Tag Archives: quant books

What quant books to read before Financial Engineering for Computer Science Engineering students?

What quant books to read before Financial Engineering for Computer Science Engineering students?

m doing my CS Engg currently. I have applied for Financial Engineering for Fall 2012. Is there any prior preparation that I can do, any books I can read, so I can be better prepared for the course ?

 

https://www.quantnet.com/quantnet-best-selling-books-2011/

Stochastic calculus for Finance I and II by Steven Shreve.

 

You should focus on financial derivatives( John Hull).Since, you already have required computer skills with you from your Bachelor’s degree.All you need is more finance side knowledge: corporate finance, fixed income investments etc. In case you need more guidance, you can drop me a message on my profile.Good Luck!

 

A very useful book for preparation for an MFE program is “A Primer for the Mathematics of Financial Engineering” by Dan Stefanica and the associated solutions manual. Prof. Stefanica is the director of the Baruch MFE program and the book is based on his popular math refresher course that has been running for a few years. Having a good basis of the maths and programming is the required foundation for most of the coursework which includes Hull and Shreve in the first semester.

 

Here are some useful article from Joy Pathak, a blogger on Quantnet.com
https://www.quantnet.com/prepare-for-mfe/
and
https://www.quantnet.com/prepare-for-mfe-part-2/

 

Any one has the link of soft copy of “A Primer for the Mathematics of Financial Engineering” ?

 

You can review the topics of probability, differential equations and numerical analysis.

For probability, the books written by Sheldon Ross are written for the entry level and are pretty good (there is one called ‘First Course in Probability’ and another called ‘Probability Models’). Try to master the definitions and theorems in this book and it will be helpful when you go on to Shreve or another derivatives mathematics book. If you’ve mastered the basics, reading Shreve as Murat suggested would give you a leg up.

For differential equations, there are many books with the title ‘Advanced Engineering Mathematics’ and these are appropriate. Maybe you’ve used one already in your undergraduate studies. The one I used is by Dennis Zill, but there might be a better option. Even if you’ve gone through a book like this before, it’s good to review so everything’s closer in memory.

For numerical analysis there is a book by Kendall Atkinson called ‘An Introduction to Numerical Analysis’ and there is a lot of material on numerical analysis on the web as well.

Also, if you haven’t coded in C++ during your undergraduate, you should learn the syntax of C++ which I’m sure you will have no problem doing as a CS grad.

Good luck with you studies!

 

i guess there are many copies of “A Primer for the Mathematics of Financial Engineering” available at amazon.com or the like.

 

here is the link to the book http://www.amazon.com/gp/product/0979757622?tag=quantfinaneng-20&creativeASIN=0979757622

If by “soft copy”, you mean PDF, then there is none in existence.

 

You should learn some mathematical or statistical software packages like R, Matlab, and SAS

 

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Here is a list of Quant Books and Research Papers on Volume-time and Volatility

Here is a list of Quant Books and Research Papers on Volume-time and Volatility

Is there an empirical or theoretical study, ideally across different asset classes, of the relationship between s_t, the volatility of a given security at (or around) time t, and v_t, the total $ volume of the given security traded in the market at (or around) time t?

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Here are a few related studies:

• Ané, T., and H. Geman (2000): “Order Flow, Transaction Clock and Normality of Asset Returns”, Journal of Finance, 55: 2259–2284.

• Clark, P. K. (1970): “A Subordinated Stochastic Process Model of Cotton Futures Prices”, unpublished Ph.D. dissertation, Harvard University, May.

• Clark, P. K. (1973): “A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices”, Econometrica, 41 (1): 135-155.

• Mandelbrot, B., and M. Taylor (1967): “On the Distribution of Stock Price Differences”, Operations Research, 15 (6): 1057-1062.

• Mandelbrot, B. (1973): “Comments on ‘A subordinated stochastic process model with finite variance for speculative prices by Peter K. Clark’”, Econometrica, 41 (1): 157-159.

Here is how Mandelbrot and Taylor [1967] saw it:

“Price changes over a fixed number of transactions may have a Gaussian distribution. Price changes over a fixed time period may follow a stable Paretian distribution, whose variance is infinite. Since the number of transactions in any time period is random, the above statements are not necessarily in disagreement. […] Basically, our point is this: the Gaussian random walk as applied to transactions is compatible with a symmetric stable Paretian random walk as applied to fixed time intervals.”

 

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Hiemstra and Jones (Journal of Finance, 1994) did a generalized causality study, T. Andersen (Journal of Finance, 1996) used a microstructure framewok. More recently, Giot and Laurent (Journal of Empirical Finance, 2010) used a realized vol/jump component approach.

