The relationship between the Nasdaq Composite Index and energy futures markets
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DOIhttp://dx.doi.org/10.21511/imfi.15(4).2018.01
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Article InfoVolume 15 2018, Issue #4, pp. 1-16
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This paper sheds light on the relationship between the Nasdaq Composite Index and a newly proposed Energy Futures Conditions Index (EFCI). While various financial conditions indices provide information about the financial stability of a country, the existence of an energy condition index, using futures markets, is scarce. Using weekly data over the period 1992–2017, this paper introduces an energy futures index using principal component analysis and test its predictability over the Nasdaq Composite Index. The EFCI captures 95% of the variability inherent in crude oil, heating oil and natural gas futures’ total reportable positions. Stability in forecast errors over different lags suggests a one week lag is sufficient to forecast weekly Nasdaq Composite Index. 95% prediction levels support that the estimated model captures actual equity market index values, except for the 2000 technology bubble. Distributions of level data were non-normal, not serially correlated and homoscedastic under the whole sample period, with diagnostics on pre and post technology bubble crisis showing mixed results. While differencing ensured homoscedastic errors in the forecasting model, Granger causality supported non-causality from both energy futures and equity markets, suggesting no evidence of cross market information flows.
- Keywords
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JEL Classification (Paper profile tab)G15, G18, Q47
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References49
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Tables9
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Figures6
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- Figure 1. Net positions, total reportable positions
- Figure 2. Principal component analysis
- Figure 3. Energy Futures Conditions Index model (EFCI)
- Figure 4. Actual and estimated market index (1992–2017)
- Figure 5. Dickey-fuller autoregressive coefficients
- Figure 6. Actual and forecasted Nasdaq Composite Index and EFCI values (2007–2017)
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- Table 1. Contract specifications
- Table 2. Correlation among heating oil, natural gas and crude oil net positions
- Table 3. Forecast errors
- Table 4. Regression statistics
- Table 5. Regression statistics and diagnostic tests
- Table 6. Pre and post crisis robustness test
- Table 7. Stationarity test
- Table 8. Heteroskedasticity test
- Table 9. Forecast evaluation
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- Adrian, T., Boyarchenko, N., & Giannone, D. (2016). Vulnerable Growth (Federal Reserve Bank of New York Staff Report, September, No. 794).
- Aggarwal, R. (1988). Stock Index Futures and Cash Market Volatility. Review of Futures Markets, 7, 290-299.
- Aramonte, S., Jahan-Parvar, M. R., Schindler, J. W., & Rosen, S. (2017). Firm-Specific Risk- Neutral Distributions: The Role of CDS Spreads (FRB International Finance Discussion Paper No. 1212).
- Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Econometrics, 18(1), 1-22.
- Beaton, K., Lalonde, R., & Luu, C. (2009). A Financial Conditions Index for the United States. Bank of Canada discussion papers.
- Bessembinder, H., & Chan, K. (1992). Time-Varying Risk Premia and Forecastable Returns in Futures Markets. Journal of Financial Economics, 32(2), 169-193.
- Blattberg, R. C., & Gonedes, N. J. (1974). A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices. Journal of Business, 47(2), 244-280.
- Bloomberg (2018). Bloomberg Commodity Index, Bloomberg Commodity Index (BCOM) 2018 Target Weights Announced.
- Caballero, R. J., & Kurlat, P. (2008, October). Flight to Quality and Bailouts: Policy Remarks and a Literature Review (Working Paper).
- Cardarelli, R., Elekdag, S., & Lall, S. (2011). Financial Stress and Economic Contractions. Journal of Financial Stability, 7(2), 78-97.
- CFTC (2018). Traders in Financial Futures: Explanatory Notes. Commodity Futures Traders Commission.
- Dudley, W. C. (2010). Comments: Financial Conditions Indexes: A Fresh Look after the Financial Crisis. Remarks at the University of Chicago Booth School of Business Annual U.S. Monetary Policy Forum, New York, February 26.
- EIA (2016). US Energy Information Administration. Short-Term Energy Outlook, April.
- EIA (2017). US Energy Information Administration. Energy & Financial Markets: What drives Crude Oil Prices?
- Figlewski, S. (1981). Futures Trading and Volatility in the GNMA Market. Journal of Finance, 36(2), 445-456.
- Friedman, M. (1953). The case for flexible exchange rates. In Essays in positive economics (pp. 157-203). Chicago: University of Chicago Press.
- Gomez, E. (2011). Financial Conditions Index: Early and Leading Indicator for Colombia. Ensayos sobre Politica Economica, 66, 174-220.
- Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
- Grosche, S. (2012). Limitations of Granger Causality Analysis to assess the price effects from the financialization of agricultural commodity markets under bounded rationality (Discussion Papers 121868). University of Bonn, Institute for Food and Resource Economics.
- Gurrib, I. (2008). Do large hedgers and speculators react to events? A stability and events analysis. Applied Financial Economics Letters, 4(4), 259-267.
- Gurrib, I. (2009). Measurement of large hedgers and speculators risk in major US Futures markets. Journal of Risk, 12(2), 79-103.
- Gurrib, I. (2018). Are key market players in currency derivatives markets affected by financial conditions? Investment Management and Financial Innovations, 15(2), 183-193.
- Hakkio, C. S., & Keeton, W. K. (2009). Financial stress: What is it, how can it be measured, and why does it matter? Federal Reserve Bank of Kansas City Economic Review.
- Hamao, Y., Masulis, R. W., & Nag, V. (1990). Correlations in price changes and volatility across international stock markets. Review of Financial Studies, 3, 281-307.
- Hartzmark, M. L. (1987). Returns to individual traders of futures: aggregate results. Journal of Political Economy, 95(6), 1292-1306.
- Hatzius, J. (2010). Financial Conditions Indexes: A Fresh Look after the Financial Crisis (NBER Working Paper Series w16150).
- Hilliard, J. E., & Reis, J. A. (1999). Jump Processes in Commodity Futures Prices and Options Pricing. American Journal of Agricultural Economics, 81(2), 273-286.
- Houthakker, H. S (1957). Can speculators forecast prices? Review of Economics and Statistics, 39(2), 143-151.
- IBRD (2017). Commodity Markets Outlook (International Bank for Reconstruction and Development/ World Bank Quarterly Report).
- IMF (2014). Global Liquidity – Issues for Surveillance (IMF Policy Paper). Washington, DC.
- IMF (2017). Are countries losing control of domestic financial conditions? (IMF Global Financial Stability Report, Chapter 3, April).
- Kaldor, N. (1939). Speculation and Economic Stability. Review of Economic Studies, 7(1), 1-27.
- Keynes, J. M. (1930). A Treatise of Money (Vol. 2). London: McMillan.
- Khoury, N., & Perrakis, S. (1998). Asymmetric information in commodity futures markets: theory and empirical evidence. The Journal of Futures Markets, 18(7), 803- 825.
- King, M., & Wadhwani, S. (1990). Transmission of volatility between stock markets. Review of Financial Studies, 3(1), 5-33.
- Kliesen, K. L., Owyang, M. T., & Vermann, E. K. (2012, September/ October). Disentangling Diverse Measures: A Survey of Financial Stress Indexes. Federal Reserve Bank of St. Louis Review, 94(5), 369-97.
- Koop, G., & Korobilis, D. (2014). A New Index of Financial Conditions. European Economic Review, 71, 101-116.
- Lin, S. X., & Tamvakis, M. N. (2001). Spillover effects in energy futures markets. Energy Economics, 23, 43-56.
- Meese, R., & Rogoff, K. (1983). Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample? Journal of International Economics, 14(2), 3-24.
- Nelson, W. R., & Perli, R. (2007). Selected Indicators of Financial Stability. In Risk Management and Systemic Risk (pp. 343-372). Frankfurt, Germany: European Central Bank.
- Nurske, R. (1944). International currency experience. League of Nations, Geneva.
- Panagiotidis, T., & Rutledge, E. (2007). Oil and gas markets in the UK: Evidence from a cointegrating approach. Energy Economics, 29(2), 329-347.
- Qu, Z., & Perron, P. (2007). Estimating and Testing Multiple Structural Changes in Multivariate Regressions. Econometrica, 75(2), 459-502.
- Rey, H. (2013). Dilemma Not Trilemma: The Global Financial Cycle and Monetary Policy Independence. Paper presented at Global Dimensions of Unconventional Monetary Policy Symposium, Jackson Hole, WY, August.
- Santoni, G. J. (1987). Has Programmed Trading made Stock Prices more Volatile? Review- Federal Reserve Bank of St. Loius, 69(5), 18-29.
- Stock, J. H., & Watson, M. (2002). Forecasting Using Principal Components from a Large Number of Predictors. Journal of the American Statistical Association, 97(460), 1167-1179.
- Swiston, A. (2008). A U.S. Financial Conditions Index: Putting Credit Where Credit is Due (IMF Working Paper WP/08/161).
- Working, H. (1953). Futures Trading and Hedging. American Economic Review, 43(3), 314-343.
- Yoo, J., & Maddala, G. S. (1991). Risk premia and price volatility in futures markets. Journal of Futures Markets, 11(2), 165-177.