Index changes (FTSE indices) – paper review

Every quarter the constituents of the FTSE 100 Index are reviewed, some companies may be removed to be replaced by others. An effect has been observed whereby companies joining the FTSE 100 Index experience a positive and permanent impact on their share prices.

This article presents a brief review and listing of academic papers on changes made to FTSE indices.

Traders are interested in changes to equity indices due to the potential arbitrage profits; but academics have a wider interest because for them changes to indices act as something like a laboratory for testing theories of stock market efficiency and behavioural finance. Briefly, when a stock joins (or leaves) an index, nothing changes to the company itself and so (in an efficient market) there should be no change to the share price. Academics therefore get excited (the term is used here relatively loosely) when this is not the case.


Kougoulis and Coakley (2004) found that shares joining the FTSE 100 Index experienced an increase in comovement (price movement correlation with other shares); shares leaving the index experienced the opposite effect. Mase (2008) supported the previous findings and in addition found that increases in comovement had become larger in recent years, and that the overall increase in comovement was due to new additions to the index rather than previous FTSE 100 constituents re-joining the index.

Price pressures

Another favourite of academics. If a share price moves without new information is the move temporary (price pressure hypothesis) or permanent (imperfect substitutes hypothesis)? Mazouz and Saadouni (2007) found strong evidence for the price pressure hypothesis: prices increased (decreased) gradually starting before the index change announcement date of inclusion (exclusion) and then reversed completely in less than two weeks after the index change date. The existence of the temporary price changes (price pressure hypothesis) was also found by Opong and Antonios Siganos (2013) and Biktimirov and Li (2014). Interestingly, Mase (2007) comments that the temporary prices changes to shares joining/leaving the FTSE 100 Index is in contrast to the case for S&P 500 index changes where permanent price changes have been found.

Information efficiency

Daya and Mazouz and Freeman (2012) (and other papers) found that informational efficiency improved for stocks added to the FTSE 100, but did not diminish after deletion.

Now, onto the more useful topics.

Price changes

Gregoriou and Ioannidis (2006) found that price and trading volumes of newly listed firms increased. That confirms what we already knew or suspected. But, interestingly, they (and other papers here) attribute the cause to information efficiency: stocks with more available information increase investor awareness. However, Mase (2007) does say that investor awareness and monitoring due to index membership do not explain the price effects. But not mentioned here is the influence of index funds.

And, finally, the interesting stuff.

Anticipatory trading

Fernandes and Mergulhao (2011) found that a trading strategy based on addition/deletion probability estimates gave an average daily excess return of 11 basis points over the FTSE 100 index. Opong and Siganos (2013) found “significant net profitability” from an investment strategy based on firms on the FTSE reserved list. And a strategy based on the FTSE 100 quarterly revisions was profitable if CFDs were used and traders could deal within the bid/ask spread.

INDEX (of papers listed below)

[Papers listed in reverse date order; indicates major paper.]

  1. Asymmetric stock price and liquidity responses to changes in the FTSE SmallCap index [2014]
  2. Compositional changes in the FTSE 100 index from the standpoint of an arbitrageur [2013]
  3. Information efficiency changes following FTSE 100 index revisions [2012]
  4. Anticipatory Effects in the FTSE 100 Index Revisions [2011]
  5. Comovement in the FTSE 100 Index [2008]
  6. The Impact of Changes in the FTSE 100 Index [2007]
  7. The price effects of FTSE 100 index revision: what drives the long-term abnormal return reversal? [2007]
  8. New evidence on the price and liquidity effects of the FTSE 100 index revisions [2007]
  9. Investor awareness and the long-term impact of FTSE 100 index redefinitions [2006]
  10. Information costs and liquidity effects from changes in the FTSE 100 list [2006]
  11. Comovement and Changes to the FTSE 100 Index [2004]

Asymmetric stock price and liquidity responses to changes in the FTSE SmallCap index
Authors [Year]: Ernest N. Biktimirov and Boya Li [2014]
Journal [Citations]: Review of Quantitative Finance and Accounting, 42(1), pp95-122
Abstract: We examine market reactions to changes in the FTSE SmallCap index membership, which are determined quarterly based on market capitalization and are free of information effects. Our main results are asymmetric price and liquidity responses between the firms that are shifted between FTSE indexes and the firms that are new to FTSE indexes. Firms promoted from a smaller-cap to a larger-cap FTSE index experience a permanent increase in stock price accompanied by improvements in liquidity. Similarly, firms demoted from a larger-cap to a smaller-cap FTSE index experience a permanent decrease in stock price accompanied by declines in liquidity. In contrast, firms added to the FTSE SmallCap index that were not previously in FTSE indexes show a transitory price gain and declines in liquidity. The results support the liquidity and price pressure hypotheses.
Ref: AA704

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10 strange financial papers

While, of course, there are many very serious – and fascinating – academic papers on finance, such as Multifractality and long-range dependence of asset returns: the scaling behavior of the Markov-switching multifractal model with lognormal volatility components, there are other papers that are…well, a little strange. This article lists ten such papers.

