Tag Archives: estimating

Estimating linear factor model

Estimating linear factor model

From one of my fave people to learn the modelling off of

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PDF Downlaod Taking on risk at 4pm: Estimating cost of 4pm fix for market makers from Thalesians of London

PDF Downlaod Taking on risk at 4pm: Estimating cost of 4pm fix for market makers from Thalesians of London

Check it out here as this came from someone highly influential and profitable

http://www.thalesians.com/finance/index.php/Main_Page

https://docs.google.com/file/d/0B4H_ElQbt5sRZXl3Q3FKZnNvVUk/edit

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Bayesian analysis for estimating the markets with Matlab source code. Same process to find Malaysian lost plane MH370

Bayesian analysis for estimating the markets with Matlab source code. Same process to find Malaysian lost plane MH370

Same analytical process to find lost plane MH370
http://mi.eng.cam.ac.uk/~mjfg/local/4F10/ derived
http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html <– mostly definitions but pg 2 has good diagram of ‘generative models’ (also refer to A generative model for generative models section)
http://mi.eng.cam.ac.uk/~mjfg/local/4F10/lect1.2up.pdf
https://code.google.com/p/bnt/ <– Bayes Net framework!!
Various Bayesian Vector Autoregression code:
https://sites.google.com/site/dimitriskorobilis/matlab/code-for-vars
https://sites.google.com/site/dimitriskorobilis/matlab/code-for-vars
https://sites.google.com/site/dimitriskorobilis/matlab/bss
http://alumni.cs.ucr.edu/~mvlachos/PKDD05/PKDD05_Handout.pdf <– Another really good time series presentation with Matlab overview (very advanced with some models I have not seen before)
Course with Bayesian included: http://faculty.wcas.northwestern.edu/~lchrist/course/syllabus.htm
Handout: http://faculty.wcas.northwestern.edu/~lchrist/course/presentation1.pdf <– no code
http://www.stat.duke.edu/~mw/Prado+West-JSMCE-2014webpages.pdf <– no cod

Bayesian Matlab excerise: http://personal.strath.ac.uk/gary.koop/MoF_Computer_Session4.pdf
Code at: http://personal.strath.ac.uk/gary.koop/Polish_Ministry_of_Finance_course.html
Naive bayes and conditional probability calculation http://stackoverflow.com/questions/19744115/naive-bayes-and-conditional-probability-calculation <– source code provided
Mentions tutorial

http://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1521.pdf <– how the ECB uses it

http://fmwww.bc.edu/ec-p/software/matlab/mbook.pdf <– massive 300+ with Matlab code examples

http://venus.unive.it/r.casarin/Summer2013/SlidesCasarinSMC.pdf <-chapter dedicated to Bayesian but not code

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.116.711&rep=rep1&type=pdf <– no code

http://stat.duke.edu/research/BEST/BEST2011-12/Xie.pdf <–excellent analytic article but no code

http://personal.strath.ac.uk/gary.koop/KoKo_Manual.pdf <– code references but may be duplicated  http://personal.strath.ac.uk/gary.koop/Polish_Ministry_of_Finance_course.html

NOTE: Most of the internal help topics on Bayesian have been covered by other model analysis

Video from https://quantlabs.net/blog/2014/04/intro-to-baynesian-analysis-network-toolbox-in-matlab/

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Oh me oh my: Python and R vs Matlab and new stock return, beta MLE estimating!

HI there

A couple of summaries since last Friday:

1. Python is no different in terms of R vs Matlab.
I will stick with my Matlab after this decent comparison.

I won’t debate this any further with myself!
I was thinking of Python for trading until I saw this
very recent comparison with Matlab and R

2. This got me further thinking about the usual Microsoft
Windows vs open source debate which of course includes
R, Python,Java, and Linux.
I settled with Excel, .NET,
and Matlab for my future. As for Excel with XLQ, I
summarized with these views:
DO I use Excel for real time data feed analytics with

technical analysis indicators? Use Matlab DotNET C++?

