Risk Per­spec­tives for Com­modi­ties and Stock Mar­kets in In­dia

Economic Challenger - - CONTENTS - − Dr. S.D. Vaishtha & − Dr. Ummed Singh

AB­STRACT

This study pro­vides op­por­tu­ni­ties to de­ci­sion−mak­ers for hedg­ing the fluc­tu­a­tions of one mar­ket. In this pa­per, an at­tempt has been made to ex­am­ine the na­ture of risk in In­dian com­mod­ity (Agri prod­ucts) and stock mar­kets. To mea­sure the volatil­ity of the se­lected mar­kets, av­er­ages and stan­dard de­vi­a­tions were used, and to study the di­rec­tion be­tween the prices of com­mod­ity and stock mar­kets, Pear­son’s co­ef­fi­cient of cor­re­la­tion was ap­plied. It was ob­served that In­dian com­mod­ity and stock mar­kets were not sim­i­lar on the ba­sis of risk.

Key Words: Com­mod­ity mar­ket, Share mar­ket, Risk,

IN­TRO­DUC­TION

When an in­di­vid­ual, an in­sti­tu­tion, a com­pany and a group of any of th­ese want to park their funds to earn yield in fu­ture, the volatil­ity of mar­ket needs to be un­der­stood. If an in­vestor wants to go with share mar­ket and com­mod­ity mar­ket, the volatil­ity in over­all mar­kets would re­quire thor­ough anal­y­sis be­fore mak­ing an in­vest­ment de­ci­sion. This over­all mar­ket volatil­ity will help in­vestors to un­der­stand the na­ture and quan­tity of over­all mar­ket risks and this anal­y­sis helps to pro­tect de­ci­sion−mak­ers’ funds from risks of spec­u­la­tive mar­ket op­er­a­tions. In the present re­search work, some ef­forts have been made by the re­searcher to un­der­stand the na­ture of risks and to pro­vide some sig­nif­i­cant risk based in­di­ca­tiors to safely play in com­mod­ity or stock mar­kets.

OVER­ALL MAR­KET RISKS (IN COM­MOD­ITY AND STOCK MAR­KETS)

The over­all mar­ket risk refers to the rate of gy­ra­tion in in­dex prices of that mar­ket or on the other hand, it is the prob­a­ble de­vi­a­tion from the ex­pected in­dex prices.

RE­VIEW OF LIT­ER­A­TURE

In the past, var­i­ous re­search works have been con­ducted on this topic and some of the renowned works are men­tioned be­low:

Ku­mar, et. al., (2008) made an em­pir­i­cal study of volatil­ity, risk pre­mium and sea­son­al­ity in risk−re­turn re­la­tion of the In­dian stock mar­ket and com­mod­ity mar­ket and com­mod­ity mar­kets. Volatil­ity clus­ter­ing and asym­met­ric na­ture were ex­am­ined for In­dian stock and com­mod­ity mar­kets. The risk−re­turn re­la­tion­ship and sea­son­al­ity in risk−re­turn were also an­a­lyzed by the re­searcher with the help of in­dex S&P CNX Nifty for a pe­riod of 18 years and with the help of com­mod­ity (Gold and Soy­bean) prices.

They found that, asym­met­ric prop­erty was showed by stock and com­mod­ity mar­kets and risk−re­turn−re­la­tion­ship was pos­i­tive though in­signif­i­cant for Nifty and Soy­bean whereas sig­nif­i­cant pos­i­tive re­la­tion­ship was found in the case of Gold.

Roy, et al. (1995) fo­cused on two key is­sues, namely: (a) what is the av­er­age level of volatil­ity and whether it has in­creased in the cur­rent pe­riod; (b)whether the present trend of share price

move­ment is likely to im­pair the devel­op­ment process of our econ­omy through the study ’Stock Mar­ket Volatil­ity: Roots and Re­sults’. In this study, they ex­am­ined that, sev­eral volatil­ity mea­sures based on dif­fer­ent price in­dices had been used to eval­u­ate the stock price move­ments in his­tor­i­cal per­spec­tive. In such, in­stance, the con­clu­sion was es­sen­tially the same, i.e., stock mar­ket volatil­ity had in­creased in that pe­riod if the changes in share prices had been in re­sponse to fun­da­men­tal eco­nomic fac­tors.

