# Tag Info

## Hot answers tagged visualization

46

Visualization should lead to truth and understanding. As such, I find that simple visualizations tend to be the best. My favorite visualization for showing relationships is the scatterplot. Once you start to even introduce a line plot, you are implying continuities between data that may not exist. And trying to introduce more advanced visualizations like ...

19

The Google Motion Chart is a particularly elegant visualization for 'replaying' time series data. There is also an R package to interface with it.

16

Nanex has an interesting way of showing the order-book: The following images show CME's emMni future (S&P 500) depth of book and trades. The images are rainbow (ROYGBIV) color coded by the relative size at each depth level. Red indicates a lot of size, violet indicates size approaching 0. Note that a full minute before each event, the depth starts ...

14

You can directly imply a probability distribution from a volatility skew. Note that, for any terminal probability distribution $p(S)$ at tenor $T$, we have the model-free formula for the call price $C(K)$ as a function of strike $K$ $$C=e^{-rT} \int_0^\infty (S-K)^+ p(S) dS$$ Therefore we can write e^{rT} \...

13

I don't know why it was removed, but the R package "orderbook" was available: http://journal.r-project.org/archive/2011-1/RJournal_2011-1_Kane~et~al.pdf http://cran.r-project.org/web/packages/orderbook/index.html In the IBrokers package, the function "reqMktDepth" is used for streaming order book data. http://cran.r-project.org/web/packages/IBrokers/...

10

Shane's advice is good. I think it's worth adding the following two techniques not already mentioned: Self-Organizing Maps (SOMs) Seriation (pdf pertaining to R package seriation, but great intro to the topic). They are not explicit visualize techniques, per se. Instead, they are algos that transform underlying data in ways that aim to lead to greater/...

9

Implied volatility is the volatility implied by some model. You will have a skew if your model is implying different volatilities for different strikes. However, the realized volatility of the underlying will be the same for all strikes. So, when you are dealing with realized vol, you can drop the "moneyness" axis. Volatility cones can help you compare ...

7

So one such visualization package is demonstrated in http://www.tradeworx.com/movie/booklet_demo/temp/booklet_demo2.mov. AFAICT it looks like a tk script. Trading Technologies (TT) sells another visualization tool. But TBH writing your own tool takes a few hours and allows you to focus on what information you are interested in finding.

7

Here are a few recent examples: http://stackoverflow.com/questions/4951193/find-largest-5-value-less-than-1-lowest-5-values http://tables2graphs.com/doku.php?id=04_regression_coefficients#figure_6 http://tables2graphs.com/doku.php?id=03_descriptive_statistics#figure_5 http://chartporn.org/category/innovative/

6

And then music... Victor Neiderhoffer, in a 2001 interview: The market plays music all the time. The problem is you never know how the music of the market is going to end. But a good framework is that it will end on the tonic. Consonance to dissonance back to consonance. And whenever there's tremendous dissonance, strident moves in one direction, a good ...

5

To me, coloring by data value is a great way to bring applications alive. If traditional ways are not enough, probably taking 3D in use would be a way: And of course 2D heatmap is a very handy for sure. I'm developing data visualization software components with 3D technologies, so definitely all feedback and ideas are welcome :-)

5

Although quite simple connected scatterplots can give interesting new insights on how time series perform together: http://steveharoz.com/research/connected_scatterplot/ As an example: Gold vs. S&P 500 from 1970 till today: The green point marks 1970, the red point is today. Every point is a year, moving vertically upwards means rise in the S&P ...

5

There are many price driven financial data finsualization concepts are available such as candle stick stock charts. However, there is an advanced charting concept, Mano Stick which is supply & demand driven charting concept. Mano Stick is a multidimentional charting concept which is able to display price information along with volume information to show ...

5

I don't trust either. That a stock didn't trade carries information about its liquidity and about the magnitude of innovations in its fundamental value. If it is feasible within your model, try to incorporate the framework of Rosett (1959, “A Statistical Model of Friction in Economics”, Econometrica). For a recent application of the friction model to ...

