Skip to main content
Have a personal or library account? Click to login
Capabilities of Statistical Residual-Based Control Charts in Short- and Long-Term Stock Trading Cover

Capabilities of Statistical Residual-Based Control Charts in Short- and Long-Term Stock Trading

By:   
Open Access
|Mar 2016

References

  1. 1. Alexander, S. S. (1961). Price movements in speculative markets: Trends or random walk.,(2), 7–26.
  2. 2. Alexander, S. S. (1964). Price movements in speculative markets: Trends or random walk, number 2.(2), 25–46.
  3. 3. Almenberg, J., & Dreber, A. (2012).. Retrieved from
  4. 4. Alwan, L. C. (1991). Autocorrelation: Fixed versus variable control limits.(2), 167–188.
  5. 5. Alwan, L. C., & Roberts, H. V. (1988). Time-series modeling for statistical process control.(1), 87–95.
  6. 6. Benić, V., & Franić, I. (2008). Stock market liquidity: Comparative analysis of Croatian and regional markets.,(4), 477–498.
  7. 7. Best, M., & Neuhauser, D. (2006). Walter A. Shewhart, 1924, and the Hawthorne factory.(2), 142–143.
  8. 8. Bogan, V. (2008). Stock market participation and the internet.(1), 191–212.
  9. 9. Box, G. E. P., & Jenkins, G. M. (1976).. San Francisco: Holden-Day.
  10. 10. Box, G. E. P., Luceno, A., & Paniagua-Quinones, M. D. C. (2009).. Hoboken, NJ: John Wiley & Sons.
  11. 11. Caporale, G. M., Howells, P. G. A., & Soliman, A. M. (2004). Stock market development and economic growth: The causal linkage.(1), 33–50.
  12. 12. Corrado, J. C., & Lee, S. H. (1992). Filter rule tests of the economic significance of serial dependencies in daily stock returns.(4), 369–387.
  13. 13. del Castillo, E. (2002).. New York: John Wiley & Sons.
  14. 14. Dryden, M. M. (1969). A source of bias in filter tests of share prices.(3), 321–325.
  15. 15. Dumičić, K., & Žmuk, B. (2011a). Metode statističke kontrole kvalitete. In K. Dumičić & V. Bahovec (Eds.),(pp. 459–539). Zagreb: Element.
  16. 16. Dumičić, K., & Žmuk, B. (2011b). Monitoring delivery time with control charts. In B. Katalinić (Ed.),(pp. 1199–1200). Vienna: DAAAM International.
  17. 17. Fama, E. F., & Blume, M. E. (1965). Filter rules and stock-market trading.(1), 226–241.
  18. 18. Gandy, A. (2012). Performance monitoring of credit portfolios using survival analysis.(1), 139–144.
  19. 19. Guiso, L., Sapienza, P., & Zingales, L. (2008). Trusting the stock market.(6), 2557–2600.
  20. 20. Harris, T. J., & Ross, W. H. (1991). Statistical process control procedures for autocorrelated observations.(1), 48–57.
  21. 21. Hubbard, C. L. (1967). A control chart for postwar stock price levels.(6), 139–145.
  22. 22. Hunter, J. S. (1986). The exponentially weighted moving average.(4), 203–210.
  23. 23. Hyndman, R. J. (2001).. Retrieved from
  24. 24. Kovarik, M., & Klimek, P. (2012). The usage of time series control charts for financial process analysis.(3), 29–45.
  25. 25. Kovarik, M., & Sarga, L. (2014). Implementing control charts to corporate financial management., 246–255.
  26. 26. Levich, R. M., & Rizzo, R. C. (1998).. Retrieved from
  27. 27. Lewellen, J. (2002). Momentum and autocorrelation in stock returns.(2), 533–563.
  28. 28. Lillo, F., & Farmer, J. D. (2004). The long memory of the efficient market.(3), 1–35.
  29. 29. Liu, C. S., & Tien, F. C. (2011). An evaluation of single-featured EWMA-X (SFEWMA-X) control chart with process mean shifts and standard deviation changes.(2), 111–121.
  30. 30. Lu, C. W., & Reynolds, M. R. (1999a). Control chart for monitoring the mean and variance of autocorrelated processes.(3), 259–274.
  31. 31. Lu, C. W., & Reynolds, M. R. (1999b). EWMA control charts for monitoring the mean of autocorrelated processes.(2), 166–188.
  32. 32. Lu, C. W., & Reynolds, M. R. (2001). CUSUM chart for monitoring an autocorrelated process.(3), 316–334.
