Uncertainty affects business cycles and asset prices. We estimate firm-level productivity and decompose total uncertainty risk measured as cross-sectional productivity dispersion into macro uncertainty (an aggregate component) and micro uncertainty (an idiosyncratic component). We find that macro uncertainty is multidimensional, strongly countercyclical, and priced among stocks, but micro uncertainty is acyclical and not priced. Moreover, we show that the expected investment growth factor proposed in Hou, Mo, Xue, and Zhang (2021) captures macro uncertainty risk which helps us understand the success of the q5-model.
This paper examines how longevity shocks impact corporate debt markets. We show that changes in life expectancy influence corporate debt through life insurers, who adjust the duration of their bond portfolios to match their liabilities. When longevity unexpectedly shifts, insurers alter their demand for corporate bonds of specific maturities, affecting corporate term spreads. In response, corporations adjust new debt maturities, with the effect concentrated among insurer-dependent firms and those with investment-grade ratings, which insurers prefer.
We develop a statistical learning framework for constructing the stochastic discount factor (SDF) portfolio. To address the dimensionality challenge, we extend the MAXSER method (Ao et al., 2019) to allow for N >> T; prove that it surely screens for useful characteristics; and establish asymptotic normality for the SDF loading estimates. Using 153 characteristics returns from cross-sectional regressions (Fama and French, 2020), our framework not only constructs an SDF with a high out-ofsample Sharpe ratio that successfully prices the cross-section of expected returns, but also allows us to identify key characteristic themes and test the significance of their contributions.
This paper examines the financial impacts of transition risk on firms and aggregate economy through the deployment of solar power plants (SPPs) in China. We found that more SPPs were deployed in areas with lower solar radiation and negatively affected the local economy. Cities with SPPs experienced a lower local GDP growth of approximately 0.8-1.8%. At the firm level, SPP deployment decreased corporate investment and debt financing, and increased financing costs in other sectors. These effects were more pronounced for private firms, firms relying on external fiancing or productive firms. The crowding-out effect under capital misallocation drives our findings.
Examining a cross section of seven regional Emission Trading System (ETS) and the national ETS in China, we explore the interplay between firms and governments. We find heterogeneous adaptation among firms. Firms in regions anticipating stringent policies reduce emissions and invest in decarbonization technology, whereas expectations of leniency lead to increased emissions. Meanwhile, governments set up more stringent carbon policies when firms decarbonize more proactively. The results are robust to allowance allocation policies, such as cap-and-trade or tradable performance standards. Our findings underscore the importance of strategic interactions between firms and governments in decarbonization.
We test whether the diversification of marginal investor affects the underlying firm’s cost of equity. We use institutional investor holdings data to identify the marginal investor. We measure institutional investor diversification as the goodness of fit of a benchmark asset pricing model with respect to the investor portfolio returns. We find that firms with less diversified investors have a higher cost of equity and lower real investment. These findings are not driven by firm size, idiosyncratic volatility, institutional ownership, liquidity, investor stock selectivity, or behavioral biases. Collective evidence leans toward the market incompleteness explanation (Merton, 1987).
We study the duration-hedging trades of duration-sensitive strategic investors, i.e., pensions and life insurers. We use longevity shocks to identify their duration-hedging trades. Longevity shocks affect these investors' liability duration and induce them to adjust their asset duration. When longevity shocks are low (high), they buy more short- (long-) duration stocks and sell more long- (short-) duration stocks. Because prior winners (losers) have shorter (longer) duration, they behave like momentum (contrarian) traders when longevity shocks are low (high). We further verify this channel using capital flows and cross-state longevity variations.
Motivated by production-based asset pricing models, we study the pricing power of fundamental risks to understand the prevailing pricing factors. We find that six aggregate productivity components trace 13 of 15 prevailing pricing factors, including all factors proposed in Fama-French six-factor model (Fama and French, 2018), q-factor model (Hou et al., 2020), and the mispricing models (Stambaugh and Yuan, 2017; Daniel et al., 2020), except for the expected investment growth factor (Hou et al., 2020) and the post-earnings-announcement drift (Daniel et al., 2020). However, the first productivity component is not captured by these factor models, which represents the labor risk.
This paper investigates how disagreement, asset returns and liquidity are affected by three types of heterogeneity in information environment: asymmetric information (AI), idiosyncratic noises (IN), and different opinion (DO). Using a market microstructure model, we incorporate analyst forecasts into endogenous informed trading. This framework allows us to empirically interpret the level of AI, IN, and DO decomposed from analyst disagreement. Our model shows that AI increases both illiquidity and pricing error; IN reduces illiquidity but increases pricing error; DO reduces both illiquidity and pricing error. Using data over 1987–2016, the empirical results support the implications of theoretical model. Moreover, we find that stocks with high AI or high IN tend to be overpriced, and stocks with low DO tend to be underpriced.
We present a theory of endogenous coalition formation in financial markets, which highlights the information sharing and market competition features of coalitions. Allied members enjoy benefits of information advantage and monopolistic power in trading, but forming coalitions incurs direct costs of setting up coalitions and indirect costs from market liquidity dry-ups. Such a trade-off determines the coalition structure of the economy. As allied members behave more monopolistically, coalitions have negative effects on price informativeness and market liquidity. From the information perspective, financial intermediaries (e.g., asset management companies in the mutual fund industry) can be viewed as coalitions of of market players (e.g., fund managers). Our theory provides novel insights about the structure of this industry.