Matching Items (6)

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Do financial analysts respond efficiently to managers' earnings guidance?

Description

When managers provide earnings guidance, analysts normally respond within a short time frame with their own earnings forecasts. Within this setting, I investigate whether financial analysts use publicly available information

When managers provide earnings guidance, analysts normally respond within a short time frame with their own earnings forecasts. Within this setting, I investigate whether financial analysts use publicly available information to adjust for predictable error in management guidance and, if so, the explanation for such inefficiency. I provide evidence that analysts do not fully adjust for predictable guidance error when revising forecasts. The analyst inefficiency is attributed to analysts' attempts to advance relationship with the managers, analysts' compensation not tie to forecast accuracy, and their forecasting ability. Finally, the stock market acts as if it does not fully realize that analysts respond inefficiently to the guidance, introducing mispricing. This mispricing is not fully corrected upon earnings announcement.

Contributors

Agent

Created

Date Created
  • 2012

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Give it to me straight: how, when, and why managers disclose inside information about seasoned equity offerings

Description

Managers’ control over the timing and content of information disclosure represents a significant strategic tool which they can use at their discretion. However, extant theoretical perspectives offer incongruent arguments and

Managers’ control over the timing and content of information disclosure represents a significant strategic tool which they can use at their discretion. However, extant theoretical perspectives offer incongruent arguments and incompatible predictions about when and why managers would release inside information about their firms. More specifically, agency theory and theories within competitive dynamics provide competing hypotheses about when and why managers would disclose inside information about their firms. In this study, I highlight how voluntary disclosure theory may help to coalesce these two theoretical perspectives. Voluntary disclosure theory predicts that managers will release inside information when managers perceive that the benefits outweigh the costs of doing so. Accordingly, I posit that competitive dynamics introduce the costs associated with disclosing information (i.e., proprietary costs) and that agency theory highlights the benefits associated with disclosing information. Examining the context of seasoned equity offerings (SEOs), I identify three ways managers can use information in SEO prospectuses. I hypothesize that competitive intensity increases proprietary costs that will reduce disclosure of inside information but will increase discussing the organization positively. I then hypothesize that capital market participants (e.g., security analysts and investors) may prefer managers to provide more, clearer, and positive information about the SEO and their firms. I find support for many of my hypotheses.

Contributors

Agent

Created

Date Created
  • 2017

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Analyzing the effects of Bollinger bands on the probability of stock options using support vector machines

Description

The purpose of this research is to efficiently analyze certain data provided and to see if a useful trend can be observed as a result. This trend can be used

The purpose of this research is to efficiently analyze certain data provided and to see if a useful trend can be observed as a result. This trend can be used to analyze certain probabilities. There are three main pieces of data which are being analyzed in this research: The value for δ of the call and put option, the %B value of the stock, and the amount of time until expiration of the stock option. The %B value is the most important. The purpose of analyzing the data is to see the relationship between the variables and, given certain values, what is the probability the trade makes money. This result will be used in finding the probability certain trades make money over a period of time.

Since options are so dependent on probability, this research specifically analyzes stock options rather than stocks themselves. Stock options have value like stocks except options are leveraged. The most common model used to calculate the value of an option is the Black-Scholes Model [1]. There are five main variables the Black-Scholes Model uses to calculate the overall value of an option. These variables are θ, δ, γ, v, and ρ. The variable, θ is the rate of change in price of the option due to time decay, δ is the rate of change of the option’s price due to the stock’s changing value, γ is the rate of change of δ, v represents the rate of change of the value of the option in relation to the stock’s volatility, and ρ represents the rate of change in value of the option in relation to the interest rate [2]. In this research, the %B value of the stock is analyzed along with the time until expiration of the option. All options have the same δ. This is due to the fact that all the options analyzed in this experiment are less than two months from expiration and the value of δ reveals how far in or out of the money an option is.

