A logarithmic, or log, scale gives equal visual weight to equal relative changes: a 10% move looks the same whether it is from a high or a low base.

The result is that the magnitudes of earlier and later booms and busts can be compared on a level playing field. In the case of the Dow Jones since 1900, information in the first half of the chart has now been fully brought to light. Further, with log scales, series experiencing exponential growth appear as straight lines, making charts easier to interpret.

Finally, the use of nominal prices absolves researchers of the need to select a deflator and deal with the theoretical issues such a choice would entail. Researchers are often still interested in inflation as one economic phenomenon among many, and they can incorporate that into charts separately. But for a quick summary of a market, there is value in plotting raw price data.

It is worth noting that, for all their advantages, log scale charts have at least one failing: they cannot show negative values, even though prices can fall below zero. Indeed, this regularly occurs in European power markets. Separately, natural gas has traded
as low as -$.29 MMBTU on a North American market amid transportation capacity constraints.

Other complications with log scales can occur with axis labelling. Most charting software automatically labels logarithmic axes with exponentially increasing values: for example, 10^0, 10^1, 10^2, and so on. In time series with meaningful units – such as exchange rates, bond prices and commodity prices - these are not the increments that are most relevant to investors. For instance, on an oil chart, we may want to label in multiples of $25 per barrel. To do this, we need to turn to more flexible charting technologies.

## Crude Oil – Logarithmic Chart with Custom Labels