The impact of hard discount control mechanism on the discount volatility of UK closed-end funds

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1 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 Ahmed F. Salhn (Egypt) The mpact of hard dscount control mechansm on the dscount volatlty of UK closed-end funds Abstract The mpact of hard dscount control mechansms on the dscount volatlty of UK closed-end funds s nvestgated. Usng ten years data, the paper starts by analyzng the man factors that nfluence the varaton n dscount volatlty across the sector. Standard devaton of net asset value returns, market value and the percentage of unquoted assets n the fund s portfolo are found to be hghly sgnfcant. As a robustness test, the whole perod s splt nto two fve years perods whch has no effect on the sgnfcance of the varables. The analyss s then extended to show that closed-end funds whch commt to a hard dscount control mechansm tend to have lower dscount volatlty. However, the last fndng s not hghly sgnfcant suggestng that n general hard dscount control mechansms could be used more effectvely to control dscount volatlty. Keywords: dscount, dscount volatlty, closed-end funds, buybacks, dscount control mechansm. JEL Classfcaton: G11. Introducton One of the man deas that nvestors consder n managng ther nvestments s the dversfcaton of the assets wthn ther nvestment portfolo. However, nvestors have to nvest large amounts of money to be able to dversfy ther portfolos well. Closed-end funds are companes that rase captal from nvestors and nvest t n a dversfed portfolo of assets. These companes enable small nvestors to obtan dvers-fcaton benefts for a relatvely modest outlay. Closed-end fund shares usually trade at a dscount to net asset value. Ths s one of the most puzzlng ssues n fnance. The puzzle s not only concerned wth the typcally wde dscounts across the sector but also the varaton of these dscounts both over tme and across funds. One of the most successful solutons to the wdenng n dscounts and ts volatlty s the shares repurchase or buybacks. Closed-end funds have been allowed to buy back shares snce 1980 but the actual number of buybacks has ncreased dramatcally snce the end of 1999 when restrctons that prevented closed-end funds dstrbutng ther captal profts by buyng back shares were removed (Adams and Angus, 2011). The purpose of ths work s to analyse the extent to whch dscount volatlty has been reduced by the buyback transactons conducted by closed-end funds that have a hard dscount control mechansm durng the perod from July 2008 to June Our analyss wll start by nvestgatng the man factors Ahmed F. Salhn, Ahmed F. Salhn, Teachng Assstant, Faculty of Commerce, Caro Unversty, Egypt. The author would lke to thank Andrew Adams from Herot Watt Unversty for hs comments. Also thanks for The Assocaton of Investment Companes (AIC) for ther help wth the statstcal data of nvestment companes. I gratefully acknowledge the provson of buybacks data by Chrs Brown from J.P. Morgan Cazenove. 68 affectng dscount volatlty across funds. We wll then analyze the dfferences n dscount volatlty between closed-end funds that have hard dscount control mechansms and those that do not. In secton 1, an overvew of dscount, dscount volatlty and buybacks has been presented. Secton 2 revews the lterature related to ths work. Possble factors that mght nfluence the dscount volatlty have been descrbed n secton 3. The models employed wll also be descrbed n ths secton. Secton 4 descrbes the data and the methodology. Emprcal fndngs have been dscussed n secton 5 and the fnal secton concludes. 1. Dscount, dscount volatlty and buybacks 1.1. Dscount. Closed-end funds are allowed to have loans n ther captal structure. The amount obtaned by subtractng these loans from total assets s called net asset value (NAV) whch s regularly dsclosed on a per share bass. NAV s the man determnant of the company s performance durng ts lfe. However, closed-end fund shares are lsted n the stock exchange and the determnant of ther prces s the forces of supply and demand. The dfference between the prce and the NAV per share s called a dscount f the prce s lower than the NAV per share or called a premum n the reverse case. Closed-end funds shares are often traded at a dscount rather than a premum, whch means that the buyer of the fund s share wll be beneft from the underlyng assets of the fund for less than ther value n the market. Ths s one of the most puzzlng ssues n the fnancal world. Fgure 1 shows the average dscount to NAV over the perod 1975 tll the end of 2010 n the UK s conventonal closed-end fund sector. In ther survey of closed-end fund Dmson and Mno- Kozersk (1999) classfed the explanatons of the closed-end funds dscount puzzle nto two man