The machine learning technique used to analyze the data and the probability

is support vector machines. Support vector machines analyze data that can be classified in one of two or more groups and attempts to find a pattern in the data to develop a model, which reliably classifies similar, future data into the correct group. This is used to analyze the outcome of stock options.

Contributors

Agent

Created

Date Created
  • 2015

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Essays in finance

Description

In the first chapter, I develop a representative agent model in which the purchase of consumption goods must be planned in advance. Volatility in the agent's portfolio increases the risk

In the first chapter, I develop a representative agent model in which the purchase of consumption goods must be planned in advance. Volatility in the agent's portfolio increases the risk that a purchase cannot be implemented. This implementation risk causes the agent to make conservative consumption plans. In the model, this leads to persistent and negatively skewed consumption growth and a slow reaction of consumption to wealth shocks. The model proposes a novel explanation for the negative relation between volatility and expected utility. In equilibrium, prices of risky assets must compensate for the utility loss. Hence, the model suggests a new mechanism for generating the equity risk premium. Importantly, because implementation risk does not rely on the co-movement of asset prices with marginal utility, the resulting equity premium does not require concavity of the intratemporal utility function.

In the second chapter, I challenge the view that equity market timing always benefits

shareholders. By distinguishing the effect of a firm's equity decisions from the effect of mispricing itself, I show that market timing can decrease shareholder value. Additionally, the timing of equity sales has a more negative effect on existing shareholders than the timing of share repurchases. My theory can be used to infer firms' maximization objectives from their observed market timing strategies. I argue that the popularity of stock buybacks, the low frequency of seasoned equity offerings, and the observed post-event stock returns are consistent with managers maximizing current shareholder value.

Contributors

Agent

Created

Date Created
  • 2015

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Analysts and corporate liquidity policy

Description

This paper examines how equity analysts' roles as information intermediaries and monitors affect corporate liquidity policy and its associated value of cash, providing new evidence that analysts have a direct

This paper examines how equity analysts' roles as information intermediaries and monitors affect corporate liquidity policy and its associated value of cash, providing new evidence that analysts have a direct impact on corporate liquidity policy. Greater analyst coverage (1) reduces information asymmetry between a firm and outside shareholders and (2) enhances the monitoring process. Consistent with these arguments, analyst coverage increases the value of cash, thereby allowing firms to hold more cash. The cash-to-assets ratio increases by 5.2 percentage points when moving from the bottom analyst-coverage decile to the top decile. The marginal value of $1 of corporate cash holdings is $0.93 for the bottom analyst-coverage decile and $1.83 for the top decile. The positive effects remain robust after a battery of endogeneity checks. I also perform tests employing a unique dataset that consists of public and private firms, as well as a dataset that consists of public firms that have gone private. A public firm with analyst coverage can hold approximately 8% more cash than its private counterpart. These findings constitute new evidence on the real effect of analyst coverage.

Contributors

Agent

Created

Date Created
  • 2012

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Did small investors benefit from the Global Settlement?

Description

Responding to the allegedly biased research reports issued by large investment banks, the Global Research Analyst Settlement and related regulations went to great lengths to weaken the conflicts of interest

Responding to the allegedly biased research reports issued by large investment banks, the Global Research Analyst Settlement and related regulations went to great lengths to weaken the conflicts of interest faced by investment bank analysts. In this paper, I investigate the effects of these changes on small and large investor confidence and on trading profitability. Specifically, I examine abnormal trading volumes generated by small and large investors in response to security analyst recommendations and the resulting abnormal market returns generated. I find an overall increase in investor confidence in the post-regulation period relative to the pre-regulation period consistent with a reduction in existing conflicts of interest. The change in confidence observed is particularly striking for small traders. I also find that small trader profitability has increased in the post-regulation period relative to the pre-regulation period whereas that for large traders has decreased. These results are consistent with the Securities and Exchange Commission's primary mission to protect small investors and maintain the integrity of the securities markets.

Contributors

Agent

Created

Date Created
  • 2011