Instrument financier | EPFL Graph Search

Les instruments financiers sont des titres ou contrats, dont certains sont négociables sur les marchés réglementés, certains exclusivement utilisés pour anticiper une rentabilité ou un risque financier ou monétaire. En France, les instruments financiers sont définis par l'article L. 211-1 du Code monétaire et financier, qui est, certes, une liste limitative, mais néanmoins suffisamment générale dans ses définitions pour ne pas constituer un frein a priori au développement des marchés financiers et à la création de nouveaux produits. Types d'instruments financiers

les titres financiers : ** les titres de capital : *** les actions ordinaires *** les actions de préférence ** les titres de créance : *** les obligations *** les titres de créances négociables *** les obligations complexes ** les parts de placements collectifs (ou titres financiers à finalité particulière) ***OPCVM ***FIA
les contrats financiers (ou instruments financiers à terme, ou produits dérivés) :

Essays in Financial Economics

Marc André Frattaroli

This thesis consists of three chapters that study separate subjects in the area of corporate governance and financial intermediation. In the first chapter, I study a protectionist anti-takeover law introduced in 2014 in France that covers a subset of all firms in the economy. The law decreased affected firms' likelihood of becoming the target of a merger or acquisition and had a negative impact on shareholder value. There is no evidence that management of those firms subsequently altered firm policies in its interest. Investment, employment, wages, profitability, and capital structure remain unchanged. The share of annual CEO compensation consisting of equity instruments increased by 8.4 percentage points, suggesting that boards reacted to the loss in monitoring by the takeover market by increasing the pay-for-performance sensitivity. In the second chapter, which is co-authored work with Rüdiger Fahlenbrach, we conduct a detailed analysis of investors in successful initial coin offerings (ICOs). The average ICO has 4,700 contributors. The median participant contributes small amounts and many investors sell their tokens before the underlying product is developed. Large presale investors obtain tokens at a discount and flip part of their allocation shortly after the ICO. ICO contributors lack the protections traditionally afforded to investors in early stage financing. Nevertheless, returns nine months after the ICO are positive on average, driven mostly by an increase in the value of the Ethereum cryptocurrency. In the third chapter, which is joint work with Christoph Herpfer, we investigate how bankers use information from lending relationships to help borrowers combine resources in strategic alliances. Firms that have borrowed from the same banker or share an indirect connection through a network of bankers are significantly more likely to enter an alliance. Consistent with bankers overcoming informational frictions, their ability to facilitate alliances decreases with network distance, and is stronger for opaque borrowers. Firms connected to more potential partners via banker networks enter more alliances. These alliances are associated with positive announcement returns and brokering banks are more likely to receive future underwriting mandates.

EPFL2020

Does protectionist anti-takeover legislation lead to managerial entrenchment?

Marc André Frattaroli

I study a protectionist anti takeover law introduced in 2014 that covers a subset of all firms in the economy. The law decreased affected firms' likelihood of becoming the target of a merger or acquisition and had a negative impact on shareholder value. There is no evidence that management of those firms subsequently altered firm policies in its interest. Investment, employment, wages, profitability, and capital structure remain unchanged. The share of annual CEO compensation consisting of equity instruments increased by 8.4 percentage points, suggesting that boards reacted to the loss in monitoring by the takeover market by increasing the pay-for-performance sensitivity. (C) 2019 Elsevier B.V. All rights reserved.

ELSEVIER SCIENCE SA2020

Numerical methods for option pricing: polynomial approximation and high dimensionality

Francesco Statti

Options are some of the most traded financial instruments and computing their price is a central task in financial mathematics and in practice. Consequently, the development of numerical algorithms for pricing options is an active field of research. In general, evaluating the price of a specific option relies on the properties of the stochastic model used for the underlying asset price. In this thesis we develop efficient and accurate numerical methods for option pricing in a specific class of models: polynomial models. They are a versatile tool for financial modeling and have useful properties that can be exploited for option pricing. Significant challenges arise when developing option pricing techniques. For instance, the underlying model might have a high-dimensional parameter space. Furthermore, treating multi-asset options yields high-dimensional pricing problems. Therefore, the pricing method should be able to handle high dimensionality. Another important aspect is the efficiency of the algorithm: in real-world applications, option prices need to be delivered within short periods of time, making the algorithmic complexity a potential bottleneck. In this thesis, we address these challenges by developing option pricing techniques that are able to handle low and high-dimensional problems, and we propose complexity reduction techniques. The thesis consists of four parts: First, we present a methodology for European and American option pricing. The method uses the moments of the underlying price process to produce monotone sequences of lower and upper bounds of the option price. The bounds are obtained by solving a sequence of polynomial optimization problems. As the order of the moments increases, the bounds become sharper and eventually converge to the exact price under appropriate assumptions. Second, we develop a fast algorithm for the incremental computation of nested block triangular matrix exponentials. This algorithm allows for an efficient incremental computation of the moment sequence of polynomial jump-diffusions. In other words, moments of order 0, 1, 2, 3... are computed sequentially until a dynamically evaluated criterion tells us to stop. The algorithm is based on the scaling and squaring technique and reduces the complexity of the pricing algorithms that require such an incremental moment computation. Third, we develop a complexity reduction technique for high-dimensional option pricing. To this end, we first consider the option price as a function of model and payoff parameters. Then, the tensorized Chebyshev interpolation is used on the parameter space to increase the efficiency in computing option prices, while maintaining the required accuracy. The high dimensionality of the problem is treated by expressing the tensorized interpolation in the tensor train format and by deriving an efficient way, which is based on tensor completion, to approximate the interpolation coefficients. Lastly, we propose a methodology for pricing single and multi-asset European options. The approach is a combination of Monte Carlo simulation and function approximation. We address the memory limitations that arise when treating very high-dimensional applications by combining the method with optimal sampling strategies and using a randomized algorithm to reduce the storage complexity of the approach. The obtained numerical results show the effectiveness of the algorithms developed in this thesis.

EPFL2019

Numerical methods for option pricing: polynomial approximation and high dimensionality

Francesco Statti

EPFL2019

Essays in Financial Economics

Marc André Frattaroli

EPFL2020