2 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 categores. The frst category s the economc explanatons whch nclude the mscalculaton of net asset value, agency cost explanatons, tax tmng and segmented markets. The other category s the attempts to explan closed-end fund dscounts from the behavoral perspectve. 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Source: The Assocaton of Investment Companes (AIC), UK. Fg. 1. Dscount of nvestment companes (Ex VCTs, AIM and Euronext members), % 1.2. Dscount volatlty. Dscount volatlty s one part of the closed-end funds dscount puzzle and s a component of the rsk attached to closed-end fund shares. Dscount volatlty means that the share returns do not reflect the returns of the underlyng net assets n the fund s portfolo. Ths appears to contradct the Effcent Market Hypothess whch states that share prces should always reflect all the avalable nformaton (Fama, 1970). Such dscount volatlty makes closed-end funds less attractve. One of the underlyng causes of the dscount volatlty, as we wll see later, s the volatlty of net asset value returns. However, dscount returns lead to an excess volatlty compared to ts net asset value returns volatlty. Share prce volatlty as reported by (Pontff, 1997) exceeded the volatlty of underlyng assets returns by 64 percent n the US. Adams (2000b) nvestgated both the excess volatlty n the UK and the part that dscount volatlty s takng as a component of the closed-end funds rsk Buybacks. Closed-end funds have been allowed to repurchase ther shares snce 1980 by usng captal reserves but very few companes used ths permsson untl the end of the twenteth century (Adams and Angus, 2011). However, buyback transactons dramatcally ncreased after changes were made to the Companes Act at the end of 1999 whch gves closedend funds permsson to dstrbute profts by repurchasng ther own shares (Investment Companes Dstrbuton of Profts Regulatons, 1999). Shares buybacks offer advantages to closed-end funds n both the short and long run. Frst, buybacks drectly enhance the net asset value per share whch wll beneft the remanng shareholders after the mplementaton of the repurchase. Closed-end funds usually buyback shares at a dscount compared to net asset value. Ths means that after the executon of the buyback transacton, the dfference between the prce that the company pad to repurchase ts own shares and the net asset value per share beforehand wll enhance the exstng net asset value per share. As a consequence of reducng the supply of the fund s shares at the mplementaton of the buyback transacton, share prces wll ncrease and dscounts wll narrow. The other beneft, whch we wll test n ths work, s that share buybacks affect on the level of dscount volatlty (AIC, 2010). Closed-end funds can choose between two dfferent buybacks strateges n attemptng to manage dscounts and dscount volatlty. The frst one s to commt to a hard dscount control mechansm (HDCM), whch requre that the company buy ts own shares when dscount reaches a pre-specfed level. The other strategy s to buy back shares when dscount wden but closed-end funds n ths case retan flexblty as to when, how and at what level of dscount the buyback strategy wll be mplemented. Ths strategy s called a Soft Dscount Control Mechansm (SDCM). Shares buybacks mprove the lqudty of the closedend fund shares through satsfyng the supply of shares when the fund repurchases ts own shares and satsfyng the demand for shares by sellng these shares n the case of holdng them as treasury shares. As dscount narrowng strategy, the queston of buybacks was a controversal ssue amongst practtoners n the early days. At the start of 1998, 69

