Rice Futures Trading Activity & Spot Price Volatility
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1 Rice Fuures Trading Aciviy & So Price Volailiy
2 Theory Emirical Work Rice Fuures Marke Economerics Resuls
3 Theory Why should he level of fuures rading aciviy affec so rice volailiy? Maniulaion and echnical facors disor fuures rices, and raders in he fuures marke ac on false signals Lack of seculaion in he fuures marke and ure hedge rading in ha marke could lead o insabiliy in he so marke raders in he fuures marke are no as well informed as he aricians in he so marke
4 Emirical Works Bessembinder e al (992) Equiy Markes Aniciaed fuures rading aciviy lowers so rice volailiy Unexeced fuures rading aciviy increases so rice volailiy ang e al (2005) Agriculural Commodiy Markes Unexeced increase in fuures rading volume Granger causes so rice volailiy This causaliy is weak when i comes o oen ineres Unexeced increase in fuures rading volume exlain a significan variaion in so rice volailiy (FEVD )
5 Execed vs. Unexeced Trading Aciviy Why searae commercial and non-commercial rading aciviy? (Figlewski 98) Commercial ineres is informed Non-commercial ineres is no as well informed Theory (Kyle 985 Admai & Pfleiderer 988): Order imbalances generae smaller rice volailiy when marke has a large number of informed raders Theory (Es & Es 976) The more raders disagree (less informed) on he valuaion effec of new informaion, he higher he volailiy and volume
6 Rice Fuures Marke Hisory Dojima rice fuures marke in Osaka New Orleans fuures marke Chicago Coon & Rice Exchange CBOT 99 o resen
7 Rice Fuures on CBOT Thin rading relaive o oher major grains Trading volume of corn & whea conracs exiring May 200 were 83 & 2783 and ha of rice was 32 (March 8 h 200) Increase in non-commercial ineres 23% of long oen ineress in 99 55% of long oen ineress in 2009 Decrease in share of non-commercial shor osiions
8 Raw Daa Weekly rice so rices ( ) U.S. No. 2 Long Grain Paddy rice Fuures volume & oen ineress from Daasream ( ) Volume and oen ineress from he neares conrac, and rolled over on he las rading day of ha conrac
9 Mehodology Esimae so rice volailiy-garch (,) Divide fuures rading aciviy ino oen ineres & rading volume Isolae he unexeced ar of he rading volume and oen ineres Subrac he four week moving average from he weekly average o derend Use ARIMA model o searae he execed and unexeced movemen in rading volume and oen ineres Use BIC o deermine he mos aroriae ARIMA model ARIMA (,0,9) o esimae execed TV ARIMA (,,) o esimae execed OI
10 Mehodology Use Granger Causaliy es o see if eiher unexeced rading volume or oen ineres cause cash rice volailiy Bivariae VAR model Forecas Error Variance Decomosiion o deermine he magniude of variabiliy in cash rice volailiy due o level of rading aciviy Bivariae recursive VAR model
11 Resuls Granger Causaliy Tes UTV χ 2.5 (+) df 5% Forecas Error Variance Decomosiion Imulse Resonse 96.% UTV 3.9% o q q UTV q
12 Resuls Granger Causaliy Tes UTV χ (-) df Forecas Error Variance Decomosiion Imulse Resonse UTV.6% UTV UTV 98.% UTV o q q UTV q
13 Resuls Granger Causaliy Tes UOI χ (-) df Forecas Error Variance Decomosiion Imulse Resonse 99.7% UOI 0.3% o q q UOI q
14 Resuls Granger Causaliy Tes UOI χ (+) df % Forecas Error Variance Decomosiion Imulse Resonse UOI UOI 95.% UOI.9% UOI o q q UOI q
15 Resuls (differen order) Forecas Error Variance Decomosiion Imulse Resonse 93.2% UTV 6.8% UTV 0.7% UTV UTV 99.3% o q UTV q q UTV o q UTV q q
16 Resuls (differen order) Forecas Error Variance Decomosiion Imulse Resonse 99.5% UOI 0.5% UOI.0% UOI UOI 96% o q UOI q q UOI o quoi q q
17 Fuures & So rices Granger Causaliy Tes FV χ (-) df Forecas Error Variance Decomosiion Imulse Resonse 99.5% FV 0.5% o i i FV i
18 Fuures & So rices Granger Causaliy Tes FV χ (-) df Forecas Error Variance Decomosiion Imulse Resonse FV 0.9% FV FV 89.% FV o i i FV i
19 Fuures & So rices Forecas Error Variance Decomosiion Imulse Resonse 97.5% FV 2.5% FV 8.08% FV FV 9.9% o i FV i i FV o i FV i i
20 Aendix ARIMA (,0,9) ARIMA (,,) ^ 2... ) (... ) ( ) ( e e e 2 ) (
21 Aendix Recursive VARs q q q o q q q o error UTV a UTV error UTV a
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3. Caial gains ax and e sock rice volailiy Our main urose in is secion is o underake an examinaion of e sock rice volailiy by considering ow e raional seculaor s olding canges afer e ax rae on caial gains
Introduction D P. r = constant discount rate, g = Gordon Model (1962): constant dividend growth rate.
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