A long list of questions could be compiled to which the simple answer is no. A good source for such questions is headings from the UK newspaper, the Daily Mail (e.g. Are we all going to die next Wednesday?). Another good source is academic papers. In one paper below the implicit question is: are stock returns affected by ghostly legends? Short (and long) answer: no. Another paper finds a correlation between a country’s linguistic diversity and stock market trading volumes. Perhaps this simply results from the number of trades that have to by reversed following language confusion: “I thought you said buy?”, “No, I say sardine!”

A strong contender for the Paper in Poor Taste Award would be the one below looking at the influence of sudden celebrity deaths on the stock market (the inclusion of the word “sudden” in the title will no doubt be appreciated by the judges of this award). John Kay recently wrote an excellent article about the wisdom of crowds (The parable of the ox); appearing here is a paper that tackles the same topic but in a rather left-field context. The paper finds that the price movements of tourism stocks on the Tel Aviv Stock Exchange more accurately forecast the success of ceasefire agreements in the Levant than did editorials in the Jerusalem Post and New York Times.

How is your well-being? The authors of a paper here believe it (that is, your well-being) is affected by the stock market and that the government should do something about it. And if the government doesn’t do something about it, this other paper reckons we’re all going to the loony bin.

Finally, nomination for one of the creepiest papers must go to the one here that found that when CEOs are away from their headquarters companies announce less news than usual. Fair enough, but to analyse this the author identified CEO absences by “merging corporate jet flight histories with records of CEOs’ property ownership near leisure destinations”. We’ve had shareholder activists, are we now to see the rise of shareholder stalkers – would-be analysts hiding in the bushes with binoculars checking on the holiday timetables of CEOs?

INDEX (of papers listed below)

  1. Anomalies in Finance: Superstition in the Italian Stock Market [2010]
  2. Ghostly Traditions and Market Performances [2013]
  3. Chinese superstition in US commodity trading [2014]
  4. Linguistic Diversity and Stock Trading Volume [2013]
  5. Tailspotting: Identifying and profiting from CEO vacation trips [2012]
  6. Local sports sentiment and returns of locally headquartered stocks: A firm-level analysis [2012]
  7. The Effects of Sudden Celebrity Deaths on the US Stock Market [2011]
  8. The Oracle or the Crowd? Experts versus the Stock Market in Forecasting Ceasefire Success in the Levant [2011]
  9. Does the Market Make us Happy? The Stock Market and Well-being [2013]
  10. Do stock prices drive people crazy? [2014]

Anomalies in Finance: Superstition in the Italian Stock Market
Authors [Year]: McGuckian, Fergus J [2010]
Journal [Citations]:
Abstract: The efficiency of global financial markets has long been a topic of contention for both academics and industry professionals alike. Evidence suggests that most of the time, asset markets do a good job of correctly processing and assimilating information into prices. However, a substantial literature has built up proof which indicates that this is quite often not the case. A wide variety of anomalies and so called ‘effects’ have been documented revealing stock price behaviour that is inconsistent with the predictions of traditional models. These inconsistencies illustrate departures from theory and are unexplainable within the mainstream economics paradigm; conversely, many anomalies can be accounted for using explicit insights from behavioural finance. This study discusses the theoretical debate and investigates whether financial markets are affected by superstition and if so, if this is reflected in asset prices. A new discovery is added to the literature, namely the Friday 17th anomaly; with regard to the Italian MIB Storico index results indicate that in comparison to regular Fridays – which are aggregately positive – returns for Friday the 17th are four times larger and statistically different.
Ref: AA469

Ghostly Traditions and Market Performances
Authors [Year]: Yang, Der-Yuan and Andy Chien [2013]
Journal [Citations]:
Abstract: Old traditions never die; they just fade away. However, some are still deeply embedded in our life and practiced every day. This paper examines some notable Taiwanese ghostly legends, testing their potency on the stock markets. The results show that though some ancient beliefs still carry heavy weight in our daily life ostensibly, their impact on the stock market has been negligible. To be sure, some of the customs of our ancestors may have lingered around long er than expected, but contrary to our expectations, their spirits have languished, showing no vigor as financial guidance.
Ref: AA485
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Triple Witching – paper review

This article presents a brief review and listing of academic papers on triple witching.