3 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 Brown et al. (1998) from Cazenove state that although the announcement of the buybacks wll make the share prce rse and result n a narrowng of the dscount, the actual repurchase wll enhance the net asset value per share and result n a wdenng of the dscount agan. They argue that share buybacks, n theory and over the short term, would narrow the dscount untl the completon of the actual buyback program. However, n the long term, the man determnants of the level of the dscount are the market s pont of vew on the qualty of management of the fund, nvestment performance and the sentment n the market. One of the crtcsms they mentoned n ther report s that share buybacks may be consdered a partal open endng of the fund, and ths s nconsstent wth the nature of closed-end funds. Another crtcsm that related to the buybacks strategy s that t ncreases the level of the gearng whch may expose the fund to more rsk when the market falls. It also rases the total expense rato results from spreadng the fxed costs over a small base, due to the buybacks, and hence, ncreases the expenses for the remanng shareholders (AIC, 2010). 2. Lterature revew Many academc papers have tred to explan the closed-end funds dscount puzzle n both the US and the UK. The basc puzzle s that exstence of a dscount contradcts the effcent market hypothess presented by Eugene Fama n the 1960s. The Effcent Market Hypothess states that the prce of any share should reflect all the nformaton avalable about that share (Fama, 1970). Closed-end fund dscounts arguably represent a breachng to ths hypothess as closed-end fund share prces should reflect manly the value of the underlyng portfolo, whch s dsclosed regularly as net asset value per share. Explanatons of the puzzle have taken two major tracks; one of them s consstent wth ratonal expectatons of the nvestors or economc explanatons n the words of (Dmson and Mno-Kozersk, 1999). Ths ncludes some explanatons such as net asset value mscalculatons and agency costs. The other category of explanatons s the behavoral approach that argues that rratonalty of the market must be taken nto account. Dmson and Mno- Kozersk (1999) pont out that enthusasm about equty shares n general and enthusasm about partcular shares such as county-specfc shares are accompaned by the exstence of premums. They also argue that hgh dscount volatlty of countryspecalze funds cannot be explaned only by the behavor of the foregn market. Another part of the closed-end fund puzzle s the tme seres and cross-sectonal volatlty of dscounts. Dscount volatlty means that the returns acheved n the underlyng assets of the closed-end fund are not exactly captured n the prces of the fund s shares. Ths agan contradcts to the effcent market hypotheses and results n ncreased rsk attached to the closed-end fund shares. Shller (1981) argues that volatlty of share prces s too hgh to be explaned by changes n the shares fundamentals. In the US, Pontff (1997) shows that the volatlty of the closed-end fund dscounts s 64% hgher than the volatlty underlyng asset returns. Ths s confrmed n the UK by the work of Adams (2000b) showng the exstence of the excess volatlty of the closed-end fund shares compared wth that of net asset value. Usng three and sx months returns, Adams (2000a) shows that dscount volatlty s an mportant component of the total rsk of closed-end funds n the UK, however, ths mportance reduces for longer-term return ntervals. However, Malkel and Xu (2005) fnd no evdence of excess volatlty of closed-end fund returns. They fnd that the volatlty of fund returns s 1.31% whch s smlar to the volatlty of net asset value return, whch s 1.42%. Ther argument for the exstence of dscounts s that the net asset value can be vewed as the realzed value of the fund whereas the fund share prces are the expectaton of the future value of the fund. 3. Factors that may have an mpact on the dscount volatlty There are many factors that may nfluence dscount volatlty. We wll consder only three factors that we beleve are lkely to have a sgnfcant mpact. In ths secton, we frst defne dscount volatlty and show how to measure t. We then dscuss the three factors that we expect to have an mpact on the dscount volatlty. Fnally, we dscuss the lkely mpact of buybacks on dscount volatlty and ths wll be tested n secton Dscount volatlty: defnton and measurement. Follow Adams (2000a), dscount volatlty wll be defned as the standard devaton of monthly dscount returns. The dscount return can be calculated as follow: Dsrt Prcrt NAV Ln( NAV NAV ), t t 1 rt Ln( Prc / Prc t t 1 ) (1) where Ds rt s the dscount return for perod t, Prc rt s the share prce return for perod t, NAV rt s the net asset value return for perod t, Prc t s the share prce n perod t, NAV t s the net asset value n perod t, Prc t-1 s the share prce n perod t-1, and NAV t-1 s the net asset value n perod t-1. 70

