What are some good books/papers to read for someone who knows little about quantitative finance but would like to know more. More specifically, what are good books for those who have a solid math and cs background.
You need to be a little more specific regarding your interests and background. If you are interested in theory, there are plenty of books discussing specific models. However, most practical or buzzword (e.g. HFT) books are rubbish (think about it: if you have a profitable operation, why would you write a book? Unless, like me, you have a screw loose :P )
If you want some practical discussions, "Trading and Exchanges" by Larry Harris is a bit dated, but nothing comes close. Most of the descriptions are still valid today (even if some of the mechanics have changed)
If you want something more along the lines of what a financial engineer would know:
- "Options, Futures, and other Derivatives" by John Hull (goes over basic models without delving too deeply into theoretical math aspects)
- "Stochastic Calculus for Finance II" by Steve Shreve (goes over the basic stuff but has enough stats to keep a grad student happy)
- "Monte Carlo Methods in Financial Engineering" by Paul Glasserman (much more practical, and goes over subtleties of monte carlo simulation and other stuff like low discrepancy sampling)
- "Modelling Fixed Income Securities and Interest Rate Options" by Robert Jarrow (walks through how to perform certain simulations, covers lots of little details most theoretical books skip)
If you want something more theoretical:
- "Introduction to Stochastic Calculus Applied to Finance" by Lamberton and Lapeyre (Nice little intro)
- "Arbitrage Theory in Continuous Time" by Tomas Bjork (Slower discussion, larger breadth)
- "Brownian Motion and Stochastic Calculus" and "Methods of Mathematical Finance" by Karatzas and Shreve (Solid theoretical foundation, for the more mathematically inclined)
There was a good non-measure theoretic discussion of financial models but the name escapes me ATM.
John Hull is canon. Read it, live it, love it, keep it under your pillow. It is truly superb.
Nassim Taleb's "Dynamic Hedging" is the finest book I'm aware of on the subject of actually trading/managing vol portfolios. It's REALLY good. And dense.
"Paul Wilmott on Quantitative Finance" vol 1-3 are worth having as a reference, perhaps.
I'm finding this a more interesting and detailed read than _Capital Markets for Quantitative Professionals_. For instance, the book traces through everything that happens when placing, executing, and settling typical trades.
On the other hand, I've taken the Canadian Securities Course, so perhaps Capital Markets is a better introduction for total beginners.
Trading and Exchanges was my detailed introduction to what really happens in the markets. I wish I could find a similarly detailed and coherent book on corporate actions.
It's a few years out of date, but not painfully so. Madoff was still a huge market maker, not a scandal, and it makes no mention liquidity rebates.
Edit: I should add that I had no trading background before reading the book, I was just an engineer at a finance startup who still thought "order" and "trade" were synonyms.
It really depends on which angle you're coming from, when you mean "hacker".
Quantitative finance is all math, so in order to really understand it, you need a solid background in probability and statistics. Even the most basic concepts make heavy use of probability, so without strong fundamentals you won't get very far.
There are other concepts, such as risk-free returns, etc that also play a big part in quant finance. A book that I really enjoyed that gave a good background in a lot of these concepts was "Trading Strategies for Capital Markets".
One of the basic concepts of quantitative finance revolves around the Black-Scholes equation, which calculates a price for an option. I would suggest first looking this up as well as how it was derived, to see if you want to pursue this further. If you're having a hard time with this, then quant finance may not be what you're looking for.
A video tutorial website that seems decent for quant finance is Nathan's Lessons:
If what you REALLY mean is you want to program trading algorithms, that's a bit of a different beast. For that you really need to understand how algorithmic trading works, how the market microstructure works, how to place trades, etc. For this there are a bunch of books but the best introductory book is definitely "Trading and Exchanges: Market Microstructure for Practitioners". It's a bit old, but still largely relevant and gives you a lot of the history. I really wish they would update this book, because I would buy it again. Another decent book is "Algorithmic Trading and DMA".
Are you really interested in learning quant finance (learning how to mathematically model various parts of financial markets, pricing/measuring risk of specific instruments, etc.) or are you interested in programming systems for the financial industry (trading/risk/compliance/banking/etc)?
