International Peer-Reviewed JournalOpen AccessISSN 2456-8880
irejournals@gmail.com+91-7433024337

Home / Current Issue / Paper 1710208

1710208 Vol 9 · Issue 2 Download Paper

Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday

Rahul Durgia

Subject area: Management and Commerce  ·  Area of research: Finance / Economics / Business Management

DOI: https://doi.org/10.64388/IREV9I2-1710208-1563

Abstract

This comprehensive research paper presents an extensive quantitative analysis of the Nifty 50 index's weekly behavioral patterns spanning a decade from 2015 to 2025, with specific focus on price movements from Friday market open to the subsequent Thursday market close. The study establishes a robust statistical foundation for developing systematic weekly option selling strategies in the rapidly evolving Indian derivatives market. Through rigorous examination of over 470 weekly trading cycles encompassing various market conditions including bull markets, bear markets, and periods of extreme volatility, this research identifies consistent and exploitable patterns in index behavior. The analysis reveals that approximately 70% of weekly movements fall within ?300 points of the Friday opening price, while extreme movements exceeding ?700 points occur in only 5.3% of weeks, providing strong statistical support for strategic options positioning. The study employs sophisticated statistical methodologies including distribution analysis, volatility clustering examination, and extreme value theory to develop a comprehensive understanding of weekly price behavior. The findings inform the development of a rules-based options selling strategy that systematically capitalizes on time decay (theta) while implementing multi-layered risk management protocols through data-driven strike price adjustments and dynamic stop-loss mechanisms.The research demonstrates the strategy's potential for generating consistent passive income within clearly defined risk parameters, with theoretical returns significantly exceeding traditional fixed-income investments. The empirical evidence supports the viability of systematic options selling approaches when implemented with appropriate discipline and risk management safeguards. This study contributes significantly to the academic literature on systematic trading strategies and provides practical insights for both retail and institutional traders seeking to exploit the structural characteristics of weekly options in emerging market derivatives. The findings offer valuable guidance for evidence-based derivative trading decisions and establish a benchmark for future research in this rapidly expanding field.

References

[1] Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. *Journal of Political Economy*, 81(3), 637-654.

[2] Merton, R. C. (1973). Theory of rational option pricing. *Bell Journal of Economics and Management Science*, 4(1), 141-183.

[3] Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. *Econometrica*, 50(4), 987-1007.

[4] Mandelbrot, B. B. (1963). The variation of certain speculative prices. *Journal of Business*, 36(4), 394-419.

[5] Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291.

[6] Hull, J. C. (2021). *Options, Futures, and Other Derivatives* (10th ed.). Pearson Education.

[7] Natenberg, S. (2014). *Option Volatility and Pricing: Advanced Trading Strategies and Techniques* (2nd ed.). McGraw-Hill Education.

[8] Sinclair, E. (2013). *Option Trading: Pricing and Volatility Strategies and Techniques*. John Wiley & Sons.

[9] National Stock Exchange of India. (2025). *Historical Index Data - Nifty 50*. Retrieved from https://www.nseindia.com/reports-indices- historical-index-data

[10] Securities and Exchange Board of India. (2024). *Annual Report 2023-24*. SEBI Publications.

[11] Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. *Journal of Econometrics*, 31(3), 307-327.

[12] Cont, R. (2001). Empirical properties of asset returns: Stylized facts and statistical issues. *Quantitative Finance*, 1(2), 223-236.

[13] Gatheral, J. (2006). *The Volatility Surface: A Practitioner's Guide*. John Wiley & Sons.

[14] Rebonato, R. (2004). *Volatility and Correlation: The Perfect Hedger and the Fox* (2nd ed.). John Wiley & Sons.

[15] Derman, E., & Miller, M. B. (2016). *The Volatility Smile*. John Wiley & Sons.

How to cite this paper

Rahul Durgia " Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday" Iconic Research And Engineering Journals Volume 9 Issue 2 2025 Page 1150-1160 https://doi.org/10.64388/IREV9I2-1710208-1563
Rahul Durgia " Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday" Iconic Research And Engineering Journals, vol. 9, no. 2, Aug. 2025, doi: https://doi.org/10.64388/IREV9I2-1710208-1563
Rahul Durgia (2025). Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday. Iconic Research And Engineering Journals, 9(2). doi: https://doi.org/10.64388/IREV9I2-1710208-1563
Rahul Durgia " Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday" Iconic Research And Engineering Journals, vol. 9, no. 2, Aug. 2025. Crossref, https://doi.org/10.64388/IREV9I2-1710208-1563
@article{1710208,
      author = {Rahul Durgia},
      title = { Weekly Behavior of the Nifty Index: A Comprehensive Decade-Long Study for Strategic Option Selling from Friday to Thursday},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {2},
      pages = {1150-1160},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710208.pdf},
      abstract = {This comprehensive research paper presents an extensive quantitative analysis of the Nifty 50 index's weekly behavioral patterns spanning a decade from 2015 to 2025, with specific focus on price movements from Friday market open to the subsequent Thursday market close. The study establishes a robust statistical foundation for developing systematic weekly option selling strategies in the rapidly evolving Indian derivatives market. Through rigorous examination of over 470 weekly trading cycles encompassing various market conditions including bull markets, bear markets, and periods of extreme volatility, this research identifies consistent and exploitable patterns in index behavior. The analysis reveals that approximately 70% of weekly movements fall within ?300 points of the Friday opening price, while extreme movements exceeding ?700 points occur in only 5.3% of weeks, providing strong statistical support for strategic options positioning. The study employs sophisticated statistical methodologies including distribution analysis, volatility clustering examination, and extreme value theory to develop a comprehensive understanding of weekly price behavior. The findings inform the development of a rules-based options selling strategy that systematically capitalizes on time decay (theta) while implementing multi-layered risk management protocols through data-driven strike price adjustments and dynamic stop-loss mechanisms.The research demonstrates the strategy's potential for generating consistent passive income within clearly defined risk parameters, with theoretical returns significantly exceeding traditional fixed-income investments. The empirical evidence supports the viability of systematic options selling approaches when implemented with appropriate discipline and risk management safeguards. This study contributes significantly to the academic literature on systematic trading strategies and provides practical insights for both retail and institutional traders seeking to exploit the structural characteristics of weekly options in emerging market derivatives. The findings offer valuable guidance for evidence-based derivative trading decisions and establish a benchmark for future research in this rapidly expanding field.},
      month = {August},
      doi = {https://doi.org/10.64388/IREV9I2-1710208-1563}
  }