4 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, Factors that may nfluence the dscount volatlty. Closed-end funds announce the net asset value per share on regularly bass as t s consdered a proxy for evaluatng the management performance. In addton, management performance mght be the man factor that wden or narrow the dscount (Berk and Stanton, 2007). Therefore, we expect that the hgher volatlty of net asset value return, the hgher the fluctuatons n the dscount. Moreover, hgh standard devaton of net asset value returns wll restrct the ablty of dscount traders to hedge the underlyng assets and result n fluctuatons of ther dscount returns. For ths reason, we nclude the standard devaton of net asset value return as an explanatory varable. Partcular nvestment styles of closed-end funds may be assocated wth lower (hgher) standard devaton of net asset value returns. For example, nternatonal funds and venture captal funds tend to have lower volatlty of net asset value. Dversfcaton of assets wthn the closed-end funds portfolo lead to elmnate the rsk by reducng the dosyncratc varaton n the portfolo. Ths s consdered as one of the attrbutes of nternatonal funds that have dversfed portfolo of assets rather than, for example, domestc funds. Therefore, t s expected that ths type of funds wll have lower dscount volatlty. Another example s venture captal funds whch tend to have low volatlty of net asset value. Ths s because they manly nvest n unquoted assets that, by ther nature, are dffcult to value, so the net asset value of these funds s not very volatle. The second factor that we consder n our model s the marketablty of the closed-end fund shares. Low marketablty of the closed-end fund shares means that arbtrageurs would not be able to capture hgh dscount tradng profts resultng n a greater dscount tradng range and thus, hgher level of dscount volatlty. Funds wth a hgher level of marketablty tend to have hgher market value, ether because of lower tradng expenses or because nvestors consder marketablty n ther prcng of the shares (Longstaff, 1995). We therefore nclude ln(market value) as a proxy for marketablty n the model s explanatory varables. The last factor that we expect to have an nfluence on dscount volatlty s the percentage of unquoted assets n the portfolo of the closed-end fund. Some funds such as venture captal funds have a hgh percentage of underlyng assets whch are unquoted. These assets are not valued frequently and result n an artfcally stable net asset value of the fund. As share prces reflect the market perspectve of the value of these assets, the percentage of unquoted assets n the portfolo of the fund mght nfluence dscount volatlty. Hence, we add the percentage of unquoted assets wthn the fund s portfolo as an explanatory varable. The model for dscount volatlty s, therefore, as follows: Dscvol ln mv Lnmv stdevnavr unq Stdevnavr Unq, (2) where Dscvol s the dscount volatlty of fund, s the regresson constant, Stdevnavr s the standard devaton of net asset value of fund, Lnmv s the natural logarthm of the market value of fund, Unq s the percentage of assets whch are unquoted n the portfolo of fund. stdevnavr, lnmv and unq are the regresson coeffcents and s the error term that reflects all the factors that the model does not nclude Hard dscount control mechansms and dscount volatlty. As dscussed n secton one, closed-end fund can adopt ether soft or hard dscount control mechansms. The latter means that the fund has a rgorous dscount level that requres acton n order to return the dscount to the pre-specfed level. Most of closed-end fund that follow a hard dscount control mechansm n the UK use a share buyback strategy to nfluence the dscount and thereby stablze varaton n the dscounts. We expect that funds wth a hard dscount