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Factor-Based Investing

Developing investment portfolios based on factors that have historically led to outperformance or reduced risk.

Written by Hivelr Quantum Alpha · 3 min read >
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Factor-Based Investing, also known as smart beta, is a strategy that challenges traditional approaches to investing by emphasizing specific factors or characteristics that have historically influenced asset returns.

Instead of relying solely on market capitalization, this approach focuses on factors like value, size, momentum, and others, which are systematically selected and weighted to create investment portfolios.

By leveraging these factors, investors seek to achieve improved risk-adjusted returns compared to conventional market-weighted strategies.

This article provides a glimpse into factor-based investing and its potential to enhance portfolio performance through a more targeted and systematic approach.


Factor-based investing, a strategy rooted in financial research, has transformed investment approaches over the decades. It gained momentum in the 1960s and 1970s with the advent of modern portfolio theory by researchers like Sharpe and Markowitz.

This theory emphasized the importance of diversification and led to the foundation of factor models.

The 1980s and 1990s marked a significant step with Fama and French’s introduction of the Three-Factor Model. This model expanded beyond traditional risk factors to include size and value as key determinants of returns.

The new millennium brought the term “smart beta,” signifying the shift from passive indexing to systematic factor-driven strategies. The 2000s saw the identification of additional factors, such as momentum and low volatility, gaining traction among institutional and retail investors.

In the 2010s, factor-based investing became mainstream, evidenced by the proliferation of exchange-traded funds (ETFs) designed to track specific factors. Multi-factor strategies emerged, leveraging combinations of factors for enhanced diversification.

Today, factor investing continues to evolve, fueled by technology-driven advancements that refine factor analysis and portfolio construction.

This concise history highlights how factor-based investing evolved from theoretical concepts to practical strategies that offer investors a nuanced approach to achieving optimized returns.

Key Factors

Factor-based investing involves selecting stocks or assets based on specific characteristics that have historically led to outperformance or reduced risk. Several key factors are commonly used in factor-based strategies:

Value Factor: The value factor focuses on stocks that appear undervalued based on fundamental metrics such as price-to-earnings (P/E) and price-to-book (P/B) ratios. This factor assumes that the market sometimes misprices stocks, providing opportunities for investors to capitalize on discounted valuations. Stocks with lower valuation ratios are considered attractive, as they may have the potential to generate higher returns when their intrinsic value is recognized and reflected in the market price.

Size Factor: The size factor is rooted in the notion that smaller companies often have greater growth potential and agility. They may be better positioned to capitalize on new opportunities and adapt to market changes. This growth potential can lead to higher returns as investors seek to benefit from the expansion of these companies as they capture market share or develop innovative products or services.

Momentum Factor: The momentum factor identifies stocks with strong recent price performance. It’s grounded in the idea that trends persist in the market, and stocks that have performed well over a certain period are likely to continue performing well. This factor is based on investor psychology and the behavioral tendency to follow winning stocks, potentially leading to continued price momentum.

Quality Factor: The quality factor focuses on stocks of companies with solid financials, stable earnings, and low debt levels. Quality reflects a company’s ability to weather economic downturns and market volatility. Companies with strong fundamentals are often considered less risky and more likely to deliver consistent returns over the long term.

Low Volatility Factor: The low volatility factor targets stocks or assets with lower historical price volatility. It’s based on the notion that less volatile investments provide better risk-adjusted returns. These investments are believed to offer stability during market downturns, making them attractive for risk-averse investors seeking downside protection.

Factor-based investing allows investors to tilt their portfolios towards these factors to enhance returns or manage risk potentially. However, it’s important to recognize that factor performance can vary over different market cycles, and consistent outperformance is not guaranteed.

Investors considering factor-based strategies should conduct thorough research, understand the underlying rationale for each factor, and ensure that their chosen factors align with their investment objectives and risk tolerance.

Fama and French’s Three-Factor Model

Developed by Eugene Fama and Kenneth French in the 1990s, the Three-Factor Model revolutionized factor-based investing. The model includes three factors: market risk or beta (captured by the market portfolio), size (captured by the difference in returns between small-cap and large-cap stocks), and value (captured by the difference in returns between high book-to-market and low book-to-market stocks).

A real-world application of the Three-Factor Model is Dimensional Fund Advisors (DFA). DFA constructs portfolios based on the principles of the model. They overweight small-cap and value stocks, exploiting the size and value factors, which have historically offered higher returns over the long term. DFA’s evidence-based approach and consistent application of the Three-Factor Model have contributed to its success in providing investors with risk-adjusted returns that outperform traditional market indices.

Low Volatility Factor Portfolio

The low volatility factor focuses on investing in stocks with lower historical volatility. This factor aims to provide better risk-adjusted returns, as less volatile stocks tend to experience smaller price swings during market downturns.

The PowerShares S&P 500 Low Volatility ETF (SPLV) is an example of a successful implementation of the low volatility factor. The ETF tracks an index that selects the 100 least volatile stocks from the S&P 500.

This strategy has proven appealing to risk-conscious investors seeking stability in their portfolios. During market downturns, low volatility strategies like SPLV have historically exhibited more resilience than broader market indices.

These applications highlight how factor-based strategies can be successful when applied with discipline and a long-term perspective.

It’s important to note that past performance does not guarantee future results, and market conditions can change. Factor-based investing requires ongoing research, monitoring, and alignment with individual investment goals and risk tolerance.


Factor-based investing introduces a structured approach to constructing investment portfolios that diverges from traditional market-cap-weighted strategies. Factors represent underlying attributes like value, momentum, and size, historically influencing asset performance.

While these factors have exhibited relationships with enhanced returns, it’s crucial to remember that past performance does not guarantee future results. Factor interaction can be intricate, and combining factors requires careful thought to avoid unintended outcomes.

The risk-return trade-off should be evaluated, considering that factors can deliver higher returns and carry inherent risks. Maintaining a patient, long-term perspective is paramount, given that factors’ impact often unfolds over market cycles.

It’s also essential to factor in costs associated with implementing these strategies, including management fees and trading expenses.

Lastly, considering diversified factor exposure and periodic monitoring for rebalancing ensures alignment with the investment objectives.

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Written by Hivelr Quantum Alpha
Empowering Investors with Quantitative Finance. Profile

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