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Concept

Plateforme électronique de trading

Dans la finance, une plateforme électronique de trading, est un système informatique permettant de passer des ordres pour des produits financiers via un réseau et grâce à un intermédiaire financier. Différents produits financiers peuvent être négociés sur la plateforme de trading, via un réseau avec un intermédiaire financier ou directement entre les participants ou les membres de la plateforme de trading. Il s'agit de produits, tels que des actions, des obligations, des devises, des matières premières, des produits dérivés et autres, négociés avec un intermédiaire financier, tel qu’un courtier, un teneur de marché, une banque d'investissement ou la bourse. Ces plates-formes permettent aux utilisateurs d'effectuer des transactions électroniques à partir de n'importe quel endroit et s'opposent à la négociation traditionnelle sur le marché libre et à la négociation par téléphone. Parfois, le terme de plateforme de trading est également utilisé pour désigner le système informatique de t

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Chargement

Equilibrium Models for Derivatives Markets with Frictions

Yuan Zhang

This thesis develops equilibrium models, and studies the effects of market frictions on risk-sharing, derivatives pricing, and trading patterns. In the chapter titled "Imbalance-Based Option Pricing", I develop an equilibrium model of fragmented options markets in which option prices and bid-ask spreads are determined by the nonlinear risk imbalance between dealers and customers. In my model, dealers optimally exploit their market power and charge higher spreads for deep out-of-the-money (OTM) options, leading to an endogenous skew in both prices and spreads. In stark contrast to theories of price pressure in option markets, I show how wealth effects can make customers' net demand for options be negatively correlated with option prices. Under natural conditions, the skewness risk premium is positively correlated with the variance risk premium, consistent with the data. In the chapter titled "The Demand for Commodity Options", we develop a simple equilibrium model in which commercial hedgers, i.e., producers and consumers, use commodity options and futures to hedge price and quantity risk. We derive an explicit relationship between expected futures returns and the hedgers' demand for out-of-the-money options, and show that the demand for both calls and puts are positively related to expected returns, and the relationship is asymmetric, tilted towards puts. We test and confirm the model predictions empirically using the commitment of traders report from CFTC. In the chapter titled "Electronic Trading in OTC Markets vs. Centralized Exchange", we model a two-tiered market structure in which an investor can trade an asset on a trading platform with a set of dealers who in turn have access to an interdealer market. The investor's order is informative about the asset's payoff and dealers who were contacted by the investor use this information in the interdealer market. Increasing the number of contacted dealers lowers markups through competition but increases the dealers' costs of providing the asset through information leakage. We then compare a centralized market in which investors can trade among themselves in a central limit order book to a market in which investors have to use the electronic platform to trade the asset. With imperfect competition among dealers, investor welfare is higher in the centralized market if private values are strongly dispersed or if the mass of investors is large.

EPFL2018

Chargement

In the chapter

When to Introduce Electronic Trading Platforms in Over-the-Counter Markets?'' An equilibrium in a market is determined in which traders have the choice between using an electronic platform with a request-for-quote protocol or calling a dealer directly. The main takeaway is that platforms increase the bargaining power of traders with search costs, thereby increasing their market participation and potentially also welfare. Another friction that affects trading in OTC markets are informational frictions. market participants may learn from trading activity on platforms and trade on that information in other trading venues. The interplay between an electronic trading platform in the dealer-to-customer market and the interdealer market is analysed in the chapter

Electronic Trading in OTC Markets vs. Centralized Exchange.'' In that chapter, a two-tiered OTC market is compared with a fully centralized market, showing that informed traders may prefer the two-tiered structure in order to benefit from their information. This ability of decentralized OTC markets to deal with asymmetric information is also a major benefit of OTC markets compared to exchange markets in welfare considerations. In the chapter ``Informed Traders and Dealers in the FX Forward Market,'' it is analyzed whether such informational frictions exist, whether dealers are able to mitigate those by charging different markups to different clients and whether we behavior consistent with the alleviation of informational frictions.

