Submitted by Jadi Castro (jadiana.castro@ucb.br) on 2017-02-21T18:01:09Z No. of bitstreams: 1 AdaoVoneTeixeiradeAssuncaoDissertacao2016.pdf: 1069424 bytes, checksum: 2cec9cf848a40c34902559e8d8f0c95c (MD5) / Approved for entry into archive by Kelson Anthony de Menezes (kelson@ucb.br) on 2017-02-21T18:02:23Z (GMT) No. of bitstreams: 1 AdaoVoneTeixeiradeAssuncaoDissertacao2016.pdf: 1069424 bytes, checksum: 2cec9cf848a40c34902559e8d8f0c95c (MD5) / Made available in DSpace on 2017-02-21T18:02:24Z (GMT). No. of bitstreams: 1 AdaoVoneTeixeiradeAssuncaoDissertacao2016.pdf: 1069424 bytes, checksum: 2cec9cf848a40c34902559e8d8f0c95c (MD5) Previous issue date: 2016-03-31 / Aplicamos o Modelo Autoregressivo de Dura????o Condicional (ACD) Mercado de Futuros de Taxa Interbanc??ria Brasileira. A amostra foi constru??da com base em contratos M??s antes da expira????o para replicar a curva de obriga????es de um m??s eo per??odo estudado Vai de julho de 2013 a setembro de 2015. Utilizamos M??xima Verossimilhan??a Estimativa baseada nas distribui????es de probabilidade mais populares na literatura ACD: Exponencial, gama e Weibull e verificou-se que a estimativa baseada na A distribui????o exponencial foi a melhor op????o para modelar os dados. / We applied the basic Autoregressive Conditional Duration Model (ACD) to the Brazilian Interbank Rate Futures Market. The sample was built using contracts in the month prior to expiration to replicate a one month bond curve and the period studied goes from july of 2013 to september of 2015. We used Maximum Likelihood Estimation based on the most popular probability distributions in the ACD literature: exponential, gamma and Weibull and we found that the estimation based on the exponential distributional was the best option to model the data.

<p>In this thesis we study the Birnbaum-Saunders autoregressive conditional du- ration (BS-ACD) model. As opposed to the standard ACD model, formulated in terms of the conditional mean duration, the BS-ACD model specifies the time-varying model dynamics in terms of the conditional median duration. By means of Monte Carlo simulations, we examine the asymptotic behaviour of the maximum likelihood estimators. We then present a study of numerical efficacy of some optimization algorithms in relation to the BS-ACD model. On a practical side, we fit the BS-ACD model to samples for six securities listed on the New York Stock Exchange.</p> / Master of Science (MSc)

Nous analysons dans cette thèse le pouvoir de contribution du marché d’options à l’efficience informationnelle et à la stabilité du marché des actions françaises cotées sur Euronext-LIFFE pour la période 1996-2006.Nous nous proposons, en outre, de définir dans quelle mesure la fusion d’Euronext avec le Liffe en 2002 et les conditions macroéconomiques de 1996-2006, influencent cette contribution.L’étude de l’introduction d’options sur les caractéristiques des actions met en évidence, (i) l’absence d’impact aussi bien sur la volatilité que sur le risque systématique des actions mesuré par le bêta, (ii) un effet prix négatif qui reste statistiquement non significatif dans la majorité des séances, (iii) une hausse significative du volume, (iv) une baisse de la fourchette de prix. La modélisation VAR montre que l’introduction de l’option ne renforce l’ajustement du volume par rapport à la volatilité des actions significativement qu’au seuil de 10%. En outre, la proportion des agents informés sur le marché des actions n’est pas plus importante à la suite de la création d’options.La modélisation Log-ACD (Autoregressive Conditionnel Duration) augmentée par l’introduction de la liquidité comme variable explicative ne détecte aucun effet de l’introduction de l’option sur le renfort informationnel des actions.Par ailleurs, notre étude met en évidence que l’objectif du marché d’options est la couverture (respectivement la spéculation et/ou arbitrage) en période de forte volatilité (respectivement faible). La fusion d’Euronext avec le Liffe en 2002 n’introduit pas de changement significatif au niveau de l’amélioration du processus d’ajustement des prix aux nouvelles. Le résultat global de l’absence d’effet de l’introduction de l’option sur les actions, s’explique par le trading fondé, actuellement en France, sur la volatilité. Ce qui amenuise le pouvoir prédictif des options. / We investigate the impact of option listing on the underlying stock dynamics and the informational efficiency of the stock market, using data from the French Euronext Paris stock market about new option listing that occurred over the period 1996 – 2006. We take into account the implementation of a new trading system after the Euronext merger with the Liffe market in 2002 and the macroeconomic changes over the period.Considering different characteristics of stocks, we observe (i) no effect on both volatility and systematic risk measured by the beta, (ii) a negative price effect, although insignificant at the majority of times, (iii) a significant rise in the volume and, finally (iv), a significant decrease in the spread bid-ask. By estimating a VAR model, we highlight a better adjustment to new information, observable jointly through contemporaneous and delayed relations between volume and volatility. However, when decomposing volatility into the contributions of informed and non-informed agents, we cannot document any migration of informed traders to the underlying stock market after option listing. We confirm the absence of impact of option listing on the underlying stock pricing efficiency by examining the stock price duration dynamics, using a modified Log-ACD model that accounts for liquidity captured by trade size.On the other hand, we show that in high volatility periods (low volatility periods), the option market plays a hedging role (speculation and/or arbitrage). The implementation of the new trading system after the Euronext merger with the Liffe market in 2002 appears to have no significant impact on the underlying stock. The global result about the absence impact of option listing is justified by the underlying stock’s volatility-driven trading. These strategies disturb the connection between option and underlying stock markets and the predictive power of option prices.

