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What is the Point of (the Hundreds of Thousands of Billions of) Stock Transactions?

Introduction

Financial markets play a key role in today's economies. Although some socioeconomic studies have focused on the financialization and marketisation of our societies, mainstream economics attach little importance to these issues. Most of the papers praise the contribution of finance to growth, and very few appraise the level of financial activity that could be optimal. There is a broad consensus among economists that financial markets are important to achieving strong economic growth. However, in certain circumstances, it could be argued that financial deepening may hurt. This issue began to emerge following the financial crisis (Main Street versus Wall Street). In their provocatively article titled "Too much finance?", Arcand et al. (2015) determine that an increase in credit above a certain threshold, estimated at around 100% of GDP, is damaging to the economy. (1) Taking a completely different approach, albeit with a fairly similar objective, Philippon (2010) shows that excessive growth in the financial sector can lead to poor allocation of talents.

This article builds on these ideas by exploring the growth in trading activity and, more specifically, stock market transactions. The aim is to identify the potential problems the excessive growth in stock trading may bring and to survey the literature that has identified them.

We begin by setting out some stylised facts. Since the liberalisation and the demutualization of the stock markets, it is difficult to quantify the total amount of stock trades. I have used several sources to build a global database covering all countries over a 40-year period (1975-2015), which includes trades performed on historical stock exchanges, but also certain alternative platforms.

The value of stock traded provides a key indicator of the growing importance of finance and its influence. Even more than market capitalisation, it helps us to assess a fundamental feature of the financialization. In forty years, between 1975 and 2015, global stock market trades have risen from $300 billion to $115,000 billion. (2) This increase is equally staggering when calculated as a percentage of world income, rising from 5% of GDP in 1975 to nearly 150% today. At the same time, the average investment horizon has decreased eightfold from 4 years to 6 months, with a majority of investments which barely last few milliseconds ... How has this explosion of activity benefited the economy? Although this question is tackled in many public debates, albeit coloured by implicit ideologies, it is surprisingly rarely addressed in the academic literature.

We then review the various arguments and the way they are structured. Generally speaking, the increase in trading volumes is seen in a positive light: an improvement in liquidity helps to reduce the cost of capital and, as such, should have a positive impact on investment and growth. However, it is very likely that this relationship is nonlinear and that the marginal effect is decreasing. Furthermore, modern financial theory advocates reducing the number of trades due to the significant challenges involved in "beating the market". Many theoretical and empirical studies have even suggested that above a certain threshold, the increase in trading volumes has a negative effect. The reasons for this are, firstly, that the shortening of investment horizons puts pressure on listed companies, whereas the involvement of long-term investors seems favourable. Secondly, research in behavioural finance has shown that investors are often over-confident and therefore perform too many trades. Finally, this upward trend in trading volumes has brought with it a lack of transparency and a growing distrust of the markets.

To conclude, we set out some of the reforms that have been introduced to, if not reduce, then at least limit this growth. These measures have all had a very limited effect. Only comprehensive reforms of the way stock markets are organised could reverse this trend. Ultimately, these issues take us deeper than trading volume to question the very purpose of markets.

Some Stylised Facts

The strong growth in stock market activity is a well-known stylised fact. However, with the end of stock exchange monopolies, their demutualization, the emergence of new platforms, and the ensuing fragmentation of trades (Macey and O'Hara 2005), it has become increasingly difficult to document this trend.

The Main Databases Available

Four types of institutions collect and publish aggregate data on stock market activity: (i) international public organisations; (ii) professional associations; (iii) specialised agencies in publishing financial information; and (iv) the stock exchanges themselves.

The World Bank is the main source of data that can be used to monitor stock market activity over a long period and for wide range of countries. The "world development indicators" (WDI) provide annual data since 1975 on the market capitalisation of listed companies (in USD, and as a % of GDP) and on the total value of shares traded (in USD, as a % of GDP, and as a % of market capitalisation). The main problem with these data is that they only take into account electronic order book trades on historical stock markets, involving domestic companies.

