Did the new French tax on financial transactions influence trading volumes, price levels and/or volatility

on the taxed market segment? - A trend analysis -

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Contents

1. INTRODUCTION .................................................................................................... 2

2. THE APPROACHES USED AND MARKETS ANALYSED ................................. 3

3. EVOLUTION OF TRADING VOLUMES ............................................................... 5

3.1 Trends in trading volumes on the taxed French market ................................... 6

3.2 Trends in trading volumes on untaxed French, German and Italian markets ... 9

4. EVOLUTION OF PRICE VOLATILITY ............................................................... 12

5. EVOLUTION OF PRICE LEVELS ........................................................................ 16

6. CONCLUSIONS ..................................................................................................... 19

ANNEX 1: MARKETS ANALYSED – POPULATION OF COMPANIES .................. 21

ANNEX 2: TRADING VOLUME .................................................................................. 27

ANNEX 3: PRICE VOLATILITY .................................................................................. 28

ANNEX 4: PRICE VARIATION ................................................................................... 29

ANNEX 5: MONTH-ON-MONTH (MOM) % CHANGE IN VOLUMES .................... 30

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1. INTRODUCTION

On 1 August 2012, France introduced a national tax on certain financial transactions with French shares and certain derivatives as well as cancelled orders in the context of 'high-frequency-trading'. The tax on transactions was applied in 2012 to the trading in the shares of 108 companies with market capitalisation in excess of EUR 1 bn. (large caps). This paper attempts to investigate the possible impacts of this tax on the French stock market, notably with respect to its potential impacts on

• trading volumes (liquidity), • share prices (cost of capital), and • volatility (market efficiency),

as economic analysis typically claims that a tax on financial transactions might have an effect on these parameters with the result that taxed markets might be both less efficient and trigger higher cost of capital for investors aiming at raising capital with the help of issuing shares.1 Box 1: The main characteristics of the French tax on financial transactions2 The transaction tax (0.2% of the purchase price) is due on a transfer of ownership of shares of listed companies established in France, and with a capitalisation of at least €1billion at 1 January of the calendar year in which the tax is due. The tax is to be paid by the purchaser. Tax collector is the financial intermediary if present; otherwise it is the purchaser himself. Where the Central Securities Depository (CSD) holding the issuance account is in France, securities dealers and their clients must (or in some cases may opt to) submit FTT declarations and tax payments to this CSD, Euroclear, who submits them to the tax authorities. The tax applies to net transactions (change in ownership at the end of a trading day) and is expected to have generated €199million in 2012, €690 million in 2013 and is expected to generate €702million in 2014. This corresponds to 0.03% of France’s GDP. The tax on cancelled (or modified) high-frequency trading orders (0.01% of the value of the orders) applies in case the ratio of cancelled orders to all orders during one trading day exceeds 80%. The tax is payable by each financial intermediary (except if undertaken in the context of market making) established in France and using automated algorithm trading characterised by the successive sending of purchase or selling orders and the modification or cancelation of the initial trading orders, respectively, within a time period of no more than half a second.

1 An extensive literature review on the effects of securities transactions taxes and financial transactions taxes,

in general, was included in the initial impact assessment accompanying the Proposal for a Council Directive on a common system of financial transaction tax and amending Directive 2008/7/EC (SEC(2011) 1102 final).

2 For more details about the legal provisions, see Art. 235 ter ZD bis of the French general tax code, as amended by Law no. 2013-1279 of 29 December 2013 and supplemented by Decree no. 2012-957 of 6 August 2012) .

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The reasons assumed to trigger these effects can be found in market actors reacting to increases in transaction costs (in this case: the tax), and, thus, lower net (after tax) rates of return. Indeed, traders might factor in the tax in their bids in so far as potential purchasers might want to pay less so as to make up the difference between the pre-tax and the after-tax price.3 On the other hand, potential sellers might not accept such a decline in prices and – at the end of the day – the outcome for price levels will depend on whether the market is characterised as being a seller or a buyer market. In any case, trading volumes should go down as some marginal buyers and sellers might want to wait for better deals before they actually engage in a trade. The purpose of this paper is to analyse to what extent introducing the tax could have had a lasting effect on trading volumes, price levels and volatility in the taxed market segment. Thus, for this analysis it is less relevant on how trends (potentially) changed at or around the date of the introduction of the tax but on how trends (potentially) changed in the longer run. Therefore, the paper analyses trends in the above parameters in the 12-months period before the introduction with the respective trends in the 6-months period after the introduction of the tax, as it is assumed that a new “equilibrium” with respect to trading volumes, share prices and volatility should have been achieved after such a period. To this extent, it differs from other analyses undertaken on this subject4 that primarily aim at measuring the short-term impact (so-called “event analysis”) of the tax. In terms of methodology, in all these papers the approach to measuring the impact on liquidity is substantially different from the simple approach followed by the current paper, focusing on the bid-ask spread instead of other indicators.

2. THE APPROACHES USED AND MARKETS ANALYSED

An economically robust analysis trying to identify and measure effects of the tax, i.e. causality instead of correlation would, in principle, require regression analyses comprising all significant parameters potentially having an impact in order to separate the effects of the tax from the effects of all the other factors. Such analysis would require quantifiable information on the development of all the other explanatory parameters over time. Moreover, given the high number of potential explanatory factors it would require longer time series so as to arrive at statistically significant coefficients (“difference in difference” method). Against this background, a first analysis could be based on two approaches:

• one can compare evolutions on the market segment affected by the tax before the tax was introduced with trends after the tax was introduced and/or

3 See e.g. Matheson, Th. (2011): Taxing financial transactions: Issues and evidence, IMF working paper

WP/11/54. http://www.imf.org/external/pubs/ft/wp/2011/wp1154.pdf 4 See e.g.

• Credit Suisse/Trading Strategy (2012) – Impact of French financial transaction tax, http://static.tijd.be/upload/french_FTT-762481.pdf

• Mayer, S., Wagener, M. and Weinhardt, C. (2013) – Politically motivated taxes in the financial markets: the case of the French financial transaction tax, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2211748.

• Colliard, J-E., Hoffmann, P. (2013) – Evidence on taxing transactions in modern markets, http://www.rsm.nl/fileadmin/home/Department_of_Finance__VG5_/LQ2013/Jean-Edouard_Colliard_Peter_Hoffmann.pdf.

• Haferkorn, M., Zimmermann, K. (2013) – Securities transaction tax and market quality – the case of France, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2229221.

