Build A Portfolio Resilient To Today’s Factor-Driven Markets with Alpha Theory + Omega Point

Author: Cameron Hight, Alpha Theory CEO and Founder

Omega Point research shows that since 2020, market-related “factors” have had an outsized influence on price movement and portfolio volatility.

^{Source: Alpha Theory, Omega Point - The color of each column represents the number of days in a year classified across five quintiles of factor driven vs. idio driven environments. To measure each day, a market neutral portfolio is created that is long the top decile of best performers and short the bottom decile of performers in the Russell 1000 index. Each day, performance is decomposed through the lens of various risk models to identify quintiles that best categorize the spectrum of the most “Alpha-Driven” days to the most “Factor-Driven” days. To calibrate our classification, we took the total sample of all days since Jan 1, 2007, and ranked them by Alpha Contribution to return percentage.}

As such, LPs have requested and managers have responded by increasing their usage of risk models to remove unwanted risk and isolate their alpha. 

Unifying fundamental research and risk modeling, however, can be a daunting task. That's why Alpha Theory has partnered with Omega Point to deliver an integrated solution that sizes positions using a hybrid fundamental and risk optimization.

Meet ATOP, Alpha Theory's integration with Omega Point

Alpha Theory's integration with Omega Point, ATOP, empowers managers to focus on their core competency — picking stocks.

ATOP is a position sizing toolkit that brings fundamental research and factor-based risk analysis into a unified workflow, yielding a risk-adjusted portfolio with superior returns.

Use Alpha Theory + Omega Point to supercharge alpha-generating workflows

With ATOP, managers can:

• Gain visibility into factor-level exposures of each position that drive risk and return
• Understand the drivers of systematic risk
• Enhance idea prioritization
• Leverage custom tags to hone investment analysis and more easily track strategies
• Incorporate factor-based constraints into optimal sizing rules
• Streamline operations through a consistent view of your portfolio, layering in fundamental, market, alternative, and internal data sources
• Monitor and manage portfolio exposure to a crisis or other major market events

How do Alpha Theory + Omega Point work together?

Alpha Theory provides a framework for managers to codify and quantify their company-specific fundamental research into optimal position sizes. Omega Point’s optimizer then uses this optimal position size to construct a model portfolio that effectively balances expected return with risk. 

Even top-performing funds can improve with Alpha Theory + Omega Point

In a recent case study, we illustrate how a more disciplined and factor-aware process can improve ROI and idea efficiency — even for a top-performing fund.

The data is from a former Alpha Theory client who managed a $1 billion+ global multi-sector long/short equity fund that generated cumulative returns of 38% with a Sharpe ratio of 1.0 over a nearly four-year period. In comparison, the All-Country World Index (ACWI) returned 32% with a Sharpe ratio of 0.7 and double the max drawdown.

To evaluate the potential return improvement, we backtested a strategy using the manager’s Optimal Position Size from Alpha Theory. The Alpha Theory Optimal strategy outperformed the actual strategy by almost 400 bps per year, with a Sharpe ratio of 1.27 in the same time period.

We then used Omega Point’s optimizer and Alpha Theory’s optimal position and probability-weighted return information to create a risk aware portfolio.

Our data found that the risk-adjusted optimal portfolio using ATOP outperformed the actual strategy by almost 150 bps on an annualized basis, while offering a similar level of realized volatility at the same level of gross and net exposure. This strategy produced a Sharpe ratio of 1.18, compared to the actual strategy’s Sharpe ratio of 1.00. The downside risk is also lessened, with a max drawdown of 9.02% compared to 9.78% for the actual strategy.

While the risk-adjusted optimal strategy doesn’t generate returns at the same level as the Alpha Theory Optimal strategy, it captures about 40% of the upside at the same level of risk and exposure, and is much closer to the original from an implementation standpoint.

The results of this case study highlight that it was possible to lean into the manager’s fundamental ideas, modifying portfolio construction to have higher exposure to good risk, resulting in improved performance.

Using ATOP creates a differentiated strategy that enhances investment managers’ strengths and boosts alpha returns while incurring less risk.