Ruddy, (1996) an­a­lyzed the volatil­ity of se­cu­ri­ties traded on the Na­tional Stock Ex­change ( NSE) and the Bom­bay Stock Ex­change (BSE). In this study, re­searcher em­ployed stock mar­ket trad­ing data re­lat­ing to about 3,000 se­cu­ri­ties traded on Bom­bay Stock Ex­change (BSE) and over 1,000 se­cu­ri­ties traded on NSE. Volatil­ity of in­di­vid­ual se­cu­ri­ties was also an­a­lyzed in this study and it was found that the se­cu­ri­ties traded on BSE had more volatil­ity than the se­cu­ri­ties traded on NSE. The re­searcher also showed through this study that In­dian Cap­i­tal Mar­kets were highly volatile.

Hun­jra, et.al. (2011), made a study to de­ter­mine the risk and re­turn re­la­tion­ship on the ba­sis of uni­vari­ate mod­el­ing ap­proach. To at­tain this ob­jec­tive the data were an­a­lyzed re­gard­ing gold price, cot­ton price and sugar price along with KSE 100 in­dex (for the time pe­riod of ten years) by the re­searchers. They found that, asym­met­ric and sea­sonal ef­fects were present in com­mod­ity mar­ket and stock mar­ket but asym­met­ric prop­er­ties and sea­sonal ef­fects were most dom­i­nant in the stock mar­ket prices com­par­a­tive to other com­modi­ties.

OB­JEC­TIVES OF THE STUDY

The ob­jec­tives of the present study are:

1. To study the na­ture of risk within mar­kets (Com­mod­ity and Stock mar­kets).

2. To study the re­la­tion­ship be­tween se­lected in­dices un­der the study.

STUDY AREA AND UNITS

The study is con­cerned with the in­dices se­lected from the In­dian com­mod­ity and share seg­ment. One in­dex (Dhaanya) was se­lected from the Na­tional Com­mod­ity and De­riv­a­tives Ex­change Ltd (NCDEX) and an­other in­dex (Sen­sex−30) was taken from Bom­bay Stock Ex­change (BSE). Both mar­kets (NCDEX and BSE) were matched for their tech­nol­ogy, trans­parency, in­de­pen­dent board of direc­tors and pro­fes­sional man­age­ment. Unit Pro­file: Unit wise pro­file of the se­lected units is given be­low: Sen­sex−30: Sen­sex is the pulse of the In­dian stock mar­kets. It was launched in 1986 by Bom­bay Stock Ex­change to rep­re­sent the whole mar­kets´ trend. It rep­re­sents the trend in whole mar­ket on the ba­sis of gy­ra­tion in prices of its’ 30 con­stituents and for the pur­pose of in­dex cal­cu­la­tion Free−float Mar­ket Cap­i­tal­iza­tion method­ol­ogy is used. Dhaanya: Dhaanya is an agri­cul­tural com­modi­ties in­dex com­puted by Na­tional Com­mod­ity and De­riv­a­tives Ex­change Ltd. The in­dex val­ues are cal­cu­lated us­ing the prices of 10 agri­cul­tural com­modi­ties traded on the NCDEX plat­form. The com­po­nents of Dhaanya are se­lected from di­verse sub sec­tors of the In­dian agri in­dus­try and ac­count for nearly 70% of trad­ing on the NCDEX plat­form.

SAM­PLE DE­SIGN

A to­tal of two in­dices (Dhaanya and Sen­sex−30.) were se­lected by ac­ci­den­tal sam­pling. Sam­pling de­sign is given in the Table1.

PRO­CE­DURE OF DATA COL­LEC­TION

Anal­y­sis of ev­ery re­search work is based on rel­e­vant data and it can be col­lected by two ways: by way of pri­mary data col­lec­tion and by way of sec­ondary data col­lec­tion. In our study, sec­ondary data about two units have been col­lected from dif­fer­ent sources, th­ese were: (A) News pa­pers:− (i) The Eco­nomic Times, and (ii) The Times of In­dia (B) Web­sites:− (i) Web­site of Bom­bay Stock Ex­change of In­dia −http://www.bsein­dia.com (ii) Web­site of Na­tional com­mod­ity and De­riv­a­tives Ex­change −http://www.ncdex.com Data col­lected from all the sources were matched in the man­ner of con­sis­tency and fi­nally the data (clos­ing prices re­lated to in­dices) col­lected from the web­site of BSE and web­site of NCDEX were taken for the anal­y­sis pur­poses.

TIME PE­RIOD

Ev­ery re­search work is al­ways lim­ited by short­age of time and re­sources. There­fore, un­der the study, prices of se­lected units from April, 2011 to March, 2012 were an­a­lyzed by the re­searcher with the help of mean, stan­dard de­vi­a­tion and Pear­son’s cor­re­la­tion.