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• one can compare the evolutions before and after the introduction of the tax on the taxed market with evolutions on other but untaxed markets which could serve the role of potential counterfactuals.

Both approaches are applied in this note. For the second approach a comparison of the evolutions in terms of trading volume, volatility and change in prices is analysed for the following six market segments, of which the first two have been exposed to the tax while the other four have not:

• 108 large French companies for which the trading in their shares is subject to the tax, • 35 large French companies (headquartered in France) being part of the French CAC40

index for which the trading in their shares is subject to the tax5; • 5 large French companies (not headquartered in France) being part of the French

CAC40 index for which the trading in their shares is not subject to the tax6; • 33 French companies with medium-sized market capitalisation (mid-caps) for which

the trading in their shares is not subject to the tax; • 30 large German companies (DAX) for which the trading in their shares is not subject

to the tax; • 40 large Italian companies (MIB) for which the trading in their shares is not subject to

the tax. These four latter markets serve the role of control group and potential counterfactuals. As two control markets (CAC(40)5 and mid-cap French shares) are located in the same country, it might also be possible to isolate domestic influences, other than the introduction of the tax (such as the outcome of the presidential and parliamentary elections in May and in June 2012), or the tax on cancelled orders. Annex 1 lists the companies forming part of the different samples analysed7. The analysis covers the period August 2011 to February 2013, i.e. it spans over the twelve-month period preceding the introduction of the tax and the six-month period following the introduction of the tax. This should allow detecting a break in trends in the evolution of the taxed French stock after the introduction of FTT on 1 August 2012, be it volumes traded, volatility or prices themselves. Annexes 2 to 5 present the methodologies applied. When trying to also analyse these parameters with respect to sub-populations of markets, it differentiates between trends for companies with a high capitalisation for which markets are typically more liquid and that are also affected by high-frequency algorithm trading and the availability of derivatives and for companies with a limited degree of capitalisation. This is on the one hand done with the help of weighting the shares with the respective market capitalisation. On the other hand, a specific subpopulation of large companies forming the

5 Please note that the trading in shares of five companies forming part of CAC40 is not taxed as these

companies are not having their headquarters in France. 6 These five companies are ArcelorMittal, EADS, Gemalto, Solvay and STMicroelectronics. Although they

form part of CAC40 they are headquartered in the Netherlands, in Belgium or in Luxemburg. Their capital represents about10x % of the total capitalisation of CAC40 companies. While the trading in these shares is not subject to the tax, the provisions as regards cancelled orders also apply to orders on French stock exchanges on the shares of these companies.

7 Data on trading volumes, prices etc. was downloaded from the websites of NYSE Euronext, London Stock Exchange Group and Deutsche Börse.

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taxed 35 companies of the CAC 40 index has been established and analysed as the structure of this subpopulation might be closer to the structure of the DAX and MIB market segments. This note does not analyse the effects of the availability of substitution possibilities. It focusses only on the evolution of shares of selected companies on the regulated markets of the three countries and not on other markets such as multilateral trading facilities. The analysis undertaken is a graphical plot analysis which is intuitively understood also by the less mathematically-acquainted reader while the other studies aim at detecting statistically (in) significant differences. While this analysis has a rather broad approach as it uses four alternative untaxed markets as potential counterfactuals and analyses different subgroups of the taxed market segment it (as the other studies) is subject to some inherent limitations. The most important is that it can be expected that the effects of the tax might be entirely 'overshadowed' by more decisive factors like the economic cycle at the sectoral, national or global level, business trends, competitive situations of the companies, changes in the tightness of monetary policy, domestic and international policy factors such as changes in governments etc. This limitation is also characterising the other studies that aim at measuring causality by identifying statistically (in) significant changes in trends within or across markets.

3. EVOLUTION OF TRADING VOLUMES

An FTT taxing the purchase of shares could negatively impact on liquidity mainly for two reasons:

• some marginal investors might withdraw from the market in case they cannot pass through these additional cost to the sellers or their clients in case the rate of return after taxes is no longer attractive or even negative, and

• some investors might engage in substitution activities by purchasing untaxed products such as derivatives.

This decline in trading volumes could then, in turn, cause higher volatility, reduce the security of getting a deal at a given price or increase the bid-ask spread. The trends in traded volumes of the shares provide a measure for the potential change in liquidity over time. Most interesting in the context of the note is to what extent one can identify a break in the trend towards a more negative / less positive slope of the trend curve as expressed by its regression function, and as compared to other markets not being exposed to the tax. The trends in traded volumes of shares were calculated using two different approaches that have actually provided similar results:

• in the first approach, the number of shares traded was taken as such and not weighted at all. The outcome is presented in Graphs 1 and 2, 1c and 2c;

• in the second approach, the number of shares traded was weighted with the share of the capital of the individual company in the whole sample at a given point in time (i.e. 1 January 2012) so that the trading in shares of highly-capitalised companies gets more weight than the trading of shares in less-capitalised companies. The outcome of this approach is presented in Graphs 1b and 2b.

The formulas used (see Annex 2) practically aggregate at the level of the whole sample monthly trading volumes (first approach) and weighted monthly averages of trading volumes

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(second approach), respectively. The weighting has been done according to the individual company capitalisation ratio against the capitalisation of the whole sample; this is why in the second approach the result had to be multiplied by the number of companies in the sample. The data has been “normalised” in both cases (i.e. adjusted to a “normal” month of 22 trading days). The trends for the different markets analysed were calculated by simply looking at the number of shares traded per day and normalising the trading days across all months in the observation period. So, trading volumes are not influenced by price fluctuations or the size of individual transactions. 3.1 Trends in trading volumes on the taxed French market

From the results for the 108 taxed French shares (see graph 1) one can first depict that the trend in the volume of the shares in the period pre-dating the introduction of the tax had been rather unstable, but in general downward: a period of steady decline until the end of 2011 was followed by a temporary recovery in volumes traded until April 2012 before volumes declined again. Graph 1: Trading volumes on the taxed French market segment

- August 2011 to February 2013 -

Second, one can witness a sharp fall in trading volumes in August, the month of the introduction of the tax, and a recovery of traded volumes immediately thereafter (indicating that the month of August might have seen an “undershooting” of trading volumes, potentially caused by uncertainty surrounding the hasty introduction of the tax). In principle, one would have expected a further decline, as purchasing such shares should have been considered as being less attractive than before the introduction of the tax. However, there seems to have been a reversal in trend figures with a measurable positively sloped change in the trend line

