524 search results for "trading"

R / Finance 2010 Open for Registration

February 5, 2010
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The annoucement below went out to R-SIG-Finance earlier today. For information is as usual the the R / Finance 2010 page: Now open for registrations: R / Finance 2010: Applied Finance with R April 16 and 17, 2010 Chicago, IL, USA The second annu...

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R / Finance 2010 Open for Registration

February 5, 2010
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The annoucement below went out to R-SIG-Finance earlier today. For information is as usual the the R / Finance 2010 page: Now open for registrations: R / Finance 2010: Applied Finance with R April 16 and 17, 2010 Chicago, IL, USA The second annual ...

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R / Finance 2010 Open for Registration

February 5, 2010
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The annoucement below went out to R-SIG-Finance earlier today. For information is as usual the the R / Finance 2010 page: Now open for registrations: R / Finance 2010: Applied Finance with R April 16 and 17, 2010 Chicago, IL, USA The second annu...

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[Event] R / Finance 2010: Applied Finance with R

February 5, 2010
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[Event] R / Finance 2010: Applied Finance with R

One of the greatest event on R is under way… R / Finance 2010: Applied Finance with R April 16 & 17, Chicago, IL, US The second annual R / Finance conference for applied finance using R, the premier free software system for statistical computation and graphics, will be held this spring in Chicago, IL, USA on Friday April 16

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R/Finance 2010: Registration Open

February 5, 2010
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R/Finance 2010: Registration Open

As posted by Dirk Eddelbuettel on R-SIG-Finance: R / Finance 2010: Applied Finance with R April 16 & 17, Chicago, IL, US The second annual R / Finance conference for applied finance using R, the premier free software system for statistical comput...

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Practical Implementation of Neural Network based time series (stock) prediction -PART 4

February 4, 2010
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Practical Implementation of Neural Network based time series (stock) prediction  -PART 4

Consider this an introduction to how we need to pre-process the data.I mentioned earlier that a financial time series is typically a unit root or non-stationary signal, what this means is that if you sample statistical properties over time, they will o...

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Practical Implementation of Neural Network based Time Series (Stock) Prediction – PART 3

February 1, 2010
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Practical Implementation of Neural Network based Time Series (Stock) Prediction – PART 3

Ok, now that we have seen how well the perfect sine wave signal was learned, let's turn it up a notch and see how well the complex sine wave was learned.Fig 1. Summary of Actual Vs. Predicted out of sample complex sine waveformUh Oh. What happened, the...

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Practical Implementation of Neural Network based time series (stock) prediction – PART 2

January 30, 2010
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Practical Implementation of Neural Network based time series (stock) prediction – PART 2

As a brief follow up to the series, I want to take a moment to describe a bit about Weka, which is the machine learning tool that we will be using to implement the neural network. It is a fantastic open source JAVA based tool that was developed at the...

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Practical Implementation of Neural Network based time series (stock) prediction – PART 1

January 29, 2010
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Practical Implementation of Neural Network based time series (stock) prediction  – PART 1

The following introduction is to allow viewers to understand the basic concepts and practical implementation of neural nets towards a financial time series. I will not go too deep into detail about the mathematics behind the neural net at the moment. ...

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LSPM with snow

January 10, 2010
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LSPM with snow

My last post provided examples of how to use the LSPM package. Those who experimented with the code have probably found that constrained optimizations with horizons > 6 have long run-times (when calc.max >= horizon).This post will illustrate how the s...

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