Quantifying the relationship between news and trading volume and price


A recent academic paper finds evidence for a relationship between the volume of news mentions of certain stocks and the volume of trading size of price change in those stocks.


There have been quite a few papers on the relationship between news or information searching and market movements. But this paper, Quantifying the Relationship Between Financial News and the Stock Market, tries to measure the relationship.

To research this the authors, Merve Alanyali, Helen Susannah Moat and Tobias Preis, studied daily issues of the Financial Times for the period 2007-2012. (As a by-product of this analysis they found that 891,171 different words appeared in the FT over this period!)

They tracked mentions of the companies in the Dow Jones Industrial Index and the corresponding movements in volume and price for these companies on the NYSE for the same day and the following day.

They found evidence for a relationship between the number of mentions of a company on a day and both the volume of trading and size of price change for a company’s stock on the same day.

The following figure from the paper shows the ranking of DJIA companies according to the correlation between FT mentions and absolute movement in the stock price.

Source: Merve Alanyali, Helen Susannah Moat and Tobias PreisThe strongest correlation among the DJIA companies they found was for Bank of America.

The paper concludes with the qualification that their analyses do not allow them to draw strong conclusions about whether news influences the markets, or the markets influence the news; but they propose that movements in the news and movements in the markets may exert a mutual influence upon each other.


Alanyali, Merve and Moat, Helen Susannah and Preis, Tobias, Quantifying the Relationship Between Financial News and the Stock Market. Sci. Rep. 3, 3578; DOI:10.1038/srep03578 (2013)


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Markets no more informative than they were 50 years ago

Quick summary

A recent academic paper, Have Financial Markets Become More Informative?, found that the extent to which stock and bond prices predict company earnings has not increased since 1960.


The paper starts with a quote from Eugene Fama-

The primary role of the capital market is allocation of ownership of the economy’s capital stock. In general terms, the ideal is a market in which prices provide accurate signals for resource allocation: that is, a market in which firms can make production-investment decisions… under the assumption that security prices at any time ‘fully reflect’ all available information.

So, in an ideal market prices convey information which drives investment which results in economic growth.

The authors observe that in the past 50 years there have been a number of developments that, one might think, would improve the informative role of markets, such as:

  1. Financial markets have developed tremendously in the last few decades, reducing the cost of trading and increasing liquidity.
  2. Information technology now delivers data quickly and cheaply.

So, given these developments the authors ask if market prices have become commensurately more informative. Or, to put it another way, have prices become better at predicting earnings?

To research this the authors analysed data for the S&P 500 companies since 1960.

The following figure from the paper shows the equity market-predicted variation, which measures the size of the predictable component of earnings that is due to prices, or total price informativeness in the model.

Figure 2. Forecasting earnings with equity prices. Source: Jennie Bai, Thomas Philippon, Alexi SavovThe research shows that while market prices are positive predictors of future earnings, there is no evidence of an increasing trend in equity price informativeness.

The authors conclude that their findings contradict the view that improvements in financial markets (e.g. liquidity) and information technology have increased information production.

Finally, the authors ponder why this might be; their suggestion is that while our ability to store and transmit information has undoubtedly improved, the important thing for investors is the interpretation of information *.


Bai, Jennie and Philippon, Thomas and Savov, Alexi, Have Financial Markets Become More Informative? (November 2013).

* I would just point out that the current best-selling book on investing is The Intelligent Investor by Benjamin Graham, a book first published in 1949.


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Information effects and stock returns

Does an increase in newsflow on a stock anticipate increased returns?

In today’s computerised world it is easy to monitor the amount of newsflow on particular stocks. It is also possible, using tools like Google Trends, to monitor active interest in stocks. For example, the following chart shows the number of Google searches on “AAPL” (the ticker for Apple) since 2005.

Google Trends - searches on the ticker AAPL

But can this information be used to predict share price behaviour?

Research by Yanbo Wang of INSEAD suggests it can.

In his paper (Media and Google: The Impact of Information Supply and Demand on Stock Returns) Wang found that the key factor to monitor was an increase in both

  1. supply: the newsflow (as measured by news articles in Factiva),
  2. demand: Google search volume

on specific companies. His research found that an increase in the pair of supply and demand of newsflow resulted in subsequent abnormal returns for stocks.

His explanation is-

The results are consistent with the hypothesis that an increase in information supply drives stock prices up only when an increase in information demand confirms that information supply succeeds in raising new investors’ awareness and existing investors’ additional learning effort.

The following chart plots the monthly excess returns of an equally-weighted, monthly re-balanced portfolio that is-

  • long stocks that have experienced an increase in information supply and demand the previous month, and
  • short all other stocks.

Media and Google: The Impact of Information Supply and Demand on Stock Returns, Yanbo Wang

The above portfolio generated abnormal annual returns of 16%-22%. This increased to 23%-34% when the portfolio was restricted to smaller stocks.

Wang, Yanbo, Media and Google: The Impact of Information Supply and Demand on Stock Returns (November 20, 2012)

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Strategy profitability affected by academic papers following publication

Here’s an interesting thing: it seems that people actually read academic papers.

A paper published in October 2012, Does Academic Research Destroy Stock Return Predictability?, finds that the profitability of strategies declined by, on average, 35% after the studies had been published in academic journals.

The authors, R. David McLean and Jeffrey Pontiff, looked at 82 studies published in 68 different papers in journals such as Journal of Financial Economics and Journal of Political Economy. Their main findings are:

  1. The return predictability of the 82 studies suffered a 35% decay post-publication.
  2. Publication drew attention to the anomalies which led to increased trading in anomaly stocks.
  3. The above increase in trading was seen more in large, liquid stocks than smaller cap stocks.

The publication of this paper has resulted in some interesting discussion – and reporting. The Chronicle of Higher Education headlined their article “Academic Research Destroys Stock Values“, which isn’t what the paper is saying, but is certainly a more exciting heading than the best we could come up with for this blog post.

So, while text like-

Similar to Table 3, Table 7 estimates a regression akin to Eq. (1); only the dependent variable is the normalized rank of the trading characteristic, rather than the normalized return.

is not everyone’s beach-reading choice, someone is actually reading this stuff.

The ramifications of this study are interesting. At the more trivial end:

  • Academics finally have proof that, not only are people reading their papers, but they are also acting on the research. This might result in salary increases for the academics – which means they are being rewarded for research that, in some cases, is no longer useful. Perhaps the salary increase could be proportional to how little use the research is after publication?
  • Will the vailidity of the findings of this paper itself also decay 35% after publication? Perhaps the best anomalies will no longer be published in academic papers, leading to a 35% decay in the 35% figure.
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