Estimating the Annualized Compounded Return of the Medallion Fund

核心概念

While naive compounding of yearly returns suggests an unrealistic annualized return of over 60% for the Medallion fund, a more accurate estimation based on fund sizes and trading profits reveals a still impressive but lower return of likely under 35%.

摘要

• Bibliographic Information: Guo, S., & Liu, Q. (2020). Is the annualized compounded return of Medallion over 35%? [Working Paper]. School of Economics and Management, Southwest Jiaotong University.
• Research Objective: This paper aims to accurately estimate the annualized compounded return of the Medallion fund, challenging previously reported figures exceeding 60%.
• Methodology: The authors propose two approaches:
  1. Size-Profit Compounding: This method considers the fund's size and trading profits, adjusting for cash inflows and outflows to calculate a more realistic compounded return.
  2. Net Wealth Compounding: This approach uses the growth rate of Jim Simons' net worth as a proxy for the fund's performance, acknowledging the limitations of estimating his initial wealth.
• Key Findings:
  • Naive compounding, which directly uses yearly returns, leads to an inflated estimate due to the discontinuous nature of fund sizes.
  • The Size-Profit Compounding method estimates an annualized compounded return of 31.8% before fees for the Medallion fund from 1988 to 2018.
  • Analyzing Simons' net worth growth suggests an annualized compounded growth rate of 25.6% after fees and taxes from 1988 to 2020.
• Main Conclusions:
  • The annualized compounded return of the Medallion fund is likely under 35%, significantly lower than previously reported figures.
  • The authors highlight the importance of considering fund size fluctuations and using appropriate compounding methods for accurate performance evaluation.
• Significance: This research provides a more realistic understanding of the Medallion fund's performance, contributing to a more informed discussion on hedge fund returns and investment strategies.
• Limitations and Future Research: The study acknowledges the limitations of estimating Simons' initial net worth and suggests further research on the impact of fees and taxes on fund performance.

统计

The Medallion fund started with $20 million in 1988.
Naive compounding of yearly returns suggests an annualized return of over 60%.
The Size-Profit Compounding method estimates an annualized compounded return of 31.8% before fees for the Medallion fund from 1988 to 2018.
Jim Simons' net worth was $23.5 billion as of November 16, 2020, after charitable donations of $2.7 billion.
Simons' estimated annualized compounded growth rate is 25.6% after fees and taxes from 1988 to 2020.

引用

"It is a challenge to estimate fund performance by compounded returns. Arguably, it is incorrect to use yearly returns directly for compounding, with a reported annualized return of above 60% for Medallion for the 31 years up to 2018."
"We propose an estimation based on fund sizes and trading profits and obtain a compounded return of 31.8% before fees."
"Alternatively, we suggest using the manager’s wealth as a proxy and arriving at a compounded growth rate of 25.6% for Simons for the 33 years up to 2020."
"We conclude that the annualized compounded return of Medallion before fees is probably under 35%."

从中提取的关键见解

Is the annualized compounded return of Medallion over 35%?

by Shuxin Guo, ... 在 arxiv.org 11-12-2024

https://arxiv.org/pdf/2405.10917.pdf

更深入的查询

How do the returns of the Medallion fund compare to other quantitative hedge funds during the same period?

While Medallion's returns are exceptionally high, even with the adjusted estimations of around 30%, it's crucial to understand how it compares to other quantitative hedge funds (quant funds) during the same period.

Outperformance: Medallion significantly outperforms the average returns of other quant funds. While data on quant fund returns is notoriously private and difficult to obtain, publicly available information suggests average annual returns for the industry fall significantly below 30%, even before considering fees.
Rarity: Medallion's consistent, multi-decade success is an outlier. Many quant funds experience periods of high performance followed by slumps or closures. The fact that Medallion has maintained such high returns for so long makes it an anomaly in the hedge fund world.
Survivorship Bias: It's important to consider survivorship bias when comparing Medallion to the industry. Many unsuccessful funds close, leaving only the top performers visible in databases and indices. This can inflate the perceived average returns of quant funds.
In conclusion, while direct comparisons are difficult due to data limitations, it's safe to say that Medallion's performance, even adjusted, places it in a league of its own within the quant hedge fund world.

Could the exceptional performance of the Medallion fund be attributed to factors beyond its quantitative strategies, such as insider information or market manipulation?

The question of whether Medallion's success stems solely from its quantitative strategies or involves other factors is a subject of much speculation and debate.

Secrecy and Speculation: Medallion's extreme secrecy regarding its strategies fuels speculation. The lack of transparency makes it difficult to definitively rule out any potential role of insider information or market manipulation.
Regulatory Scrutiny: Despite its secrecy, Medallion operates under the watchful eye of financial regulators. The fund has not been publicly implicated in any wrongdoing, and its long history of success makes it unlikely that sustained illegal activities would go unnoticed.
Mathematical Prowess: A more plausible explanation lies in the firm's exceptional talent pool of mathematicians, statisticians, and signal processing experts. Their ability to find subtle patterns and inefficiencies in the market, combined with sophisticated execution algorithms, could potentially explain a significant portion of their returns.
In conclusion, while the possibility of unethical or illegal activities cannot be entirely dismissed due to the fund's opacity, it's more likely that Medallion's success is primarily a result of its advanced quantitative strategies, data analysis capabilities, and rigorous risk management.

If the size of a fund significantly impacts its potential for high returns, how can investors identify and access smaller funds with similar strategies to potentially achieve higher returns?

The paper highlights a crucial aspect of fund performance: size matters. As a fund grows, its capacity to deploy capital effectively and maintain high returns diminishes. This is particularly true for strategies exploiting niche market inefficiencies, which are often limited in scale. So, how can investors identify and access smaller funds with the potential for higher returns?

Early Stage Investing: Seeking out funds in their early stages of development can provide an opportunity for higher returns. However, this comes with increased risk as early-stage funds have limited track records and higher failure rates.
Niche Strategies: Focusing on funds employing specialized or niche quantitative strategies can be beneficial. These strategies are often less scalable, making them more suitable for smaller funds.
Industry Networks and Databases: Leveraging industry networks, attending hedge fund conferences, and utilizing specialized databases can provide access to information about smaller, emerging managers.
Due Diligence: Thorough due diligence is crucial when considering smaller funds. Investors should carefully evaluate the fund's strategy, team, risk management processes, and track record (if available).
In conclusion, while identifying and accessing smaller funds with the potential for higher returns requires more effort and involves higher risk, it can be a viable strategy for investors seeking to replicate some of the success enjoyed by funds like Medallion.