Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Reading Level
      Reading Level
      Clear All
      Reading Level
  • Content Type
      Content Type
      Clear All
      Content Type
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
      More Filters
      Clear All
      More Filters
      Item Type
    • Is Full-Text Available
    • Subject
    • Publisher
    • Source
    • Donor
    • Language
    • Place of Publication
    • Contributors
    • Location
18,200,283 result(s) for "RETURNS"
Sort by:
Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence
Recent empirical evidence suggests that the variance risk premium predicts aggregate stock market returns. We demonstrate that statistical finite sample biases cannot “explain” this apparent predictability. Further corroborating the existing evidence of the United States, we show that country-specific regressions for France, Germany, Japan, Switzerland, the Netherlands, Belgium, and the United Kingdom result in quite similar patterns. Defining a “global” variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions.
Practically Poppins in every way : a magical carpetbag of countless wonders
Ever since 1934, when Mary Poppins descended from the skies over London into Cherry Tree Lane in the beloved book by P. L. Travers, the world has adored the enchanting adventures and peculiar wisdom of this magical nanny. For more than eight decades, Travers's staunch but charming heroine has been beloved in the pages of eight popular books-and in media-from movies to stage, and music to television, all around the world. Now Mary Poppins has come to light up cinema screens again in a magical, musical new incarnation, Mary Poppins Returns. From the Walt Disney Studios, this film is a colorful and charming new story--a sequel to the 1964 classic-featuring an all-star cast and brought to life by a stellar creative team. In Depression-era London, a now-grown Jane and Michael Banks, along with Michael's three children, are visited by the enigmatic Mary Poppins following a personal, grievous loss. She's back just in time. And through her unique magical skills and presence, plus the aid of her friend Jack, Mary helps restore for the troubled family the joy and wonder that's been lost in their lives. Every incarnation of Mary Poppins has had at least one thing in common: she's always arrived out of the blue, though the stay is for an all-too brief period of time-until the wind changes or the chain breaks-whereupon she flies away again for, as Pamela Travers put it, \"Apparently . . . nowhere.\" Practically Poppins In Every Way is a showcase of the varied creative forces that have brought Mary Poppins to life, generation after generation. It is accompanied by erudite and informative text, essays, and observations by creative luminaries such as Cameron Mackintosh, Thomas Schumacher, Gavin Lee, and John Myhre, as well as renowned Disney authorities Brian Sibley, Jim Fanning, Paula Sigman Lowery, Craig D. Barton, and Greg Ehrbar.
Can Twitter Help Predict Firm-Level Earnings and Stock Returns?
Prior research has examined how companies exploit Twitter in communicating with investors, and whether Twitter activity predicts the stock market as a whole. We test whether opinions of individuals tweeted just prior to a firm's earnings announcement predict its earnings and announcement returns. Using a broad sample from 2009 to 2012, we find that the aggregate opinion from individual tweets successfully predicts a firm's forthcoming quarterly earnings and announcement returns. These results hold for tweets that convey original information, as well as tweets that disseminate existing information, and are stronger for tweets providing information directly related to firm fundamentals and stock trading. Importantly, our results hold even after controlling for concurrent information or opinion from traditional media sources, and are stronger for firms in weaker information environments. Our findings highlight the importance of considering the aggregate opinion from individual tweets when assessing a stock's future prospects and value.
Dissecting Anomalies
The anomalous returns associated with net stock issues, accruals, and momentum are pervasive; they show up in all size groups (micro, small, and big) in cross-section regressions, and they are also strong in sorts, at least in the extremes. The asset growth and profitability anomalies are less robust. There is an asset growth anomaly in average returns on microcaps and small stocks, but it is absent for big stocks. Among profitable firms, higher profitability tends to be associated with abnormally high returns, but there is little evidence that unprofitable firms have unusually low returns.
Takeovers and the Cross-Section of Returns
This paper considers the impact of the takeover likelihood on firm valuation. If firms are more likely to acquire when there is more free cash or lower required rates of return, the targets become more sensitive to shocks to cash flows or the price of risk. Ceteris paribus, firms exposed to takeovers have different rates of return than protected firms. Using takeover likelihood estimates, we create a \"takeover factor,\" buying (selling) firms with a high (low) takeover likelihood, which generates \"abnormal\" returns. Several tests confirm that the takeover factor helps explaining cross-sectional differences in equity returns and is related to takeover activity.
HETEROGENEITY AND PERSISTENCE IN RETURNS TO WEALTH
We provide a systematic analysis of the properties of individual returns to wealth using 12 years of population data from Norway’s administrative tax records. We document a number of novel results. First, individuals earn markedly different average returns on their net worth (a standard deviation of 22.1%) and on its components. Second, heterogeneity in returns does not arise merely from differences in the allocation of wealth between safe and risky assets: returns are heterogeneous even within narrow asset classes. Third, returns are positively correlated with wealth: moving from the 10th to the 90th percentile of the net worth distribution increases the return by 18 percentage points (and 10 percentage points if looking at net-of-tax returns). Fourth, individual wealth returns exhibit substantial persistence over time. We argue that while this persistence partly arises from stable differences in risk exposure and assets scale, it also reflects heterogeneity in sophistication and financial information, as well as entrepreneurial talent. Finally, wealth returns are correlated across generations. We discuss the implications of these findings for several strands of the wealth inequality debate.
Expectations of Returns and Expected Returns
We analyze time series of investor expectations of future stock market returns from six data sources between 1963 and 2011. The six measures of expectations are highly positively correlated with each other, as well as with past stock returns and with the level of the stock market. However, investor expectations are strongly negatively correlated with model-based expected returns. The evidence is not consistent with rational expectations representative investor models of returns.
Infrequent Rebalancing, Return Autocorrelation, and Seasonality
A model of infrequent rebalancing can explain specific predictability patterns in the time series and cross-section of stock returns. First, infrequent rebalancing produces return autocorrelations that are consistent with empirical evidence from intraday returns and new evidence from daily returns. Autocorrelations can switch sign and become positive at the rebalancing horizon. Second, the cross-sectional variance in expected returns is larger when more traders rebalance. This effect generates seasonality in the cross-section of stock returns, which can help explain available empirical evidence.
ESG Preference, Institutional Trading, and Stock Return Patterns
Socially responsible (SR) institutions tend to focus more on the environmental, social, and governance (ESG) performance and less on quantitative signals of value. Consistent with this difference in focus, we find that SR institutions react less to quantitative mispricing signals. Our evidence suggests that the increased focus on ESG may have influenced stock return patterns. Specifically, abnormal returns associated with these mispricing signals are greater for stocks held more by SR institutions. The link between SR ownership and the efficacy of mispricing signals only emerges in recent years with the rise of ESG investing, and is significant only when there are arbitrage-related funding constraints.