STA­TIS­TI­CAL METH­ODS

To meet the ob­jec­tives of the study, raw data were treated with dif­fer­ent kinds of anal­y­sis. For car­ry­ing out the anal­y­sis the dif­fer­ent types of sta­tis­ti­cal tools were used like, to know the volatil­ity within the mar­kets, mean and stan­dard de­vi­a­tion were used.

To study the na­ture of risk within the mar­kets the volatil­ity was mea­sured in the clos­ing prices of Sen­sex−30 and Dhaanya in­dices with the help of av­er­ages and stan­dard de­vi­a­tions. The data are of monthly na­ture. Month to month volatil­ity was ar­rived at by assess­ing the stan­dard de­vi­a­tions. It was found that volatil­ity was in­creas­ing or de­creas­ing in the re­verse trend of the prices of Sen­sex−30 and it was un­cer­tain of na­ture when prices of Sen­sex− 30 were in sta­ble po­si­tion (as in­di­cated in Ta­ble− 2 and Chart−1 and 2). Volatil­ity in prices of Dhaanya in­dex was un­cer­tain of na­ture dur­ing the pe­riod of April to Novem­ber and af­ter that, it was go­ing up in same di­rec­tion as in­dex prices (as in­di­cated in Ta­ble−2 and Chart−1 and 2).

To ex­am­ine the as­so­ci­a­tion be­tween the move­ments of Senex−30 and Dhaanya in­dices the daily clos­ing prices of monthly na­ture were an­a­lyzed with the help of Pear­son’s co­ef­fi­cient of cor­re­la­tion and then it was found that the prices of both in­dices were neg­a­tively cor­re­lated in many months. High level of neg­a­tive as­so­ci­a­tion was found in the month of De­cem­ber only, mod­er­ate neg­a­tive cor­re­la­tion was found in the months of April, May, July, Septem­ber and March and low level of neg­a­tive cor­re­la­tion was found in the months of Au­gust and Novem­ber. High level of pos­i­tive cor­re­la­tion was found in the prices of both in­dices in the months of Oc­to­ber and Jan­uary and mod­er­ate pos­i­tive cor­re­la­tion was found in the months of June and Fe­bru­ary.

FIND­INGS

1) The risk trend in the value of Sen­sex−30 was re­verse to price move­ments. 2) The risk in the value of Dhaanya in­dex was of gy­rated na­ture. 3) Re­la­tion­ship be­tween both the in­dices was found neg­a­tively cor­re­lated in many of the months.

CON­CLU­SION

With the above study it can now be con­cluded that In­dian com­mod­ity mar­kets and stock mar­kets are dis­sim­i­lar on the ba­sis of na­ture of risk. This study also in­fers that, wiser in­vest­ment de­ci­sions can be taken by in­vestors or they can se­lect the more ap­pro­pri­ate mar­ket through un­der­stand­ing of the over­all risk within the mar­ket. This study also leads the de­ci­sion− mak­ers to play a strate­gic game against the risks be­tween two and more than two mar­kets.

REF­ER­ENCES

1. Ku­mar, Bra­jesh and Singh, Priyanka, "Volatil­ity Mod­el­ing, Sea­son­al­ity and Risk− Re­turn Re­la­tion­ship in Garch−in−Mean Frame­work: The Case of In­dian Stock and Com­mod­ity Mar­kets", The 5th Con­fer­ence of Asia−Pa­cific As­so­ci­a­tion of De­riv­a­tives Pa­per, June−2008, Avail­able at SSRN: htpp://ssrn.com/ab­stract=1140264 2. Hun­jra, Ah­mad Im­ran, Azam, Muham­mad, Ni­azi, Ghu­lam Shab­bir Khan, Butt, Babar Za­heer, Rehman, Kashif Ur and Azam, Rauf I., "Risk and Re­turn Re­la­tion­ship in Stock mar­ket and Com­mod­ity Prices: A Com­pre­hen­sive Study of Pak­istani mar­kets", World Ap­plied Sciences Jour­nal, Vol. 13, No. 3, 2011, pp.470−481. 3. Roy, Malay K and Kar­makar, Mad­husu­dan (1995), "Stock Mar­ket Volatil­ity: Roots and Re­sults", Vikalpa, Vol. 20, No. 1, Jan­uary −March 1995, p.p. 37−48. 4. Reddy, Yar­ram Subha (1996), "Volatil­ity of Se­cu­ri­ties Traded on the Na­tional Stock Ex­change and Bom­bay Stock Ex­change: A Com­par­i­son", De­ci­sion, Vol. 23, No. 1−4, Jan−Dec 1996, p.p. 1−24.

Source: Based on Ta­ble−2

Chart−1: Month wise Mean Prices of In­dices

Source: Based on Ta­ble−2

Chart−2: Month wise Volatil­ity of In­dices

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