These figures are taken from the World Federation of Exchanges (WFE), which does, however, provide more comprehensive data that include OTC trades and those reported by trade reporting Facilities (TRF), as well as trades involving foreign shares or performed on certain alternative platforms, particularly BATS. However, the data collected is dependent on members' goodwill. (3)

With the fragmentation of the markets over the past decade, being able to compare the activity of different trading platforms has become critical and new providers have decided to offer such services. Between 2010 and 2014, Thomson Reuters published a freely available detailed monthly report (known as the "Market Share Report") on stock exchange trades performed on the main platforms. The data were collected from each trading venue (including "historical" stock exchanges, multilateral trading facilities (MTFs), dark pools and OTC markets), before being broken down and aggregated for certain countries. This source was widely used by public authorities, practitioners and researchers, but Thomson Reuters decided to suspend the service, seemingly due to errors in the procedures for collecting and aggregating data. Fidessa currently provides fairly similar data via its Fragulator website.

Finally, it is possible to obtain data from trading platforms themselves. BATS, the world's leading alternative trading platform, publishes global data on stock trades in Europe and the USA. These data include not only trades that go through BATS, but also trades performed on competitor platforms.

Matching the Data

Although the World Bank gets its data from the WFE, it significantly underestimates stock market activity. Firstly, World Bank data only consider order book trades, which account for just three-quarters of the total value of trades. Secondly, these data do not include trades performed on alternative platforms, despite the fact that they are now major players. The WFE database only provides data for BATS, the world's leading alternative platform, while there are dozens.

To achieve a more truthful vision of changes in stock trades at global level, we have matched WDI and WFE data. We have also provided Thomson Reuters data by way of comparison, when these were available. However, we were not able to provide sufficiently reliable information on OTC or dark pool trades. (4)

The Growth in Stock Trading

Figure 1 shows the global growth in stock trades between 1975 and 2015. In forty years, worldwide equity trades have risen from around $300 billion to over $100,000 billion (Fig. la). This increase is equally staggering when calculated as a percentage of world income, rising from only 5% of GDP in 1975 to nearly 150% today (Fig. lb). Finally, as a proportion of market capitalisation, trades have increased from 25% to more than 100%, and even over 200% in some years (Fig. 1c). (5) It is also interesting to take the reverse of this turnover ratio to calculate the average investment horizon, which was 4 years in 1975, compared with 6 months today--this is of course an average as the so-called high-frequency traders have much shorter horizons, often far below a second.

These figures reveal the challenges involved in measuring growth in stock market activity. Firstly, as previously noted, defining the scope is key. In 2015, the WFE reported $115,000 billion in trades, whereas the World Bank (albeit working from the same sources) reported only $77 billion. Secondly, due to the significant variations in stock market prices, the value of shares traded from one year to the next can fluctuate wildly, as was seen when the dotcom bubble burst in 2000 and during the financial crisis. Finally, it should be noted that while we are only taking account here of trades performed on historical stock exchanges and BATS, there are dozens of alternative platforms in operation today.

Despite all this, the key finding remains the same: for around forty years, there was a sustained upward trend in stock market activity (the same could be said of the foreign exchange and derivatives market). The issue is not so much the reasons for this trend--it is clearly explained by advances in new information technologies, coupled with the liberalisation of the markets (6)--but rather how it has been assessed by the scholars. In the following section, we will set out different interpretations of this trend.

Interpretations of the Rise in Stock Trading

Academic literature has focused very little on the increase in stock market activity and what the "optimal" level should be. This lack of interest is symptomatic of the little importance attached to thinking on the purpose of stock markets. The rise in financial trading is commonly seen as the natural consequence of technological advances and a sure sign of economic growth. Many initiatives have been put in place worldwide since the 1980s to encourage stock trading. However, even mainstream economic analysis raises serious doubts over the utility and the rationality of such large volumes of trades.

From the Perspective of Financial Macroeconomics

In the 1990s, the World Bank largely gave voice to the idea that finance was a key determinant of growth, (7) a view that garnered an extensive consensus, at least among economists (Wachtel 2003). In this literature, an increase in equity trade volumes is often a key indicator in assessing financial growth. (8) Ross Levine was highly influential on this issue. In a widely cited article (Levine and Zervos 1998), he concludes that the relationship between the value of share trades (relative to GDP or market capitalisation) and economic growth is predictive. (9) In terms of methodology, the study is very basic (involving a cross-sectional analysis of 43 countries), far from what we would usually expect in publications of this standing, even by the standards of that time. It also turns out that the results are not robust, but are skewed by a handful of small countries (Zhu et al. 2004), and depends on the period (Rousseau and Wachtel 2011). In later articles (Rousseau and Wachtel 2000; Beck and Levine 2004), the panel dimension is taken into account, but the sample is still quite small. In addition, the technique used is unreliable and does not properly address endogeneity problems (Roodman 2009). In total, there are more than twenty econometric studies that attempt to estimate the impact of stock market activity on growth (see Table 1 in Appendix). By and large, these produce very mixed results: of the 211 estimates compiled by Valickova et al. (2015), only around half concluded that it has a significant effect. (10)

