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The Ultimate Position Sizing Guide - Part 3: Fundamental Optimization & Position Sizing Best Practices
Fundamental Optimization brings structure, accountability, and continuous improvement to position sizing, helping managers unlock more consistent Alpha while complementing broader portfolio management strategies.
In Part 1 and Part 2 of our Ultimate Guide to Position Sizing, we outlined the case for adding structure to position sizing and addressed the common hurdles managers face when implementing it. While the journey requires effort, the long-term benefits are clear.
Now, in the final part of the series, we shift from theory to practice, introducing Fundamental Optimization, a proven approach built alongside leading hedge funds and asset managers. We’ll share key best practices to help firms strengthen their position sizing processes.
What is Fundamental Optimization?
Fundamental Optimization transforms intuitive sizing into a structured, data-driven framework. It connects fundamental research and conviction with quantitative rigor, aligning position sizes with expected returns while accounting for volatility, liquidity, and risk.
By combining elements of the Kelly Criterion, Position Sizing Bands, and Mean-Variance Optimization, it offers a flexible, transparent system that maximizes risk-adjusted returns without sacrificing the manager’s expertise and insights.
Best Practices for Fundamental Optimization
1. Capture Everything
Build a centralized repository of all critical inputs—price targets, bull and bear probabilities, risk scores, qualitative factors like conviction, and more. Capturing and quantifying this data lays the groundwork for more disciplined, effective sizing decisions.
2. Build Consensus Across Stakeholders
A lasting framework requires buy-in from portfolio managers, CIOs, and analysts. Clear communication of the vision and benefits, combined with active analyst participation, helps ensure alignment, ownership, and accountability across the team.
3. Refresh Inputs Regularly
Markets move fast. Managers who frequently update price targets and conviction scores consistently outperform those relying on outdated data. Keeping inputs current helps maintain accurate sizing and reduces exposure to unexpected risks.
4. Empower the Right Behaviors Automatically
Attaching names to forecasts fosters accountability and encourages thoughtful, diligent input updates. A structured feedback loop between research quality and portfolio impact enhances individual performance and strengthens the entire process.
5. Capture Critical Nuances with Checklists
Not every important insight fits neatly into a model. Checklists help systematically incorporate subjective and overlooked factors—such as management quality, ESG data, or upcoming catalysts—into the sizing decision, making the framework more comprehensive and transparent.
6. Stay Consistent
Effective position sizing demands regular reinforcement. Scheduled reviews and updates ensure the framework stays sharp and prevents best practices from fading over time.
7. Optimize Continuously Through Feedback
Collecting and analyzing data on an ongoing basis turns every trade into an opportunity for improvement. A strong feedback loop helps managers refine decision-making and stay competitive in a dynamic environment.
The Bottom Line
Fundamental Optimization empowers managers to systematically align their best research ideas with portfolio outcomes. It creates a disciplined sizing process that is both rigorous and adaptable—helping teams unlock more consistent Alpha over time.
While structured sizing is powerful, it’s one piece of the larger portfolio management puzzle. Managers must also manage risk exposures and navigate shifting market conditions to achieve sustainable long-term success.
Download Part 3 of our white paper to learn more about this topic. Follow Alpha Theory's LinkedIn page as we continue to explore best practices that can help you unlock position sizing alpha in your portfolio.
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