The expiry of stock index futures, stock index options and stock options happens in a programmed calendar throughout the year. On four days a year these three different types of derivative all expire on the same day – the third Friday of the months of March, June, September and December. This day is sometimes referred to as triple witching day, and is associated with increased trading volumes and volatility.


Following the 1987 stock market crash there was great interest in program trading (a term not so commonly used today) and its impact on volatility. This led to a minor flurry of academic interest in associated topics such as triple witching.

The earliest mention of triple witching we can find in an academic paper is Feinstein and Goetzmann (1988), which looked at the increased volatility caused by the coincident expirations. A couple of years later Stoll and Whaley (1990) found greatly increased trading volume in the last half-hour on expiration days. However, they did not find any significant difference between stocks subject to program trading and other stocks.

In June 1987 the settlement of S&P 500 and NYSE index futures was changed (to settle at the open and not the close) in an attempt to decrease the impact of expiration. The effect of this was the topic of the most cited paper on triple witching, Stoll and Whaley (1991). Not surprisingly, perhaps, they found that volume and volatility of the S&P 500 and NYSE contracts was lower at the close and higher at the open for the period after June 1987 compared to the period before. The impact on price at the open was slightly smaller post-June 1987 than it had been at the close pre-June 1987.

Academic interest in triple witching then waned, albeit articles continued to appear on the more general topic of option expiration.

A rare, recent article (Stratmann and Welborn, 2012)  found a positive relationship between ETF settlement failures and ETF short sale volume, the cost to borrow ETFs, and triple witching days.

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US holidays and European markets


European stock markets tend to have positive and high returns on days when the NYSE is closed. The effect is significant when the previous day’s return on the NYSE has been positive.

Brief overview

The US has six holidays every year that are not holidays in Europe:

  • Martin Luther King Day (the third Monday in January)
  • President’s Day (the third Monday in February)
  • Memorial Day (last Monday in May)
  • Independence Day (the fourth of July)
  • Labour Day (the first Monday in September)
  • Thanksgiving day (the fourth Thursday in November)

How do the European equity markets  behave on these days when the US markets are closed?

This was the question asked by the authors of an academic paper (Casado, Muga and Santamaria, 2011).

The authors analysed open and close values for the CAC40, DAX, FTSE 100, IBEX35 and EUROSTOXX50 (for the euro-zone stock market)  for the period 1991-2008. Their results were remarkable.

Their research found the average daily returns for the European markets when the US market was closed was 0.32%, which was 15 times greater than the daily returns on all days.The greatest (NYSE-closed) daily returns were 0.42% for the German market.

Interestingly they found similar results for the open to close data on the NYSE-closed days. Meaning that the information from the previous day’s US market had been fully absorbed at the market open, and the effect is attributable to European trading.

Because the effect is so great it has a clear economic significance as it is possible to obtain significant returns after deducting trading costs by trading index futures.

The following figure from the paper shows the result of systematically buying FTSE 100 futures at the open on a NYSE-closed day and where the previous day’s NYSE return was positive, and then closing the position at the close on the same day. The red line is the equity chart for the strategy (left axis), and blue line the FTSE 100 Index (right axis).

Casado_The effect of US holidays on the European marketsThe strategy had positive returns in both bull and bear periods for the market.


Casado, Jorge and Muga, Luis and Santamaria, Rafael, The Effect of US Holidays on the European Markets: When the Cat’s Away (2011)


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Is the weather getting you down?

There have been quite a few academic papers written on the relationship between the weather and the stock market (links to 24 such papers are given below). Does lousy weather depress stock prices, and does the sun encourage investors to take on more risk? These are the types of questions that the papers try to answer.

In this article we’re going to look at one such paper (Dowling and Lucey, 2005), on the basis that as the authors are at Trinity College, Dublin, they may know something about rain.

The main reasoning behind most of the research into the weather and the stock market is the belief that investors’ mood influences their behaviour, and the weather can act as a proxy for mood (and, importantly, the weather can be measured). And this is the broad approach of the Dowling and Lucey paper.


