Financial Performance of Investment Companies Using the Treynor-Black Method: An Analysis of Risk-Adjusted Returns and Portfolio Optimization

This study evaluates the financial performance of investment firms using the Treynor-Black Method, which optimizes portfolios by combining high-alpha assets with the market portfolio to enhance risk-adjusted returns. The study applies the method to a sample of investment firms to examine its effectiveness in improving key performance metrics, including the Sharpe Ratio, Treynor Ratio, and Jensen's Alpha. The findings indicate that the Treynor-Black Method substantially improves portfolio performance, with optimized portfolios exhibiting higher Sharpe and Treynor Ratios and positive Jensen's Alpha. These results suggest systematic risk management and effective value addition through active management. However, the study acknowledges limitations such as reliance on historical data, potential data quality issues, and challenges in estimating alpha and beta. These constraints highlight the need for careful interpretation and suggest future research directions, including the use of real-time data and alternative optimization approaches. The study provides practical insights for investment managers, offering an enhanced framework for portfolio construction and performance evaluation. It contributes to the field by validating and extending the Treynor-Black Method, enhancing strategies for aligning portfolios with risk-return objectives.

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Publication Details

Journal
RIGGS Journal of Artificial Intelligence and Digital Business
Published
2025-05-04
DOI
https://doi.org/10.31004/riggs.v4i2.457
Primary Topic
Risk Management in Financial Firms
Type
article
Field-Weighted Citation Impact
0.00
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article

Financial Performance of Investment Companies Using the Treynor-Black Method: An Analysis of Risk-Adjusted Returns and Portfolio Optimization

Yusnindar Yusnindar, A. A. Abdul Manap, Lilik Swartana Angga Buana, Saut Pane et al.
RIGGS Journal of Artificial Intelligence and Digital Business
Risk Management in Financial Firms
article

Financial Performance of Investment Companies Using the Treynor-Black Method: An Analysis of Risk-Adjusted Returns and Portfolio Optimization

Yusnindar Yusnindar, A. A. Abdul Manap, Lilik Swartana Angga Buana, Saut Pane, Mohamad Ramadhan Agung
article en

Abstract

This study evaluates the financial performance of investment firms using the Treynor-Black Method, which optimizes portfolios by combining high-alpha assets with the market portfolio to enhance risk-adjusted returns. The study applies the method to a sample of investment firms to examine its effectiveness in improving key performance metrics, including the Sharpe Ratio, Treynor Ratio, and Jensen's Alpha. The findings indicate that the Treynor-Black Method substantially improves portfolio performance, with optimized portfolios exhibiting higher Sharpe and Treynor Ratios and positive Jensen's Alpha. These results suggest systematic risk management and effective value addition through active management. However, the study acknowledges limitations such as reliance on historical data, potential data quality issues, and challenges in estimating alpha and beta. These constraints highlight the need for careful interpretation and suggest future research directions, including the use of real-time data and alternative optimization approaches. The study provides practical insights for investment managers, offering an enhanced framework for portfolio construction and performance evaluation. It contributes to the field by validating and extending the Treynor-Black Method, enhancing strategies for aligning portfolios with risk-return objectives.

RIGGS Journal of Artificial Intelligence and Digital BusinessVol. 4(2)
Universitas Jayabaya (ID)
Openalex Percentile: Top 83%
Risk Management in Financial Firms
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Financial Performance of Investment Companies Using the Treynor-Black Method: An Analysis of Risk-Adjusted Returns and Portfolio Optimization — Yusnindar Yusnindar, A. A. Abdul Manap, et al. · RIGGS Journal of Artificial Intelligence and Digital Business (2025) | TGRS Research Map | TGRS