PERFORMANCE ASSESSMENT OF AGRICULTURAL FUTURES MARKETS IN INDIA

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PERFORMANCE ASSESSMENT OF AGRICULTURAL FUTURES
MARKETS IN INDIA

• JATINDER BIR SINGH
• NCDEX Institute of Commodity Markets and Research
  (NICR)

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Need for study???

• Almost three and half years of futures trading in
  agricultural commodities
• Agricultural futures are more relevant in an
  agrarian economy like India
• To know clearly how have they fared? Do they need
  some change? What are their effects on prices?
• What ails futures trading in agricultural
  commodities?

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EMPIRICAL QUESTIONS

• To look into the inter-relationship between the
  spot and futures markets for the agricultural
  commodities.
• Study the role of the different participants in
  the futures market and the inter-relationship
  between the commercial hedgers and the
  speculators.
• Forecasting ability of futures prices
• Hedging efficiency of agricultural futures
  markets
• Price influence on physical markets.

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DATA

• Daily futures prices and spot prices of
  agricultural commodities-pepper, soya oil, jeera,
  chana, guar seed, mentha oil, castorseed, wheat,
  from NCDEX, MCX and NMCE
• Also production and imports data to look at total
  supply
• Hedging limits utilized by hedgers
• Primary spot price data in maturity month

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HypothesisConvergence of spot and futures

• Arbitrage should force convergence and basis
  should approach zero at expiration. So no basis
  risk and no need to predict convergence.
• If perfect convergence doesnt exist it means
  existence of delivery options and costs of
  arbitration

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Methodology Predictability of Basis

• Return to short hedgerX(B2-B1)
• Convergence of SP and FP at maturity of contract
• ?Bt ? ?B1t ?t
• Regress change in basis (B2-B1) on initial basis
  (B1)slope-1, intercept0
• Initial basis (B1) basis immediately after the
  expiry of preceding contracts
• Final basis(B2) 1st trading day of expiration
  month and delivery day

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Arbitrage Principle-Mispricing

• Xt,TF t,T-Ste(rs-d)(T-t) is difference
  between FP and theoretical spot price
• Departure of X t,T outside a range means lack of
  arbitrage capital.
• Is Mispricing time dependent on maturity

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Likely explanation--?

• Futures prices quote higher than fundamental
  values (accg to stock-to-use ratio)
• Wrong polling methods-not representative spot
  prices
• Prices quoted refer to different quality
• Cartel among traders

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Futures Prices as Forecasts

• Fti ? ?Ft ?ti
• where Ft is forecast and Fti is actual price
  realization
• Or alternatively
• Fti- Ft ? (?-1)Ft ?ti
• where i can be maturity or can be before
  maturity. This is forecast evaluation tool.
• Week-form efficiency ? ?-10
• Current price is the best estimate of coming
  price and has no ability to forecast prices.

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Forecasting Efficiency

• Evaluation equation
• Pti- Pt ? ?(Ft-Pt ) ?ti (1)
• or Pti ? ?Ft-?Pt ?ti (2)
• Where ?1- ?
• The evaluation eqn.(2) have large R2 but may have
  little or no ability to forecast price change.
  Same with basis equation (1)

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Forecasting Efficiency-technical issues

• Appraisal of efficiency of different maturity
  months separately vs. judging efficiency of all
  pooled contracts in one equation.
• The effects of outliers
• The nature of price distribution including the
  possibility of nonstationary series
• The possibility of bias of OLS estimator in
  fitting models with a lagged endogeneous
  variables
• If Jeera actual December 2007 prices are
  underestimated by October futures Prices, doesnt
  mean market is inefficient.

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HEDGING EFFICIENCY
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HEDGING EFFICIENCY
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Hedging effectiveness
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Hedging effectiveness
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Hedging effectiveness
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PRICE INFLUENCE

• Hypothesis Futures prices influences inventory
  decisions and hence stabilize effect on spot
  prices
• Methodology
• nit
• Mit ( ? (pitj p itj-1)2 / nit )1/2
• j1
• where Mit is the volatility of month i in
  year t (monthly volatility of weekly changes),
  nit are number of the weeks in month i in year t
  and pitj is the price in week j in month i in
  year t.
• Normalized variance Vit Mit / pit
• where pit is average monthly price.

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PRICE INFLUENCE

• 11
• In Vta b InPt ?cjdjt aD b(DIn Pt)
• j1
• 11
• ? cj(D djt) ?
• j1
• where dj are monthly dummy variables, where
  j1,2,3,11 denote the eleven dummies for 12
  months of the season. D stand for the dummy for
  the period 2004-2007.
• Use model selection criteria-AIC, SBC

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Price Inluence

• dj can tell us about seasonal nature of
  volatility----Does futures trading help changing
  intra-seasonal volatility.
• Most important issue is inter-year price
  variability. Futures markets encourage rate of
  storage hence stabilize spot prices.
• We can also look at intertemporal price
  relationships to know the effects of futures
  markets on allocating inventories with in a year.
• Improvements- We can use time varying volatility
  changing the length of estimation window. Can use
  rolling estimation-extending estimation by one
  period. To take time-dependence we use
  exponentially weighted volatility estimates.

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THANK-YOU