These studies have all come up against the same problems. Firstly, the total number of trades is a very rudimentary indicator of the way stock markets play their role in allocating capital. (11) There is also the long-standing problem of identification: financial and economic growth are largely concomitant, making it extremely difficult to identify causal relationships. Finally, there are serious doubts over the functional form of the relationship between trading volumes and growth.

An active stock market doubtless offers savers more investment opportunities and makes it easier to finance companies. However, should we infer from this that an increase in stock trading necessarily goes hand in hand with economic growth? The mistake lies in remaining implicitly wedded to a linear understanding of the relationship between finance and growth. Several recent articles (Cecchetti and Kharroubi 2012; Law and Singh 2014; Arcand et al. 2015) have empirically demonstrated that this relationship is non-monotonic and that there is a threshold above which financial development no longer has a positive impact on growth. (12) These articles focus primarily on the credit-to-GDP ratio, with a turning point of 100%.

There are several reasons for a nonlinear relationship, which is a very general form. Firstly, it can be explained by the decrease in marginal gains as we approach the productivity frontier (Aghion et al. 2005). Secondly, the financial sector is unlike other industries: A rapid rise in activity--which in itself is difficult to measure--does not necessarily mean that the financial sector is playing its role more effectively. The quality of financial services is more important than their quantity (Beck 2012). Finally, there is the question of the optimal size of the financial sector (Holmstrom and Tirole 1993) and the allocation of talent. Remarkably, this notion of poor allocation of talent had previously been discussed in James Tobin's work (1984), which now seems rather visionary: "Very little of the work done by the securities industry (...) has to do with the financing of real investment. (...) we are throwing more and more of our resources, including the cream of our youth, into financial activities remote from the production of goods and services (...) that generate high private rewards disproportionate to their social productivity". In the same article, Tobin also voiced concerns over the increase in stock trades: "What is clear is that very little of the work done by the securities industry, as gauged by the volume of market activity, has to do with the financing of real investment in any very direct way. Likewise, those markets have very little to do, in aggregate, with the translation of the saving of households into corporate business investment".

Since the financial crisis, the potential negative effect of financial growth seems to have been widely acknowledged. So far, most thinking has focused on the growth in intermediation activities, but there is no reason why it should not be applied to the growth in stock trades. The fact that investors can easily dispose of securities thanks to an active secondary market indisputably significantly benefits growth. This is particularly true when markets are relatively illiquid, but as they grow, there is every reason to believe that the marginal effect will decrease and even become negative.

From the Perspective of Portfolio Choice Theory and the Efficient Market Hypothesis

Portfolio choice theory was developed in the 1950s and 1960s and revolutionised our understanding of finance. It is based on a simple notion: the principle of diversification. Nowadays, it is universally recognised that, for the vast majority of investors, the best investment strategy is to have as diverse a portfolio as possible, which happens to be the market portfolio. At the same time, researchers were developing the theory of the informational market efficiency, which explains and postulates that it is extremely difficult to "beat the market". The bulk of what constitutes the modern financial theory, as is taught on finance courses and found in textbooks, clearly advocates "buy-and-hold" investment strategies. The optimal level of trades should therefore be very low. In many theoretical models, particularly those involving rational expectations, it should even tend towards zero, as with Milgrom and Stokey's famous "no-trade theorem" (1982).

