We study whether changes in financial intermediaries' demand for duration affect corporate financing. Life insurers provide a natural setting because revisions in life expectancy alter the duration of their liabilities. Improvements in longevity increase insurers' purchases of long-maturity corporate bonds and the duration of their corporate bond portfolios, generating plausibly exogenous variation in intermediary demand. Positive longevity shocks are associated with lower corporate term spreads. Consistent with these market-level responses, firms with greater exposure to insurer demand issue longer-maturity debt. The findings identify a financial-market transmission mechanism linking longevity revisions to corporate financing.
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-of-sample 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 find that SPPs negatively affects the local economy. Cities with SPPs experienced a lower local GDP growth of 0.8-1.8%. At the firm level, building SPPs decreases corporate investment and debt financing, and increases financing costs in other sectors, with stronger effects for private, externally financing dependent, and more productive firms. We establish causality via staggered adoption, neighborhood-pair comparisons, and an instrumental variable strategy. We show that 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.
Do life insurers, the largest holders of U.S. corporate bonds, stabilize or fragment the liquidity of the bonds they hold? The literature treats institutional buy-and-hold ownership as one-directional for liquidity. We show the effect is conditional on the bond's own liquidity. As insurer ownership rises, illiquidity traces an inverted-U in bonds that are already liquid and a U-shape in bonds that are already illiquid, so insurers fragment liquid bonds, where moderate ownership raises transaction costs, and stabilize illiquid bonds, where moderate ownership lowers them. Two equilibrium forces generate the flip. Clientele displacement shrinks the active-trading float and raises search costs, dominating in liquid bonds. Order-flow diversification lowers the dealer's inventory risk when insurer and active-trader flows are balanced, dominating in illiquid bonds. The conditional pattern holds across ten illiquidity measures, within investment-grade bonds, within issuer bond pairs, and around NAIC rating changes. Because insurers stabilize thin markets and fragment liquid ones, their contribution to bond-market fragility is state dependent and not captured by aggregate measures of insurer exposure.
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.