5

http://lobster.wiwi.hu-berlin.de/forum/viewtopic.php?f=4&t=30 R code, pictures and discussion, it's easy to modify it

4

Firstly, it may depend vastly on your choice of platforms (e.g. R, Python, or Java). Some of the most common ones: Python Out of the box: Orange Self-customized: Scikit-learn and PyBrain Java Out of the box:RapidMiner and KNIME Self-customized-prone:Weka R: Machine learning in R. Secondly, it vastly depends on your purpose while choosing whether ...

4

Accordingly to this comparison (look for post written by Martin) Rapidminer is more powerful in terms of implemented mining algorithms and scales better for large datasets. Being originally a WEKA user my impression is that Rapidminer is also easier to use than WEKA.

4

I spent some time (a month or so) using RapidMiner at the start of the year; then I added the R plugin, thinking R was just a library of stats functions. Then I learned more R, discovered it also comes with loads of machine learning functions, and realized R is a superset of everything RapidMiner was giving me. Playing with RapidMiner drag and drop was fun, ...

4

Try to give David Spiegelhalter a read/listen to David Spiegelhalter's work and research. He is a statistician and a Professor of the Public Understanding of Risk at Cambridge England. Rather than new ways of calculating risk, he looks at ways of communicating risk to a general public that doesn't have any knowledge of stats. I Linked an interesting video-...

3

The real contenders for a desktop based tool are RapidMiner and R. If you like Windows or Mac, you will like RapidMiner. If you like command line or Linux, you will like R. I would say RapidMiner has a flatter learning curve. The previous lecturer in the course I teach used R and the students (MBAs) complained about the learning curve. They did not in my ...

3

Which is/are the most extensible? RapidMiner and R. Besides, RapidMiner offers extensions for seamlessly integrating R and Weka, hence can combine the power and extensibility of all three platforms within RapidMiner. And you can download RapidMiner and its extension for R and Weka for free. Which is the most efficient in terms of a minimal learning ...

3

I've been using HighStock, which produces very slick interactive charts with a relatively small amount of JavaScript. Among other things, it can produce candlestick/OHLC charts with volume bars, take a look at the examples page.

3

Following on from alpha's answer, you might be able to use some of the ideas and tools described on this blog to link R, and maybe also MATLAB/Octave, to the Metatrader platform to use the charting capabilities of Metatrader. Linked from this blog is this page where there is a dll tool available, with downloadable open code, to call R directly from ...

3

I would recommend performing visualization intensive tasks and UIs on a separate front-end, given R and Matlab are not optimized to efficiently render charts and other visualizations. If you are able to run WPF/Silverlight apps on your machine I can highly recommend SciChart (http://www.scichart.com/). It fulfills all your stated requirements. The library ...

2

Take a look at http://www.modulusfe.com/stockchartsl/ They have a nice demo (requires Microsoft Silverlight plugin). You can zoom and scroll, add lines and technical indicators, save image etc. Also see this SO question.

2

if you are dealing with FX data only; i have found MetaTrader to be the best. my automated trading system is built in Java; and I output data files to MT4 folder; that get picked up automatically by a custom indicator that I have built; which simply reads the data file and plot it on the currency pair that I am viewing. MT4 charts are extremely fast; ...

2

By stock chart application you mean you are making a charting tool for traders? Typically there is a choice to plot trade, bid or ask, and almost all the time they will want to look at trade prices. If a stock hasn't been trading then the flatline (or gap) on the chart communicates that.

2

download gnuplot better then matlab , R and has almost every thing you will need It can also do everything mentioned in the other posts, and even visualize data in real time, at no cost as its open source and offers output to almost any format you want even LaTex for your thesis.

2

Great question, I love to visualize data! A visualization is really the most efficient way to display a large amount of information to be processed by the human brain IMO. Depending on what exactly you are trying to plot and visualize, I would suggest trying the javascript API for WebGL called Three.js. Examples of Three.js are here: http://threejs.org/...

2

I came across B/View which is a Java application that visualizes the order book for a single stock on a single day. It encompasses some of the basic features I would expect in such a tool. It appears to be more a demonstration than a general purpose tool.

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