Quantitative and Algorithmic Trading
This thread is dedicated to Quantitative and Algorithmic Trading.
The first page should be viewed as a focal point regarding above mentioned topics.
This first page is under construction and, if interested, visit it from time to time to see, if new material/links have arrived.
"There is a difference between saying that there is predictability and the ability to predict"
"Although there is always more profit in long term forecasting, from a mathematical point of view, there is more reliability in short term forecasting."
“Make everything as simple as possible.” (A. Einstein) But not simpler.
"Trading's not a game – It's an IQ test" {algodude}
Software For Business Intelligence Analytics http://www.johncon.com/ndustrix/
First, a few things to consider
Behavioural Finance http://www.behaviouralfinance.net/
Gambler's fallacy http://en.wikipedia.org/wiki/Gambler's_fallacy
Illusion of Control http://illusion-of-control.behaviouralfinance.net/
Nonlinear Dynamics http://www.nonlineardynamics.org/
Harmonic Pattern Success Rates http://www.trade-forex-harmonic-patterns...ccess.html
How to Learn Algorithmic Trading http://quantivity.wordpress.com/2010...thmic-trading/
How to Learn Algorithmic Trading: Part 2 http://quantivity.wordpress.com/2010...rading-part-2/
How to Learn Algorithmic Trading: Part 3 http://quantivity.wordpress.com/2010...rading-part-3/
Statistics knowledge
Mean reversion (finance) http://en.wikipedia.org/wiki/Mean_reversion_(finance)
A Mean-Reversion Theory of Stock-Market Crashes Pairs trade http://en.wikipedia.org/wiki/Pairs_trade
Regression toward the mean http://en.wikipedia.org/wiki/Regression_toward_the_mean
Ornstein–Uhlenbeck process http://en.wikipedia.org/wiki/Ornstein–Uhlenbeck_process
Pairs trade Pairs trade http://en.wikipedia.org/wiki/Pairs_trade
Probability distribution http://en.wikipedia.org/wiki/Probability_distribution
List of probability distributions http://en.wikipedia.org/wiki/Probability_distribution
Log-normal distribution http://en.wikipedia.org/wiki/Log-normal_distribution
Fat-tailed distribution http://en.wikipedia.org/wiki/Fat_tail
in finance, fat tails are considered undesirable because of the additional risk they imply. For example, an investment strategy may have an expected return, after one year, that is five times its standard deviation. Assuming a normal distribution, the likelihood of its failure (negative return) is less than one in a million; in practice, it may be higher. Normal distributions that emerge in finance generally do so because the factors influencing an asset's value or price are mathematically "well-behaved", and the central limit theorem provides for such a distribution. However, traumatic "real-world" events (such as an oil shock, a large corporate bankruptcy, or an abrupt change in a political situation) are usually not mathematically well-behaved.
Find The Right Fit With Probability Distributions http://www.investopedia.com/articles...stribution.asp
Probability density function http://en.wikipedia.org/wiki/Probabi...nsity_function
PIMCO - Understanding tail risk http://investments.pimco.com/Marketi...Risk_PU001.pdf
Investopedia explains 'Tail Risk'
When a portfolio of investments is put together, it is assumed that the distribution of returns will follow a normal pattern. Under this assumption, the probability that returns will move between the mean and three standard deviations, either positive or negative, is 99.97%. This means that the probability of returns moving more than three standard deviations beyond the mean is 0.03%, or virtually nil. However, the concept of tail risk suggests that the distribution is not normal, but skewed, and has fatter tails. The fatter tails increase the probability that an investment will move beyond three standard deviations.
Distributions that are characterized by fat tails are often seen when looking at hedge fund returns.
http://www.investopedia.com/terms/t/tailrisk.asp
Are the Skewness and Kurtosis Useful Statistics? http://www.spcforexcel.com/are-skewn...ful-statistics
Books
Quantitative trading http://k-512.googlecode.com/files/AlgoTra.pdf
This is a good book to start reading with…..
Introduction To OpenQuant Strategy Development http://www.smartquant.com/introducti...t_strategy.pdf
Software
Matlab http://www.mathworks.de/products/matlab/
GNU Octave http://www.gnu.org/software/octave/
O-Matrix http://www.omatrix.com/
Scilab http://www.scilab.org/
R http://www.r-project.org/
RIZM http://equametrics.com/
ARB-Maker http://arb-maker.com/
Blogs
Software Trading http://softwaretrading.co.uk/
Quantivity http://quantivity.wordpress.com/
Algodude http://www.algodude.com/
Quantitative Trading http://epchan.blogspot.co.uk/
The Psy-Fi Blog http://www.psyfitec.com/
Quantitative Research and Trading http://jonathankinlay.com/
Quantitative Systematic Market Analysis http://qusma.com/
Quantified Strategies http://www.quantifiedstrategies.com/
marketsci blog http://marketsci.wordpress.com/
Quandl - New search engine for financial, economic and social datasets http://www.quandl.com/
Investopedia - Global Professional Exams http://www.investopedia.com/professi...alarchive.aspx
This thread is dedicated to Quantitative and Algorithmic Trading.
