Overview of RENOIR

Example output

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is a project of the

Department of Computer Oriented Statistics and Data Analysis (COSADA)

at the University of Augsburg, Germany


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About the Dataset

RENOIR has been developed for analysing market share changes and monitoring portfolio performance, all using interactive graphics. The focus lies on changes between time periods using skyline plots, a new graphic which shows % changes, absolute changes and shares in one coherent plot.

As an example consider looking at the DAX, the German stock market index.
(Data available from the webpage: DAX Dataset ). The DAX comprises the 30 German shares with the biggest stock market values, including Daimler Chrysler, Deutsche Bank, Siemens and Volkswagen. It is similar to the Dow-Jones-Index in New York and the Nikkei Index in Tokyo. The 30 shares may be grouped into eight main sectors: Consumer & Retail, Insurance, Chemicals & Pharmaceuticals, Banking & Finance, Automobile & Transport, Utilities & Telecommunications, Software & Technology, Machinery & Industrial.

Fig. 1: Diagram with relative Changes in the DAX    Fig. 1: Diagram with relative Changes in the DAX
Fig. 1 shows the relative change of market value for each of the eight groups between September and October 2001. (The names have been left out to reduce clutter.) Apart from Software & Technology with a gain of 6.7% every sector lost up to 30% during the period, almost certainly due to the after-effects of September 11th. The three worst sectors were the first column, Consumer & Retail with a loss of 30.0%, the second, Insurance (-27.3%), and the fifth, Automobile & Transport (-22.3%). This is not so surprising as these are sectors heavily influenced by such a catastrophe.

The diagram is misleading in that all groups are treated as if they are the same size. In fact Consumer & Retail is a fairly small sector compared to the two others: Automobile & Transport is seven times bigger, and Insurance ten times bigger. In spite of this, it is common to compare only relative changes and not take absolute size into account.


Skyline Plots

Fig. 2: RENOIR-Diagram takes relative and absolute changes into account
 Fig. 2: RENOIR-Diagram takes relative and absolute changes into account
In skyline plots the x-value represents the size of the sector (so that the widths of the columns are no longer equal) and the relative change of each sector is plotted on the y-axis. Relative changes are represented by the heights of the columns and the absolute changes by their areas (= relative change * size). Figure 2 shows the skyline plot corresponding to Figure 1. The order and the heights of the columns are the same, but the width is proportional to size. Consumer & Retail in the first column (-30.0%) can now be more readily compared with the ten times bigger Insurance sector in the second column (-27.3%). The mean change for the DAX as a whole is marked by the broken line (-13.4%).

This diagram shows the big difference in absolute changes between Consumer & Retail and Insurance or Automobile & Transport. In spite of a similar relative loss, the change in the last two sectors influences the total DAX value much more than Consumer & Retail: the absolute changes are nine and five times bigger - in the skyline plot this can be seen from the bigger column areas.

It is not the exact size of the absolute change that is interesting (areas cannot be compared as easily as heights), but the area should give you a rough idea of the importance of each change. The relative change is a good criterion for identifying successful groups, but in order to get the most important change you have to take the absolute change into account. Both variables are important!


Interactive Possibilities

Fig. 3: Diagram sorted by absolute change
 Fig. 3: Diagram sorted by absolute change
Sorting

It can be very useful to sort the columns by their areas (the absolute changes) (menu 'Data' -> 'Sorting' -> 'absolute Changes within Groups') or by their heights (the relative changes) (menu 'Data' -> 'Sorting' -> 'relative Changes within Groups'). The three sectors discussed above have been highlighted in red to identify them quickly. The smaller effect of the Consumer & Retail sector and the much larger losses of the other two sectors can be seen at once. It is also clear that Insurance and Automobile & Transport are the two sectors with the most negative influence on the DAX in this period.

Querying and Selection

Querying and selection is essential for skyline plots because there can be so many columns. Both default and detailed querying (mouse move with key 'i' or 'd' pressed) are available. Selecting a column by a dragged mouse move, it is marked in red.
Fig. 4: Diagram, drilled down in Automobile & Transport
 Fig. 4: Diagram, drilled down in Automobile & Transport

Drill Down/Up

Within the DAX the sectors had different relative changes and within the sectors so do the various shares. By clicking on a column in the original diagram you can drill down into the sector. In Figure 4 for Automobile & Transport you get the changes for Volkswagen, Preussag, Lufthansa, BMW, Deutsche Post and Daimler Chrysler. The grey 'shadow plot' in the background shows the size of the parent sector and hence which columns belong together.

You can drill down (up) in all sectors by pressing the down (up) arrow key.




Fig. 5: Zoom of Sector Automobile & Transport
 Fig. 5: Zoom of Sector Automobile & Transport
Zoom

To get more details you can zoom in with selection of the sector with the middle mouse key as in Figure 5. A new window opens with a diagram containing only the zoomed sector (Figure 6). A bird's eye view is automatically generated in the floating parameter window where the red rectangular shows which part is currently zoomed.