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indicating that liquidity (as measured by trading volumes) on the taxed market has even recovered after the temporary undershooting in August. However, this gradual recovery could not completely offset the effects of the structural break that occurred in August 2012, i.e. the endpoint of the trend line for the period 8/2012 to 2/2013 was still 11% below the endpoint of the trend line 8/2011 to 7/2012 if extrapolated to 2/2013, although it was already above the end-point of the trend-line August 2011 to February 2013 (see graph 1). When one weighs the volumes with the capitalisation of the companies one can observe that the slope of the trend figures for both measures (non-weighed and weighted) has been rather similar before the introduction of the tax while it diverges for the period after this event (see graph 1b), i.e. while the non-weighed trading volumes show an improvement in liquidity (as measured by trading volumes), the weighted trading volumes show a continuation of the decline in liquidity witnessed already before the introduction of the tax. Also, the sharp decline of trading volumes witnessed in summer 2012 started already in July and was much more pronounced. This can be taken as an indication that just before and notably after the introduction of the tax the trading volumes of the “smallest” of the 108 companies (as measured by their capitalisation) had performed rather dynamically while the liquidity for the market segment of larger companies suffered a further set-back. In the aggregate, the trend line after the introduction of the tax exhibited relatively the same negative slope as it exhibited before the introduction of the tax for the weighted index while the slope turned positive for the non-weighted index. Graph 1b: Trading volumes on the taxed French market segment

- August 2011 to February 2013 (capitalisation-weighted)

This invites for the conclusion that the trading volumes of the “larger” of the 108 companies performed much less dynamically than those of the entire sample. This hypothesis is confirmed if one only looks at the change in trends for the 35 companies with the highest

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capitalisation and forming part of CAC 40 for which the purchase of shares is taxed (see graph 1c as compared to graph 1). Thus, while trading volumes for the entire market segment of taxed shares (108 FR) experienced a monthly decline on average by about 1.4% over the entire observation period they declined on average by 2.5% for the CAC 40 (35) market segment. The gradual recovery in trading volumes as of January 2013 could not offset the effects of the structural break that occurred in July and August 2012, i.e. the endpoint of the trend line for the period 8/2012 to 2/2013 was 28.5% below the endpoint of the trend line 8/2011 to 7/2012 if extrapolated to 2/2013, and still some 2% below the long-term trend. Graph 1c: Trading volumes on the taxed CAC40 (35) French market segment

- August 2011 to February 2013

There might be two narratives for explaining this impact on the trading in the shares of larger companies as compared to the trading in the shares of smaller companies of the sample in case one wanted to turn the observable correlation into a tax-induced causality:

• One reason might be that some of the traders that were not really interested in the shares themselves but in exploiting price volatility of the shares actually traded might have shifted their focus to investing in (untaxed) derivatives the values of which would correlate with the price changes of the underlying shares, or in untaxed French shares considered as close substitutes, such as CAC40(5) or French mid-cap companies (see next section).

• Another reason might have been that together with the tax on the purchase of shares there was also a tax on the cancelled orders of high-frequency algorithm traders imposed and some of the high-frequency algorithm trading might have been discouraged by this tax8.

8 There is nevertheless an indication that the tax on the cancelled orders did not yield any revenues in 2012 –

see the Information report on the tax measures comprised by the law on public finance (2013) – http://www.assemblee-nationale.fr/14/rap-info/i1328.asp. It is possible that the threshold was set too high or

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Indeed, both high-frequency algorithm traders as well as derivatives products are more prominent on markets for liquid shares of highly-capitalised companies than on markets for less liquid shares of smaller companies. So, the effects on these actors should have been more tangible for the very liquid share market of the bigger companies as compared to the less liquid markets of the smaller companies. 3.2 Trends in trading volumes on untaxed French, German and Italian markets Another approach for trying to find out in how far the introduction of the tax could have had an impact on trading volumes and, thus, on the liquidity of the taxed market segment would be to compare the trends before and after the introduction of the tax on 1 August 2012 on the taxed market segment with the trends before and after that date on other, non-taxed market segments. This was done with the help of four non-taxed markets (CAC(40)5, mid-cap French, the German and the Italian market). The actual average month-on-month percentage changes9 for the different markets and the different sub-periods are presented in Table 1; the methodology used is presented in Annex 5. This “difference in difference” comparison shows that for the six months after the introduction of the French FTT

• two (untaxed) markets – 33 FR and 40 IT - showed on average a very positive development in trading volumes in excess of 8% growth per month,

• one (taxed) market – 108 FR – experienced subdued but still positive growth in trading volumes,

• three markets, CAC40(35), CAC40(5) and 30 DE (of which only the first was taxed) experienced a continuation of shrinking trading volumes already experienced in the first observation period.

Table 1 Average month-on-month (MOM) percentage changes

Segment Period

108 FR 33 FR CAC40 (35)

CAC40 (5)

30 DE 40 IT

08/2011-07/2012 -0.3% -2.5% -0.6% -2.8% -3.2% 2.5% 08/2012-02/2013 1.3% 9.2% -3.3% -0.7% -1.1% 8.5% 08/2011-02/2013 -1.4% -4.9% -2.5% -1.7% -3.0% 0.9% Also, there was only one market (segment) – 40 IT – that was for the entire period August 2011 to February 2013 characterised by an overall (modest) increase in trading volumes. Graph 2 shows that on three out of the six market segments exhibited (108 FR, 33 FR and 40 IT) there was an absolute improvement (the negative slope turned positive) in the liquidity performance trend as measured by trends in trading volumes after 1 August 2012. On the untaxed German market and the French CAC40(5) market segment this improvement was only relative (i.e. the decrease in trading volumes slowed down compared to the period before August 2012). For the taxed CAC40(35) market segment the decline continued even at a higher rate (minus 2.5% m.o.m. as compared to minus 0.6% m.o.m.).

that traders changed their behavior in order to stay below the taxation threshold for cancelled orders, or that they simply relocated.