This gives rise to one of the most challenging conundrums facing financial theory, which has been expertly described by Kenneth French. For this staunch advocate of market efficiency and main co-author of Eugene Fama, there is no reason why investors should waste billions in transaction fees to have their portfolio actively managed (French 2008; for a response, see Cochrane 2013). Dow and Gorton (1997) even develop a theoretical model in which portfolio managers have interests in performing trades purely to justify their high fees. (13)

Financial transactions have, in theory, three key purposes: arbitrage, liquidity requirement, and the arrival of news. (14) The question is therefore whether the increase in the value of share traded corresponds to growth of the same magnitude of these needs. Intuitively, the answer should be no: as the markets grow and information circulates freely, arbitrage opportunities are likely to decrease (15); there is no reason why liquidity requirements on the secondary market should not remain constant overall; and finally, it is difficult to see why there should be significantly more relevant information about companies, today than was the case ten or twenty years ago.

With regard to the increase in stock market activity, it is clearly very difficult to identify what relates to each of these factors. Much of this rise is doubtless linked to the increase in arbitrage and high-frequency trading. However, if we take institutional investors alone, we still see a sharp rise in activity and a fall in investment horizons (Bolton and Samama 2013; Cremers et al. 2017a).

Furthermore, there are very few empirical studies on the link between market efficiency and stock market activity. However, a recent study has shown that shares held by short-term investors are more likely to be subject to return anomalies (Cremers and Pareek 2015).

From the Perspective of Financial Market Microstructure

Financial market microstructure places special emphasis on liquidity, which can be defined as the propensity to easily and quickly buy or sell an asset on the market, without affecting its price too much. According to this approach, liquidity is a market's key attribute. However, research into microstructure stresses the idea that liquidity and trading volume should not be confused. Liquidity is in fact multidimensional. Most recent articles (Goyenkoa et al. 2009) use several measures to assess all these dimensions (e.g. transaction costs, depth and resilience) and many studies (Jones 2002; Johnson 2008) have shown that trading volume is a very poor indicator. To see this, we need only to observe that transaction costs have remained remarkably stable since the early 2000s, despite the fact that the number of trades has increased significantly during this period. (16)

Furthermore, recent experience has shown that despite the sharp rise in stock trading, there can still sometimes be a sudden lack of liquidity, as was the case during the "flash crash" in 2010. For several microstructure specialists, the primary reason for this crash was a liquidity problem (Easley et al. 2011). (17) This episode serves as a clear illustration of the problem of "ghost liquidity", where liquidity seems abundant, but proves to be lacking just when it is most needed. (18)

The increase in trades should also be viewed in relation to the fragmentation of trading platforms. The aim of the Markets in Financial Instruments Directive (MiFID) in Europe, as with the Regulation National Market System (Reg NMS) in the USA, was to bring down transaction costs to boost liquidity. In practice, its effect has been somewhat uncertain (Gresse 2010).

How can the effect of liquidity on the cost of capital for businesses be assessed? Most theoretical approaches take as starting point a simple valuation model, where the price of an asset is equal to the present value of its future cash flows, less transaction costs (Foucault, 2006). According to this approach, illiquidity, measured in terms of transaction costs, is automatically linked to a requirement for higher profitability. (19) This finding has also been shown to be true in practice (Amihud and Mendelson 1986; Brennan and Subrahmanyam 1996; Fang et al. 2009; etc.). This being the case, as was discussed above, more trades do not necessarily mean lower transaction costs and improved liquidity. If we look more specifically at the effect trading volume has on stock returns, while initial studies (Brennan et al. 1998) suggested a positive relationship, more recent articles have, on the contrary, concluded that it has a negative impact (Chordia and Swaminathan 2000). It also seems that it is not so much liquidity as liquidity risk that influences the cost of capital (Chordia et al. 2001). The phenomenon of ghost liquidity that has come with the increase in stock trades has therefore probably had a negative effect for businesses.

Analyses of the increase in trading volumes now inevitably lead to the question of the effect of high-frequency trading (HFT), which gives rise to three types of problems. Firstly, there are the potential effects on market volatility. In this regard, despite suspicions that HFT destabilises the markets, many empirical studies have concluded that it has a neutral or positive effect overall (Brogaard et al. 2014; Boehmer et al. 2014). However, once again the problem mainly arises in periods of crisis: High-frequency traders could be important contributors to liquidity during normal market conditions, but seems to consume more liquidity than they provide during periods of high volatility. Besides, despite the increase in trading volumes, liquidity crises are becoming increasingly frequent. (20)

The second problem linked to HFT concerns the lack of transparency that it creates. We have so far considered only the increase in trading volumes, but it should also be noted that the number of orders has increased faster still. In 1993, around 1000 orders per minute were sent to the US stock market for all types of securities. By 2001, this figure had risen to around 15,000, followed by 150,000 in 2005, before hitting the million in 2008. At its peak in August 2011, the number of orders per minute was exceeding 3 million (Angel et al. 2015). The order-to-trade ratio was stable slightly above one until the early 2000s, but subsequently rose sharply to over 30. This caused serious concerns over the potential for manipulation of stock market prices (through, for example, quote stuffing or spoofing).

