos de reversión a la media

Las estrategias de inversión pairs trading se basan en desviaciones del precio entre pares de acciones correlacionadas y han sido ampliamente implementadas por fondos de inversión tomando posiciones largas y cortas en las acciones seleccionadas cuando surgen divergencias y obteniendo utilidad cerrando la posición al converger. Se describe un modelo de reversión a la media para analizar la dinámica que sigue el diferencial del precio entre acciones ordinarias y preferenciales de una misma empresa en el mismo mercado. La media de convergencia en el largo plazo es obtenida con un filtro de media móvil, posteriormente, los parámetros del modelo de reversión a la media se estiman mediante un filtro de Kalman bajo una formulación de estado espacio sobre las series históricas. Se realiza un backtesting a la estrategia de pairs trading algorítmico sobre el modelo propuesto indicando potenciales utilidades en mercados financieros que se observan por fuera del equilibrio. Aplicaciones de los resultados podrían mostrar oportunidades para mejorar el rendimiento de portafolios, corregir errores de valoración y sobrellevar mejor periodos de bajos retornos.

Aplicando estratégias simultâneas de momento e valor no mercado brasileiro

A teoria de Finanças Comportamentais surge como uma nova abordagem ao mercado financeiro, argumentando que alguns eventos podem ser mais bem explicados se as restrições da racionalidade do investidor são relaxadas. Conceitos de psicologia e limites à arbitragem são usados para modelar as ineficiências, criando a idéia de ser possível ganhar sistematicamente do mercado. Este trabalho propõe um novo modelo, simplista na sua implementação, para aproveitar os retornos anormais advindos de estratégias de momentum e reversão à média simultaneamente. A idéia de um efeito momentum de longo prazo mais forte que o de curto prazo é introduzida, mas os resultados empíricos mostram que a dinâmica do mercado brasileiro rejeita este conceito. O modelo falha em conseguir retornos positivos e livres de risco.

Uma nova estratégia de negociação em pares

Uma das principais vantagens das estratégias de negociação em pares está relacionada à baixa correlação com os retornos do mercado. Ao tomar posições compradas e vendidas, estas estratégias são capazes de controlar a magnitude do beta de mercado, mantendo-se praticamente zero ou estatísticamente não significativas. A idéia consiste na realização de arbitragem estatística, aproveitando os desvios de preços de equilíbrio de longo prazo. Como tal, elas envolvem modelos de correção de equilíbrio para os pares de retornos dos ativos. Nós mostramos como construir uma estratégia de negociação de pares que é beneficiada não só pela relação de equilíbrio de longo prazo entre os pares de preços dos ativos da carteira, mas também pela velocidade com que os preços ajustam os desvios para o equilíbrio. Até então, a grande maioria das estratégias envolvendo negociação em pares se baseavam na hipótese de que a obtenção de retornos positivos estaria relacionada à reversão à média caracterizada pela relação de cointegração dos pares, mas ignorava a possibilidade de seleção dos pares testando a velocidade de ajustamento do Vetor de Correção de Erros desta relação. Os resutados deste trabalho indicaram baixos níveis de correlação com o mercado, neutralidade das estratégias, associados a retornos financeiros líquidos e Índice de Sharpe anualizados de 15,05% e 1,96 respectivamente.

Pairs trading in the UK equity market: risk and return

In this paper, we provide the first comprehensive UK evidence on the profitability of the pairs trading strategy. Evidence suggests that the strategy performs well in crisis periods, so we control for both risk and liquidity to assess performance. To evaluate the effect of market frictions on the strategy, we use several estimates of transaction costs. We also present evidence on the performance of the strategy in different economic and market states. Our results show that pairs trading portfolios typically have little exposure to known equity risk factors such as market, size, value, momentum and reversal. However, a model controlling for risk and liquidity explains a far larger proportion of returns. Incorporating different assumptions about bid-ask spreads leads to reductions in performance estimates. When we allow for time-varying risk exposures, conditioned on the contemporaneous equity market return, risk-adjusted returns are generally not significantly different from zero.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Turbulence in collisionless plasmas: statistical analysis from numerical simulations with pressure anisotropy

