Abstract We propose to impose a weighted l1 and squared l2 norm penalty on the portfolio weights to improve out-of-sample (OOS) performances of portfolio optimization when the number of assets becomes large. We show that under certain conditions, the realized risk of the optimal minimum variance portfolio (MVP) obtained from the strategy can asymptotically be lower than those of benchmark portfolios with a high probability. Our theoretical results imply that penalty parameters for the weighted-norm penalty can be specified as a simple function of the number of assets and sample size. With the theoretical results, we also develop an automatic calibration procedure for choosing the penalty parameters. We demonstrate superior OOS performances of the weighted-norm MVP with two real data sets. Finally, we propose several alternative norm penalties and show that their OOS performances are comparable to the weighted-norm strategy.

Abstract This paper examines the relation between corporate lobbying and fraud detection. Using data on corporate lobbying expenses between 1998 and 2004, and a sample of large frauds detected during the same period, we find that firms’ lobbying activities make a significant difference in fraud detection: Compared to nonlobbying firms, on average, firms that lobby have a significantly lower hazard rate of being detected for fraud, evade fraud detection 117 days longer, and are 38% less likely to be detected by regulators. In addition, fraudulent firms on average spend 77% more on lobbying than nonfraudulent firms, and they spend 29% more on lobbying during their fraudulent periods than during nonfraudulent periods. The delay in detection leads to a greater distortion in resource allocation during fraudulent periods. It also allows managers to sell more of their shares.

This study shows the influence of investor sentiment on the market's mean–variance tradeoff. We find that the stock market's expected excess return is positively related to the market's conditional variance in low-sentiment periods but unrelated to variance in high-sentiment periods. These findings are consistent with sentiment traders who, during the high-sentiment periods, undermine an otherwise positive mean–variance tradeoff. We also find that the negative correlation between returns and contemporaneous volatility innovations is much stronger in the low-sentiment periods. The latter result is consistent with the stronger positive ex ante relation during such periods.

Abstract We show that the financial sector’s asset supply elasticities are sufficient statistics summarizing its macroeconomic effects for a large class of financial frictions. These elasticities are crucial for a wide range of policy questions, ranging from the size of fiscal multipliers to the relative effectiveness of asset purchases targeting the financial sector versus tax cuts targeting households. Workhorse macroeconomic models imply different values of these elasticities, generating output responses to policies that differ by orders of magnitude. We construct empirical measures of these elasticities and evaluate their policy implications in a quantitative model with household heterogeneity and illiquidity.

Abstract This study compares and contrasts US and international accounting and financial reporting practices for cryptocurrency. We analyze the financial statements of 40 global companies that have exposure to cryptocurrencies, including cryptocurrency purchases, mining, payments, trading, and investments in ICOs and early-stage blockchain ventures. We document inconsistency between Generally Accepted Accounting Principles (GAAP) and International Financial Reporting Standards (IFRS), as well as distortions that can mislead users in assessing asset value, liquidity, profitability, and cash-generating abilities across firms. In particular, firms receiving cryptocurrencies in revenue-generating activities account for cryptocurrencies as intangibles using different measurement bases and classify the associated cash inflows differently. Some firms place cryptocurrencies in the usual long-term location of intangibles, while others consider intangibles as liquid, short-term assets. Limited guidance about crypto-assets from both IFRS and GAAP lets companies choose which existing standard to apply and how to apply it. Understanding the financial and valuation implications of these new virtual assets is vital for future accounting research and professional practice.

This study explores the role of investor sentiment in a broad set of anomalies in cross-sectional stock returns. We consider a setting in which the presence of market-wide sentiment is combined with the argument that overpricing should be more prevalent than underpricing, due to short-sale impediments. Long-short strategies that exploit the anomalies exhibit profits consistent with this setting. First, each anomaly is stronger (its long-short strategy is more profitable) following high levels of sentiment. Second, the short leg of each strategy is more profitable following high sentiment. Finally, sentiment exhibits no relation to returns on the long legs of the strategies.

What is the role of information intermediaries in corporate governance? This paper examines equity analysts’ influence on managers’ earnings management decisions. Do analysts serve as external monitors to managers, or do they put excessive pressure on managers? Using multiple measures of earnings management, I find that firms followed by more analysts manage their earnings less. To address the potential endogeneity problem of analyst coverage, I use two instrumental variables based on change in broker size and on firm's inclusion in the Standard & Poor's 500 index, and I find that the results are robust. Finally, given the number of covering analysts, analysts from top brokers and more experienced analysts have stronger effects against earnings management.

This paper examines how culture affects information asymmetry in financial markets. We extract firms traded in the United States but headquartered in regions sharing Chinese culture (“Chinese firms”), and we manually identify a group of U.S. analysts of Chinese ethnic origin (“Chinese analysts”). We find that Chinese analysts issue more accurate forecasts on Chinese firms than non-Chinese analysts. The effect is stronger among firms with less transparent information environments. Further evidence suggests that cultural proximity can go beyond language commonality and analysts’ pre-existing channels for information. Market reaction is stronger when Chinese analysts issue favorable forecast revisions or upgrades about Chinese firms.