control mechansm to be assocated wth low levels of dscount volatlty. To examne the effect we add t as an explanatory varable along wth the standard devaton of net asset value returns and ln(market value). The reason for excludng unquoted assets from the second model s that the sample used does not nclude most types of fund that have sgnfcant amounts of unquoted assets, such as hedge funds, real estate funds, prvate equty and smaller companes specalsts. Therefore, the model s as follow: Dscvol stdevnavr HDCM Stdevnavr HDCM ln mv Lnmv, (3) where Dscvol s the dscount volatlty of fund, s the regresson constant, and HDCM s a dummy varable n whch 1 denote the funds that have a hard dscount control mechansm (HDCM) and 0 for the funds that do not mplement that strategy. Stdevnavr s the standard devaton of net asset value of fund, Lnmv s the natural logarthm of the market value of fund, HDCM, stdevnavr and lnmv are the regresson coeffcents and s the error term that reflects all factors that the model does not nclude. 71

5 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, Data and methodology As dscussed, the analyss s dvded nto two sectons; the frst consders the man factors that mght have an mpact on dscount volatlty and the other nvestgates the effect of adopton of a hard dscount control mechansm on the cross-sectonal varaton n dscount volatlty. We use a dfferent sample for each of the two parts due to the dfferent purpose of each of them and due to avalablty of the requred data from DataStream Data for secton one. The sample conssts of 184 funds operatng n the UK over the perod from 1 st July 2001 tll the end of June There are three types of closed-end fund n the UK; conventonal funds, venture captal funds and splt captal funds. Our sample contans only the frst two types of funds and we exclude the splt captal funds due to ther complcated structure. Net asset value and share prces (whch are used to calculate the dscount volatlty and the standard devaton of net asset value returns) and market value are obtaned from DataStream. The percentage of unquoted assets s also obtaned from the same source, although DataStream only reports the latest value of the varable rather than a tme seres. Table 1 contans the descrptve statstcs of the varables over the perod from 1 July 2001 to 30 June The average value of the dscount volatlty s 4.88% but ths may be affected by extreme values, as suggested by the medan and the maxmum value of dscount volatlty. Ths s not the case n the standard devaton of net asset value returns whch has closed values for both the mean and the medan. The medan value of the standard devaton of NAV returns s 5.48%, whch s 1.85% greater than the medan of the dscount volatlty. The standard devaton of both dscount volatlty and standard devaton of NAV returns s relatvely hgh. Market value ranges between approxmately 2m for Talsman 1st venture captal and 3670m for 3I Group. Ths wde range makes the standard devaton of the market value very hgh ( 382m). Table 1. Descrptve statstcs for the perod from 1 July 2001 to 30 June 2011 Dscvol Stdevnavr mv( m) Unq Mean 4.88% 5.57% % Medan 3.63% 5.48% % Maxmum 22.99% 14.04% % Mnmum 1.25% 1.43% 2 0% Std. dev. 3.20% 1.85% The average value of the percentage of unquoted assets s 22.86%, however there s a great varaton between closed-end funds n ther holdng of unquoted assets n ther portfolos Data for secton two. The second part of the analyss s concerned wth the nfluence of hard dscount control mechansms on the dscount volatlty. The sample conssts of 121 funds that operate n the UK over the perod from 1 July 2008 tll 30 June The reason for choosng only three years s to reduce the effect of changng the adopton of a hard dscount control mechansm wthn the perod. Four types of closed-end fund are excluded from the study because they are consdered to be unsutable for the adopton of hard dscount control mechansm. These types of fund are prvate equty funds, real estate specalsts, hedge funds and smaller companes specalsts. These funds have hgh percentage of unquoted assets n ther portfolos whch reduce lqudty whch s needed for a hard dscount control mechansm. In excludng these types of funds, addng the percentage of unquoted assets n the model has lttle value and s not sgnfcant. As shown