The first page should be viewed as a focal point regarding above mentioned topics.
This first page is under construction and, if interested, visit it from time to time to see, if new material/links have arrived.
"There is a difference between saying that there is predictability and the ability to predict"
"Although there is always more profit in long term forecasting, from a mathematical point of view, there is more reliability in short term forecasting."
“Make everything as simple as possible.” (A. Einstein) But not simpler.
"Trading's not a game – It's an IQ test" {algodude}
Software For Business Intelligence Analytics http://www.johncon.com/ndustrix/
First, a few things to consider
Behavioural Finance http://www.behaviouralfinance.net/
Gambler's fallacy http://en.wikipedia.org/wiki/Gambler's_fallacy
Illusion of Control http://illusion-of-control.behaviouralfinance.net/
Nonlinear Dynamics http://www.nonlineardynamics.org/
Harmonic Pattern Success Rates http://www.trade-forex-harmonic-patterns...ccess.html
How to Learn Algorithmic Trading http://quantivity.wordpress.com/2010...thmic-trading/
How to Learn Algorithmic Trading: Part 2 http://quantivity.wordpress.com/2010...rading-part-2/
How to Learn Algorithmic Trading: Part 3 http://quantivity.wordpress.com/2010...rading-part-3/
Statistics knowledge
Mean reversion (finance) http://en.wikipedia.org/wiki/Mean_reversion_(finance)
A Mean-Reversion Theory of Stock-Market Crashes Pairs trade http://en.wikipedia.org/wiki/Pairs_trade
Regression toward the mean http://en.wikipedia.org/wiki/Regression_toward_the_mean
Ornstein–Uhlenbeck process http://en.wikipedia.org/wiki/Ornstein–Uhlenbeck_process
Pairs trade Pairs trade http://en.wikipedia.org/wiki/Pairs_trade
Probability distribution http://en.wikipedia.org/wiki/Probability_distribution
List of probability distributions http://en.wikipedia.org/wiki/Probability_distribution
Log-normal distribution http://en.wikipedia.org/wiki/Log-normal_distribution
Fat-tailed distribution http://en.wikipedia.org/wiki/Fat_tail
in finance, fat tails are considered undesirable because of the additional risk they imply. For example, an investment strategy may have an expected return, after one year, that is five times its standard deviation. Assuming a normal distribution, the likelihood of its failure (negative return) is less than one in a million; in practice, it may be higher. Normal distributions that emerge in finance generally do so because the factors influencing an asset's value or price are mathematically "well-behaved", and the central limit theorem provides for such a distribution. However, traumatic "real-world" events (such as an oil shock, a large corporate bankruptcy, or an abrupt change in a political situation) are usually not mathematically well-behaved.
Find The Right Fit With Probability Distributions http://www.investopedia.com/articles...stribution.asp
Probability density function http://en.wikipedia.org/wiki/Probabi...nsity_function
PIMCO - Understanding tail risk http://investments.pimco.com/Marketi...Risk_PU001.pdf
Investopedia explains 'Tail Risk'
When a portfolio of investments is put together, it is assumed that the distribution of returns will follow a normal pattern. Under this assumption, the probability that returns will move between the mean and three standard deviations, either positive or negative, is 99.97%. This means that the probability of returns moving more than three standard deviations beyond the mean is 0.03%, or virtually nil. However, the concept of tail risk suggests that the distribution is not normal, but skewed, and has fatter tails. The fatter tails increase the probability that an investment will move beyond three standard deviations.
Distributions that are characterized by fat tails are often seen when looking at hedge fund returns.
http://www.investopedia.com/terms/t/tailrisk.asp
Are the Skewness and Kurtosis Useful Statistics? http://www.spcforexcel.com/are-skewn...ful-statistics
Books
Quantitative trading http://k-512.googlecode.com/files/AlgoTra.pdf
This is a good book to start reading with…..
Introduction To OpenQuant Strategy Development http://www.smartquant.com/introducti...t_strategy.pdf
Software
Matlab http://www.mathworks.de/products/matlab/
GNU Octave http://www.gnu.org/software/octave/
O-Matrix http://www.omatrix.com/
Scilab http://www.scilab.org/
R http://www.r-project.org/
RIZM http://equametrics.com/
ARB-Maker http://arb-maker.com/
Blogs
Software Trading http://softwaretrading.co.uk/
Quantivity http://quantivity.wordpress.com/
Algodude http://www.algodude.com/
Quantitative Trading http://epchan.blogspot.co.uk/
The Psy-Fi Blog http://www.psyfitec.com/
Quantitative Research and Trading http://jonathankinlay.com/
Quantitative Systematic Market Analysis http://qusma.com/
Quantified Strategies http://www.quantifiedstrategies.com/
marketsci blog http://marketsci.wordpress.com/
Quandl - New search engine for financial, economic and social datasets http://www.quandl.com/
Investopedia - Global Professional Exams http://www.investopedia.com/professi...alarchive.aspx