Qatar Today - - DEVELOPMENT -

While the fi­nan­cial mar­kets took a bat­ter­ing last year and lay at the mercy of oil prices, two CMU-Q pro­fes­sors helped de­velop smart beta port­fo­lios that could weather th­ese tur­bu­lent con­di­tions.

While it is no se­cret that Qatar is an econ­omy that is heav­ily de­pen­dent on oil and gas, there has been a de­lib­er­ate and con­scious ef­fort by the gov­ern­ment of the State of Qatar to di­ver­sify and re­duce its reliance on com­mod­ity mar­kets. As a re­sult, a num­ber of the large lo­cal en­ter­prises have been seek­ing off­shore in­vest­ment op­por­tu­ni­ties to smooth out the highs and lows of com­mod­ity price move­ments and add sta­bil­ity to their op­er­a­tions.

“We put th­ese ef­forts to the test by de­sign­ing a smart beta port­fo­lio of com­pa­nies se­lected from the Qatar Stock Ex­change (QSE) and test­ing their per­for­mance against the re­cent oil price de­cline. This project was run as part of Fi­nan­cial Mar­kets, a cap­stone busi­ness ed­u­ca­tion course at Carnegie Mel­lon Univer­sity in Qatar (CMU- Q). The project used Q- SmartLab, a CMU- Q ini­tia­tive that fa­cil­i­tates big data an­a­lyt­ics to sup­port aca­demic re­search, cur­ricu­lum ex­pan­sion and projects that pro­vide cut­ting-edge so­lu­tions to cor­po­rate part­ners,” say Dr John O'Brien, As­so­ciate Dean and As­so­ciate Pro­fes­sor of Ac­count­ing and Dr Fuad Fa­rooqi, As­sis­tant Teach­ing Pro­fes­sor of Fi­nance at CMU- Q.

The Fi­nan­cial Mar­kets course had stu­dents screen all of the com­pa­nies listed on the QSE along dif­fer­ent met­rics like earn­ings qual­ity, liq­uid­ity and mar­ket depth. Work­ing with a short­listed set of firms, the stu­dents con­ducted a de­tailed fun­da­men­tal anal­y­sis of each com­pany to ar­rive at an in­trin­sic value.

This anal­y­sis ac­counted for growth pro­jec­tions in light of the oil price move­ment and how this would im­pact the sales and costs. While the anal­y­sis was sim­ple in some cases, in other firms the oil price drop posed down­ward pres­sure on both rev­enue and costs; us­ing quan­ti­ta­tive tools, the stu­dents ar­rived at the net im­pact on th­ese firms to come up with the tar­get share price.

It is chal­leng­ing, to at­tempt to fig­ure out how low oil prices would af­fect each of the com­pa­nies. “Take the ex­am­ple of a con­sumer goods com­pany,” says Dr Fa­rooqi. “While nat­u­rally the cost of lo­gis­tics, like im­port­ing and trans­porta­tion, may have gone down, other fac­tors like a de­mand slow­down would have a neg­a­tive im­pact.” So the team had to an­a­lyse each case deeply to tie in all the vari­ables.

“Map­ping the in­trin­sic value against the mar­ket price, we com­puted the ex­pected re­turn for each se­lected firm. This for­ward­look­ing mea­sure of re­turn, cou­pled with the his­tor­i­cal volatil­ity, was used to ar­rive at an op­ti­mal port­fo­lio mix from this group of 15 firms. As a risk mit­i­ga­tion mea­sure, we en­sured that our sin­gle firm or in­dus­try ex­po­sure was capped at cer­tain lev­els to al­low the op­por­tu­nity to di­ver­sify,” says Dr O'Brien.

The fi­nal port­fo­lio in­cluded ten firms that, when com­bined to­gether, helped the re­turns stay in­su­lated from mar­ket swings (see chart). It is ev­i­dent that the re­turns were not im­pacted too much by the drop in the com­mod­ity mar­ket, which can be con­strued as the suc­cess of the lo­cal econ­omy to di­ver­sify so that the com­pa­nies, col­lec­tively, re­main pro­tected from a re­peat of the swings in prices re­cently seen in oil and gas.

While this par­tic­u­lar method­ol­ogy is pro­pri­etary and was de­vel­oped for ed­u­ca­tional pur­poses and not for use by any ex­ter­nal agency, it would buoy the prospects of in­vest­ment firms in the re­gion to fine-tune their port­fo­lios. Dr Fa­rooqi as­serts that de­spite the cli­mate, there are still gems in the fi­nan­cial mar­kets and sci­en­tif­i­cally as­sisted port­fo­lio build­ing can still help you turn prof­its.

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