The paper actually tests for the relationship between daily Irish stock returns for the period 1988-2001 and eight mood proxies in total: two belief-based (lunar phases, Fri 13th), two biorhythm-based (seasonal affective disorder, daylight savings time changes), and four weather variables (cloud cover, humidity, rain and geomagnetic storms). We’ll just focus on the four weather variables here.

The objective was to determine whether below average stock returns were associated with bad weather, and above average returns with good weather.


The results of their analysis on the weather variables are summarised in the following table.

Lucey_Weather, Biorhythms and Stock Returns_Table 3Source: Dowling and Lucey


First, they were surprised to find a positive relationship between high levels of cloud cover and stock returns, however the relationship is not significant. Less surprisingly they did find a negative and significant relationship between rain and equity returns. Again, oddly, they found a positive relationship between humidity and returns. Regarding storms, there was a negative, but insignificant relationship.

They then combined all four variables to create a generalised GoodWeather variable and a BadWeather variable, but found no significant relationship with either and  market returns.

As a further study they found some preliminary support for the theory that investors’ moods are more susceptible to influence if they are already in a good mood. Investors were defined to be in a good mood if the market index 10-day moving average was above the 200-day moving average.


The authors found that mood states caused by the weather had influenced the stock market. Of the four weather variables they found the most significant relationship was between rain and equity returns.

So, next time you consider selling a stock look out of the window and check if your mood is being affected by the rain.


Other articles about the weather and stock returns.


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Super Bowl Indicator

This coming Sunday is Super Bowl XLVIII.

One of the most famous market predictors in the U.S. is the Super Bowl Indicator. This holds that if the Super Bowl is won by a team from the old National Football League the stock market will end the year higher than it began, and if a team from the old American Football League wins then the market will end lower.


Well, it certainly sounds far-fetched that a game of mutant rugby could affect the economy and stock market. However, in 1990 two academics published a paper (Krueger and Kennedy, 1990) finding that the indicator was accurate 91% of the time.

And then in 2010 George Kester, a finance professor at Washington and Lee University, published a paper (Kester, 2010) with new research that found that the Super Bowl Indicator still worked (although its accuracy had fallen to 79%). Kester also calculated that a portfolio that switched between stocks and treasury bills governed by the Super Bowl Indicator would be worth twice that of a simple portfolio invested continuously in the S&P 500.

And the connection between American football and the UK stock market is…?

Seeing how closely correlated the U.S. and U.K. stock markets are, it might be interesting to see how the Super Bowl Indicator applies to the U.K. market.

The following chart shows the annual returns of the FTSE All Share index since 1967 (when the Super Bowl started). The Y-axis has been capped at +/- 50%, which truncates the bars for the years 1974 (-55%) and 1975 (+136%). The years for which the Super Bowl Indicator failed to accurately predict the direction of the market has been indicated with white bars in the chart.

FTSE All-Share annual returns as predicted by the super bowl [1967-2013]As one can see, the indicator got off to a great start in the years following 1967, but recently its record has been patchy. Overall, the indicator was accurate in 72% of years (only slightly less than its accuracy rate in the US).

Unfortunately a paper (Born and Acherqui, 2013) published last year has rather spoilt the fun. The authors found that the ability of the Super Bowl Indicator to forecast the market had reduced to almost zero in the years since publication of the Krueger and Kennedy paper in 1990.

Market around the time of the Super Bowl

The chart below shows the market behavior around the time of the Super Bowl; the bars represent the average daily returns in the FTSE All Share Index since 1967 for the three days before, and three days following, the Super Bowl (which always takes place on a Sunday).

FTSE All-Share average daily returns for the six days around the Super Bowl [1967-2013]The average daily returns in the index for all days since 1967 was 0.03%; we can see therefore that the market is abnormally weak two days before a Super Bowl and abnormally strong one day before it.



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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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How often do you check your portfolio?

A recent paper publishes the results of analysing over 1 million 401(k) accounts in the U.S. over the period 2007-2008.

The research found, among other things, that account logins fell by 11% after market falls. In other words, investors did not want to see the damage done to their portfolios after the market fell (aka the Ostrich Effect).

The research generally found that investor attention to their portfolios (and, to a slightly lesser extent, their trading activity) was influenced by demographics (age, gender) and financial situation (wealth).

For example, the authors analysed the relationship between frequency of account logins and investor age (see following chart).

As can be seen, younger and older investors logged into their investment accounts more frequently than did the middle-aged.

