Research Review | 7 November 2024 | Market Analytics

Climate Risk and Predictability of Global Stock Market Volatility
Mingtao Zhou and Yong Ma (Hunan University)
March 2024
Our study investigates the informative role of climate risk in improving the predictability of global stock market volatility. By extracting the composite component from the four individual climate risk proxies of Faccini et al. (2023), we show that aggregate climate risk is a significantly positive predictor of stock volatility across 32 international markets. This predictability persists in out-of-sample tests and cannot be subsumed by relevant economic and financial uncertainty measures. However, the predictive power of aggregate climate risk exhibits noteworthy variations over time and across regions; it weakens when economic conditions deteriorate, while it strengthens in regions with advanced financial development, high energy dependence, and strong climate change readiness. Moreover, by dissecting the multi-facets of climate risk, we demonstrate that physical risks, especially natural disasters, have much stronger predictability than transition risks.

Fear in the “Fearless” Treasury Market
Tianyang Wang (Colorado State University), et al.
September 2024
This paper examines how fear affects the Treasury market and predicts Treasury bond returns. Using a text-based fear index from social and news media, we find that fear significantly predicts future Treasury returns, both in-sample and out-of-sample, and suggests the global transmission of fear. We also propose a model explaining that risk aversion shocks drive bond risk premia. Our paper further explores various dimensions of fear effects, such as term, magnitude, dynamics, and sources, and compares them with other sentiments. The results highlight the critical role of fear in Treasury market dynamics.

A Unified Framework for Value and Momentum
Jacob Boudoukh (Reichman University), et al.
August 2024
A simple unifying present value framework provides an understanding for value and momentum effects in asset prices. Through the present value formula, valuation ratios adjusted for expected future earnings growth provide estimates of expected returns. We argue and show that momentum is a reasonable proxy for growth. Momentum forecasts future earnings growth, significantly improves value’s forecast for expected returns, and is drowned out when accounting for future realized growth. Extending the analysis to more general earnings growth models, we construct theoretically-motivated single factor models based on growth-adjusted value that price the cross-section of assets well relative to popular multifactor models.

Which Way Does the Wind Blow Between SPX Futures and VIX Futures?
Ekow Aikins and Alexander Kurov (West Virginia University)
July 2024
The negative correlation between returns and volatility is well known. However, there is no consensus on whether returns cause changes in volatility or vice versa. In this paper, we investigate the contemporaneous relation between the VIX futures and E-mini S&P 500 futures markets with the aim of shedding new light on the relation between market returns and implied volatility. We use the E-mini S&P 500 futures (often referred to as SPX futures) as a proxy for stock market returns and VIX futures as a proxy for expectations of implied volatility. We consistently find that stock returns cause changes in expectations of implied volatility. To estimate the coefficients of interest, we use an identification through heteroskedasticity approach which takes advantage of predictable intraday shifts in volatility in the two futures markets.

The Wider the Value Spread, the Larger the Expected Value Premium: Evidence from Russell 1000 Component Stocks
Gengnan Chiang (Feng Chia University)
October 2024
In recent years, there has been a lively debate among academics and investment professionals regarding the presence of the value premium. However, our study, which utilizes the robust panel smooth transition regression (PSTR) model developed by González et al. (2005), has yielded a significant discovery. We have identified a substantial average value premium of 17.27% annually for Russell 1000 components from 2010 to 2019. This finding confirms the significant positive (negative) impact of value spreads on the expected returns for small-value (big-growth) stocks, offering a fresh perspective. Importantly, our research aligns with Baba et al.’s (2021) conclusion that the value premium increases with a wider value spread. This study also validates that over 30% of small-value firms shifted to big-growth firms in the Consumer Discretionary, Information Technology, and Real Estate sectors over the sample years. Finally, our robustness test demonstrates a significant value premium that persists out-of-sample from 2020 to 2022. These findings hold profound implications for the investment community, rendering them more pertinent and actionable and potentially guiding investment strategies in the future.

The Impact of Uncertainty on Volatility-Managed Investment Strategies
Richard D. F. Harris (University of Bristol)
July 2024
We investigate the relationship between the performance of volatility-managed investment strategies and uncertainty, both across stocks and over time. We demonstrate that volatility management yields a significantly larger improvement in risk-adjusted performance for stocks with low uncertainty compared to those with high uncertainty, and for the market portfolio, it yields better performance during periods of low aggregate uncertainty compared to periods of high uncertainty. We also show that differences in uncertainty can partially explain the differential performance of volatility management strategies across factor-sorted portfolios, and that sentiment-based explanations for the performance of volatility management depend on the level of uncertainty. Our results are robust to the use of alternative proxies for uncertainty and alternative volatility management strategies.

How to Improve Commodity Momentum Using Intra-Market Correlation
Radovan Vojtko and Margaréta Pauchlyová (Quantpedia)
September 2024
Momentum strategies have seen diminishing returns across various asset classes in recent years. This paper proposes an innovative approach to improve momentum performance in commodity markets using an intra-market correlation filter. We use the relationship between short-term and long-term correlations as a predictor for when to apply momentum or reversal trading depending on market conditions. Our findings demonstrate that when the short-term correlation exceeds the long-term correlation, a momentum strategy-going long on top-performing ETFs and short on underperformers-yields optimal results. Conversely, when the short-term correlation is lower, a reversal strategy is more effective. This combined approach significantly enhances returns, nearly doubling those of standalone momentum or reversal strategies, while maintaining manageable levels of risk.

Global Risk Aversion and the Term Premium Gap in Emerging Market Economies
Marco Flaccadoro and Stefania Villa (Bank of Italy)
October 2024
In this paper we analyzee the impact of shocks to global risk aversion on the term structure of sovereign spreads between emerging market economies (EMEs) and the US economy. Focusing on the difference between long- and short-term spreads (i.e. the term premium gap), we find that an increase in global risk aversion reduces the term premium gap. This finding is consistent with the evidence that during crises EMEs experience a higher risk of default with respect to safe advanced economies, and more strongly so at shorter maturities.

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