Limits to Diversification: Passive Investing and Market Risk
Lily H. Fang (INSEAD), et al.
September 2024
We show that the rise of passive investing leads to higher correlations among stocks and increased market volatility, thereby limiting the benefit of diversification. The extent to which a stock is held by passive funds (index mutual funds and ETFs) positively predicts its beta, correlation, and covariance with other stocks, but not its idiosyncratic volatility. During crisis periods, stocks with high passive holdings contribute more to market risk compared to before the crisis. Correlated trading by passive funds explains these results, which are further amplified by implicit indexing due to performance benchmarking.

Passive Investing and the Rise of Mega-Firms
Hao Jiang (Michigan State University), et al.
June 2024
We study how passive investing affects asset prices. Flows into passive funds raise disproportionately the stock prices of the economy’s largest firms, and especially those large firms that the market overvalues. These effects are sufficiently strong to cause the aggregate market to rise even when flows are entirely due to investors switching from active to passive. Our results arise because flows create idiosyncratic volatility for large firms, which discourages investors from correcting the flows’ effects on prices. Consistent with our theory, the largest firms in the S&P500 experience the highest returns and increases in volatility following flows into that index.

Passive Investment Styles
Tom Ernst (Goethe University Frankfurt), et al.
November 2024
Passive investment funds hold cash, for example to honor redemption claims. We show that in the presence of cash there is no uniquely optimal passive strategy. Instead a trade-off arises: Minimizing tracking error generates a return gap, whereas closing this gap increases tracking error. This gives rise to different passive investment styles. We theoretically and empirically document that three different styles exist, which cater to three different investor types. Furthermore, the existence of cash inevitably leads to deviations from the benchmark (positive and negative) if a fund minimizes tracking error. As a consequence, the passive industry as a whole generates a heterogeneous price impact in the cross section of stock returns resulting from these deviations.

Index Investing and Sentiment Spillover
Adem Atmaz and Zibo Zhou (Purdue University)
October 2024
We develop a dynamic model of index investing that can reconcile key cross-sectional differences between index and non-index stocks. In our model, investors with extrapolative expectations create sentiment, and index investing spills the sentiment on an index stock to all other index stocks. Primarily due to this spillover mechanism, we find that when index investors are mostly extrapolators, all consistent with empirical evidence, index stocks have higher and more volatile prices, comove more with other index stocks, exhibit stronger negative price autocorrelation, and have higher trading volume than comparable non-index stocks. Our model also reconciles the recently observed “disappearing index effect” and delivers novel implications on the flow-performance relation for index funds, the response of investor portfolios to their subjective beliefs, and the welfare costs of index investing.

Smarter Beta Investing: More Focus, Less Sustainability Bias, Same Performance
Heiko Bailer (LBBW AM) and Jonathan Miller (HSBC)
June 2024
This study demonstrates how smart beta indices, tilted towards Size, Quality, Value, and other factor tilts, can be replicated, and customized to address inherent sustainability biases while maintaining the Sharpe ratio. Using the MSCI Barra Portfolio Manager platform, the core MSCI World Factor Tilt indices are replicated and analyzed. The findings highlight the absence of pronounced factor tilts in MSCI Tilt indices for the ESG and Quality factors, while the Value Tilt index displays additional Yield and Quality tilts. A sustainability analysis of the benchmarked factor portfolios reveals a high sustainability bias with significant variations in emissions and climate transition. For example, an ESG tilt (lower ESG risk) correlates with improved sustainability, in contrast to the high emissions observed in Value and Quality indices. Customizing by reducing constituents and increasing the target tilt by 50% amplifies sustainability bias, notably doubling Value’s emissions. Integrating sustainable constraints effectively mitigates sustainability biases across the eight factor-tilt portfolios while preserving their target tilts and Sharpe ratios. This approach allows asset managers to maintain their traditional factor-based investing approach, sharpen their tilt, and adhere to increasing sustainable regulations, all while maintaining performance.

Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return
By James Picerno