9 Note that there are for instance 18 months-on-month evolutions for the 19 months in the entire period.

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Analysing the trends over the entire observation period of 18 months provides additional insights: while the four market segments in France and the German market experienced negative trends, the Italian market was characterised by a positive trend. It has to be noted however, that the decline in trading volumes on the German market had been the most pronounced (on average -3.2% per month) until August 2012 while the Italian market showed even an absolute improvement in trading volume trends (+2.5% per month). It is also worthwhile noting in this context that the (changing) slopes on the taxed and untaxed four French market segments as well as on the Italian market have to a large extent being influenced by a structural break happening in July/August 2012, where all these markets saw a sharp fall in trading volumes, followed by a more or less dynamic bouncing back in September 2012. Graph 2: Trading volumes on different markets - August 2011 to February 2013

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Of all six market segments analysed in this paper only the small CAC40(5) market segment, i.e. the shares of the companies traded on the Paris stock exchange but falling outside the scope of the French tax because the companies are headquartered outside France, showed a performance over the entire period (dotted black line) that outperformed the performance before August 2012 (dotted red line). One reason for this might be that there had been some movement of trading volumes away from the taxed CAC40(35) to the untaxed CAC40(5) market segment as this market segment was considered by market participants as being an untaxed close substitute. When one now looks at size-determined sub-populations of the analysed markets by giving more/less weight to the shares of large/small companies (as measured by their capitalisation) one can note (see graph 2b) that this weighting had hardly an effect on the performance indicator of the (untaxed) German market, i.e. the “recovery” of the liquidity performance after August 2012 on the German market did not really differ for the weighted and the non-weighted index. Neither did it have a significant effect on the untaxed French market, while it had an effect on both the (taxed) French and the untaxed Italian markets. One other interesting finding of measuring the liquidity performance (as measured by the evolution of the capitalisation-weighted trading volumes) of the four markets (graph 2b) is that the liquidity performance of shares of the larger companies has been much more subdued for both the period before and the period after August 2012. In the period before August 2012 only in the Italian case, the liquidity performance as visible when comparing the IT charts of graphs 2 and 2bis was on a positive trend. Trading in the shares of the very large Italian companies had been on a declining trend in the entire observation period, but on a less pronounced ascending trend before August 2012 than after this cut-off date. Graph 2b: Trading volumes on different markets

- August 2011 to February 2013 (capitalisation-weighted)

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One explanation for arriving at different trends for different markets when comparing un-weighted and weighted trading volumes could be that the homogeneity of the different analysed markets is different. The samples of the 30 German companies and the 33 mid-cap French companies are actually rather homogenous with respect to the capitalisation of the companies covered as compared to the taxed French and Italian samples.10 When comparing the more homogenous (un-weighted and weighted, respectively) French CAC40(35) market segment with the rather homogenous (un-weighted and weighted, respectively) German DAX market segment one can see that their performance is in so far similar as in both market segments trading volumes continue their downward trend also after August 2012. However, in the French CAC40(35) market segment this downward trend seems to have been more pronounced after the introduction of the tax than in Germany, with average declines per month of -3.3% and -1.1%, respectively (see graph 2c). This might, however, partly be explained by the developments before August 2012, where the trend in Germany had been much more negative than in France (CAC40(35)), with trading volumes declining by about 3.2% and 0.6%, respectively. Graph 2c: Trading volumes on CAC 40 (35) and DAX 30

- August 2011 to February 2013

4. EVOLUTION OF PRICE VOLATILITY11

It is often claimed that the more liquid a market is the less volatile its prices will be. Arguing along these lines would also – at least implicitly - mean that the more liquid a market is the better. A negative "shock" on liquidity would, thus, have a measurable positive knock-on effect on price volatility, i.e. price volatility could be expected to increase. Others argue that liquidity (as measured by trading volumes) is not an end in itself but a means to an end, the end itself being the absence of price volatility beyond acceptable levels

10 Of the 30 German companies covered, only 10 had a capitalisation of less than EUR 10 bn., and each of

these latter had a capitalisation of at least EUR 5 bn. In contrast, in the French and in the Italian sample two third of all companies had a capitalisation of below EUR 10 bn., often as little as EUR 1 bn. to EUR 3 bn.

11 This section looks at the interaction between volatility and liquidity as approximated by trading volumes and trading volumes in relation to market capitalisation. To this extent, it does neglect other dimensions of liquidity, such as market depth or bid-ask spread size.

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also in the presence of large orders, together with a high likelihood of getting also larger orders settled in a timely manner, and without having a measurable impact on prices. This latter school of thought would then assume that beyond a threshold additional liquidity does not really contribute to less price volatility and vice versa, i.e. a decline in liquidity would not trigger more volatility for as long as liquidity remains above this threshold. With respect to the impact of introducing or increasing a tax on financial transaction on price volatility the economic literature is rather inconclusive, i.e. some authors have found that levying an FTT increased volatility while other found the opposite or no effect at all.12 Against this background it would first be interesting to measure to what extent different markets with different degrees of liquidity also exhibit different degrees of volatility so as to test the first hypothesis (correlation between liquidity and volatility) and then to measure to what extent the (relative) decline in liquidity (as measured by trading volumes) on the market for taxed French shares has triggered an increase in volatility on these markets as compared to other markets that did not suffer from such a (relative) reduction in liquidity. This can either be done by comparing trends in liquidity (as measured by trading volumes) with trends in price volatility over time on the same market or by comparing the levels in liquidity and price volatility across markets and determine in how far lower levels of liquidity go hand in hand with higher degrees of volatility. For the measurement of the liquidity (as approximated by trading volumes) of the different markets two approaches were used, the trading volumes themselves as analysed in section 2 of this note and the turnover velocity as expressed by the ratio of annual turnover over total capitalisation of a market segment. Table 2: Turnover velocity for the four selected samples*

Turnover

(EUR mn.) Capitalisation

(EUR mn.) Average aggregate annual

turnover velocity (%) 108 FR companies 712,382 1,231,703 58 CAC40 (35) 581,423 905,311 64 CAC40 (5) 61,305 84,659** 72 FR mid-caps 8,234 30,083 27 IT companies 430,273 335,480 128 DE companies 746,437 662,658 113

*) data for 2012 **) data as of 14.02.2014! Average annual trading volumes in the 108 taxed French shares reached about EUR 712 billion in 2012, or about 58% of the aggregate capitalisation of EUR 1.23 trillion of these companies. The trading volumes in the shares of the CAC40 (35) accounted for 81%, and it represented about 64% of the aggregate capitalisation of these companies. This turnover velocity is – as can be seen from Table 2 – significantly superior to what can be observed on the market for French mid-cap companies (about 27% of the aggregate capitalisation) while it is inferior to what can be observed on other large stock markets, such as Germany (113%) or Italy (128%), i.e. the most liquid markets were the Italian and the German market while 12 For more details on this see e.g. the literature survey referred to in footnote 1.