n Table 2, the average value of dscount volatlty s 3.43% whch s relatvely close to the medan, wth maxmum level of 19.1% for Blue Planet Worldwde Fnancals Investment Trust. The average value of the standard devaton of net asset value returns s approxmately twce the average value of the dscount volatlty. Table 2. Descrptve statstcs for the perod from 1 July 2008 to 30 June 2011 Dscvol Stdevnavr mv( m) Unq Mean 3.43% 7.43% % Medan 3.01% 7.16% % Maxmum 19.10% 16.32% % Mnmum 1.13% 2.15% % Std. dev. 2.22% 2.12% % The four types of closed-end funds that we excluded tend to have lower market values than the others. Ths affects the average market value for ths sample so that t s 51m more than the average for the frst sample. The lowest market value s 8.72m for Blue Planet Internatonal Fnancals Investment Trust and the maxmum value n ths sample s 2,080m for Allance Trust. Data on whether funds have a hard dscount control mechansm s obtaned from J.P. Morgan Cazenove Investment Companes annual revew n 2008, 2009 and As mentoned n the last secton, hard dscount control mechansm s ncluded as a dummy varable wth value 1 for the funds that have such a mechansm and 0 for the funds that do not apply ths mechansm. 72

6 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 There are 31 funds n the sample that adopt a hard dscount control mechansm representng 26% of the whole sample. As shown by Table 2, the excluson of hedge funds, prvate equty, smaller companes and real estate specalsts reduces the average of the percentage of unquoted assets to 0.83% rather than 22.86% n the frst sample. The maxmum value of the percentage of unquoted assets n ths case s 16.5% and ts standard devaton declnes from 36.28% to 2.67%. 5. Emprcal fndngs Ths secton contans both an analyss of the factors that may nfluence the dscount volatlty and an examnaton of the effect of hard dscount control mechansms on the dscount volatlty. We carry out regressons usng the ordnary least squares method to mplement both of these studes. In the frst secton, we start by usng the whole sample perod to examne the factors that nfluence the dscount volatlty. Then we splt ths perod nto two fve perods to test the robustness of the regresson coeffcents. In the second secton, we add the hard dscount control mechansm as an explanatory varable to the regresson to show ts effect on dscount volatlty Factors that nfluence dscount volatlty. In model (1), there are three explanatory factors n the regresson, namely standard devaton of net asset value returns, the natural logarthm of market value and the percentage of unquoted assets wthn the fund s portfolo. Table 3 shows hgh negatve correlaton between standard devaton of net asset value returns and the percentage of unquoted asset n the fund s portfolo. Ths s a reasonable relaton as the unquoted assets are not subject to frequent changes n value and hence the aggregate value of the underlyng portfolo of assets wll be more stable than that of the underlyng portfolo for funds that have a low percentage of unquoted assets. There s also a negatve correlaton between the market value and the percentage of unquoted assets. Ths relatonshp results from the nature of the nvestment style of funds that have relatvely low market value. These funds manly nvest n smaller companes, prvate equty and real estate sectors whch tend to have a hgh percentage of unquoted assets n ther portfolos. Ths correlaton wll not be a problem when such types of fund are excluded from the sample. The expected sgn of the correlaton between dscount volatlty and standard devaton of net asset value returns s postve. As we dscussed n secton three, the hgh standard devaton of net asset value returns wll make t more dffcult for dscount anomaly traders to hedge the underlyng assets, and therefore the dscount returns wll be volatle. It s to be expected also that the correlaton between dscount volatlty and the percentage of unquoted assets wll be postve. The hgh percentage of unquoted assets wll result n a hstorcal valuaton of the underlyng assets and ths wll create dffcultes n the prcng of shares based on the net asset value. Ths n turn wll reduce the correlaton between the share prce and the net asset value per share, hence ncreasng the dscount volatlty. On the other hand, the