This book, "Algorithmic Trading and DMA: An introduction to direct access trading strategies" (http://www.amazon.com/Algorithmic-Trading-DMA-introduction-s...) is pretty darn good if you are a programmer. However, if you really meant "quant finance," then others can give you better suggestions :)
edit: I just remembered, Paul Wilmott and Hull have several introductory books if you are interested in what is usually called "quantitative finance." This means how to price options, futures, etc. From what I recall, this does NOT mean using statistical correlations to trade two similar stocks, making market-making models, etc.
I am a quant. I work at a bank. We do a fair amount of portfolio optimization & price-analytics, in Scala, Matlab,C++, CPLEX. Its not hard to get your feet wet with financial modeling, though reasoning about the models does take an MFE or comparable education.
For example, here's a tiny scala pricer I coded up in 5 minutes to spit out the price of a google at-the-money call expiring 47 days from now, on Dec 17 using a 10k Monte-Carlo simulation.
--
val risk = 0.28 // google has a 28% implied vol
val T = 47.0/365 // 47 days annualized
println((1 to 10000).toList.map(_=>Random.nextGaussian).map(x=>595 * exp((-risk * risk/2) * T + risk * sqrt(T) * x)).map(x=>max(0,(x-595))).sum/10000)
--
Output: $23 & change ( its selling at about $23 right now )
To veyron's excellent list, I'd add Brandimarte's "Numerical Methods in Finance".
Exactly. Where I used to work, anyone without a quant background would be urged to buy a copy of Grinold and Kahn the bible you suggested above or "Quantitative Equity Portfolio Management" by Chincarini and Kim.
Any of Paul Wilmott's books. Either his single Introduction to Quantitative Finance, or his three volume set. His focus is on knowing where models work and where they break down, and how to avoid using them naively. http://wilmott.com/
Mark Joshi's (markjoshi.com) site has a pretty good set of information for aspiring quants (in particular, see the "advice for aspiring quants" bit).
The "careers" forum on nuclearphynance.com is also pretty good, and might also shatter some preconceptions about how easy it is to waltz into the industry. (note: nuclearphynance seems to be down at the time of writing)
Here is a reddit link that collects a few quants (from nuclear phynance mostly) saying that the labour market, especially the junior labour market, is tight and not likely to expand any time soon:
If there's a SE, discussions on HN, thousands of MFE's being minted, and so many books on quant finance topics, you really have to wonder if the quant labour market isn't saturated.
Ernie Chan's book, "Quantitative Trading: How to Build Your Own Algorithmic Trading Business ", is a good starting point. It's a nice blend of theory and pragmatic practice. Chan provides example implementations in Matlab to help readers get started.
The best resource for mastering probability, and financial mathematics are Yufeng Guo's guides to passing actuarial exams. He takes the hacker approach to teaching fairly difficult concepts so you can focus on solving problems quickly. Most of the books recommended here are too traditional in their approach,(boring) this is a true hacker guide to learning how to frame problems correctly and then the math needed to solve them. If you are a decent programmer you can figure out the application afterward. I used them to pass the introductory actuarial exams and they are awesome.
Hull is always the first recommendation. After that, it depends what area you're interested in. You could move on to Shreve for more hard core quantity material, or go to Tsay (Analysis of Financial Time Series) for a time series primer. You could try Natenberg for options material or Grinld and Khan for portfolio management. Not too much useful material on HFT out there. Agreed that Harris is useful but out of date.
[+] [-] veyron|14 years ago|reply
If you want some practical discussions, "Trading and Exchanges" by Larry Harris is a bit dated, but nothing comes close. Most of the descriptions are still valid today (even if some of the mechanics have changed)
If you want something more along the lines of what a financial engineer would know:
- "Options, Futures, and other Derivatives" by John Hull (goes over basic models without delving too deeply into theoretical math aspects)
- "Stochastic Calculus for Finance II" by Steve Shreve (goes over the basic stuff but has enough stats to keep a grad student happy)
- "Monte Carlo Methods in Financial Engineering" by Paul Glasserman (much more practical, and goes over subtleties of monte carlo simulation and other stuff like low discrepancy sampling)
- "Modelling Fixed Income Securities and Interest Rate Options" by Robert Jarrow (walks through how to perform certain simulations, covers lots of little details most theoretical books skip)
If you want something more theoretical:
- "Introduction to Stochastic Calculus Applied to Finance" by Lamberton and Lapeyre (Nice little intro)
- "Arbitrage Theory in Continuous Time" by Tomas Bjork (Slower discussion, larger breadth)
- "Brownian Motion and Stochastic Calculus" and "Methods of Mathematical Finance" by Karatzas and Shreve (Solid theoretical foundation, for the more mathematically inclined)
There was a good non-measure theoretic discussion of financial models but the name escapes me ATM.