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liquidity on the taxed French market was only half of this. The untaxed French mid-cap market was characterised by a turnover velocity which reached only half of that of the taxed French market and a quarter of that of the German and Italian market. There exist different approaches to measure price volatility. The approach most commonly used for measuring volatility, and also used in this note, is to measure the standard deviation of prices. Annex 4 provides more details on the methodology used.13 When comparing the average price volatility (as shown at the y-axis) on the different markets over the entire observation period (see the right-hand plots of graphs 3 to 7) it can be seen that the more liquid a market is, the smaller the average standard deviation over the 19 months analysed, as it ranges from less than 0.4 for the highly liquid Italian market (graph 6) to more than 5 for the rather illiquid French mid-cap market (graph 4)14. Thus, the results seem to confirm that – at least in the longer run - more liquid markets are exhibiting a less volatile price performance. These results hold for both capitalisation-weighted indices (not shown here) and un-weighted indices and for both liquidity as measured by the turnover velocity and liquidity as measured by trading volumes. With respect to the short-term (from month to month) volatility on the different markets over the observation period the above picture is confirmed for all market segments analysed, i.e. the more liquid the market the less pronounced is also the short-term volatility. However, the picture becomes much more nuanced when one does not look at the levels or short-term (monthly) fluctuations of volatility across markets but at the trends in volatility on a given market segment, be it over the entire observation period or be it when comparing these trends before and after August 2012. Indeed, while there was in all cases the expected negative correlation between the levels of liquidity and the levels of volatility when comparing these variables across different markets with different degrees of liquidity, the correlation over time on a given market changes in several cases. While the correlation between the trends in volatility and the trends in liquidity (as measured by trading volumes) on the entire taxed French, Italian and un-taxed French markets shows the expected negative sign for both the entire period and the sub-periods, it is positive for the entire period and the sub-periods when only looking at the highly-capitalised taxed French (CAC40(35)) and the German market segments (see graphs 3 to 7).

13 In this paper the focus is on price volatility as measured by changes in prices from day to day – averaged at

monthly level - over the whole sample of companies. Other studies, especially those that focus on analysing short-term developments typically focus on intra-day price changes, which might give higher price fluctuations. However, as the purpose of this paper is to compare trends both over different periods within a market and (across over different periods) across different markets it is sufficient to analyse the volatility developments at the monthly level. Also, as the French FTT does not tax intraday transactions but only changes in positions at the end of the trading day intra-day price changes might in any case be hardly affected by the French FTT.

14 Note that the amplitude of the changes is different as the scales of the graphs are different volatility ranging from less than 0.2 for the highly liquid Italian market (graph 6) to around 9 for the rather illiquid French mid-cap market (graph 4).

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Graphs 3 to 7: Trading volumes (left) and volatility (right) performance over time on different markets – August 2011 to February 2013 Graph 3

Graph 4

Graph 5

Graph 6

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Graph 7

5. EVOLUTION OF PRICE LEVELS

A standard claim, also made in the Commission’s impact assessments in the context of a tax on financial transactions, is that potential purchasers of a security will factor in their own cost of the tax as well as the costs of “depreciation”, i.e. the lower price they are expecting when they will sell the product on, albeit at a discounted level etc. along the lifetime of the product traded when they make a price offer. Thus, they will offer a lower price than they would do in the absence of the tax, so that the expected net return (after taxes and depreciation) remains unaffected by the tax. This should then exert a (measurable) downward pressure on prices in secondary markets (i.e. where shares are traded), with a measurable downward effect on the price of shares on the primary market, i.e. when they are issued for the raising of capital. In the light of this hypothesis it is worthwhile to have – in the context of a “difference-of-difference” approach a look at the (average) percentage variation of prices for the samples used – with reference to August 2011 – and find out in how far there was an observable downward pressure on prices of the taxed shares, either as compared to the trend preceding the introduction of the tax on the taxed market or as compared to other but untaxed markets. For the taxed French market two samples are given: the entire taxed market (FR 108) and the segment with the 35 biggest French companies contained in CAC 40 and headquartered in France, for the untaxed markets the untaxed French mid-cap market and the (untaxed) German DAX and the (untaxed) Italian MIB are used as potential counterfactuals. The methodology used is presented in Annex 415. 15 Note that 18 values have been derived for instance for the whole period of 19 months (the reference starting

point is August 2011).

17

All graphs show a remarkable similarity of the price evolutions for the samples in the 5 market segments analysed with respect to average monthly percentage changes in prices for the entire period analysed, as well as in sub-periods and fluctuations within these sub-periods. Indeed, all markets had been characterised by a certain overall decline in prices until the end of 2011 before they changed to a more bullish performance until March 2012. This was followed by another slump in prices until June 2012 and a subsequent “recovery”. The very much synchronised developments across the analysed markets could be serving as an indication that price developments on these markets had been largely determined by “megatrends” and parameters that dominated the developments on markets for all three countries while parameters affecting only single markets were much less influential. Notably, it would not be possible to claim on the basis of these findings that there had been a negative impact of the tax on the price evolution of taxed French shares. Despite these similarities in trends and fluctuations there had, nevertheless, been some differences: when looking at the trend lines over the entire observation period the markets with the highest monthly price rises had been the German (+1.8% m.o.m.) and the French mid-cap (+1.4% m.o.m.) markets, while for the other two markets – taxed French (108) (+1.3% m.o.m.) and Italian (+1.1% m.o.m.) market segments – the price increase was a bit weaker. The highly capitalised French companies (CAC40 (35)) also witnessed similar monthly price trend over the entire observation period (+1.5% m.o.m.), performing somewhat better than the whole population of taxed French companies. Also, the German market had its trough a bit earlier (September 2011) than the other markets (December 2011). A somewhat less dynamic performance on all these markets in the run-up to August 2012 is observable (notably on the Italian market) which was then at least partially compensated by a more dynamic rally (more pronounced in the Italian compared to the German market, for instance). When looking at price trends (in terms of average monthly price increases) since August 2012 one can see that trends and fluctuations exhibited similar features over this period for all the markets, but that the untaxed French (+3.1% m.o.m.) and Italian (+2.9% m.o.m.) markets performed somewhat better as compared to the taxed 108 French companies (+ 2.1% m.o.m.) and the untaxed German (+1.6% m.o.m.). The highly capitalised segment of the taxed French companies (CAC40 (35)) performed slightly worse (+1.9% m.o.m.) than the whole population of taxed French companies but still better than the German market. Thus, contrary to what one would have expected on the basis of economic models, the levying or the French FTT did not go hand in hand with an absolute or relative decline in prices of the taxed French shares, neither in comparison with the price trend observed before the introduction of the tax nor if compared with price developments (for the same period) in other, non-taxed markets. The reasons for an absence of measurable effects on share prices could be manifold: the tax has been absorbed by the financial sector, the tax might have triggered a widening of the bid-ask spread16, the tax was treated as additional transaction cost and passed on to clients without affecting the equilibrium price, the effect of the tax was simply too small as compared to other

16 Some studies have indeed concluded that the introduction of the French FTT has widened the bid-ask

spread. See e.g. Colliard, J-E., Hoffmann, P. (2013), op.cit. and Haferkorn, M., Zimmermann, K. (2013) op.cit.