Looking at the columns widths for shares in Automobile & Transport, Daimler Chrysler (highlighted) seems to be nearly as big as the rest of the stocks together. With a loss of only 13.9% it performed much better than the other stocks in the sector. Lufthansa lost 25.9% (third column), Volkswagen 28.4% (first column). BMW had the worst result of -34.2% (fourth column). Querying shows, that the absolute loss of Daimler Chrysler is bigger than the loss of BMW (compare the areas). The relatively 'good' result of Daimler Chrysler and its large share of the sector raises the result of the sector as a whole up to -22.3%. Without Daimler Chrysler the sector would have performed worse than Insurance (-29.2%).

Fig. 6: Diagram with zoomed Sector Automobile & Transport and highlighted Daimler Chrysler
 Fig. 6:  Diagram with zoomed sector Automobile & Transport and highlighted Daimler Chrysler
Fig. 7: Parameter window with bird's eye view
 Fig. 7: Parameter window with bird's eye view

Changing Categories and Time Period

The parameter window shows the bird's eye view, a list of the variables in the data set and the two time periode compared. The time periods can be changed by the pop-up option menus. The order of the categories can be changed by drag and drop.

Linking

In Figure 1 the same data are highlighted as in the zoomed window. This shows Daimler Chrysler as a proportion of the whole sector: only 28.3% of the change in Automobile &  Transport is due to Daimler Chrysler, but the company's weight in the sector was nearly 50%.




Fig. 8: Linked Diagram with highlighted Daimler Chrysler-part
 Fig. 8: Linked Diagram with highlighted Daimler Chrysler-part
Fig. 9: Analysis of Structure Diagram  Fig. 9: Analysis of Structure Diagram

Analysis of Structure

Raw data rather than shares and changes can be displayed in an 'Analysis of Structure' plot. Here the y-height is the size in October 2001, and the stocks are plotted in columns of equal width along the x-axis, but cumulated into the sectors as before. The second column,  Insurance, is the biggest sector. The first column Consumer & Retail is one of the smallest sectors, while Automobile & Transport is somewhere in the middle. As Daimler Chrysler is still highlighted, its relative size to its sector Automobile & Transport of 50.1% can be seen by querying.

Sorting in Total

Drilling down in all sectors at the same time and sorting them by 'absolute Changes in Total' shows which stock had the most influence (whether positive or negative) on the DAX. The columns highlighted here are: Allianz, Munich Reinsurance (both belong to the Insurance sector) and Deutsche Bank with losses and Siemens with the biggest gain. Sorting by relative changes gives us the most/least successful stocks (relative to their size).
Fig. 10: Diagram drilled down in all sectors with Sorting Menu
 Fig. 10: Diagram drilled down in all sectors with Sorting Menu
Fig. 11: Diagram sorted by absolute change, the three worst stocks are highlighted (Allianz, Munich Reinsurance, Deutsche Bank)  Fig. 11: Diagram sorted by absolute change, the three worst stocks are highlighted (Allianz, Munich Reinsurance, Deutsche Bank)

Change Over Time


But how is the development over several periods of time? And how bad is this month compared to other periods? For these questions, a plot with change over time is necessary: select the 'Change over time' box in the parameter window and pull the new category 'Change over Time' up to the first position as in Figure 12. Then we get the diagram on the right, showing the changes of the DAX for each period using alternating backgrounds to seperate them. The periods start with 11/2000-12/2000, 12/2000-01/2001,... and end with 10/2001-11/2001. But as the deviation from the mean during all the periods is very high, we should scale the axis first, before analysing the diagram.
Fig. 12: Selecting Change over Time in the parameter window
 Fig. 12: Selecting Change over Time in the parameter window
Fig. 13: Diagram with Change over Time  Fig. 13: Diagram with Change over Time
Fig. 14: Change over Time Diagram with scaled axis
 Fig. 14: Change over Time Diagram with scaled axis

Scaling of Axis


By clicking outside the right hand border of the diagram we can rescale to the height of 94.02% as a new maximum value. The result is shown in Figure 14. The second last period is the one we analysed before: September to October 2001. Now it is obvious, that in this period the DAX lost a lot, but compared to the total development and the loss in the other periods it was little: the loss in the time after September 11th was very bad, but the profit, which was made after it until the end of the period, 'balanced' it again. There is some evidence of cyclic behaviour. If there is a big change in one period, there is a reaction in the next.

Examining Daimler Chrysler over time in Figure 15 by querying and selection suggests that the variability of the smaller companies in the sector was greater: the bigger losses they suffered in the immediate aftermath of September 11th were compensated by the bigger gains they made at other times.

Fig. 15: Diagram with the development over time, the stock Daimler Chrysler is red highlighted  Fig. 15: Diagram with the development over time, the stock Daimler Chrysler is red highlighted

Further possibilities

If you are interested in experimenting with RENOIR yourself, click on 'Applet' to open a test-version where the DAX-Dataset can be analysed by clicking on menu 'File' -> 'Test-Dataset'.

RENOIR can be used for analysing other kinds of dataset as well: financial control, risk management, market share analysis, and election results. Wherever you have positive data, changing over time, grouped in different categories such as regions, sectors, business areas or what ever, RENOIR can help you.

If there are further questions which cannot be answered by the help (menu 'Help' -> 'Help - Shortcuts'), contact me per email .

(C)Copyright 2003 Dept. of Computer Oriented Statistics and Data Analysis, University of Augsburg, All rights reserved