Posts Tagged Options Futures

Quantitative Finance Reading List – Theoretical Foundations



Not everybody wants to become a theoretical physicist. Some consider the academic environment too relaxed, others are not keen on the politics or the necessity to continually hunt for funding early in their career. A job in Quantitative Finance offers an attractive alternative.

Financial engineering has both strong theoretical and applied components, is immensely intellectually stimulating and fast-paced. A significant degree of background knowledge and an exceptional academic record are required even to achieve an interview. If you have recently decided that academia is not where your career path lies and you possess strong technical skills then the reading list outlined below will get you started towards becoming a quant.

This is the first part in a multi-part series on textbooks suitable for becoming a quantitative analyst. The remaining parts will focus on implementation, further mathematical excursions, interview skills and numerical methods. This article will concentrate on the theory of financial engineering for those who have not had an exposure to finance before.

Mathematical Finance

A great place to start learning about the world of derivatives is with the classic text Options, Futures and Other Derivatives by John Hull. It is light on the mathematics, but covers a lot of ground. Specifically, it is a good introduction to derivative markets for those who haven’t had prior exposure to finance.

Once you’re comfortable with the concepts used in the financial markets the next step is to begin learning about arbitrage and the Black-Scholes model in a more mathematical manner. Dan Stefanica’s A Primer for the Mathematics of Financial Engineering will provide all of the calculus (differentiation, integration, taylor expansion etc) needed to tackle the Black-Scholes equation. It will also cover “the Greeks” and basic risk neutral pricing. This is a great book for somebody who doesn’t have the required undergraduate mathematical background needed for later texts.

At this stage you will be ready to tackle the intermediate works such as Mark Joshi’s Concepts and Practice of Mathematical Finance (an excellent book, highly recommended), Paul Wilmott on Quantitative Finance (extremely comprehensive and humourous explanations!), Baxter and Rennie’s Financial Calculus and Salih Neftci’s Introduction to the Mathematics of Financial Derivatives. A good working knowledge of the contents of these books is sufficient theory for any front office desk quant interviews.

If you wish to delve deeper into the mathematical theory underpinning derivatives pricing then Bernt Oksendal’s Stochastic Differential Equations is a great start, as it has plenty of SDE exercises to work through.

A rather heavy going text for desk work, but an essential book for researching financial engineering, is the two volume masterpiece by Steven Shreve – Stochastic Calculus for Finance (Vol I and Vol II). Vol I concentrates on the discrete pricing models while Vol II focuses on continuous models. Be warned that for the Vol II, a strong background in undergraduate mathematics is required – particularly in Real Analysis, Probability Theory and Measure Theory.

Summary and Suggested Reading Chronology
Options, Futures and Other Derivatives – John Hull A Primer for the Mathematics of Financial Engineering – Dan Stefanica The Concepts and Practice of Mathematical Finance – Mark Joshi Financial Calculus: An Introduction to Derivative Pricing – Martin Baxter, Andrew Rennie Stochastic Calculus for Finance II: Continuous-Time Models – Steven Shreve In the next article, texts on implementation will be presented which will give you the knowledge you need to begin creating your own quant models.

By: Michael Halls-Moore

About the Author:
QuantStart is a leading quant finance resource with quant jobs, quant articles, financial engineering tutorials and the latest quant events.

Visit www.QuantStart.com now and sign up for the free newsletter!



Kansieo.com

Tags: , , , , , , , , , , , , , , , , , , ,

Econometrics in Finance



Econometrics refers to developing quantitative methods to analyze economic principles. Theoretical econometrics uses statistical properties while applied econometrics usually applies econometric methods to the various theories. Finance domain is increasingly using the technique like risk management, portfolio management etc.

Econometrics is used in finance to evaluate quantitative problems and uses various techniques like financial models, volatility estimation, capital asset pricing, risk adjusted returns etc. Financial econometrics is viewed as a merger of economics, finance, statistics and applied mathematics. For the various issues in financial world, economics renders theoretical foundation while statistics and applied mathematics using quantitative techniques are used to solve quantitatively. The vast amount of data generated in financial markets on asset returns, volatility usually requires study over a period of time using techniques like time series. Econometrics is widely used for derivative products like options, futures etc.

Regression analysis is one of the primary methods. It usually involves modeling and analyzing various variables to establish a relationship between dependant variable and many independent variables. This technique is useful to understand the changes in the dependant variable to any changes in independent variable. Methods of Moments, Bayesian methods, Generalized Method of Moment etc are other important methods used in econometrics.

The general steps involved in developing an econometric model are:

• Understanding the problem – It involves formulation of a theoretical model to relate two or more variables.

• Collecting data – It involves accumulating relevant data from public domain like Reuters or any published information and also from surveys.

• Selection of method – This step involves choosing an appropriate estimation method like single or multiple equation technique.

• Statistical evaluation – It involves framing assumptions for estimating parameters of the model and analyzing the aptness of the estimates in relation to the data.

• Evaluating the model – The model is then assessed from theoretical perspective.

• Implementation of the model – the model is then used for the identified issue and also for making forecasts. The step also results in courses of action needed.

Econometrics is being widely used in fields including finance and knowledge of its various techniques helps investors manage their portfolios well.

By: Dharmendar Kumar

About the Author:
For more information on econometrics and its importance, you can visit jrank.org, it helps you find the exact site that would provide more information and you can also integrate to this free search engine into other websites. Statistics plays an important role in financial analysis and you can find detailed information on it in the finance category of Jrank encyclopedia



Caffeinated Content

Tags: , , , , , , , , , , , , , , , , , , ,