18

parameters having a much more important effect on price developments of equity markets etc. Whatever explanation one prefers: the bottom line remains the same: there is no indication whatsoever that the introduction of the tax had a measurable effect on share prices. Graph 8: Monthly calculated average percentage change (over August 2011) in prices for different markets and market segments

19

6. CONCLUSIONS

This paper investigated to what extent perceptions that the introduction of a tax on securities transactions triggers a fall in liquidity (trading volumes) and share prices as well as an increase in volatility would be confirmed or challenged by empirical evidence of a real case. The case at hands was the policy change that took place in France on 1 August 2012 when a tax at a rate of 0.2% was introduced on the purchase of shares of French companies with a capitalisation in excess of EUR 1 billion, and a tax of 0.01% on cancelled orders in share trading in case it was carried out as high-frequency algorithm trading and the ratio of cancelled orders to all orders exceeded 80%. To this end, this paper analysed the liquidity (trading volumes), volatility and price performance of the newly-taxed French market over a 19-month period spanning from 12 months before to six months after the introduction of the tax, and also compared it with the same performance indicators on three other markets, i.e. the German DAX, the Italian MIB and the French mid-cap market and that were not exposed to the introduction of such a tax. The bottom line of the results of this analysis is that it cannot be confirmed that the introduction of the FTT in France has triggered a decline in share prices, and neither can it be confirmed that the volatility of the taxed market increased after the introduction of the tax. On the other hand a certain decline of around 10% in liquidity (as measured by trading volumes) could be observed, notably as a result of a slump in trading volumes around the date of the introduction of the tax. Indeed, liquidity (as measured by trading volumes) suffered a major setback just before and around the introduction of the tax, and – despite its dynamic rebound afterwards - it could not fully offset this setback. This notably holds for the trading in the very liquid market for the highly-capitalised French companies. This invites for the conclusion that the market for the very large French companies on the taxed market somewhat underperformed with respect to trading volumes, but that this (relative) underperformance was more than offset by the outperformance of the smaller companies on the taxed market. The reason for this might have been that the trading in those shares is much more liquid and, thus, also more influenced by high-frequency trading and the availability of (untaxed) close substitutes such as derivatives. The fact that there had been no negative impact whatsoever on price levels and dynamics invites for the conclusion that the tax had been absorbed with no effect on the equilibrium market prices of the shares. This would be reassuring with respect to the feared-for slight negative economic effects (before the recycling of the tax revenues) simulated to be triggered by higher cost of capital. Also, if confirmed and transposable to other financial markets such as fixed-income markets (corporate and government bonds and bills) this would mean that the tax might have an impact on trading volumes and the bid-ask spread but not on volatility and on the equilibrium price and, thus, on the cost of borrowing for government bonds. A somewhat counterintuitive finding and potentially deserving more analysis has been that there was not in all instances a clear negative correlation between the trends in liquidity (as measured by trading volumes) and the trends in volatility of given markets over the observation period, i.e. a decline in liquidity on a market did not correlate with an increase in volatility.

20

One explanation for not finding a measurable effect of the introduction of the tax might be that the size of the tax “shock” was simply too small to trigger such measurable effects and that other much more important economic as well as policy parameters drive the liquidity, price and volatility performance of securities markets. Another (complementary) explanation might be that by exempting intra-day trading and taxing only changes in positions at the end of a trading day the most price-sensitive market segment actually remained untaxed while the less price-sensitive segment, i.e. those trades where investors are really interested in getting ownership of a share, simply accepted the tax. These hypotheses would perhaps deserve additional analysis as well.

21

ANNEX 1: MARKETS ANALYSED – POPULATION OF COMPANIES

List of taxed French companies (subject to FTT)

No. Component ISIN Market capitalisation (EUR mn.)