❆❜str❛❝t ❚❤✐s ❞✐♣❧♦♠❛ t❤❡s✐s ❞❡❛❧s ✇✐t❤ ♣r♦♣❡rt✐❡s ♦❢ ❆❈❉ ♣r♦❝❡ss ❛♥❞ ♠❡t❤♦❞s ♦❢ ✐ts ❡st✐♠❛t✐♦♥✳ ❋✐rst✱ t❤❡ ❜❛s✐❝ ❞❡☞♥✐t✐♦♥s ❛♥❞ r❡❧❛t✐♦♥s ❜❡t✇❡❡♥ ❆❘▼❆ ❛♥❞ ●❆❘❈❍ ♣r♦❝❡ss❡s ❛r❡ st❛t❡❞✳ ■♥ t❤❡ s❡❝♦♥❞ ♣❛rt ♦❢ t❤❡ t❤❡s✐s✱ t❤❡ ❆❈❉ ♣r♦❝❡ss ✐s ❞❡☞♥❡❞ ❛♥❞ t❤❡ r❡❧❛t✐♦♥ ❜❡t✇❡❡♥ ❆❘▼❆ ❛♥❞ ❆❈❉ ✐s s❤♦✇♥✳ ❚❤❡♥ ✇❡ s❤♦✇ t❤❡ ♠❡t❤♦❞s ♦❢ ❞❛t❛ ❛❞❥✉st♠❡♥t✱ ❡st✐♠❛t✐♦♥✱ ♣r❡❞✐❝t✐♦♥ ❛♥❞ ✈❡r✐☞❝❛t✐♦♥ ♦❢ t❤❡ ❆❈❉ ♠♦❞❡❧✳ ❆❢t❡r t❤❛t✱ t❤❡ ♣❛rt✐❝✉❧❛r ❝❛s❡s ♦❢ ❆❈❉ ♣r♦❝❡ss✿ ❊❆❈❉✱ ❲❆❈❉✱ ●❆❈❉✱ ●❊❱❆❈❉ ✇✐t❤ ✐ts ♣r♦♣❡rt✐❡s ❛♥❞ t❤❡ ♠♦t✐✈❛t✐♦♥❛❧ ❡①❛♠♣❧❡s ❛r❡ ✐♥tr♦❞✉❝❡❞✳ ❚❤❡ ♥✉♠❡r✐❝❛❧ ♣❛rt ✐s ♣❡r❢♦r♠❡❞ ✐♥ ❘ s♦❢t✇❛r❡ ❛♥❞ ❝♦♥❝❡r♥s t❤❡ ♣r❡❝✐s✐♦♥ ♦❢ t❤❡ ❡st✐♠❛t❡s ❛♥❞ ♣r❡❞✐❝t✐♦♥s ♦❢ t❤❡ s♣❡❝✐❛❧ ❝❛s❡s ♦❢ ❆❈❉ ♠♦❞❡❧ ❞❡♣❡♥❞✐♥❣ ♦♥ t❤❡ ❧❡♥❣t❤ ♦❢ s❡r✐❡s ❛♥❞ ♥✉♠❜❡r ♦❢ s✐♠✉❧❛t✐♦♥s✳ ■♥ t❤❡ ❧❛st ♣❛rt✱ ✇❡ ❛♣♣❧② t❤❡ ♠❡t❤♦❞s st❛t❡❞ ✐♥ t❤❡♦r❡t✐❝❛❧ ♣❛rt ♦♥ r❡❛❧ ❞❛t❛✳ ❚❤❡ ❛❞❥✉st♠❡♥t ♦❢ t❤❡ ❞❛t❛ ❛♥❞ ❡st✐♠❛t✐♦♥ ♦❢ t❤❡ ♣❛r❛♠❡t❡rs ✐s ♣❡r❢♦r♠❡❞ ❛s ✇❡❧❧ ❛s t❤❡ ✈❡r✐☞❝❛t✐♦♥ ♦❢ t❤❡ ❆❈❉ ♠♦❞❡❧✳ ❆❢t❡r t❤❛t✱ ✇❡ ♣r❡❞✐❝t ❢❡✇ st❡♣s ❛♥❞ ❝♦♠♣❛r❡ t❤❡♠ ✇✐t❤ r❡❛❧ ❞✉r❛t✐♦♥s✳ ✶