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Description:Machine Learning based portfolios designed to smooth the ride for investors--seeking consistent returns with less...
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Login Register Firm Firm Overview Philosophy People Relationship Management Investment and Operations Teams Strategies Decathlon Decathlon Javelin Market Neutral Sector Rotation Mutual Funds Decathlon Market Neutral Fund Fund Documents Access Us BCM’s Blog Contact Us Select Page Home Smart Portfolios for Diversifying Your Exposure We are living in an increasingly connected world with information flowing faster than ever. Markets adjust much more rapidly to good and bad news than they did in the past, with ready access to vast amounts of data and the technology needed to quickly analyze and act on it. It is becoming near impossible for humans to keep track of the shifting patterns and act quickly enough to take advantage. Using proprietary machine-learning technology, BCM’s opportunistic strategies seek to provide a tactical edge to a strategic allocation portfolio by acting nimbly to help enhance risk-adjusted returns, manage overall portfolio volatility and smooth the ride for investors. Learn More About Our Approach Growth While risk management is foundational to all BCM strategies, they pursue growth as the primary objective. BCM’s strategies can provide a tactical edge when paired with a strategic portfolio. Technology BCM’s strategies seek to combine machine learning technology and principles of behavioral finance to capitalize on alpha opportunities and manage risk while removing bias and emotion. Smoother Ride BCM’s disciplined systems are designed to provide a smooth ride across diverse market environments while seeking to maximize risk adjusted returns and improve the investment experience. Investment Solutions One of our core beliefs is that while market patterns may change, the patterns of human behaviors and biases will not. Our quantitatively driven investment solutions seek to remove emotions from the investment decision making process and provide a smooth ride for investors— consistent returns with less volatility . We offer multiple portfolio solutions to help investors achieve this, each deploying a varying approach to risk management. Global, go-anywhere strategies using machine learning to seek opportunistic growth within varying risk parameters—allowing investors to choose their desired level of risk. Core, 100% equity sector rotation, or as a portion of diversified portfolios that seeks growth and has the ability to provide defense in down markets. Machine learning strategy designed as a potential wealth preservation” vehicle that aims to provide limited exposure and consistent, uncorrelated, low-risk total returns. A suite of proprietary, quantitative tools and machine learning capabilities that can be employed to develop custom solutions for RIAs and institutional investors. Access BCM Strategies: Don’t see your preferred TAMP or custodian shown below? Call (844) 401-7699 or click here to explore how to work with BCM. This website has been independently produced by Beaumont Capital Management LLC. Beaumont Capital Management LLC is independent of, and has no affiliation with, Charles Schwab & Co., Inc. or any of its affiliates (Schwab”). Schwab is a registered broker-dealer and member SIPC. Schwab has not created, supplied, licensed, endorsed, or otherwise sanctioned these materials nor has Schwab independently verified any of the information in them. Beaumont Capital Management provides investment solutions, while Schwab maintains custody of assets in a brokerage account and will effect transactions for accounts on instruction. Firm Information About BCM Contact Us Press Inquiries Careers Disclosure Privacy Policy ADV Form CRS Investment Solutions Market Neutral Fund Decathlon Sector Rotation Subscribe to the BCM Blog – A Bird’s Eye View for timely content Copyright © 2024 Beaumont Capital ManagementYou are now entering the Mutual Funds section of the website. Decathlon Market Neutral Fund (DECMX/DECIX) You are now entering the Mutual Funds section of the website. Fund...
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