expected sgn for the correlaton between dscount volatlty and market value s negatve. Funds wth hgher market value tend to have hgher levels of marketablty, whch wll work to reduce the varaton n the dscount. Table 3 shows the correlaton coeffcent between the dependant varable and ts explanatory varables together wth the correlatons between the explanatory varables. Table 3. Correlaton matrx for the perod from 1 July 2001 to 30 June 2011 Stdevnavr Ln(mv) Dscvol Stdevnavr ln(mv) Unq As expected, the correlaton coeffcent between dscount volatlty and both the standard devaton of net asset value returns and the percentage of unquoted assets s postve and wth the market value s negatve. However, the correlaton between the percentage of unquoted assets and market value s hgh suggestng the possblty of a multcollnearty problem n the regresson. The multple regresson results support the expectatons that all the explanatory varables n the model have an effect on the level of dscount volatlty. The explanatory varables are all sgnfcant at the 0.5% sgnfcance level. Table 4. Regresson results of the effect of explanatory varables on dscount volatlty for the perod from 1 July 2001 to 30 June 2011 Explanatory varables Constant Stdevnavr Ln(mv) Unq R 2 = 0.53 Coeffcents (Standard error) ( ) ( ) ( ) ( ) t-statstc p-value As mentoned n the prevous secton, the percentage of unquoted assets wthn the fund s portfolo s a 73

7 Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 hstorcal value whch not subject to hgh changes. Ths mght explan the hgh sgnfcance of ts coeffcent. However, ts coeffcent mght be affected by the multcollnearty problem ndcated by the hgh correlaton wth the standard devaton of net asset value returns. The adjusted R-square s 0.53 ndcatng the percentage of the dscount volatlty explaned by the explanatory varables n the model. As a robustness test, we dvde the sample perod nto two fve years perods; the frst starts from 1 July 2001 to 30 June 2006 and the second startng from 1 July 2006 to 30 June Table 5 and Table 6 show the regresson results for the two perods. Table 5. Regresson results of the effect of explanatory varables on dscount volatlty for the perod from 1 July 2001 to 30 June 2006 Explanatory varables Constant Stdevnavr Ln(mv) Unq R 2 = 0.56 Coeffcents (Standard error) ( ) ( ) ( ) ( ) t-statstc p-value Table 6. Regresson results of the effect of explanatory varables on dscount volatlty for the perod from 1 July 2006 to 30 June 2011 Explanatory varables Constant Stdevnavr Ln(mv) Unq R 2 = 0.49 Coeffcent (Standard error) ( ) ( ) ( ) ( ) t-statstc p-value The second set of regressons show no changes n the sgns for all the explanatory varables compared wth the 10 years perod regresson; however, there are some dfferences n both the coeffcents and the degree of the sgnfcance for these varables. The results show that both the standard devaton of net asset value returns and the percentage of unquoted assets n the second perod are more hghly sgnfcant than the frst perod. Moreover, the market value varable has a hgher sgnfcance n the frst perod compared to the second and the whole perod. Ths change n the level of the sgnfcance mght partly reflect the correlaton between market value and the percentage of unquoted assets n the fund s portfolo Hard dscount control mechansm and dscount volatlty. In ths second part of the analyss, the sgns of coeffcents for standard devaton of net asset returns and the percentage of unquoted assets wll be the same as for the frst part of the analyss. It s expected that the sgn of the coeffcent of the hard dscount control mechansm varable wll be negatve, as control of the dscount should lower the dscount volatlty. If the dscount wdens n a short perod, funds that adopt the hard dscount control mechansm should drectly take an acton to keep the dscount at the pre-specfed level. The correlaton matrx between the explanatory varables s shown n Table 7. There s no correlaton between the explanatory varables n the model; therefore, there s no multcollnearty problem n ths case. The correlaton between dscount volatlty and all the explanatory varables supports the expectaton of sgns n the relatonshp. Table 7. Correlaton matrx for the perod from 1 July 2008 to 30 June 2011 HDCM Stdevnavr Dscvol HDCM