Beat open source Java?

Check it out here.
3.How to get mentored and do a career shift from a hedge
fund developer to a HFT developer

As for my members, I posted the following alone yesterday
from the Matlab Financial Toolbox:

Maximum likelihood estimation and Mean and Covariance
Parameter Estimation

CAPM with beta estimation

Maximum likelihood estimation and Mean and Covariance
Parameter Estimation

For those that cannot afford Matlab, there is no need to
worry as I am investigating ways to include a headless
version with a .NET DLL to interface with this in a FREE
open source trading platform
like Tradelink. I may even
include parallelization using a GPU card like Tesla or
Geforce from Nvidia. Would there be a demand for an
equivelent Java JAR file?

Now remember, I have a very limited promotion which includes
ALL courses from my new Academy which is nearly $700. I may
close this off the end of next week unless I see a surge in
demand for this promotion to be extended.  

-> JOIN NOW TO GET ACCESS TO $697 OF FREE COURSES <–

 

Here is the complete course list.
See the Membership benefits listed here.
Thanks for reading,
Bryan

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Webinar coming on charting, max drawdown, Beta estimating with CAPM, and Sharpe Radtio

HI there
I have now completed the analysis with Matlab’s Financial Toolbox. I am even doing an EXCLUSIVE online event for taking questions from my  QuantLabs.net Premium members on this and the Econometrics toolbox.


–> JOIN NOW TO GET ACCESS <–

Get in on this event which happen this Monday Mar 18 at 7PM EST!
I have posted a video on all this and the direction the Membership is going|:
Youtube video on Analyzed Matlab Finance toolbox but now analyzing Stats PDE and Math
https://quantlabs.net/blog/2013/03/youtube-video-on-analyzed-matlab-finance-toolbox-but-now-analyzing-stats-pde-and-math/
The other recent Financial Toolbox topics for my Members include:
High Low Close and Bollinger Chart Demo
Performance metrics with Sharpe Ratio, risk adjusted return, Lower Partial Moments
Calculate max drawdown and expected max drawdown
Using CAPM to estimate Beta in portfolio
So if you want to start learning some of these topics listed above, get in on the party action now? Also, jump on the opportunity now for this Monday’s EXCLUSIVE LIVE online event? for QuantLabs.net Premium Members.
–> JOIN NOW TO GET ACCESS <–
Several other membership benefits listed here
Thanks Bryan

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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Analysis of forecasting and estimating the stock market with Matlab Econometrics toolboxso now moving on Statistics and Financial

Analysis of forecasting and estimating the stock market with Matlab Econometrics toolbox so now moving on Statistics and Financial toolbox

Yes they are complete for all my members! I am moving onto these other toolboxes with new scripts and videos.

You should consider about joining the membership now.

Or join my FREE newsletter to learn more about this

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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

R source code coming soon to do volatility forecasting, pair trading, cointegration, estimating, simulation, and way much more!

R source code coming soon to do volatility forecasting, pair trading, cointegration, estimating, simulation, and way much more!
As a continuation of my Algorithm, Modelling, and Strategy Development courses, I will be posting R source code to show how to do the following in the coming weeks:
1.    Trade using a GARCH volatility forecast
2.    Modelling for VAR, for simulation/estimation, Statistical Test, Cointegration with Engle & Granger Two-Step Procedure, benchmarks, Autoregressive moving average models
3.    Proper time series analysis with simple component analysis, linear filtering, decomposition, regression analysis, exponential smoothing and prediction, autocorrelation, and parameter estimation and prediction with ARIMA models.
4.    Pair trading with plotting spreads,  Dickey–Fuller  and Phillips-Perron tests, estimate parameters for back testing, creating trade signals, and back testing performance.
Remember that R is totally free as it based on open source.
As you can imagine, this will be highly valuable as QuantLabs.net will be entering a serious effort in implementing these. I have turned away several capital providers wanting me to implement these but they are not quite there yet.  If you are interested in these with many others coming, I would definitely get in the action NOW!
So don’t just there? Start learning how to accurately predict market moving events like volatility and pricing trends.
http://quantlabs.net/dlg/sell.php?prodData=m%2C3
Get even more benfits including our HFT and Algo Development courses, software tool kits, and way more!
http://quantlabs.net/quant-member-benefits/
Thanks Bryan

