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Quantitative methods of analysis in finance require mathematical and statistical applications relevant to modern financial instruments and risk management. These help companies to make a solid and sound format for their financial standings be it income, sales, stock, profit and loss.
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After plotting the graph and tabulating the data, an equation is incorporated to prove the authenticity of the variables. Statistical values should be substantial in order to make up probabilities and draw up a hypothesis that will then be proven as either relevant or irrelevant. In quantitative financial methods of analysis, there are two types of variables, the stationary and non-stationary variable. After a null hypothesis has been drawn up, statistical values are compared to critical values in order to determine whether the null hypothesis is substantial or not.
The use of numbers and data input allows for comparison between and among variables. This gives the link to the mathematical aspect of analyzing information. Quantitative methods of research gives the causal explanation, they answer the “why” question and give supporting evidence and at the same time give a description of the topic being studied in this case –finance.
In finance, quantifying, measuring as well as numerically expressing data is basically the technique for research and analysis. Numeric terms that can be analyzed with the use of statistical methods are deployed. That is any numeric value or term has to be flexible enough to be tabulated, graphically represented or fit into a pie chart.
For quantitative methods in finance to be initiated, observations over a certain period of time have to be carried out. These observations can either be numeric information or classified into numeric variables. These observations are then changed into data matrix whereby rows and columns are created- for analysis. In most cases the use of excel is required as data handling has to be precise and clear.
The use of quantitative methods in analyzing financial standings usually helps companies to avoid the undesirable effects of financial constraint. A constant financial flow is the ideal plan as it avoids facing the risk of high cost external funds.
Since quantitative analysis answer the “why” question, it is important to have a control as this will help in locating the problem source and deriving the question itself. Without that control, the cause of an anomaly cannot be easily identified. This therefore gives quantitative analysis an upper age over qualitative analysis in finance.
There are strengths and limitations in quantitative analysis. The strengths include precision that isn’t achieved through the use of reliable measurements. The use of the control, statistical techniques allow for use of sophisticated analyses and most importantly data can be replicable. Going over previous kept records can make analysts draw up a hypothesis for the financial standing of the company in the future.
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Limitations of quantitative analyses include the fact that it can lead to assumptions in dealing with similar cases. Human errors and shortcuts make quantitative analyses not ideal every time.
At the end of a research, a conclusion is drawn based on the relationship between the probability and statistics. This gives information on what affects the financial standings of a company or firm. From this information, the size of financial conservation needed for a certain period of time can be drawn up. However, the conclusion made after an intensive quantitative analysis cannot be true for different cases. Other variables that might have been overlooked also play a vital role in determining the financial standings of any company for any period of active trading time.
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