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Quantum Financier | On algorithmic trading | Page 2
https://quantumfinancier.wordpress.com/page/2
February 15, 2011. When designing a model, an aspect that I often overlook is scalability. First a definition from Investopedia: A characteristic of a system, model or function that describes its capability to cope and perform under an increased or expanding workload. A system that scales well will be able to maintain or even increase its level of performance or efficiency when tested by larger operational demands. Other avenues to consider in scalability are left to the interested reader who can always ...
quantumfinancier.wordpress.com
Basic Introduction to GARCH and EGARCH (part 1) | Quantum Financier
https://quantumfinancier.wordpress.com/2010/09/12/381
Basic Introduction to GARCH and EGARCH (part 1). September 12, 2010. As request by several readers in light of the previous series of post on using GARCH(1,1) to forecast volatility, here is a very basic introduction post on two models widely used in finance: the GARCH and EGARCH. As mentioned in one of my all time favorite blog post: Wonder of Residuals. There is a myriad of information and uses to this construct. When we fit a model, we are, or I am anyway (! Would call it level 1 adaptation. Must be e...
quantumfinancier.wordpress.com
Hello Old Friend | Quantum Financier
https://quantumfinancier.wordpress.com/2015/03/17/hello-old-friend
March 17, 2015. Reports of my death have been greatly exaggerated Mark Twain. Obviously since I have been trading full time my skill set has evolved so I can only imagine that the new perspective I hope to bring to the analysis contained moving forward will be more insightful. To all of you. From → Uncategorized. Larr; 2012 Wishes. 99 Problems But A Backtest Ain’t One →. March 18, 2015 03:31. Glad to hear you back🙂. Can I ask you what are the reasons to move to Python? March 19, 2015 14:40. I think R is...
quantumfinancier.wordpress.com
Basic Introduction to GARCH and EGARCH (part 2) | Quantum Financier
https://quantumfinancier.wordpress.com/2010/09/14/basic-introduction-to-garch-and-egarch-part-2
Basic Introduction to GARCH and EGARCH (part 2). September 14, 2010. First we construct the portfolio, see below the numbers for each individual component and the portfolio in the last column. From the standard deviation in the table, we see that SPY is far more volatile than AGG. Also note the very fat tail of SPY (normal value is 3). Finally, the negative skewness indicates that the left tail (negative returns) is longer, translating into more extreme losses. From → Uncategorized. I tried to follow alo...
quantumfinancier.wordpress.com
99 Problems But A Backtest Ain’t One | Quantum Financier
https://quantumfinancier.wordpress.com/2015/03/23/99-problems-but-a-backtest-aint-one
99 Problems But A Backtest Ain’t One. March 23, 2015. Backtesting is a very important step in strategy development. But if you have ever went through the full strategy development cycle, you may have realized how difficult it is to backtest a strategy properly. People use different tools to implement a backtest depending on their expertise and goals. For those with a programming background, Quantstrat. From → Uncategorized. Larr; Hello Old Friend. Give me good data, or give me death →. Thank you for comm...
quantumfinancier.wordpress.com
Regime Switching System Using Volatility Forecast | Quantum Financier
https://quantumfinancier.wordpress.com/2010/08/27/regime-switching-system-using-volatility-forecast
Regime Switching System Using Volatility Forecast. August 27, 2010. In the same line of thoughts as last post, today we will look at a way to incorporate the GARCH volatility model we introduced yesterday to create a regime switching strategy. It is often discussed on the blogosphere that high volatility is good for daily MR, see previous editions of the state of short-term mean-reversion report by Michael over at MarketSci here. As mentioned before on many other blogs, incorporating volatility forecast ...
matlab-trading.blogspot.com
Quantum blog: Pca - how it really works
http://matlab-trading.blogspot.com/2012/12/pca-how-it-really-works.html
The physics of trading. Sunday, December 30, 2012. Pca - how it really works. I suppose that my previous post did not provide insights on how PCA really works. Here is another try at the subject, using a simple pair as an example. Let's take SPY and IWM, which are highly correlated. If daily returns of IWM are plotted against daily returns of SPY, the relationship is highly linear (see left chart). December 31, 2012 at 1:02 AM. December 31, 2012 at 2:09 AM. January 2, 2013 at 8:28 PM. Hi Jev, thanks for ...
