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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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Issue: April 2024
Volume 9 | Issue 4
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| Paper Title: | Python: A Powerful Tool for Implementing Efficient and Reliable Quantitative Investment Strategies in Portfolio Creation |
| Authors Name: | Nikhil V S , Dr. Rashmi Akshay Yadav |
| Download E-Certificate: | Download |
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IJNRD_218109
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| Published Paper Id: | IJNRDTH00130 |
| Published In: | Volume 9 Issue 4, April-2024 |
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| Abstract: | In the rapidly evolving landscape of financial markets, the integration of technology has become increasingly crucial. This study delves into the realm of quantitative investment strategies, particularly focusing on the utilization of Python, a versatile programming language, as a powerful tool in this domain. By leveraging historical market data, we investigate the performance strategies compared to traditional methods, spanning various aspects such as risk-adjusted returns, portfolio optimization, risk management, and the reliability of back testing procedures. The methodology employed in this research encompasses a range of quantitative analyses tailored to assess the effectiveness of strategies. Firstly, we conduct Sharpe ratio analyses to gauge the risk-adjusted returns, providing insights into the efficiency of these strategies in generating returns relative to the level of risk undertaken. Additionally, portfolio standard deviation comparisons allow us to evaluate the diversification benefits offered by optimized portfolios compared to manually constructed ones, shedding light on the potential for enhanced portfolio management techniques. Furthermore, our study delves into risk management aspects by performing Value at Risk (VaR) assessments. This analysis helps elucidate whether quantitative models are successful in mitigating downside risk and minimizing portfolio drawdowns, especially during turbulent market conditions. Additionally, we scrutinize the reliability of back testing procedures, crucial for validating the performance of investment strategies under various market scenarios. The implications of our study extend beyond academia, offering valuable insights for practitioners in the financial industry. Embracing technology-driven approaches, such as quantitative strategies, can pave the way for achieving superior investment outcomes and staying competitive in today's dynamic market environment. By leveraging Python's capabilities, investors can navigate complexities more adeptly, capitalize on opportunities, and manage risks more effectively, ultimately enhancing their overall performance and resilience in financial markets. |
| Keywords: | CAGR, CAPM, Volatility, Sharpe Ratio, numpy, yfinance, VaR |
| Cite Article: | "Python: A Powerful Tool for Implementing Efficient and Reliable Quantitative Investment Strategies in Portfolio Creation", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.624-683, April-2024, Available :http://www.ijnrd.org/papers/IJNRDTH00130.pdf |
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRDTH00130 Registration ID: 218109 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: 624-683 Country: Bangalore, Karnataka, India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRDTH00130 Published Paper PDF: https://www.ijnrd.org/papers/IJNRDTH00130 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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