# Fund2Vec: Mutual Funds Similarity using Graph Learning

arXiv: https://arxiv.org/abs/2106.12987 · HTML: https://mlsanity.com/paper/2106.12987/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 40 references that are in the map.
- First posted on arXiv 24 Jun 2021.

## Builds on (most cited first, 5 of 5)

- [Distributed Representations of Words and Phrases and their Compositionality](https://mlsanity.com/paper/1310.4546/) (2013)
- [node2vec: Scalable Feature Learning for Networks](https://mlsanity.com/paper/1607.00653/) (2016)
- [Machine Learning Fund Categorizations](https://mlsanity.com/paper/2006.00123/) (2020)
- [EvalNE: A Framework for Evaluating Network Embeddings on Link Prediction](https://mlsanity.com/paper/1901.09691/) (2019)
- [hood2vec: Identifying Similar Urban Areas Using Mobility Networks](https://mlsanity.com/paper/1907.11951/) (2019)

## Built on by (most cited first, 11 of 11)

- [Quantifying Outlierness of Funds from their Categories using Supervised Similarity](https://mlsanity.com/paper/2308.06882/) (2023)
- [GReaTER: Generate Realistic Tabular data after data Enhancement and Reduction](https://mlsanity.com/paper/2503.15564/) (2025)
- [DEREC-SIMPRO: unlock Language Model benefits to advance Synthesis in Data Clean Room](https://mlsanity.com/paper/2411.00879/) (2024)
- [Learning Mutual Fund Categorization using Natural Language Processing](https://mlsanity.com/paper/2207.04959/) (2022)
- [A Case Study of Next Portfolio Prediction for Mutual Funds](https://mlsanity.com/paper/2410.18098/) (2024)
- [STRAPSim: A Portfolio Similarity Metric for ETF Alignment and Portfolio Trades](https://mlsanity.com/paper/2509.24151/) (2025)
- [Holder Recommendations using Graph Representation Learning & Link Prediction](https://mlsanity.com/paper/2212.09624/) (2022)
- [Model-Free Market Risk Hedging Using Crowding Networks](https://mlsanity.com/paper/2306.08105/) (2023)
- [Contrastive Learning of Asset Embeddings from Financial Time Series](https://mlsanity.com/paper/2407.18645/) (2024)
- [SETN: Stock Embedding Enhanced with Textual and Network Information](https://mlsanity.com/paper/2408.02899/) (2024)
- [Institutional Equity Holdings Prediction Using Node Affinities of Dynamic Graphs](https://mlsanity.com/paper/2607.12067/) (2026)

## Abstract (arXiv)

Identifying similar mutual funds with respect to the underlying portfolios has found many applications in financial services ranging from fund recommender systems, competitors analysis, portfolio analytics, marketing and sales, etc. The traditional methods are either qualitative, and hence prone to biases and often not reproducible, or, are known not to capture all the nuances (non-linearities) among the portfolios from the raw data. We propose a radically new approach to identify similar funds based on the weighted bipartite network representation of funds and their underlying assets data using a sophisticated machine learning method called Node2Vec which learns an embedded low-dimensional representation of the network. We call the embedding Fund2Vec. Ours is the first ever study of the weighted bipartite network representation of the funds-assets network in its original form that identifies structural similarity among portfolios as opposed to merely portfolio overlaps.