The third problem is a matter of fairness. Investors now have different levels of access to information, either as a result of "co-location", or because public information is sometimes released to certain stakeholders first (Easley et al. 2015). However, trading on the stock markets requires a high degree of trust (Guiso et al. 2008). For around a decade, this has really been put to the test (from the subprime mortgage crisis to record trading losses, the Madoff scandal and market manipulation ...) and HFT has done much to fuel mistrust. The ongoing decline in the number of retail investors in Western countries is both worrying and symptomatic of this dwindling trust.

A survey of readers conducted by The Economist revealed that more than half disagreed with the idea that financial innovation would boost growth and only a third felt that finance benefits the economy, compared with half who thought the opposite. (21) Academics generally tend to play down this question or even ignore it completely. According to Luigi Zingales, "Academics' view of the benefits of finance vastly exceeds societal perception. This dissonance is at least partly explained by an under-appreciation by academia of how, without proper rules, finance can easily degenerate into a rent-seeking activity". He goes on: "It is very tempting for us academics to dismiss all these feelings as the expression of ignorant populism (...). This is a huge mistake. As finance academics, we should care deeply about the way the financial industry is perceived by society. Not so much because this affects our own reputation, but because there might be some truth in all these criticisms, truths we cannot see because we are too embedded in our own world. And even if we thought there was no truth, we should care about the effects that this reputation has in shaping regulation and government intervention in the financial industry. Last but not least, we should care because the positive role finance can play in society is very much dependent upon the public perception of our industry" (Zingales 2015).

From the Perspective of Corporate Finance

For many practitioners, the key to investing successfully lies in the investment horizon. Warren Buffet, one of the world's best-known investors, has championed long-term investments, advising others to "only buy something that you'd be perfectly happy to hold if the market shut down for 10 years". However, aside from their return for investors, the crucial question is what impact investment horizons have on companies' strategies. A survey of company directors conducted by McKinsey revealed the negative impact short-termism has on companies (Barton and Wiseman 2014). Two-thirds of respondents felt that pressure to achieve short-term results has increased in recent years and half had a strategic plan covering less than 3 years, despite three-quarters acknowledging that this period should be longer. More than 85% felt that a strategic plan covering a longer period would help their company to be more innovative and improve its financial performance.

Some theorists (Coffee 1991; Bhide 1993) have highlighted that liquidity comes at a hidden cost, arguing that on highly liquid markets, there are fewer incentives for shareholders to exercise control over the companies in which they have invested. The general idea is simple. To borrow from Albert O. Hirschman: the easier the exit, the weaker the incentives to make your voice heard. It would appear that financial liberalisation has above all favoured liquidity to the detriment of investors who are actively involved in corporate governance.

Many works on corporate finance have confirmed these ideas and have shown the positive impact of having long-term shareholders. In particular, from an empirical perspective, investor short-sightedness (which is measured in terms of a large proportion of shareholders with a high turnover ratio) is associated with shorttermist behaviours that are reflected in a reduction in research and development (Bushee 1998; Aghion et al. 2013; Cremers et al. 2017b), poor assessment of investments (Derrien et al. 2013), an strengthening of market shocks (Cella et al. 2013) or a tendency to take more risks (Garel and Petit-Romec 2017). (22)

This may explain in part the vogue for private equity more suitable to accompany innovating companies. Empirically, it would appear that listed companies invest less than similar unlisted companies (Asker et al. 2015). Moreover, we observe that the number of listed companies in the USA halved between 1997 and 2012 (Doidge et al. 2017; Kahle and Stulz 2017). This idea is by no means new: as far back as 1989, Michael Jenssen was predicting an "eclipse of the public corporation" (Jensen 1989).