In recent years, we have experienced increasing interest in the understanding of the physical properties of collisionless plasmas, mostly because of the large number of astrophysical environments (e. g. the intracluster medium (ICM)) containing magnetic fields that are strong enough to be coupled with the ionized gas and characterized by densities sufficiently low to prevent the pressure isotropization with respect to the magnetic line direction. Under these conditions, a new class of kinetic instabilities arises, such as firehose and mirror instabilities, which have been studied extensively in the literature. Their role in the turbulence evolution and cascade process in the presence of pressure anisotropy, however, is still unclear. In this work, we present the first statistical analysis of turbulence in collisionless plasmas using three-dimensional numerical simulations and solving double-isothermal magnetohydrodynamic equations with the Chew-Goldberger-Low laws closure (CGL-MHD). We study models with different initial conditions to account for the firehose and mirror instabilities and to obtain different turbulent regimes. We found that the CGL-MHD subsonic and supersonic turbulences show small differences compared to the MHD models in most cases. However, in the regimes of strong kinetic instabilities, the statistics, i.e. the probability distribution functions (PDFs) of density and velocity, are very different. In subsonic models, the instabilities cause an increase in the dispersion of density, while the dispersion of velocity is increased by a large factor in some cases. Moreover, the spectra of density and velocity show increased power at small scales explained by the high growth rate of the instabilities. Finally, we calculated the structure functions of velocity and density fluctuations in the local reference frame defined by the direction of magnetic lines. The results indicate that in some cases the instabilities significantly increase the anisotropy of fluctuations. These results, even though preliminary and restricted to very specific conditions, show that the physical properties of turbulence in collisionless plasmas, as those found in the ICM, may be very different from what has been largely believed.

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. Methods: Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. Results: Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. Conclusion: To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor.

Quantum statistical correlations in thermal field theories: Boundary effective theory

We show that the one-loop effective action at finite temperature for a scalar field with quartic interaction has the same renormalized expression as at zero temperature if written in terms of a certain classical field phi(c), and if we trade free propagators at zero temperature for their finite-temperature counterparts. The result follows if we write the partition function as an integral over field eigenstates (boundary fields) of the density matrix element in the functional Schrodinger field representation, and perform a semiclassical expansion in two steps: first, we integrate around the saddle point for fixed boundary fields, which is the classical field phi(c), a functional of the boundary fields; then, we perform a saddle-point integration over the boundary fields, whose correlations characterize the thermal properties of the system. This procedure provides a dimensionally reduced effective theory for the thermal system. We calculate the two-point correlation as an example.

Phase transitions and spatially ordered counterion association in ionic-lipid membranes: A statistical model

We propose a statistical model to account for the gel-fluid anomalous phase transitions in charged bilayer- or lamellae-forming ionic lipids. The model Hamiltonian comprises effective attractive interactions to describe neutral-lipid membranes as well as the effect of electrostatic repulsions of the discrete ionic charges on the lipid headgroups. The latter can be counterion dissociated (charged) or counterion associated (neutral), while the lipid acyl chains may be in gel (low-temperature or high-lateral-pressure) or fluid (high-temperature or low-lateral-pressure) states. The system is modeled as a lattice gas with two distinct particle types-each one associated, respectively, with the polar-headgroup and the acyl-chain states-which can be mapped onto an Ashkin-Teller model with the inclusion of cubic terms. The model displays a rich thermodynamic behavior in terms of the chemical potential of counterions (related to added salt concentration) and lateral pressure. In particular, we show the existence of semidissociated thermodynamic phases related to the onset of charge order in the system. This type of order stems from spatially ordered counterion association to the lipid headgroups, in which charged and neutral lipids alternate in a checkerboard-like order. Within the mean-field approximation, we predict that the acyl-chain order-disorder transition is discontinuous, with the first-order line ending at a critical point, as in the neutral case. Moreover, the charge order gives rise to continuous transitions, with the associated second-order lines joining the aforementioned first-order line at critical end points. We explore the thermodynamic behavior of some physical quantities, like the specific heat at constant lateral pressure and the degree of ionization, associated with the fraction of charged lipid headgroups.