International financial integration helps to diversify risk but also may spread crises across countries. We provide a quantitative analysis of this trade-off in a two-country general equilibrium model with collateral-constrained borrowing using a global solution method. Borrowing constraints bind occasionally, depending upon the state of the economy and levels of inherited debt. We examine different degrees of international financial integration, moving from financial autarky, to bond and equity market integration. Financial integration leads to a significant increase in global leverage, substantially escalates the probability of crises for any one country, and dramatically increases the degree of “contagion” across countries. Outside of crises, the impact of financial integration on macroeconomic aggregates is relatively small. But the impact of a crisis with integrated international financial markets is much less severe than that under financial market autarky. Thus, a trade-off emerges between the probability of crises and the severity of crises. Using a large cross-country database of financial crises in developing and developed economies over a forty-year period, we find evidence in support of the model.

We document that leased capital accounts for about 20% of total physical productive assets used by US public firms, and its proportion is more than 40% among small and financially constrained firms. The leased capital ratio exhibits a strong countercyclical pattern over business cycles and a positive correlation with cross-sectional idiosyncratic uncertainty. We argue that existing macro models with financial frictions assume that firms cannot rent capital and overlook the effects of leasing activities on business cycle dynamics. We explicitly introduce a buy-versus-lease decision into the Bernanke–Gertler–Gilchrist financial accelerator model setting to demonstrate a novel and quantitatively important economic mechanism: that the increased use of leased capital when financial constraints become tighter in bad states significantly mitigates the financial accelerator mechanism and thus also mitigates the response of macroeconomic variables to negative total factor productivity shocks and risk shocks. We provide strong empirical evidence to support our mechanism.

We examine whether adding more founding family members as firm owners and/or managers matters to corporate governance outcomes. Based on a sample of 1242 founder-controlled publicly traded Chinese private-sector firms, we find that more such family involvement is associated with lower volumes of related party transactions suspicious of expropriating shareholder wealth. The curtailing relation is stronger when family members own firm shares and/or serve as managers, and are more arm's-length relatives instead of immediate kin of the founders. The intra-family governance effects are stronger when firms are subject to weaker capital market disciplines or have more free cash under insider discretion. The overall evidence is consistent with founding family members' information advantages and ownership incentives making them more robust monitors of managerial decisions than other formal mechanisms, which help enforce shareholder rights in emerging markets.

Information-based theories of financial intermediation focus on delegated monitoring. However, there is little evidence on how markets discipline intermediaries who fail at this function. We exploit the direct link between corporate fraud and monitoring failure and examine how a venture capital (VC) firm׳s reputation is affected when it fails to prevent fraud in its portfolio companies. We find that reputation-damaged VCs interact differently in the future with their limited partners, other VCs, and IPO underwriters because they are perceived as ineffective monitors. In addition, VCs that fail to prevent fraud experience greater difficulty in taking future portfolio companies public.

A four-factor model with two "mispricing" factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four-and five-factor alternative models. Moreover, our size factor reveals a small-firm premium nearly twice usual estimates. The mispricing factors aggregate information across 11 prominent anomalies by averaging rankings within two clusters exhibiting the greatest return co-movement. Investor sentiment predicts the mispricing factors, especially their short legs, consistent with a mispricing interpretation and the asymmetry in ease of buying versus shorting. A three-factor model with a single mispricing factor also performs well, especially in Bayesian model comparisons.

[In this article, we present a new method for pricing and hedging American options along with an efficient implementation procedure. The proposed method is efficient and accurate in computing both option values and various option hedge parameters. We demonstrate the computational accuracy and efficiency of this numerical procedure in relation to other competing approaches. We also suggest how the method can be applied to the case of any American option for which a closed-form solution exists for the corresponding European option.]

This paper examines the return spillovers between Exchange-Traded Funds (ETFs) and stocks. While traditional approaches focus on proportional relationships between ETFs and their underlying assets, we develop a high-dimensional network framework that captures spillover effects between any ETF-stock pair, regardless of their compositional relationship. By separating idiosyncratic and systematic risks, we investigate potential drivers of contagion. We document substantial heterogeneity in spillover patterns across sectors, which is previously unaddressed in the literature. Sectors such as Utilities and Real Estate exhibit robust spillovers to both their component stocks and assets in other sectors. Conversely, in sectors such as Consumer Discretionary and Finance , cross-sector influences dominate intra-sector ETF-constituent linkages. Our results also highlight that during periods of high market volatility, sources of idiosyncratic contagion become more diverse, suggesting the need for broader market surveillance beyond the few most influential ETFs.

After exogenous demand shocks caused by natural disasters, FinTech lenders are more responsive to increased demand for reconstruction mortgages than traditional banks and non-FinTech shadow banks. Both FinTech and traditional banks increase credit supply, but FinTech supply is more elastic without increases in risk-adjusted interest rates or delinquency rates. Comparing lending supply channels, banks respond to regulatory incentives to lend to damaged areas, whereas FinTech lenders supply more credit when traditional banks rely more on balance sheet financing and physical branch networks. Compared to traditional banks, FinTech lenders increase supply elasticity more aggressively in response to local competitive pressure.