[+] [-] joncooper|14 years ago|reply
Nassim Taleb's "Dynamic Hedging" is the finest book I'm aware of on the subject of actually trading/managing vol portfolios. It's REALLY good. And dense.
"Paul Wilmott on Quantitative Finance" vol 1-3 are worth having as a reference, perhaps.
[+] [-] crasshopper|14 years ago|reply
[+] [-] foobarqux|14 years ago|reply
[+] [-] JabavuAdams|14 years ago|reply
http://www.amazon.com/Trading-Exchanges-Market-Microstructur...
I'm finding this a more interesting and detailed read than _Capital Markets for Quantitative Professionals_. For instance, the book traces through everything that happens when placing, executing, and settling typical trades.
On the other hand, I've taken the Canadian Securities Course, so perhaps Capital Markets is a better introduction for total beginners.
[+] [-] kevinpet|14 years ago|reply
It's a few years out of date, but not painfully so. Madoff was still a huge market maker, not a scandal, and it makes no mention liquidity rebates.
Edit: I should add that I had no trading background before reading the book, I was just an engineer at a finance startup who still thought "order" and "trade" were synonyms.
[+] [-] steve8918|14 years ago|reply
Quantitative finance is all math, so in order to really understand it, you need a solid background in probability and statistics. Even the most basic concepts make heavy use of probability, so without strong fundamentals you won't get very far.
There are other concepts, such as risk-free returns, etc that also play a big part in quant finance. A book that I really enjoyed that gave a good background in a lot of these concepts was "Trading Strategies for Capital Markets".
One of the basic concepts of quantitative finance revolves around the Black-Scholes equation, which calculates a price for an option. I would suggest first looking this up as well as how it was derived, to see if you want to pursue this further. If you're having a hard time with this, then quant finance may not be what you're looking for.
A video tutorial website that seems decent for quant finance is Nathan's Lessons:
http://nathanslessons.com/?paged=3
-------------------
If what you REALLY mean is you want to program trading algorithms, that's a bit of a different beast. For that you really need to understand how algorithmic trading works, how the market microstructure works, how to place trades, etc. For this there are a bunch of books but the best introductory book is definitely "Trading and Exchanges: Market Microstructure for Practitioners". It's a bit old, but still largely relevant and gives you a lot of the history. I really wish they would update this book, because I would buy it again. Another decent book is "Algorithmic Trading and DMA".
[+] [-] paperwork|14 years ago|reply
This book, "Algorithmic Trading and DMA: An introduction to direct access trading strategies" (http://www.amazon.com/Algorithmic-Trading-DMA-introduction-s...) is pretty darn good if you are a programmer. However, if you really meant "quant finance," then others can give you better suggestions :)
edit: I just remembered, Paul Wilmott and Hull have several introductory books if you are interested in what is usually called "quantitative finance." This means how to price options, futures, etc. From what I recall, this does NOT mean using statistical correlations to trade two similar stocks, making market-making models, etc.
[+] [-] dxbydt|14 years ago|reply
For example, here's a tiny scala pricer I coded up in 5 minutes to spit out the price of a google at-the-money call expiring 47 days from now, on Dec 17 using a 10k Monte-Carlo simulation.
--
val risk = 0.28 // google has a 28% implied vol
val T = 47.0/365 // 47 days annualized
println((1 to 10000).toList.map(_=>Random.nextGaussian).map(x=>595 * exp((-risk * risk/2) * T + risk * sqrt(T) * x)).map(x=>max(0,(x-595))).sum/10000)
--
Output: $23 & change ( its selling at about $23 right now )
To veyron's excellent list, I'd add Brandimarte's "Numerical Methods in Finance".
