Final_1.pdf

(Tuis.) #1

  1. Once the potential pairs are identified, we verify the proposed hypoth-
    esis that the stock pairs are indeed cointegrated based on statistical evi-
    dence from historical data. This involves determining the cointegration
    coefficient and examining the spread time series to ensure that it is sta-
    tionary and mean reverting.

  2. We then examine the cointegrated pairs to determine the delta. A feasi-
    ble delta that can be traded on will be substantially greater than the slip-
    page encountered due to the bid-ask spreads in the stocks. We also
    indicate methods to compute holding periods.


SUMMARY


Statistical pairs trading is a relative value arbitrage on two securities and
is based on the premise that there is a long-run equilibrium between the
prices of the stocks composing the pair.
The degree of deviation from the long-run equilibrium is called the
spreadand represents the extent of mutual mispricing.
Any deviation from the long-run equilibrium is compensated for in sub-
sequent movements of the time series.
Pairs trading involves trading on the oscillations about the equilibrium
value.
The econometric paradigm of cointegration and error correction is cen-
tral to the analysis of the pairs-trading strategy.

FURTHER READING MATERIAL


Pairs Trading


Gatev, Evan, G., William, N. Goetzmann, and K. Greet Rouwenhorst. Pairs Trading:
Performance of a Relative Value Arbitrage Rule. NBER Working Papers 7032,
National Bureau of Economic Research Inc., 1999.


Cointegration


Engle, Robert F. and C. W. Granger. “Co-integration and Error Correction: Repre-
sentation, Estimation and Testing.” Econometrica55, no. 2 (March 1987):
251–276.
Stock, James H. and Mark W. Watson. “Testing for Common Trends.” Journal of
the American Statistical Association83, no. 404 (December 1988): 1097–1107.
Enders, Walter. Applied Econometric Time Series. (New York: John Wiley & Sons,
Inc., 1995).


84 STATISTICAL ARBITRAGE PAIRS

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