Paper Title
Python: A Powerful Tool for Implementing Efficient and Reliable Quantitative Investment Strategies in Portfolio Creation
Article Identifiers
: Authors
Keywords
CAGR, CAPM, Volatility, Sharpe Ratio, numpy, yfinance, VaR
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.
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How To Cite (APA)
Nikhil V S & Dr. Rashmi Akshay Yadav (April-2024). Python: A Powerful Tool for Implementing Efficient and Reliable Quantitative Investment Strategies in Portfolio Creation. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), 624-683. https://ijnrd.org/papers/IJNRDTH00130.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : 624-683
Other Publication Details
Paper Reg. ID: IJNRD_218109
Published Paper Id: IJNRDTH00130
Downloads: 000122017
Research Area: Other
Author Type: Indian Author
Country: Bangalore, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRDTH00130.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRDTH00130
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