Weight in the index

1 SANOFI FR0000120578 97,738 7.94

2 TOTAL FR0000120271 90,354 7.34

3 LVMH FR0000121014 68,027 5.52

4 L'OREAL FR0000120321 67,532 5.48

5 BNP PARIBAS ACT.A FR0000131104 56,373 4.58

6 GDF SUEZ FR0010208488 35,372 2.87

7 AXA FR0000120628 32,735 2.66

8 DANONE FR0000120644 32,280 2.62

9 SCHNEIDER ELECTRIC FR0000121972 30,644 2.49

10 AIR LIQUIDE FR0000120073 27,926 2.27

11 EDF FR0010242511 27,363 2.22

12 HERMES INTL FR0000052292 26,614 2.16

13 PERNOD RICARD FR0000120693 25,843 2.10

14 SOCIETE GENERALE FR0000130809 24,434 1.98

15 CHRISTIAN DIOR FR0000130403 22,770 1.85

16 PPR (Kering) FR0000121485 21,862 1.77

17 VIVENDI FR0000127771 20,911 1.70

18 VINCI FR0000125486 20,680 1.68

19 FRANCE TELECOM (Orange) FR0000133308 20,131 1.63

20 CREDIT AGRICOLE FR0000045072 18,113 1.47

21 UNIBAIL-RODAMCO FR0000124711 16,795 1.36

22 SAINT GOBAIN FR0000125007 16,725 1.36

23 ESSILOR INTL. FR0000121667 15,642 1.27

24 SAFRAN FR0000073272 14,681 1.19

25 RENAULT FR0000131906 14,499 1.18

26 CARREFOUR FR0000120172 14,237 1.16

27 LAFARGE FR0000120537 14,107 1.15

28 MICHELIN FR0000121261 12,386 1.01

29 SODEXO FR0000121220 11,058 0.90

30 PUBLICIS GROUPE SA FR0000130577 10,760 0.87

31 NATIXIS FR0000120685 10,591 0.86

32 DASSAULT SYSTEMES FR0000130650 10,474 0.85

33 ALSTOM FR0010220475 10,320 0.84

34 BUREAU VERITAS FR0006174348 10,298 0.84

35 TECHNIP FR0000131708 9,051 0.73

36 LEGRAND FR0010307819 9,040 0.73

37 DASSAULT AVIATION FR0000121725 9,010 0.73

38 CASINO GUICHARD FR0000125585 8,673 0.70

22

39 ILIAD FR0004035913 8,122 0.66

40 BOLLORE FR0000039299 8,061 0.65

41 CNP ASSURANCES FR0000120222 7,966 0.65

42 ACCOR FR0000120404 6,554 0.53

43 BOUYGUES FR0000120503 6,448 0.52

44 ADP FR0010340141 6,075 0.49

45 KLEPIERRE FR0000121964 6,054 0.49

46 EUTELSAT COMMUNIC. FR0010221234 5,809 0.47

47 CAP GEMINI FR0000125338 5,775 0.47

48 EDENRED FR0010908533 5,636 0.46

49 THALES FR0000121329 5,536 0.45

50 GECINA NOM FR0010040865 5,379 0.44

51 ARKEMA FR0010313833 5,270 0.43

52 AREVA FR0011027143 5,249 0.43

53 SUEZ ENVIRONNEMENT FR0010613471 5,095 0.41

54 VALLOUREC FR0000120354 5,010 0.41

55 VEOLIA ENVIRON. FR0000124141 4,963 0.40

56 REMY COINTREAU FR0000130395 4,960 0.40

57 ATOS FR0000051732 4,891 0.40

58 JC DECAUX SA. FR0000077919 4,879 0.40

59 ZODIAC AEROSPACE FR0000125684 4,866 0.40

60 REXEL FR0010451203 4,758 0.39

61 BIC FR0000120966 4,266 0.35

62 SCOR SE FR0010411983 4,200 0.34

63 WENDEL FR0000121204 4,157 0.34

64 CIC FR0005025004 4,131 0.34

65 IMERYS FR0000120859 3,934 0.32

66 COLAS FR0000121634 3,890 0.32

67 FINANCIERE ODET FR0000062234 3,728 0.30

68 FONC.DES REGIONS FR0000064578 3,654 0.30

69 CGG FR0000120164 3,628 0.29

70 ICADE FR0000035081 3,565 0.29

71 GROUPE EUROTUNNEL FR0010533075 3,527 0.29

72 LAGARDERE S.C.A. FR0000130213 3,448 0.28

73 VALEO FR0000130338 3,294 0.27

74 S.E.B. FR0000121709 3,125 0.25

75 EULER HERMES FR0004254035 3,072 0.25

76 BIOMERIEUX FR0010096479 2,895 0.24

77 EIFFAGE FR0000130452 2,820 0.23

78 ALCATEL-LUCENT FR0000130007 2,738 0.22

79 ERAMET FR0000131757 2,732 0.22

80 EURAZEO FR0000121121 2,658 0.22

81 AIR FRANCE -KLM FR0000031122 2,557 0.21

82 INGENICO FR0000125346 2,523 0.20

23

83 CAMBODGE NOM. FR0000079659 2,502 0.20

84 PEUGEOT FR0000121501 2,219 0.18

85 IPSEN FR0010259150 2,190 0.18

86 CFAO FR0000060501 2,178 0.18

87 VICAT FR0000031775 2,074 0.17

88 TF1 FR0000054900 1,944 0.16

89 VILMORIN & CIE FR0000052516 1,882 0.15

90 HAVAS FR0000121881 1,868 0.15

91 FONCIERE LYONNAISE FR0000033409 1,791 0.15

92 ORPEA FR0000184798 1,753 0.14

93 MAUREL ET PROM FR0000051070 1,739 0.14

94 RUBIS FR0000121253 1,723 0.14

95 METROPOLE TV FR0000053225 1,705 0.14

96 CIMENTS FRANCAIS FR0000120982 1,610 0.13

97 FAURECIA FR0000121147 1,590 0.13

98 NEOPOST FR0000120560 1,533 0.12

99 MERCIALYS FR0010241638 1,506 0.12

100 SILIC FR0000050916 1,493 0.12

101 BOURBON FR0004548873 1,458 0.12

102 VIRBAC FR0000031577 1,440 0.12

103 RALLYE FR0000060618 1,359 0.11

104 ALTAREA FR0000033219 1,313 0.11

105 FROMAGERIES BEL FR0000121857 1,285 0.10

106 SOMFY SA FR0000120495 1,250 0.10

107 NEXANS FR0000044448 1,179 0.10

108 FDL FR0000030181 1,172 0.10

Note: Companies marked in italics are also part of the CAC 40 index.

