Alphanumeric Financial Charts

Financial charting has long used alphanumerics as point indicators in charts. One of the oldest I can find is Hoyle’s Figure Chart (from The Game in Wall Street and How to Play it Successfully: 1898) which essentially plots individual security prices in a matrix organized by time (horizontally) and price (vertically).

An early figure chart. Time is implied horizontally, price vertically. A numeric "figure" is recorded for each price that occurs for each day.

An early figure chart (from Hoyle: 1898). Time is implied horizontally, price vertically. A numeric “figure” is recorded for each price that occurs for each day.

This textual representation evolved over the decades. By 1910, Wyckoff (Studies in Tape Reading: 1910) was creating charts where x and y are still time and price, but he was writing down volumes instead of prices, and connecting together subsequent observations with a line.

Wyckoff's figure chart records rising and falling prices in adjacent columns. For each price level he records the volume figures and connects together the sequence with a line.

Wyckoff’s figure chart records rising and falling prices in adjacent columns. For each price level he records the volume figures and connects together the sequence with a line.

By the 1930’s these had evolved into early point and figure charts, such as can be seen in DeVilliers and Taylor (Devilliers and Taylor on Point and Figure Charting: 1933).  Columns use X’s to plot prices and other characters to denote particular price thresholds.

DeVilliiers and Taylor's Point and Figure chart (1933).

DeVilliiers and Taylor’s Point and Figure chart (1933).

These charts look pretty close to modern financial point and figure charts. Now we typically use X’s for a column of rising prices and O’s for a column of falling prices, and other character may be used to denote particular time thresholds (e.g. 1-9, A-C to indicate the start of each month).

Modern Point and Figure chart, via Wikipedia.

Modern Point and Figure chart, via Wikipedia.

Other alphanumeric charts evolved along the way as well. Here’s an interesting depression era chart plotting a histogram of states based on state unemployment rates. Like Wyckoff, the author seems to be interested to keep the alphanumerics inside circles. Also, note standardized 2 letter codes for states did not yet exist – states are numbered instead. (from W.C.Cope’s book Graphic Presentation: 1939).

Distribution Chart made of stacked characters. Note additional information encoded in shading and added markers.

Distribution Chart made of stacked characters. Note additional information encoded in shading and added markers.

Fast forward to the 1980’s, and we have Peter Steidlmayer’s Market Profile (R) charts that appear reminiscent to the alphanumeric distributions seen in the depression era chart. In these distributions, the alphanumeric value represent times when a security traded at a specific price. Depending on the timeframe of the chart different mappings may be used. One common intraday convention is to use characters A-X and a-x to represent half hour intervals throughout the day, with a split from uppercase to lowercase at noon.

Very basic Market Profile chart

Very basic Market Profile chart

There are many, many variants of market profile charts now e.g. sierrachart.com, windotrader.com, bluewatertradingsolutions.com, prorealtime.com, cqg.com, etc, etc. Given the many possible data attributes and analytics that one might associate with a character in a chart, it can become a challenge to encode them. As a result, one can find interesting variants. Beyond position, letters and case:

  • color: of the foreground letter or background square
  • bold: to indicate a row or potentially as a highlight to one time interval, e.g. MarketDelta
  • superscripts: e.g. eSignal.
  • added symbols: asterisks, less than, greater than, etc.
  • added shapes: circles and diamonds
Market Picture Variants

Many variants of Market Profile (R) charts by various vendors. Note all the additional information added via foreground/background color, bold, superscript, etc.

Jesse Livermore (How to Trade in Stocks: 1940created his own variant of alphanumeric charts stripped down to tracking only the minimums and maximums, discarding the intervening levels and using color and underlines to indicate information.

Livermore strips down charts to a simple table recording only the local minimums and maximums, using different colored text and different colored underlines.

Livermore strips down charts to a simple table recording only the local minimums and maximums, using different colored text and different colored underlines.

One interesting discussion point is the actual use of these charts. Whenever I show these charts to the visualization research community, people are aghast and suspect. There’s so much going on in these charts, so many different things being shown simultaneously, that they don’t believe that people actually use them or that somehow these charts can’t be perceptually efficient.

On the otherhand, I’ve talked to people who’ve traded off these charts their entire career. They see patterns and pick out things immediately at very different scales: individual outliers, columns of a particular letter, the shape of a distribution, and so on. Much like an expert chess player, these market participants have learned these charts, know how to interpret them, and use them to make trading decisions.

To be fair, not everyone in the visualization community is shocked: some are genuinely curious. Instead of reducing visualizations down to just one or two attributes, here’s something heavily loaded with a lot of visual attributes. And it’s not a static poster where you have no interaction: these are on computer screens packed with interactive features. In spite of all the computational ability to filter and reduce, here’s a community that that has these densely packed charts. People are actually using them to see macro patterns (shapes of distributions) and micro readings (individual characters), but they are also able to attend to intermediate patterns such as particular letters within a distribution. Perhaps they aren’t seeing patterns as fast as preattentive recognition, but they are still seeing patterns quickly with this external cognitive aid. There’s still more that the visualization community needs to understand about expert users.

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About richardbrath

Richard is a long time visualization designer and researcher. Professionally, I am one of the partners of Uncharted Software Inc. I am also pursuing a part-time PhD in data visualization at LSBU. The opinions on this blog are related to my personal interests in data visualization, particularly around research interests related to my PhD work- this blog is about exploratory aspects of data visualization not proven principles.
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