Jorge Luis Borges was a great writer whose writings were succinct and full of deep insights, woven around a wry sense of humor on some occasions. His ‘book’ titled Labyrinths is actually a collection of short essays – a must read. He could never understand why people wrote massive tomes. Inspired by his views, I look at topics which can be expressed short.

There is this widespread belief that quantitative data is objective. Most people think that anything that is a number has to be objective. Yes, some numbers are objective. Before proceeding further, let us define objectivity: “not influenced by personal feelings, interpretations, or prejudice: based on facts; unbiased” (https://www.dictionary.com/browse/objective).

There is a vast body of numbers which will satisfy this condition – road accidents, production figures, harvests and so on. There are instances where counting conventions have to be considered before placing trust in published figures but they would otherwise measure up to the definition stated here.

I am keen on a set of figures that are displayed every day in the business press and poured over by hundreds of people analyzing it – stock prices. Based on these prices, fortunes are made and lost, made again, lost again.

Are stock prices objective data? Or are they really subjective views with a numerical expression? After all, the way stock markets are organized, stock prices depend on bidding for purchasing and selling each a product of someone’s view on the worth of a stock. Much the same is true of exchange rates too. Or even prices of derivatives. The market might well be seen as a sum of behavior – to buy or to sell. Thus, when you read ‘the market ended in an over-bought situation’ you can understand what happened during the day. Or when you read institutional investors including mutual funds selling to book profits. What is short selling? Someone’s view that the price of a certain stock is higher than justified and hence will tumble down, in some time. If this turned out right, there is gain; else, there is loss and misery.

It is important to keep this in mind when anyone looks at a time series data on stock prices.