Journal of Financial Markets最新文献

We analyze the predictive value of climate risks for state-level realized stock market volatility, computed, along with other realized moments, based on high-frequency intra-day U.S. data (September, 2011 to October, 2021). A model-based bagging algorithm recovers that climate risks have predictive value for realized volatility at intermediate and long (one and two months) forecast horizons. This finding also holds for upside (“good”) and downside (“bad”) realized volatility. The benefits of using climate risks for predicting state-level realized stock market volatility depend on the shape and (as-)symmetry of a forecaster’s loss function.

Discussions about insider trading regulation veer between the poles of forbidding insider trading to protect market integrity and allowing insider trading to foster informational efficiency. We study traders’ preferences for regulation by offering them concurrent markets with different regulatory regimes in an experimental setting. We find that informed traders’ preference for the unregulated market causes both informed and uninformed traders to be more active in the unregulated market. This market, thus, sees more trading volume, lower spreads, and less mispricing. Nevertheless, uninformed traders suffer greater losses in unregulated markets, while informed traders profit from the absence of regulation.

How does retail trading impact information supply in financial markets? We build a trading model with endogenous information supply where analysts maximize trading volume by institutional investors. In equilibrium, sell-side analysts provide higher quality signals in stocks with large retail interest, as institutional investors can trade more aggressively without revealing information. We provide empirical evidence supporting the main prediction of the model: A one standard deviation increase in retail trading leads to an additional 0.6 analysts covering the stock. To establish causality, we confirm our results using stock splits as a plausibly exogenous shock to retail trading.

In response to terrorism, households reduce their trading activity and equity ownership. While the decline in the net value of trades is consistent with increasing risk aversion, reduced Google search volumes, lower aggregate attention indices, and fewer purchases of newsworthy stocks suggest that investors pay less attention to the financial markets after attacks. Additional tests indicate that investor inattention is driven by distress-induced avoidance rather than distraction, and the effect is limited to retail investors. Finally, reduced retail trading after attacks leads to a decline in stock liquidity.

Institutional investors have a strong incentive to find natural counterparties to be able to trade larger amounts at lower costs. We show theoretically that order splitting allows institutional investors to gradually detect each other’s trading intentions, such that they can coordinate their trading to maximize gains from trade. Empirically, we confirm that investors detect counterparties in real-time and adjust their trading rate accordingly. The economic magnitudes are sizeable, as a one-standard deviation increase in natural counterparty trading volume correlates with a 11.9% increase in parent order size and a 86% reduction in average implementation shortfall.

Exploiting information transmission latency between stock exchanges in Frankfurt and London, and speed-inducing technological upgrades, we show that when cross-market latency arbitrage opportunities are linked to the arrival of information, high-frequency traders' (HFTs’) activities impair liquidity and enhance price discovery by facilitating the incorporation of public information into prices. Conversely, when cross-market latency arbitrage opportunities are driven by liquidity shocks, HFTs improve liquidity and reduce trading costs, thus incentivizing information acquisition and trading with private information. These findings underscore the complex nature of the association between trading speed and market quality and reconcile mixed evidence in the extant literature.

Closing auctions set daily closing prices for U.S. stocks and account for a striking 7.5% of daily volume in 2018, up from 3.1% in 2010. We study closing auctions in the new regime of record volume. Closing auctions appear to match volumes at low cost: closing prices typically match pre-close bid or ask prices, and price impact is lower than during continuous trading. Auction price deviations revert quickly and almost completely, on average. Auction-to-intraday volume spikes on S&P 500 additions and increases permanently afterwards, suggesting that closing volume is fueled directly and indirectly by the growth of indexing and ETFs.

We find that abnormal fourth-quarter capital expenditures are negatively correlated with future stock returns. While this evidence is linked to the asset growth factor, it cannot be entirely attributed to it. The fact that the relationship reverts with contemporaneous returns suggests that ad hoc investments may reflect changing discount rates. However, additional tests indicate that the reported effect is amplified by high payouts, low debt levels, and high idiosyncratic volatility, which is suggestive of over-investment issues. Our analysis supports the notion that firms’ investment decisions contain intricate but valuable information about stock returns.

We exploit a unique experiment, where the intraday price moves of Indian IPO listings are restricted within a narrow band, to examine the consequences of price bands for stock prices, investor trading behavior, and stock market liquidity. Based on difference-in-differences estimations, we find that price bands lead to a significant reduction in the price variability of IPO stocks. The decrease in variability is accompanied by increases in post-IPO selling by individual investors, the price impact of trades, and IPO expected returns. Bid-ask spreads remain similar. The findings provide new evidence on the effects of intraday price bands on equity markets.

We examine the associations between newspapers tone and stock market indices by translating newspapers coverage into human sentiment gauge. Our tone has positive effects on overnight stock returns and negative effects on both intraday returns and conditional volatility. The positive effect of the tone is highly significant on days of sharp price declines and when the tone is calculated using general newspapers. That positive effect, apparently thru opening prices, partly explains the overnight-intraday anomaly. The impact of negative events' coverage is about double the impact of positive events’ coverage. This asymmetry is greater when distinguishing between general and business newspapers.