TY  - JOUR
AU  - Noh,Jaesun
AU  - Engle,Robert F.
AU  - Kane,Alex
TI  - A Test of Efficiency for the S&P Index Option Market Using Variance     Forecasts
JF  - National Bureau of Economic Research Working Paper Series
VL  - No. 4520
PY  - 1993
Y2  - November 1993
UR  - http://www.nber.org/papers/w4520
L1  - http://www.nber.org/papers/w4520.pdf
N1  - Author contact info:
Robert F. Engle, III
Department of Finance, Stern School of Business
New York University, Salomon Center
44 West 4th Street, Suite 9-160
New York, NY  10012-1126
Tel: 212/998-0710
Fax: 212/995-4220
E-Mail: rengle@stern.nyu.edu

Alex Kane
Graduate School of IRPS/D-019
University of California, San Diego
La Jolla, CA   92093-0519
Tel: 619/534-5969
E-Mail: akane@ucsd.edu
AB  - To forecast future option prices, autoregressive models of implied volatility derived from observed option prices are commonly employed [see Day and Lewis (1990), and Harvey and Whaley (1992)].  In contrast, the ARCH model proposed by Engle (1982) models the dynamic behavior in volatility, forecasting future volatility using only the return series of an asset.  We assess the performance of these two volatility prediction models from S&P 500 index options market data over the period from September 1986 to December 1991 by employing two agents who trade straddles, each using one of the two different methods of forecast.  Straddle trading is employed since a straddle does not need to be hedged.  Each agent prices options according to her chosen method of forecast, buying (selling) straddles when her forecast price for tomorrow is higher (lower) than today's market closing price, and at the end of each day the rates of return are computed.  We find that the agent using the GARCH forecast method earns greater profit than the agent who uses the implied volatility regression (IVR) forecast model.  In particular, the agent using the GARCH forecast method earns a profit in excess of a cost of $0.25 per straddle with the near-the-money straddle trading.
ER  -