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For quant analytics: Really good tutorial on Bayes estimating with iterative and likelihood and sample Matlab code

For quant analytics: Really good tutorial on Bayes estimating with iterative and likelihood and sample Matlab code

http://students.cs.byu.edu/~cs470ta/goodrich/fall2005/MATLAB/BayesEstimator.html

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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Anybody got opinions on cointegration or Baysian analysis for estimating purposes and quant analysis?

Anybody got opinions on cointegration or Baysian analysis for estimating purposes and quant analysis?

Let me know your thoughts by commenting below

Thanks

 

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NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Matlab`s Econometrics Toolbox is great for forecasting, modelling, estimating, and simulating

Matlab`s Econometrics Toolbox is great for forecasting, modelling, estimating, and simulating
As I read this, this Matlab Econometrics toolbox is so powerful for these uses using GARCH, the help file includes some very solid examples which are read from Nasdaq source files. Charts and plots are also showcased for quick analysis and understanding. There are heavy uses of GARCH to make all this happen. One powerful function is called garchset.
The help files even includes examples on showing how to:
use the default GARCH(1,1) model to model the Deutschmark/British pound foreign-exchange series.
This simulates both on a single path or multiple path.
Presampling data is also shown with simulations as well.
There are even capabilities to do optimization termination on estimation data.
A great New York Stock Exchange example is used to demonstrate Estimating ARMA(R,M) Parameters. Lower bounder restrained were also included.
As for forecasting capabilities with this Econmetrics toolbox, Asymptotic Behavior can be done as well. Regression in forecasting can be done via:
Using Forecasted Explanatory Data

Generating Forecasted Explanatory Data
Regression in Monte Carlo using some Matlab functions like:
*

garchsim
*

garchinfer
*

Garchpred
There are various multiple time series models supported as well. These include:
Vector Autoregressive VAR(p)

Vector Moving Average VMA(q)

Vector Autoregressive Moving Average VARMA(p, q)

Vector Autoregressive Moving Average with eXogenous inputs VARMAX(p, q, r)

Structural Vector Autoregressive Moving Average with eXogenous inputs SVARMAX(p, q, r)
There is also coverage of Scholastic Differential Equation which includes:
#

SDE Class Hierarchy
#

SDE Objects
#

SDE Methods
#

Example: Simulating Equity Prices
#

Example: Simulating Interest Rates
#

Example: Stratified Sampling
#

Performance Considerations
There are various data set names out of the box regarding this Matlab Econometrics toolbox. This includes:
Data_EquityIdx U.S. equity indices, 1990–2001
Data_FXRates Currency exchange rates, 1979–1998
Data_GDP U.S. Gross Domestic Product, 1947–2005
Data_GlobalIdx1 Global large-cap equity indices, 1993–2003
Data_GlobalIdx2 Global large-cap equity indices and Euribor rates, 2001–2006
Data_GNP U.S. Gross National Product, 1947–2005
Data_Income1 Simulated data on income and education
Data_Income2 Average annual earnings by educational attainment in eight workforce age categories
Data_MarkPound Deutschmark/British Pound foreign-exchange rate, 1984–1991
Data_NelsonPlosser Macroeconomic series of Nelson and Plosser
Data_SchwertMacro Macroeconomic series of Schwert
Data_SchwertStock Indices of U.S. stock prices
Data_TBill Three-month U.S. treasury bill secondary market rates
Data_USEconModel Macroeconomic series for Demo_USEconModel
Data_VARMA22 Two-dimensional VARMA(2,2) specification

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