Financial economics is the branch of economics characterized by a "concentration on monetary activities", in which "money of one type or another is likely to appear on both sides of a trade".
Its concern is thus the interrelation of financial variables, such as share prices, interest rates and exchange rates, as opposed to those concerning the real economy.
It has two main areas of focus: asset pricing and corporate finance; the first being the perspective of providers of capital, i.e. investors, and the second of users of capital.
It thus provides the theoretical underpinning for much of finance.
The subject is concerned with "the allocation and deployment of economic resources, both spatially and across time, in an uncertain environment". It therefore centers on decision making under uncertainty in the context of the financial markets, and the resultant economic and financial models and principles, and is concerned with deriving testable or policy implications from acceptable assumptions.
It thus also includes a formal study of the financial markets themselves, especially market microstructure and market regulation.
It is built on the foundations of microeconomics and decision theory.
Financial econometrics is the branch of financial economics that uses econometric techniques to parameterise the relationships identified.
Mathematical finance is related in that it will derive and extend the mathematical or numerical models suggested by financial economics.
Whereas financial economics has a primarily microeconomic focus, monetary economics is primarily macroeconomic in nature.
Financial economics studies how rational investors would apply decision theory to investment management. The subject is thus built on the foundations of microeconomics and derives several key results for the application of decision making under uncertainty to the financial markets. The underlying economic logic yields the fundamental theorem of asset pricing, which gives the conditions for arbitrage-free asset pricing.
The aside formulae result directly.
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This course presents the problem of static optimization, with and without (equality and inequality) constraints, both from the theoretical (optimality conditions) and methodological (algorithms) point
The objective of this course is to provide a detailed coverage of the standard models for the valuation and hedging of derivatives products such as European options, American options, forward contract
This course provides an introduction to Distributed Ledger Technology (DLT), blockchains and cryptocurrencies, and their applications in finance and banking and draws the analogies between Traditional
En finance, l'analyse quantitative est l'utilisation de mathématiques financières, souvent dérivées des probabilités, pour mettre au point et utiliser des modèles permettant aux gestionnaires de fonds et autres spécialistes financiers de s'attaquer à deux problèmes : mieux évaluer la valeur des actifs financiers, et surtout leurs dérivés. Ces dérivés peuvent être des produits comme les warrants, les certificats ou tout autre type de dérivé ou d'option (contrats Futures sur matières premières, indices, etc.
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Les mathématiques financières (aussi nommées finance quantitative) sont une branche des mathématiques appliquées ayant pour but la modélisation, la quantification et la compréhension des phénomènes régissant les opérations financières d'une certaine durée (emprunts et placements / investissements) et notamment les marchés financiers. Elles font jouer le facteur temps et utilisent principalement des outils issus de l'actualisation, de la théorie des probabilités, du calcul stochastique, des statistiques et du calcul différentiel.
This course gives you an easy introduction to interest rates and related contracts. These include the LIBOR, bonds, forward rate agreements, swaps, interest rate futures, caps, floors, and swaptions.
Explore les applications financières des blockchains, y compris DeFi, les protocoles de prêt, les DAO, les prêts flash et les solutions d'assurance basées sur des jetons.
Explore les protocoles de prêt DeFi, les modèles de taux d'intérêt, les mécanismes de DEX basés sur l'AMM et les orientations futures de la recherche.
Déplacez-vous dans les bases de la blockchain et les applications financières, couvrant les puzzles de hachage, les arbres de Merkle, preuve d'enjeux, et les contrats intelligents.
We analyze and implement the kernel ridge regression (KR) method developed in Filipovic et al. (Stripping the discount curve-a robust machine learning approach. Swiss Finance Institute Research Paper No. 22-24. SSRN. https://ssrn.com/abstract=4058150, 2022 ...
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Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...