  33. 33. Lucas, J. M., & Saccucci, M. S. (1990). Exponentially weighted moving average control schemes: Properties and enhancements.(1), 1–12.
  34. 34. Manas, A. T. (2005).. Retrieved from
  35. 35. McLeod, A. I., & Sales, P. R. H. (1983). Algorithm AS 191: An algorithm for approximate likelihood calculation of ARMA and seasonal ARMA models.,(2), 211–223.
  36. 36. McNeese, W., & Wilson, W. (2002).. Retrieved from
  37. 37. Montgomery, D. C. (2013).. Singapore: John Wiley & Sons.
  38. 38. Montgomery, D. C., & Friedman, D. J. (1989). Statistical process control in computer integrated manufacturing environment. In J. B. Keats & N. F. Hubele (Eds.),(pp. 67–88). New York: Marcel Dekker.
  39. 39. Montgomery, D. C., Jennings, C. L., & Pfund, M. E. (2011).. Hoboken, NJ: John Wiley & Sons.
  40. 40. Montgomery, D. C., & Runger, G. C. (2011).. Hoboken, NJ: John Wiley & Sons.
  41. 41. Moskowitz, H., Wardell, D. G., & Plante, R. D. (1994). Run-length distributions of special-cause control charts for correlated processes.(1), 3–27.
  42. 42. NIST/SEMATECH. (2013).. Retrieved from
  43. 43. Noskievičová, D. (2007).. Retrieved from
  44. 44. Page, E. S. (1954). Continuous inspection scheme.(1–2), 100–115.
  45. 45. Rebisz, B. (2015). Appliance of quality control charts for sovereign risk modelling.(3), 148–160.
  46. 46. Riaz, M., Abbas, N., & Does, R. J. M. M. (2011). Improving the performance of CUSUM charts.(4), 415–424.
  47. 47. Roberts, H. V. (1959). Stock market “patterns” and financial analysis: Methodological suggestions.(1), 1–10.
  48. 48. Roberts, S. W. (1959). Control chart tests based on geometric moving averages.(3), 239–250.
  49. 49. Ryu, J. H., Wan, H., & Kim, S. (2010). Optimal design of a CUSUM chart for a mean shift of unknown size.(3), 311–326.
  50. 50. SAS Institute. (2014).. Retrieved from
  51. 51. Schmid, W. (1995). On the run length of a Shewhart chart for correlated data.(1), 111–130.
  52. 52. Schmid, W., & Schone, A. (1997). Some properties of the EWMA control chart in presence of autocorrelation.(3), 1277–1283.
  53. 53. Sewell, M. (2011).. Retrieved from
  54. 54. Sullivan, R., Timmermann, A., & White, H. (1999). Data-snooping, technical trading rule performance, and the bootstrap.(5), 1647–1691.
  55. 55. Sweeney, J. R. (1988). Some new filter rule tests: Methods and results.(3), 285–300.
  56. 56. Tachiwou, A. M. (2010). Stock market development and economic growth: The case of West African Monetary Union.(3), 97–103.
  57. 57. Tolvi, J. (2002). Outliers and predictability in monthly stock market index returns.(4), 369–380.
  58. 58. van Rooij, M., Lusardi, A., & Alessie, R. (2011). Financial literacy and stock market participation.(2), 449–472.
  59. 59. Vanbrackle, L. N., & Reynolds, M. R. (1997). EWMA and CUSUM control charts in the presence of correlation.(3), 979–1008.
  60. 60. Vasipoulos, A. V., & Stamboulis, A. P. (1978). Modification of control chart limits in the presence of data correlation.(1), 20–30.
  61. 61. Venkataramani, C. (2003).. Retrieved from
  62. 62. Wild, C. J., & Seber, G. A. F. (1999).. New York: Wiley.
  63. 63. Woodall, W. H., & Faltin, F. W. (1993). Autocorrelated data and SPC.(4), 18–21.
  64. 64. Zagreb Stock Exchange. (2014a).. Retrieved from
  65. 65. Zagreb Stock Exchange. (2014b).. Retrieved from
  66. 66. Zagreb Stock Exchange. (2014c).. Retrieved from
  67. 67. Zagreb Stock Exchange. (2014d).. Retrieved from
  68. 68. Zagreb Stock Exchange. (2014e).. Retrieved from
DOI: https://doi.org/10.1515/ngoe-2016-0002 | Journal eISSN: 2385-8052 | Journal ISSN: 0547-3101
Language: English
Page range: 12 - 26
Submitted on: Oct 1, 2015
Accepted on: Feb 1, 2016
Published on: Mar 19, 2016
Published by: University of Maribor
In partnership with: Paradigm Publishing Services
JEL:

© 2016 Berislav Žmuk, published by University of Maribor
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.