From the Perspective of Behavioural Finance

Recent research into behavioural finance has also made it possible to assess the import of an ever-greater volume of trades from a new perspective. Historically, the question of the relevance of trades has hardly been addressed in the literature: individuals trade because they see an interest in doing so. By questioning the premise of the rationality of this increase, we can examine the merits of certain trades. Much research has also highlighted the importance of psychological biases in understanding the rise in trades.

Terence Odean places special emphasis on over-confidence. Such biases could be reflected in excessive risk-taking and greater trading volumes. By comparing the net average profits of investors classed as more or less active, such research shows that there are too many trades, insofar as they result in a lower net profit (Odean 1999; Barber and Odean 2000; Barber et al. 2008). (23) This excessive confidence is also closely linked with gender: men perform many more trades than women, which once again leads to losses (Barber and Odean 2001). The same is true of the least experienced investors (Christoffersen and Sarkissian 2011).

Moreover, studies in behavioural finance have identified several "anomalies" in stock volume. For instance, the value of trades might depend on the location of the firms' headquarter (Froot and Dabora 1999) or the alphabetical order of the firms' name (Itzkowitz et al. 2015). While it is not the purpose of these papers, they provide clear evidence suggesting that there is too much trading in some cases.

Conclusion

"It is as wrong to sin by excess as to sin by default" (24)

According to Lord Turner, the former chairman of the Financial Services Authority (FSA), the financial sector has grown "beyond a socially reasonable size". In academia, several leading academics similarly feel that there is too much finance, too many fees and too many trades. At the same time as stock exchange trades have been increasing, the number of shareholders in Western countries has been falling, as has the number of listed companies in the USA. The gap is widening between the apathy of the primary market and the hyperactivity of the secondary market

This article took as its starting point that financial activity is only meaningful if it serves the economy. To avoid any misunderstanding: stock markets offer investors liquidity, without which they would be extremely reluctant to invest in ambitious long-term projects. The question here is not the trades themselves, but rather the potentially excessive number of them. The upward trend in trades raises many concerns as it could be reflected in higher costs, poorer corporate governance and greater instability. It could also lead to greater mistrust of the markets.

How, then, can we limit this increase in stock trades? Among the solutions, there is the idea of putting a few grains of sand in the overly well-greased wheels of global finance, namely by introducing a financial transaction tax (FTT). By increasing transaction costs, such a tax could help to reduce trading volumes. (25) Although such a tax could hardly be expected to separate the wheat (useful trades) from the chaff (those that increase instability), it would at least help to curb the upward trend. Empirical studies conducted in countries where such FTTs are (or have been) in place show that they have a small negative impact on trading volumes, although they have any harmful impact on market liquidity or volatility (Capelle-Blancard and Havrylchyk 2016; Capelle-Blancard 2017; Capelle-Blancard and Poulain 2017).

Moreover, order-matching process could be reviewed. The general idea would be to ensure that competition relates to price, and not the speed with which a trade is executed. This would help to eliminate economic rents, improve liquidity and curb the technological arms race. Two measures are generally proposed: (i) replace continuous listing with a series of very frequent fixings, for example, every minute (Budish et al. 2015); (ii) deliberately introduce a very short but randomised delay when sending orders to reduce the advantage associated with speed. (26) The actual framework for achieving these objectives is to foster the competition between platforms to give rise to new solutions of "slow markets" that could respond to investors' needs. Some attempts have been made in this direction, but they have had to make a point. The market failures outlined in this article argue in favour of public intervention.

Ultimately, the issue of trading volumes cannot be ignored. There remain many question marks over both its positive and negative effects. Either way, the concerns to which it gives rise are valid. To curb the upward trend, a comprehensive review of the way in which the markets are organised seems necessary. To do this, we must examine the purpose of the stock markets, as failure to do so risks fuelling greater mistrust of the financial sector.