EPFL2020

Chargement

Demystifying Rational Financial Decision-Making

Anjali Devi Vanapilli Nursimulu

Is the human brain wired for wealth? The setting is the high-velocity financial environment. Undoubtedly, the development of sophisticated derivative instruments has improved the allocation of risk across economies, highlighting the nexus between banking and finance and economic development. But bouts of irrational exuberance raise concerns about the unprecedented pace of financial innovations. The recent past has witnessed the rapid growth of algorithmic and automated trading as competitive strategies to capture gains, for example, from zero-latency trades. At the same time, financial headlines have been set ablaze by behavioral treatises related to our evolutionary hardwiring for such emotions as greed and fear; seemingly, we are not predisposed to make rational financial decisions. This research takes a step back and explores to what extent the human brain is well adapted to assess risk and reward in financial markets. The research implemented three novel behavioral experiments, one of which used high resolution electrical neuroimaging and is organized along two distinct themes that relate to specific features of financial trading. The first theme concerns the speed of financial decisions. Are decisions made under short time constraint more likely to be biased than under less time pressure? How fast does the brain process financial information? The second theme is (financial) volatility. To what extent are individuals adept at making financial forecasts? The dearth of knowledge on these topics prompted the inductive and transversal bent of this research. Several new insights emerged that challenge the behavioral views of financial decision-making. First, fast decisions as observed on the trading floor is well-captured by moment-based theory, a workhorse of Classical Finance. This is in marked contrast to the generally accepted view that fast decisions impose a bound on rationality; rational decisions are assumed to take time-to-build. Surprisingly, biases loom larger with longer decision time. Second, analysis of electrical brain signals indicates that the brain is very fast at extracting complex monetary reward features from the environment. The behavioral and electrophysiological findings highlight the need to better calibrate the speed of decisions. Third, decision-making (here, learning and forecasting) may go awry when individuals face financial volatility; but not always. The overall findings lead to the proposition that the border between rational and irrational financial decisions is much more razor-thin than opined by behaviorists. The research paints a complex picture about how emotions affect decisions. High emotional quotient and long investment time horizon respectively distinguishes professional traders and long-term investors from novice traders and investors chasing short-term gains; the latter two groups are more likely to react emotionally. Real experts in high-velocity environments are rare and forecasts are bound to be imperfect; algorithmic and automated trades are important aids to diverse players in financial markets. Last but not least, extrapolating from the findings, regulatory policy should concern the transparency of financial products and technology-enabled trades and preferential access to trading platforms. Financial institutions, on the other hand, ought to review their business models paying particular attention to their reward system.

EPFL2011

Chargement

Bourse des valeurs

La bourse des valeurs est le lieu où s'échangent les valeurs mobilières, c'est-à-dire des titres financiers négociables, interchangeables et fongibles : actions, obligations, titres de créances négo

Banque d'investissement

Une banque d'investissement est une banque, ou une division de la banque, qui rassemble l'ensemble des activités de conseil, d'intermédiation et d'exécution ayant trait aux opérations dites de haut

Produit dérivé financier

Un produit dérivé ou contrat dérivé ou encore derivative product est un instrument financier :

dont la valeur fluctue en fonction de l'évolution du taux ou du prix d'un autre produit appelé sous-ja

EE-570: Power system restructuring and deregulation

This course presents different types and mechanisms of electricity markets. It addresses in particular their impacts on power/distribution systems operation and consequently the appropriate strategies capable to ensure a secure and reliable functioning.

FIN-413: Financial applications of blockchains and distributed ledgers

This course provides an introduction to distributed ledger technology, blockchains and cryptocurrencies, and their potential applications in finance and banking.

FIN-407: Financial econometrics

This course aims to give an introduction to the application of machine learning to finance. These techniques gained popularity due to the limitations of traditional financial econometrics methods tackling big data. We will review and compare traditional methods and machine learning algorithms.