This dissertation is centered around two comprehensive themes: the extraction of information embedded in equity index option prices, and how to use this information in order to be able to make optimal decisions in the equity index option markets. These problems are important for decision makers in the equity index options markets, since they are continuously faced with making decisions under uncertainty given observed market prices. The methods developed in this dissertation provide robust tools that can be used by practitioners in order to improve the quality of the decisions that they make. In order to be able to extract information embedded in option prices, the dissertation develops two different methods for estimation of stable option implied surfaces which are consistent with observed market prices. This is a difficult and ill-posed inverse problem which is complicated by the fact that observed option prices contain a large amount of noise stemming from market micro structure effects. Producing estimated surfaces that are stable over time is important since otherwise risk measurement of derivatives portfolios, pricing of exotic options and calculation of hedge parameters will be prone to include significant errors. The first method that we develop leads to an optimization problem which is formulated as a convex quadratic program with linear constraints which can be solved very efficiently. The second estimation method that we develop in the dissertation makes it possible to produce local volatility surfaces of high quality, which are consistent with market prices and stable over time. The high quality of the surfaces estimated with the second method is the crucial input to the research which has resulted in the last three papers of the dissertation. The stability of the estimated local volatility surfaces makes it possible to build a realistic dynamic model for the equity index derivatives market. This model forms the basis for the stochastic programming (SP) model for option hedging that we develop in the dissertation. We show that the SP model, which uses generated scenarios for the squared local volatility surface as input,  outperforms the traditional hedging methods that are described in the literature. Apart from having an accurate view of the variance of relevant risk factors, it is when building a dynamic model also important to have a good estimate of the expected values, and thereby risk premia, of those factors. We use a result from recently published research which lets us recover the real-world density from only a cross-section of observed option prices via a local volatility model. The recovered real-world densities are then used in order to identify and estimate liquidity premia that are embedded in option prices. We also use the recovered real-world densities in order to test how well the option market predicts the realized statistical characteristics of the underlying index. We compare the results with the performance of commonly used models for the underlying index. The results show that option prices contain a premium in the tails of the distribution. By removing the estimated premia from the tails, the resulting density predicts future realizations of the underlying index very well.

L’indice CAC40 est la première chose à laquelle on pense lorsqu’on parle de bourse en France. Cependant il n’est pas négociable. C’est pourquoi sont apparus des contrats dérivés comme le contrat future FCE dont le sous-jacent est le CAC40 qui peuvent être achetés et vendus. Leurs valeurs sont très proches mais non égales. Quel est donc la relation qui lie le contrat FCE au CAC40 ? A l’aide de données téléchargeables quotidiennement sur Internet et accessibles à tous une réponse va être apportée. Dans une première partie nous présentons le contrat à terme dérivé du CAC40, les raisons de le « trader » et le comparons aux autres contrats future dérivés d’indices boursiers dans le monde. Nous étudions ensuite la relation FCE/CAC40 en terme d’efficience informationnelle. Pour cela nous allons étudier différentes notions de base et tenter de les modéliser. Enfin dans une dernière partie nous nous intéressons à cette même relation d’un point de vue microstructure, en étudiant en particulier des variables non prix (volume et position ouverte), et la volatilité. Nous allons enfin tenter d’apporter une modélisation de la volatilité en fonction de ces variables. / The CAC 40 index is the first thing that comes to mind when talking about financial markets. However it is not negotiable. Therefore appeared derivative contracts such as futures contract FCE whose underlying is the CAC40 index which can be bought and sold. Their values are very close but not equal. So what is the relationship between the FCE contract and the CAC40? Using daily downloadable data on the Internet and accessible to everyone, answers will be given. In the first part we present the future contracts derived from the CAC40, the reasons to trade it, and we compare it to other stock index futures in the world. We then study the relationship FCE / CAC40 in terms of informational efficiency. For that we will study different notions of basis and try to model them. Finally in the last part we are interested in the same relationship but with a microstructure point of view, studying in particular non-price variables: volume and open interest, and volatility. Finally, we will try to modelise volatility with these variables.

Between 1993 and 2016, the U.S. exchange traded fund (ETF) market has proliferated from one product worth $6.5 million USD to 1,455 products worth over $2 trillion USD. Despite its dramatic growth, the ETF market has yet to be the subject of sociological inquiry even though fields such as the social studies of finance have begun examining the origins of index derivatives (Millo 2007), options (MacKenzie 2006), hedge funds (Hardie and MacKenzie 2007), and foreign exchange markets (Knorr Cetina and Bruegger 2002). Thus, the purpose of this dissertation is to provide the first historical sociology of ETF innovation in the United States, using an approach inspired by the social studies of finance. This project empirically traces the emergence of the ETF by compiling an account of precursory strategies, concept development, regulatory negotiations, and early product marketing. The concept of agencement is used to frame the historical narrative of the ETF as a product of two distinct assemblages that formed in the U.S. between 1970 and 2000: first, the socio-technical integration between humans and their technologies that affected trading strategies, and second, the collaborative relationships that were formed between innovators and regulators. The mixed qualitative research consists of 36 interviews triangulated with archival records, documents sourced through Freedom of Information Act requests, private collections, and government files. Concluding analysis suggests that strategies foreshadowing the ETF began to emerge as early as the 1970s, and innovator-regulator collaborations were integral to early product qualification - a process not yet explored in literature on financial regulation.

When a stock is added into the S&P 500 Index, it is automatically "cross-listed" in the index derivative markets (i.e., S&P 500 Index futures and Index options). I examined the effects of such cross-listing on the trading volume and return volatility of the underlying component stocks. Traditional finance theory asserts that futures and "cash" markets are connected by arbitrage mechanism that brings both markets to equilibrium. When arbitrage opportunities arise, arbitrageurs buy (sell) the index portfolio and take short (long) positions in the corresponding index derivative contracts until prices return to theoretical levels. Such mechanical arbitrage trading tends to create large order flows that could be difficult for the market to absorb, resulting in price changes. Utilizing a list of S&P 500 index composition changes occurring over the period September 1976 to December 2005, I investigated the market-adjusted volume turnover ratios and return variances of the stocks being added to and deleted from the S&P 500, surrounding the effective day of index membership changes. My primary finding is that, after the introduction of the S&P 500 index futures and options contracts, stocks added to the S&P 500 experience significant increase in both trading volume and return volatility. However, deleted stocks experience no significant change in either trading volume or return volatility. Both daily and monthly return variances increase following index inclusion, consistent with the hypothesis that derivative transactions "fundamentally" destabilize the underlying securities. I argue that the increase in trading volume and return volatility may be attributed to index arbitrage transactions as derivative markets provide more routes for index arbitrageurs to trade. Other index trading strategies such as portfolio insurance and program trading may also contribute to the results. On the other hand, a deleted stock is not associated with changes in trading volume and volatility since it represents an extremely small fraction of the market value-weighted index portfolio, and the influence of index trading strategies becomes slight for these shares. Furthermore, evidence is provided that trading volume and return volatility are positively related.