List of mid-cap French companies

No. Component ISIN Market capitalisation

(EUR mn.) Weight in the

index

1 EUROFINS SCIENT. FR0000038259 2297 0.0764

2 TELEPERFORMANCE FR0000051807 1852 0.0616

3 PLASTIC OMNIUM FR0000124570 1811 0.0602

4 NEXITY FR0010112524 1400 0.0465

5 IPSOS FR0000073298 1319 0.0438

6 FIMALAC FR0000037947 1115 0.0371

7 ALTEN FR0000071946 1037 0.0345

8 UNIBEL FR0000054215 987 0.0328

9 BRASSERIE CAMEROUN CM0000035113 909 0.0302

10 TECHNICOLOR FR0010918292 889 0.0296

11 ARTOIS NOM. FR0000076952 877 0.0292

12 UBISOFT ENTERTAIN FR0000054470 833 0.0277

24

13 ALTRAN TECHN. FR0000034639 825 0.0274

14 APERAM LU0569974404 805 0.0268

15 LISI FR0000050353 798 0.0265

16 FFP FR0000064784 792 0.0263

17 LDC FR0000053829 779 0.0259

18 BONGRAIN FR0000120107 775 0.0258

19 FAIVELEY TRANSPORT FR0000053142 759 0.0252

20 EUROSIC FR0000038200 731 0.0243

21 SOPRA GROUP FR0000050809 705 0.0234

22 ESSO FR0000120669 700 0.0233

23 BENETEAU FR0000035164 678 0.0225

24 ELEC.STRASBOURG FR0000031023 677 0.0225

25 STALLERGENES FR0000065674 676 0.0225

26 BOIRON FR0000061129 674 0.0224

27 MEDICA FR0010372581 671 0.0223

28 CANAL PLUS(STE ED) FR0000125460 662 0.0220

29 BONDUELLE FR0000063935 629 0.0209

30 SIIC DE PARIS NOM. FR0000057937 625 0.0208

31 NORBERT DENTRESS. FR0000052870 610 0.0203

32 MONCEY (FIN.) NOM. FR0000076986 594 0.0197

33 DERICHEBOURG FR0000053381 592 0.0197

List of Italian companies

No. Instrument ISIN Market capitalization

(EUR mn.) Weight in the index

1 ENI IT0003132476 63,986.74 19.07

2 ENEL IT0003128367 27,080.73 8.07

3 UNICREDIT IT0004781412 24,535.81 7.31

4 INTESA SANPAOLO IT0000072618 22,174.68 6.61

5 GENERALI ASS IT0000062072 19,941.06 5.94

6 TENARIS LU0156801721 17,959.98 5.35

7 LUXOTTICA GROUP IT0001479374 16,044.72 4.78

8 SNAM IT0003153415 12,316.26 3.67

9 TELECOM ITALIA IT0003497168 11,629.40 3.47

10 FIAT INDUSTRIAL IT0004644743 11,455.47 3.41

11 SAIPEM IT0000068525 9,078.16 2.71

12 ATLANTIA IT0003506190 8,866.50 2.64

13 ENEL GREEN POWER IT0004618465 7,244.50 2.16

14 TERNA IT0003242622 6,384.74 1.90

15 STMICROELECTRONICS NL0000226223 5,703.75 1.70

16 FIAT IT0001976403 5,474.64 1.63

17 EXOR IT0001353140 5,448.68 1.62

18 MEDIOBANCA IT0000062957 4,655.70 1.39

25

19 PIRELLI E C IT0004623051 4,196.41 1.25

20 SALVATORE FERRAGAMO IT0004712375 3,495.97 1.04

21 PRYSMIAN IT0004176001 3,388.81 1.01

22 CAMPARI IT0003849244 3,352.03 1.00

23 MEDIOLANUM IT0001279501 3,245.78 0.97

24 UBI BANCA IT0003487029 3,193.99 0.95

25 LOTTOMATICA IT0003990402 3,170.53 0.95

26 TOD'S IT0003007728 3,084.64 0.92

27 PARMALAT IT0003826473 3,057.48 0.91

28 BCA MPS IT0001334587 2,629.51 0.78

29 BANCO POPOLARE IT0004231566 2,475.93 0.74

30 AUTOGRILL SPA IT0001137345 2,342.77 0.70

31 FINMECCANICA IT0003856405 2,337.87 0.70

32 MEDIASET S.P.A IT0001063210 2,158.58 0.64

33 BUZZI UNICEM IT0001347308 2,050.93 0.61

34 BCA POP EMIL ROMAGNA IT0000066123 1,926.42 0.57

35 AZIMUT IT0003261697 1,831.05 0.55

36 BCA POP MILANO IT0000064482 1,827.97 0.54

37 IMPREGILO IT0003865570 1,644.32 0.49

38 DIASORIN IT0003492391 1,526.38 0.45

39 A2A IT0001233417 1,394.77 0.42

40 ANSALDO STS IT0003977540 1,165.94 0.35

List of German companies

No. Instrument ISIN Market capitalization

(EUR mn.) Weight in the index

1 Siemens AG DE0007236101 66,988.90 10.11

2 BASF SE DE000BASF111 65,368.13 9.86

3 BAYER AG DE000BAY0017 60,325.84 9.10

4 SAP AG DE0007164600 54,476.74 8.22

5 Allianz SE DE0008404005 47,678.06 7.19

6 Daimler AG DE0007100000 40,982.19 6.18

7 Deutsche Bank AG DE0005140008 30,276.28 4.57

8 E.ON SE DE000ENAG999 26,696.79 4.03

9 Deutsche Telekom AG DE0005557508 25,407.84 3.83

10 Volkswagen AG Vz DE0007664039 24,576.05 3.71

11 Linde AG DE0006483001 24,548.71 3.70

12 BMW AG St DE0005190003 23,370.54 3.53

13 Münchener Rück AG DE0008430026 21,673.64 3.27

14 RWE AG St DE0007037129 15,282.95 2.31

15 Deutsche Post AG DE0005552004 14,965.41 2.26

16 Adidas AG DE000A1EWWW0 14,080.25 2.12

17 Fresenius SE & Co. KGaA DE0005785604 11,362.42 1.71

18 Henkel AG & Co. KGaA Vz DE0006048432 10,841.57 1.64

26

19 Fresenius Medical Care AG & Co. KGaA St DE0005785802 10,840.39 1.64

20 Deutsche Börse AG DE0005810055 8,680.24 1.31

21 Continental AG DE0005439004 6,957.56 1.05

22 ThyssenKrupp AG DE0007500001 6,916.96 1.04

23 Infineon Technologies AG DE0006231004 6,684.67 1.01

24 Deutsche Lufthansa AG DE0008232125 6,624.07 1.00

25 Merck KGaA DE0006599905 6,520.27 0.98

26 HeidelbergCement AG DE0006047004 6,433.99 0.97

27 Commerzbank AG DE0008032004 6,308.99 0.95

28 K+S Aktiengesellschaft DE000KSAG888 6,088.02 0.92

29 Beiersdorf Aktiengesellschaft DE0005200000 6,076.62 0.92

30 LANXESS AG DE0005470405 5,623.67 0.85

27

ANNEX 2: TRADING VOLUME

First approach: aggregated monthly volumes (non-weighted)

Second approach: aggregated weighted monthly volumes

i – individual company n – number of companies j – entry (trading day) m – number of entries in the month V – gross volume wi – capitalisation weight ci – individual company capitalisation

ct – total sample capitalisation �22 – used in order to normalise the month �n – used in order to aggregate the weighted averages

∑ �∑ ������

�����

�� 22

28

ANNEX 3: PRICE VOLATILITY

First approach: average monthly standard deviation of prices (non-weighted)

Second approach: aggregated weighted average monthly standard deviation of prices

Ơ – standard deviation i – individual company j – entry (trading day) n – number of companies m – number of entries in the month �j – daily price � ̅– average price for the period (month) wi – capitalisation weight ci – individual company capitalisation ct – total sample capitalisation

29

ANNEX 4: PRICE VARIATION

First approach: monthly percentage change in prices (non-weighted) (reference = August 2011)

Second approach: weighted monthly percentage change in prices (reference = August 2011)

i – individual company j – entry (trading day) 0 – reference (August 2011) n – number of companies m – number of entries in the month �j – daily price � ̅ – average price for the period (month) wi – capitalisation weight ci – individual company capitalisation ct – total sample capitalisation

30

ANNEX 5: MONTH-ON-MONTH (MOM) % CHANGE IN VOLUMES

EST(V) – estimated monthly volume according to the linear trend line 0 – reference (start of the period) T – time/current month nT – number of months in the period