Cheng, Peiran (2012) U.S. Energy Futures Markets: Liquidity and Optimal Speculative Position Limits. Masters thesis, Concordia University.
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Abstract
U.S. energy prices have grown dramatically since the 2007 financial crisis. Speculators are blamed for market manipulation, and regulators seek additional tools to control the market. Given the growing roles of liquidity and position limits in finance along with recent Wall Street legislation changes made by the Dodd-Frank Act, we carry out studies to test how effectively price impact liquidity measures measure liquidity, whether position limits have impacts on market liquidity, and how optimal speculative position limits should be modeled, based on microstructure theories. Using the major New York Mercantile Exchange (NYMEX) energy futures data from Bloomberg, we compare low-frequency liquidity proxies with high-frequency liquidity benchmarks, run an event study on futures contracts’ liquidity following the launching of the Dodd-Frank Act, and develop a theory-based position limits model. Our empirical results indicate that the new price impact liquidity proxy developed in this thesis is more effective in measuring liquidity than the Amihud (2002) proxy. Further, contrary to Grossman's (1993) finding, position limits on financial futures do not force traders to move to foreign substitute markets. Finally, position limits for single commodity derivatives should be based on corresponding underlying spot market factors, and strong fluctuations in optimal position limits over time suggest that exchanges should update position limits on a high-frequency basis.
| Divisions: | Concordia University > John Molson School of Business > Finance |
|---|---|
| Item Type: | Thesis (Masters) |
| Authors: | Cheng, Peiran |
| Institution: | Concordia University |
| Degree Name: | M. Sc. |
| Program: | Administration (Finance option) |
| Date: | August 2012 |
| Thesis Supervisor(s): | Shanker, Latha |
| Keywords: | Position limits, Energy, Liquidity. |
| ID Code: | 974615 |
| Deposited By: | PEIRAN CHENG |
| Deposited On: | 30 Oct 2012 18:16 |
| Last Modified: | 18 Jan 2018 17:38 |
References:
Amihud, Y., 2002. Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets 5, 31-56.Berkman, H., Eleswarapu, V., 1998. Short-term traders and liquidity: a test using Bombay Stock Exchange data. Journal of Financial Economics 47, 339-355.
Boehmer, E., Musumeci, J., Poulsen, A., 1991. Event study methodology under conditions of event induced variance. Journal of Financial Economics 30, 253-272.
Brown, S., Warner, J., 1985. Using daily stock returns: the case of event studies. Journal of Financial Economics 14, 3-31.
Brown, S., Warner, J., 1980. Measuring security price performance. Journal of Financial Economics 8, 205-258.
Cooper, S., Groth, K., Avera, W., 1985. Liquidity, exchange listing and common stock performance. Journal of Economics and Business 37, 19-33.
Cowen, A.R., Sergeant, A.M.A., 1996. Trading frequency and event study test specification. Journal of Banking and Finance 20, 1731-1757.
Dutt, H.R., Harris, L.E., 2005. Position limits for cash-settled derivative contracts. Journal of Futures Markets 25, 945-965.
Gastineau, G. L., 1991. Option position and exercise limits: Time for a radical change. Journal of Portfolio Management 19, 92-96.
Goyenko, R.Y., Holden, C.W., Trzcinka, C.A., 2009. Do liquidity measures measure liquidity? Journal of Financial Economics 92, 153-181.
Grossman, S.J., 1993. The case for eliminating position limits on financial futures. Journal of Financial Engineering 2, 39-42.
Hasbrouck, J., 2004. Liquidity in the futures pits: inferring market dynamics from incomplete data. Journal of Financial and Quantitative Analysis 39, 305-326.
Hasbrouck, J., 2009. Trading costs and returns for US equities: estimating effective costs from daily data. Journal of Finance 64, 1445-1477.
Holden, C., 2009. New low-frequency liquidity measures. Working Paper, Indiana University.
Huang, R., Stoll, H., 1996. Dealer versus auction markets: a paired comparison of execution costs on NASDAQ and the NYSE. Journal of Financial Economics 41, 313-357.
Kumar, P., Seppi, D.J., 1992. Futures manipulation with “cash settlement”. Journal of Finance 47, 1485-1502.
Kyle, A.S., 1984. A theory of futures market manipulations. In R. W. Anderson (Ed.), Industrial organization of futures markets. Lexington, MA: D.C. Heath.
Lee, C., Ready, M., 1991. Inferring trade direction from intraday data. Journal of Finance 46, 733-746.
Lesmond, D., 2005. Liquidity of emerging markets. Journal of Financial Economics 77, 411-452.
Lesmond, D., Ogden, J., Trzcinka, C., 1999. A new estimate of transaction costs. Review of Financial Studies 12, 1113-1141.
Pastor, L., Stambaugh, R., 2003. Liquidity risk and expected stock returns. Journal of Political Economy 111, 642-685.
Patell, J., 1976. Corporate forecasts of earnings per share and stock price behavior: empirical tests. Journal of Accounting Research 14, 246-276.
Pirrong, S.C., 1993. Manipulation of the commodity futures market delivery process. Journal of Business 66, 335-369.
Pirrong, S.C., 1993. The self-regulation of Commodity exchanges: The case of market manipulation. Journal of Law and Economics 38, 141-206.
Roll, R., 1984. A simple implicit measure of the effective bid-ask spread in an efficient market. Journal of Finance 39, 1127-1139.
Sanger, G., McConnell, J., 1986. Stock exchange listings, firm value and security market efficiency: the impact of NASDAQ. Journal of Financial and Quantitative Analysis 21, 1-25.
Telser, L.G., 1993. A review of the case for position limits on agricultural futures. Journal of Financial Engineering 2, 33-38.
Dodd-Frank Act – CFTC website. http://www.cftc.gov/lawregulation/doddfrankact/index.htm.
Position Limits – CFTC website. http://www.cftc.gov/LawRegulation/DoddFrankAct/Rulemakings/DF_26_PosLimits/index.htm
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