From 2007 to June 2013, a small group of fee-paying, high-speed traders receive the Michigan Index of Consumer Sentiment two seconds before its broader release. Within this early peek window, we find highly concentrated trading and a fast price discovery of less than 200 milliseconds. Outside this narrow window, general investors trade at fully adjusted prices. We further establish a causal relationship between the early peek mechanism and the fast price discovery by isolating the impact of the early peek arrangement along two dimensions. In cross section, we use other news releases without the early peek (as controls); in time series, we use the sudden suspension of the early peek arrangement in July 2013 (as the treatment). Our difference-in-difference tests directly connect the early peek arrangement to more efficient price discovery — it results in faster price discovery, lower volatility, and faster resolution of uncertainty. These results show that contrary to the common perception, tiered information release may help to reduce, rather than enhance, the informational advantage of faster traders and improve the efficiency of the price discovery process in financial markets.

We document the central role of collateral in the pricing of tri-party repos. Markets are competitive for repos with safe collateral but are severely segmented for repos with risky collateral, such as equities and low-grade corporate bonds. Fund families are the sole contributors to the segmentation, and collateral concentration is the main determinant in the substantial variation in repo pricing, both across and within segments. The segmented structure points to Fidelity as a systemically important player and the markets potential fragility. Facing market segmentation, dealers optimize financing costs by allocating their collateral across fund families.

Portfolios selected based on the sample covariance estimates may not be stable or robust, particularly so in situations with a large number of assets. The l1 or l2 norm constrained portfolio optimization method has been used as a robust method to control the sparsity or to shrink the estimated weights of assets. In this paper, we propose to add an additional l∞ norm constraint or to add a pairwise l∞ norm constraint in the l1 norm constrained minimum-variance portfolio (MVP) problem. The l∞ constraint controls the largest absolute component of the weight vector and the pairwise l∞ constraint encourages retaining the cluster structure of highly correlated assets in MVP optimization. By simulation study and analysis of empirical data, we find that the proposed portfolios often have better out-of-sample performance in terms of Sharpe ratios, variances and turn-overs than existing popular portfolio strategies including the l1 norm constrained MVP, l2 norm constrained MVP and the 1/N portfolio. In addition, we provide moment shrinkage interpretations of the new strategies and an upper bound of errors in the approximation of the empirical optimal portfolio risk based on the theoretical optimal portfolio risk.

We find large overnight returns with no abnormal variance before nonfarm payrolls, ISM, and GDP announcements, similar to the pre-FOMC returns. To explain this common pattern, we propose a two-risk model with the uncertainty about the magnitude of the impending news’ market impact as an additional risk, and link the pre-announcement return directly to the accumulation of heightened uncertainty and its later resolution prior to the announcement. We empirically test and verify the model’s distinct predictions on the joint intertemporal behavior of return, variance, and particularly VIX – a gauge of impact uncertainty by our model, surrounding macroeconomic announcements.

ABSTRACT We propose a market‐wide liquidity measure by exploiting the connection between the amount of arbitrage capital in the market and observed “noise” in U.S. Treasury bonds—the shortage of arbitrage capital allows yields to deviate more freely from the curve, resulting in more noise in prices. Our noise measure captures episodes of liquidity crises of different origins across the financial market, providing information beyond existing liquidity proxies. Moreover, as a priced risk factor, it helps to explain cross‐sectional returns on hedge funds and currency carry trades, both known to be sensitive to the general liquidity conditions of the market.

Urban forests are ubiquitous, yet their impacts and values remain largely unknown. We study a massive urban afforestation policy in Beijing that planted 1/3 of a million acres of greenery in less than a decade. We conduct a remote-sensing audit of the program, finding that it contributes to a substantial greening up of the city. This causes significant downwind air quality improvement, reducing average PM2.5 concentration at city population hubs by 4.2%. Rapid vegetation growth unexpectedly led to a 7.4% increase in pollen exposure. Analysis of medical claims data shows that increased aeroallergens triggered emergency room visits, mirroring pollution effects though much less severe. Monetized net health benefits of the program amount to 1.5% of the city’s GDP. Urban forests are only partially capitalized in housing values, with buyers mainly appreciating proximity to green spaces but not the air quality improvements they bring.