 

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it’s not exactly on-point, but might be handy if you’re creating a framework, the author gave the paper at last year’s sofie conference in chicago:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1525410

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Stochastic subordination and time change are classical theoretical machinery, per literature cited by Marcos.

Numerous time / clock formalisms have been proposed and empirical evaluated; for example: Mendelbrot with “trading time”; Dacorogna et al. (2001) with “upsilon time”; and Derman with “intrinsic time” (2002).

Literature on this topic continues to be active; for example, see references in McCulloch (2011).

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Gallant Rossi Tauchen, RFS 1993, volatility and volume for the S&P500

 

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Also: George Tauchen, Harold Zhangb, Ming Liua; Volume, volatility, and leverage: A dynamic analysis; Journal of Econometrics Volume 74, Issue 1, September 1996, Pages 177–208

The paper recommended by Thierry Michel [Trading activity, realized volatility and jumps (Giot, Laurent, Petitjean, 2010, Journal of Empirical Finance 17, 168-175] includes lieterature review and can be found here http://www.core.ucl.ac.be/~laurent/pdf/Petitjean.pdf

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George Tauchen, Harold Zhangb, Ming Liua; Volume, volatility, and leverage: A dynamic analysis; Journal of Econometrics Volume 74, Issue 1, September 1996, Pages 177–208 can be found here:

http://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/1897/Tauchen_volume_volatility_and_leverage.pdf?sequence=1

It uses NONLINEAR, non-parameteric impulse response analysis to investigate the relationship between Volatility, Volume and the Leverage Effect. The nonlinearity is explored through perturbation analysis (so it is dealing with small nonlinearities).

 

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the following are detailed citation for references in above comment:

Dacorogna, Michel et al. (2001), An Introduction to High-Frequency Finance. http://books.google.com/books?id=dobO95EBcqsC

Derman, Emanuel (2002), “The perception of time, risk and return during periods of speculation”. http://www.ederman.com/new/docs/qf-market_bubbles.pdf

Mandelbrot, B. and Taylor, H. (1967), “On the Distribution of Stock Price Differences”, Operations Research 15, 1057-1062. http://www.jstor.org/stable/168611

McCulloch, James (2011), “Fractal Market Time”. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1803888

 

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Quant Books on Algorithmic Trading

Quant Books on Algorithmic Trading

Hi,

What books would you recommend on algorithmic trading? In particular, I’m interesting in reading about feature modeling (e.g. coming up with strategies) and back testing strategies.

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The Evaluation and Optimization of Trading Strategies gives some basic fundamentals

 

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I just finished “Cybernetic Trading Strategies: Developing a Profitable Trading System with State-of-the-Art Technologies”. It’s an older book but it gives a good starting point on how to model, test and deploy a strategy. I found it very informative.

 

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Here is my most recent and best reading list for learning or enhancing HFT trading knowledge for quant development

Here is my most recent and best reading list for learning or enhancing HFT trading knowledge for quant development

Just read and I personally rave about:

http://www.amazon.com/Algorithmic-Trading-DMA-introduction-strategies/dp/0956399207/ref=sr_1_1?s=books&ie=UTF8&qid=1327329939&sr=1-1

Brand new to do but looks very advanced on the math side:

http://www.lulu.com/product/hardcover/advances-in-high-frequency-strategies/18823205#

Still to re-read:

http://www.amazon.com/High-Frequency-Trading-Practical-Algorithmic-Strategies/dp/0470563761

Ernest Chan

http://www.amazon.com/Quantitative-Trading-Build-Algorithmic-Business/dp/0470284889/ref=ntt_at_ep_dpt_1

 

 

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Haven’t found much quant books on JAVA for Financial Technology whereas there are many books for C# and C . Any suggestions for good books

Haven’t found much quant books on JAVA for Financial Technology whereas there are many books for C# and C . Any suggestions for good books (basic and advanced) for trading system development?

 

Please suggest books on Java for trading system development

 

since the wheel is there do not re invent the wheel. I suggest a cost effective algorithm trading station that works for broker to market maker level.email:saroh_h@yahoo.com

 

can you recommend a good book for C++ ?

Thank you in advance & Happy New Year,

 

Lots of good C/C++ books. That being said, Remember a principle of automation ….. It is very very very foolish to automate a system that has not existed as a manual system for at least one day. What part of the financial technology are of interest? Strategy Architecture, Strategy development, Strategy Testing, Trading, Trade Management, Money Management, Risk Management ….. the list goes on and on. It is easy to be a jack of all trades and a master of none.

 

a very simple rule of system analysis and design is based upon knowledge of the faculty and in depth knowledge of problem. in stock trading in few second a millionaire becomes begger

 

 

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