Acknowledgements I am grateful to Jezabel Couppey-Soubeyran, Jerome Glachant, Christophe Moussu, Arthur Petit-Romec and the anonymous referee for stimulating discussions and suggestions, as well as Published online: 14 December 2017

Appendix
Table 1 A summary of studies on the effect of the
volume of stock exchange trades on growth

Study                         Sample          Period

Atje and Jovanovic (1993)     40 countries    1980-1988

Harris (1997)

Levine and Zervos (1998)      43 countries    1976-1993

Rousseau and Wachtel (2000)   47 countries    1966-1995

Arestis et al. (2001)         5 countries

Manning (2003)                42 countries    1976-1993

Minier (2003)                 42 countries    1976-1993

Zhu et al. (2004)

Beck and Levine (2004)        40 countries    1976-1998

Rioja and Valev (2004)        74 countries    1980-1995

Liu and Hsu (2006)            1 country       1981-2001

Lee and Shen (2006)           48 countries    1976-2001

Tang (2006)                   14 countries    1981-2000

Naceur and Ghazouani (2007)   11 countries    1979-2003

Saci et al. (2009)            30 countries    1988-2001

Yay and Oktayer (2009)        21 countries    1975-2006

Yu et al. (2012)              7 countries     1980-2009

Chakraborty (2010)            1 country       1993-2005

Shen et al. (2011)            46 countries    1976-2005

Compton and Giedeman (2011)   90 countries    1970-2004

Arcand et al. (2015)          126 countries   1960-2010

Study                         Indicator          Estimation

Atje and Jovanovic (1993)     ST/GDP             OLS

Harris (1997)

Levine and Zervos (1998)      ST/GDP, Turnover   OLS

Rousseau and Wachtel (2000)   ST/GDP

Arestis et al. (2001)                            VECM

Manning (2003)                ST/GDP, Turnover   IV

Minier (2003)                 Turnover           OLS

Zhu et al. (2004)             ST/GDP

Beck and Levine (2004)        Turnover           OLS, GMM

Rioja and Valev (2004)        ST/GDP, Turnover

Liu and Hsu (2006)            Turnover           GMM

Lee and Shen (2006)           ST/GDP, Turnover   Panel

Tang (2006)                   ST/GDP, Turnover   OLS

Naceur and Ghazouani (2007)   ST/GDP, Turnover   GMM

Saci et al. (2009)            ST/GDP, Turnover   GMM

Yay and Oktayer (2009)        Turnover           GMM

Yu et al. (2012)              ST/GDP             Panel

Chakraborty (2010)            Turnover           OLS

Shen et al. (2011)            ST/GDP, Turnover   OLS

Compton and Giedeman (2011)   Turnover           OLS, GMM

Arcand et al. (2015)          Turnover           OLS, GMM

Study                         Effect          Comments

Atje and Jovanovic (1993)     +

Harris (1997)                 Insignificant   Replication of
                                              Atje-Jovanovic

Levine and Zervos (1998)      +

Rousseau and Wachtel (2000)   +

Arestis et al. (2001)         Insignificant

Manning (2003)                ?

Minier (2003)                 +

Zhu et al. (2004)             Insignificant   Replication of
                                              Levine-Zervos

Beck and Levine (2004)        +

Rioja and Valev (2004)        +, ?

Liu and Hsu (2006)            Insignificant

Lee and Shen (2006)           ?

Tang (2006)                   Insignificant

Naceur and Ghazouani (2007)   Insignificant

Saci et al. (2009)            +

Yay and Oktayer (2009)        +

Yu et al. (2012)              Insignificant

Chakraborty (2010)            Insignificant

Shen et al. (2011)            Insignificant

Compton and Giedeman (2011)   Insignificant

Arcand et al. (2015)          +               Nonlinearity test


Paul Wachtel for his valuable comments and support.

https://doi.org/10.1057/s41294-017-0049-x

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(1) Universite Paris 1 Pantheon-Sorbonne (Centre d'Economie de la Sorbonne), Labex ReFi (Financial Regulation Lab) & Paris School of Business, Paris, France

(1) See also Cecchetti and Kharroubi (2012) and Law and Singh (2014).

(2) The data come primarily from the World Bank, but in some cases have been supplemented with figures for alternative platforms for the recent period (cf. Section 2).

(3) For example, Euronext data include trades performed in Amsterdam, Brussels, Lisbon and Paris altogether, while those for LSE Group (which, it should be noted, is not a member), cover trades in London and Milan.

(4) One solution could be to use data provided by BATS or Fidessa.