[+] [-] joshu|14 years ago|reply
A big part of algorithmic trading and stat arb is portfolio management, including deriving alpha, building risk models, etc.
The bible is: http://www.amazon.com/Active-Portfolio-Management-Quantitati...
[+] [-] justnoise|14 years ago|reply
[+] [-] SkyMarshal|14 years ago|reply
[+] [-] reverend_gonzo|14 years ago|reply
Also, http://quant.ly/ is essentially Hacker News for quants and often has interesting articles.
[+] [-] notyourwork|14 years ago|reply
[+] [-] willpower101|14 years ago|reply
[+] [-] b_emery|14 years ago|reply
http://blog.hiremebecauseimsmart.com/post/2860511335/design-...
Note, scroll way down to see the content, the formatting is screwy. Note 2, I'm not a quant but the math I do overlaps tremendously.
edit: previous HN discussion: http://news.ycombinator.com/item?id=2130508
[+] [-] crasshopper|14 years ago|reply
[+] [-] rfurlan|14 years ago|reply
Evidence Based Technical Analysis: http://www.amazon.com/Evidence-Based-Technical-Analysis-Scie...
Pairs Trading: http://www.amazon.com/Pairs-Trading-Quantitative-Methods-Ana...
Quantitative Trading: http://www.amazon.com/Quantitative-Trading-Build-Algorithmic...
An Introduction to High Frequency Finance: http://www.amazon.com/Introduction-High-Frequency-Finance-Ra...
Trading and Exchanges: Market Microstructure for Practitioners: http://www.amazon.com/Trading-Exchanges-Market-Microstructur...
I also wrote a couple of very introductory articles, sadly I never got past part #2: http://www.bitcortex.com/2008/12/28/pragmatic-automated-trad... http://www.bitcortex.com/2009/01/04/pragmatic-automated-trad...
I am could mentor 1-2 HN readers that are serious about getting into quant trading. Just let me know you are interested :)
[+] [-] hugh3|14 years ago|reply
The "careers" forum on nuclearphynance.com is also pretty good, and might also shatter some preconceptions about how easy it is to waltz into the industry. (note: nuclearphynance seems to be down at the time of writing)
[+] [-] crasshopper|14 years ago|reply
http://www.reddit.com/r/quantfinance/comments/jl5ea/there_ar...
If there's a SE, discussions on HN, thousands of MFE's being minted, and so many books on quant finance topics, you really have to wonder if the quant labour market isn't saturated.
[+] [-] jcardente|14 years ago|reply
http://www.amazon.com/Quantitative-Trading-Build-Algorithmic...
Chan's blog is informative as well,
http://epchan.blogspot.com/
[+] [-] king_magic|14 years ago|reply
http://www.amazon.com/Complete-Quantitative-Professionals-Mc...
Great book. It's what I recommend to my new developers when we hire them without previous financial services experience.
[+] [-] pg_bot|14 years ago|reply
Here is his page on actex, take a look at some of the previews and I think you will be sold. http://www.actexmadriver.com/contributorinfo.cfm?ContribID=8...
[+] [-] raymondh|14 years ago|reply
[+] [-] adrianscott|14 years ago|reply
Evolution, Complexity, and the Radical Remaking of Economics http://www.amazon.com/Origin-Wealth-Evolution-Complexity-Eco...
don't let the false prophets of equilibrium theory and efficient market theory bend your ear too far ;)
if you get into looking for a job, there are a few books that list common questions for quant jobs also...
[+] [-] zweiterlinde|14 years ago|reply
[+] [-] shogunmike|14 years ago|reply
- 'The Concepts and Practice of Mathematical Finance' - 'C++ Design Patterns and Derivatives Pricing'
Also of note is Baxter & Rennie:
- 'Financial Calculus: An Introduction to Derivative Pricing'
Once you've studied those and have a good grasp of Measure Theory, you'll want to tackle Shreve, Vol II.
And a brief plug of my (slightly out of date!) quant finance website, Quantstart.com.
[+] [-] gresrun|14 years ago|reply
http://www.amazon.com/Triumph-Contrarian-Investing-Beating-A...
[+] [-] apparatchik|14 years ago|reply
also this one: http://news.ycombinator.com/item?id=1238906 with a comment by pg there