Stdevnavr Ln(mv) Table 8 shows the regresson results of the mpact of the hard dscount control mechansm along wth the standard devaton of net asset value returns and the market value on the dscount volatlty of closed-end funds. As n the last regresson, standard devaton of net asset value returns and market value are sgnfcant at the 0.5% sgnfcance level. Market value s more hghly sgnfcant than both the hard dscount control mechansm and the standard devaton of net asset value returns. The sgn of the hard dscount control mechansm s as expected but ts coeffcent s only sgnfcant at the 5% level. Ths result rases questons about the strength of the mplementaton of the hard dscount control mechansm as a strategy for controllng the dscount and managng ts volatlty. Table 8. Regresson results of the mpact of HDCM on dscount volatlty for the perod from 1 July 2008 to 30 June 2011 Explanatory varables Constant HDCM Stdevnavr Ln(mv) R 2 = 0.42 Coeffcent (Standard error) ( ) ( ) ( ) ( ) t-statstc p-value A lkely explanaton of the low level of the sgnfcance of the hard dscount control mechansm s 74

8 that closed-end funds that adopt such mechansms do not apply them wth suffcent rgour. Data from J.P. Morgan Cazenove Investment Companes Annual Revews support ths explanaton. The revews report on the closed-end funds that have a hard dscount control mechansm and whether or not these funds are at ts dscount control target. In 2008, only 29% of the funds that were adoptng a dscount control mechansm were at ther dscount target, whle n 2009, the percentage rose to 38%. In 2010, the percentage rose even further to approxmately twce ts fgure n 2009 to reach 64% of the funds that were adoptng a hard dscount control mechansm. Conclusons Ths work examnes the factors that mght nfluence the dscount volatlty of closed-end funds n the UK. Standard devaton of net asset value returns, market value and percentage of unquoted assets n the fund s portfolo, are hghly sgnfcant. References Investment Management and Fnancal Innovatons, Volume 10, Issue 3, 2013 As a robustness test, we splt the sample perod nto two fve years perods and carry out the regresson. The result supports the frst regresson wth hgh sgnfcance of all the three factors. However, for both the regressons, there s hgh correlaton between market value and percentage of unquoted assets and between the latter and the standard devaton of net asset value returns, suggestng the possblty of a multcollnearty problem. The second part of the work consders the effect of the hard dscount control mechansm on the dscount volatlty of closed-end funds. The results show that the adopton of a hard dscount control mechansm reduces the level of the dscount volatlty. However, ths relatonshp s only just sgnfcant at the 5% level. An explanaton of ths weak result s that closed-end funds that commt to a hard dscount control mechansm do not apply t suffcently rgorously. 1. Adams, A.T. (2000a). Components of Rsk for Investment Trusts, UK: Ednburgh Unversty. 2. Adams, A.T. (2000b). Excess Volatlty And Investment Trusts, Cfmr Ed. UK: Management School and Economcs, The Unversty Of Ednburgh. 3. Adams, A.T. & Angus, R. (2011). Investment Trusts: Why Not Elmnate The Dscount? Professonal Investor. 4. AIC (2010). A Handbook for Drectors of Investment Companes, UK: The Assocaton of Investment Companes. 5. Berk, J.B. & Stanton, R. (2007). Manageral Ablty, Compensaton, and the Closed-End Fund Dscount, The Journal of Fnance, 62, pp Brown, C., Hales, J. & Parknson, N. (1998). Do Buybacks Work? Cazenove Research, London, UK: Cazenove. 7. Dmson, E. & Mno-Kozersk, C. (1999). Closed-End Funds: A Survey, Fnancal Markets, Insttutons & Instruments, 8, pp Fama, E.F. (1970). Effcent Captal Markets: A Revew of Theory and Emprcal Work, The Journal of Fnance, 25, pp Longstaff, F.A. (1995). How Much Can Marketablty Affect Securty Values? The Journal of Fnance, 50, pp Malkel, B.G. & Xu, Y. (2005). The Persstence and Predctablty of Closed-End Fund Dscounts, SSRN Elbrary. 11. Pontff, J. (1997). Excess Volatlty and Closed-End Funds, The Amercan Economc Revew, 87, pp Shller, R.J. (1981). Do Stock Prces Move too Much to be Justfed by Subsequent Changes n Dvdends? The Amercan Economc Revew, 71, pp

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