(5) Market capitalisation has increased from USD 1200 billion (20% of GDP) in 1975 to nearly USD 70,000 billion (100% of GDP) in 2015.

(6) We are only commenting here on the increase in stock exchange trades. The growth of the financial sector can be explained more generally by the ageing population and increase in world savings (related to living standards improvements and reinvestment of income by exporting countries), as well as the undertaxation of the financial sector and the guarantees from which it benefits, which could be seen as indirect subsidies.

(7) The World Bank often maintains a dual and crude vision of financial growth. For example, the following statement can even now be found in the metadata that accompany the series on market capitalisation: "Both banking systems and stock markets enhance growth, the main factor in poverty reduction. At low levels of economic development commercial banks tend to dominate the financial system, while at higher levels domestic stock markets tend to become more active and efficient relative to domestic banks."

(8) In their meta-analysis of the link between finance and growth. Valickova et al. (2015) found that, of the 67 studies analysed, 15% of the estimates used the value of stock exchange trades (relative to GDP or market capitalisation) as an indicator of financial growth.

(9) Atje and Jovanovic (1993) had previously adopted a similar approach and concluded that there was a positive link, but their findings were shown to be invalid by Harris (1997).

(10) The main studies are set out in the appendix.

(11) Beck, Thorsten, Finance and Growth: Lessons from the literature and the recent crisis, July (2012): "the measures of financial depth and intermediation the literature has been using might be simply too crude to capture quality improvements at high levels of financial development". See also CapelleBlancard and Labonne (2016) for a discussion of the usual indicators of financial growth.

(12) According to Valickova et al. (2015), 22% of estimates of the link between finance and growth consider a potential non-linear nature relationship. See also Beck et al. (2014).

(13) The idea underpinning this is that investors cannot distinguish if portfolio manager is "actively doing nothing" or "simply doing nothing".

(14) Here, we consider the "ultimate" reasons and put aside the transactions related to market making and the supply of liquidity carried out by the financial intermediaries.

(15) Foucault et al. (2017) show empirically that the automation of trades on the foreign exchange market has led to a reduction in the duration of arbitrage trades (of around 6 ms), but has also brought with it a 3-6% increase in transaction costs (bid-ask spread). Cf. also Budish et al. (2015).

(16) According to Angel et al. (2015), the average bid-ask spread on the US markets (NYSE and Nasdaq) is in the region of $2.

(17) "Our analysis shows that the liquidity problem was slowly developing in the hours and days before the collapse. Just prior to the inauspicious trade, volume was high and unbalanced, but liquidity was low."

(18) For a macroeconomic approach to the effects of liquidity on this cycle, see Naes et al. (2011).

(19) However, this kind of approach often assumed that the investor's investment horizon is fixed. If we reduce the investment horizon by increasing the number of trades, we get the opposite effect to lowering transaction costs.

(20) "For a period of time, the Flash Crash seemed like an isolated event. However, flash events in the U.S. Treasury markets on October 15, 2014, reignited discussion about the vulnerability of liquid automated markets to severe dislocations and disruptive trading. (...) such systemic events (...) may be a feature of the 'new normal'." (Kirilenko et al. 2017).

(21) In France, a survey of 18 to 35-year-olds showed that out of more than 200,000 respondents, 90% of this generation believe that finance runs the world, http://generation- what.francetv.fr.

(22) For an analysis of the short-termism argument, see Roe (2014).

(23) "This paper takes a first step towards demonstrating that overall trading volume in equity markets is excessive by showing that it is excessive for a particular group of investors: those with discount brokerage accounts. These investors trade excessively in the sense that their returns are, on average, reduced through trading" (Odean 1999).

(24) Attributed to Confucius.

(25) It should also be noted that rather than penalising short-term investors, one approach could be to reward long-term investors with "loyalty shares" (Bolton and Samama 2013).

Gunther Capelle-Blancard (1)

[mail] Gunther Capelle-Blancard

gunther.capelle-blancard@univ-parisl.fr

Caption: Fig. 1 Changes in global stock trades since 1975. a in $ billion, b as a % of GDP, c as a % of market capitalisation (turnover ratio). Source: WDI (World Bank), WFE and Market Share Report (Thomson Reuters) data. Author's calculation. WDI data only consider electronic order book trades and domestic shares (i.e. excluding OTC or dark pool trades)
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