Investment management
Martin Bradstreet
Martin Bradstreet Partners LP
About the managerThe manager
Fund manager
Martin Bradstreet is an investor, entrepreneur, and former high-stakes poker professional. From January 2006 to February 2012, he earned more than $1 million in poker profits through online and live play. He has invested actively since 2022 and writes the investment newsletter “Investing with Martin” on Substack.
In April 2025, Mr. Bradstreet founded ALPHAPORT.AI, an investment research terminal. Previously, he founded and led Martov Co, a Montreal-based virtual reality game studio, from April 2016 to April 2025. His responsibilities included software development, fundraising, hiring, and studio management.
- Management company
- Martin Bradstreet Investment Management LLC
- Fund
- Martin Bradstreet Partners LP
- Enquiries
- martin@martinbradstreet.com
Disclosures
Purpose of this website
This website provides general information about Martin Bradstreet Investment Management LLC and Martin Bradstreet Partners LP. It does not provide individualized investment, legal or tax advice.
Investment risks
Investing involves risk, including the possible loss of capital. Past performance does not guarantee future results. An investment’s suitability depends on the investor’s circumstances.
Offering materials
This website is not an offer to sell or a solicitation of an offer to buy an interest in a fund. Any offering, if made, would be made through applicable offering documents and subject to their terms and investor eligibility requirements.
Performance and sources
Any performance displayed here represents Martin Bradstreet’s selected personal accounts, not the historical results of Martin Bradstreet Partners LP. AlphaPort calculates time-weighted returns from the selected account history in USD, adjusting for evidenced external cash flows. Returns reflect fees already included in the source account values; no additional fund management or performance fee adjustment is applied. SPY total returns, including dividends, provide the benchmark. Partial or multi-month periods are identified in the table. Source dates accompany the data; missing observations are not treated as zero returns.