The study that has been conducted in this article assists to determine the predictability of jump arrivals specifically in the stock markets of the United States. The article uses more effective methods, a new non-parametric test to assess jump predictors up to the level of the intraday. The author has used the new parameter to identify jump dynamics and the way these dynamics are distributed across the United States stock markets.
The results obtained in the non-parametric study indicate that there is a high possibility of the dynamic jumps occurring immediately after the release of macroeconomic data. The macroeconomic information includes nonfarm payroll reports, market index jumps, Federal Reserve announcements, and jobless claims among others. The study has also displayed a strong correlation between an organization’s specific jump predictors and other aspects such as analyst recommendations, earning releases, dates of dividends, and jumps on the previous stock.
It is evident from the study that systemic jumps are distinguishable from other jumps such as idiosyncratic ones. The jump predictors are the tools used to differentiate the systematic jumps from other jumps. In addition, the individual stock jumps are correlated to the company’s specific news events such as prescheduled earnings releases. The study has also shown that the likelihood of jumps misclassification can be reduced by a very big margin by using the high frequency returns.
The article has drawn its conclusion by making a strong suggestion on how to prevent the jumps from occurring in the financial markets. It suggests that financial institutions should use different pricing models in cases of individual equity and not index options.
This article addresses jumps and information flow, the two major drivers in financial markets. The author has assessed the main theme by conducting a non-parametric study. A non-parametric study is one of the most acceptable methods used to assess the issues that influence the operations of the financial markets, such as, the United States stock market. The author has been successful in the study since she was able to determine the factors relating to this subject and the correlation between them. For instance, she has found out that the individual stock jumps are correlated with prescheduled earnings releases (451).
The author is speaking from the first person narration. She talks directly to her audience, which comprises of the players in the financial markets. The author has explained every bit of the non-parametric study which she uses to determine the jumps in the financial markets. The concept of the first person narration has the effect of enhancing the credibility of an article. The targeted audience tends to have more interest in the first person rather than the third person narrator.
This article has been well-structured, which makes it easy to understand and follow all the concepts addressed in it. The article has an abstract, introduction, methodology, results, conclusion and suggestions. These are normally the main aspects in a good article. The aspects are instrumental in providing directions to the people who read the article. This kind of structuring also helps to ensure a proper flow of information throughout an article.
The author’s purpose of producing this article was to inform the target audience about the jumps in a financial market. This is, therefore, an informative article that addresses the occurrence of jumps in the financial markets. The author has carried out a non-parametric study to establish the factors that bring about the occurrence of these jumps. The study has assisted the author to build the confidence of the readers, who are able to see sense in what is addressed in this article.