The authors interpreted the results as showing that middle-aged people were (in effect) busy with other matters, whereas older people were concerned about their retirement pots and younger people were happy to play with the online service.

Further analysis looked at the relationship between account activity and size of account (see following chart).

Not surprisingly, there was a positive correlation here: the larger the account the more frequent the portfolio checks. But the increase in account logins tend to tail off above an account size of $500,000. (By extension, it can be assumed that Warren Buffett isn’t logging in too regularly to his check his 401(k) account).


Sicherman, Nachum and Loewenstein, George and Seppi, Duane J. and Utkus, Stephen P., Financial Attention (October 10, 2013).

Available at SSRN: or

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Sun and the stock market

When the sun shines do you find yourself hovering over the trading screen enthusiastically adding stocks to your portfolio? Or on cloudy days when the rain beats against the window do you sit morosely at your desk, your finger stabbing at the sell button?

Two academic papers seem to think this is how you behave. The first paper[1], published in 2003, analysed 26 international stock exchanges and found that sunshine was “strongly positively correlated” with market index returns. The authors attributed this to sunny weather fostering an “upbeat mood”. They even claimed it was possible (after trading costs) to trade profitably on the weather. A second paper[2], published in 2007, found that the sunshine effect was stronger for stock exchanges further away from the equator (e.g. exchanges in dark, gloomy northern European countries), and that the effect did not exist on the equator itself.

This seemed a fun and easy topic to study, so we dived in.

The chart below plots daily sun hours (at Heathrow) against the FTSE 100 Index return on the same day.

Sun hours v FTSE 100 Index

At first glance, you might think that the chart shows no correlation between the two series (i.e. sun hours and index returns). And you’d be right. Even second or third glances will not reveal any positive correlation. In fact, if you look very closely and squint, you may even see a negative correlation – which is not at all what we want.

We should have stopped there. But we were motivated to find some correlation. We’d read the academic papers and also paid a reasonable amount of cash for the weather data (stock tip: if the Met Office is ever privatised…).

So, on we went.

Perhaps the effect does not exist for the FTSE100 Index which, after all, is heavily influenced by foreign investors, who are trading from their pools in the Caribbean or skyscrapers in Shanghai and who are unlikely to be affected greatly by how sunny it is in Orpington. So, we looked at sun hours and the FTSE 250 Index – an index more closely reflecting UK PLC and possibly attracting more domestic investors.

No, no correlation.

Perhaps the effect really displays itself for smaller stocks? We drafted in the FTSE Small Cap Index.

No correlation.

The AIM market – home of optimistic punters with a sunny disposition. Surely, the sunshine effect will reveal itself there?


OK. Let’s start manipulating the data.

We calculated the average daily sun hours for the winter and summer periods, and then adjusted the daily sun hours data by calculating the daily divergence of sun hours from their seasonal average. After all, just two hours of sunshine in the winter could be considered a sunny day. That should do it.


We limited the analysis to just those days with extremes of sunshine (i.e. daily sun hours one standard deviation away from the average).


Perhaps the change in sun hours from one day to the next would work? In other words, the effect would kick in when a sunny day followed a cloudy day, or vice versa.


In desperation to rescue something from all the research, we looked at sun hours against daily trading volumes. If the curmudgeonly UK investor wasn’t inspired by the sun to increase his net equity exposure, perhaps he at least punted around a bit more. Well, finally, on this one…….

No. No correlation.

At the end of everything the best we could do was the chart below – the FTSE 250 Index plotted against the change in sun hours from the previous day.

Hardly much of an improvement on the first chart – still just a random mass of uncorrelated dots. At least the correlation is (minutely) positive, but we wouldn’t recommend trading off it.


So, who is wrong, the papers or our research?

It’s difficult to say. Our data covered the period 2007-12, while the first academic paper looked at data for the period 1982-97. Possibly the effect has changed in the intervening years.

But if the academic papers are right, and the sunshine effect does exist, this would seem to conflict with the strongest seasonality effect in the market – whereby the market in the (dark) winter months out-performs the (sunny) summer months.

Tricky thing, the market.

[1] Hirshleifer,  D. and T. Shumway (2003). Good day sunshine:  Stock returns and the weather. The Journal of Finance 58 (3)

[2] Keel, S. P. and M. L. Roush (2007). A meta-analysis of the international evidence of cloud cover on stock returns. Review of Accounting and Finance 6 (3)

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