1. An Overview of Research Process
FINA262
Financial Data Analysis

2. 1. What is research methodology?
The process of collecting information and data for the purpose of decision making and policy implications.
“Without data you’re just another person with an opinion” W. Edwards Deming

3. 1. What is research methodology? (Continued)
The scientific method in social science developed from the key methodological approaches of positivism and empiricism.
Fundamental to the positivist approach is the idea that the study of the social world can use the tools of science in order to create understandings which are verifiable.
Empiricism gives primacy to the observable world and relies on observable data from which to deduce patterns which may form the basis of research questions, hypotheses and problems.

4. 2. Steps in research methodology
STEP 1: DEFINE THE PROBLEM OR OPPORTUNITY
STEP 2: REVIEW THE LITERATURE
STEP 3: FORMULATE YOUR HYPOTHESIS
STEP 4: CHOOSE A RESEARCH METHOD
STEP 5: COLLECT YOUR DATA
STEP 6: ANALYZE YOUR DATA
STEP 7: RESEARCH AND POLICY IMPLICATIONS

5. STEP 1: DEFINE THE PROBLEM OR OPPORTUNITY
The initial step in research methodology is to define the problem or opportunity.
If the definition is not carefully tought through and precisely formulated, resources will be wasted trying to solve the wrong problem.
To define a problem or opportunity effectively, researchers must consider several concerns;
1. The reasons for pursuing information
2. The decision maker’s objectives
3. What is already known about the issue
4. The risks associated with the problem
5. Resources available for the research activity
6. How the information will help the decision maker

6. Step 2: review the literature
A literature search is “a systematic and through search of all types of published literature in order to identify as many items as possible that are relevant to a particular topic” (Gash, 2000).
Reviewing literature provides context of the study and clarifies the relationship between the proposed research and previous research.
Literature review shows how the proposed study is unique from previous research.

7. Step 3: formulate your hypothesis
After choosing a research question, the next step is to formulate a research hypothesis.
A research hypothesis is a tentative answer to the research question. That is, after reading previous research studies, researchers predict in advance what they think the outcome of a research study will be.
The concepts addressed by the hypothesis must be clearly defined and measurable.
Research hypotheses must refer to concepts that can be studied scientifically. To say that a company’s aggressive strategies are caused by the devil isn't a testable hypothesis because this hypothesis refers to a concept (the devil) that isn't in the province of science. Science deals with what can be observed; this is the basis for empirical observation.

8. Step 4: choose a research method
Let the literature be your guide!
A through literature review is the best starting point for choosing your methods because evaluating previous researchers' efforts can suggest a path to answer your own research question.
"You might find out that people have used certain designs and that they've worked well or that there have been problems."

9. Step 5: collect your data
Researcher should ask “Where will I get the information?”
The data may already exist as secondary data- data that has already been collected for a purpose other than the current study or it may have to be primary data-original data gatehered to satisfy the purpose of the current study.
Secondary data is used whenever possible, because it tends to be much less expensive than primary data, and such data is also available in a timely manner.

10. Step 6: analyze your data
Once data collection is complete, the next step is to analyze the information.
Analysis makes sense of the data so that decision makers can draw conclusions about the variables.
No matter which analytical procedure is used, the results must provide, in a timely manner, the information that the decision maker seeks.
It is no longer necessary to analyze data using manual methods. High-speed computers use statistical software to perform all sorts of calculations like E-views and SPSS.

11. Step 7: research and policy implications
After the data has been collected and properly analyzed, research and policy implications should be reported.
All results should be explained in details.
According to the results of the study, researcher should suggest policy implications to decision makers.

12. Criteria of good research
1. The purpose of the research should be clearly defined and common concepts be used.
2. The research procedure used should be described in sufficient detail to permit another researcher to repeat the research for further advancement, keeping the continuity of what has already been attained.
3. The procedural design of the research should be carefully planned to yield results that are as objective as possible.
4. The researcher should report with complete frankness, flaws in procedural design and estimate their effects upon the findings.

13. Criteria of good research (continued)
5. The analysis of data should be sufficiently adequate to reveal its significance and the methods of analysis used should be appropriate. The validity and reliability of the data should be checked carefully.
6. Conclusions should be confined to those justified by the data of the research and limited to those for which the data provide an adequate basis.
7. Greater confidence in research is warranted if the researcher is experienced, has a good reputation in research and is a person of integrity.

14. Types of research Descriptive vs. Analytical:
Descriptive research includes surveys and fact-finding enquiries of different kinds.
In social science and business research we quite often use the term Ex post facto research for descriptive research studies.
The main characteristic of this method is that the researcher has no control over the variables; he can only report what has happened or what is happening.
Most ex post facto research projects are used for descriptive studies in which the researcher seeks to measure such items as, for example, frequency of shopping, preferences of people, or similar data.

15. Descriptive vs. Analytical:
Ex post facto studies also include attempts by researchers to discover causes even when they cannot control the variables.
The methods of research utilized in descriptive research are survey methods of all kinds, including comparative and correlational methods.
In analytical research, on the other hand, the researcher has to use facts or information already available, and analyze these to make a critical evaluation of the material.

16. Applied vs. Fundamental:
Research can either be applied (or action) research or fundamental (to basic or pure) research.
Applied research aims at finding a solution for an immediate problem facing a society or an industrial/business organisation, whereas fundamental research is mainly concerned with generalisations and with the formulation of a theory.
“Gathering knowledge for knowledge’s sake is termed ‘pure’ or ‘basic’ research.” Research concerning some natural phenomenon or relating to pure mathematics are examples of fundamental research.
Research to identify social, economic or political trends that may affect a particular institution or the marketing research or evaluation research are examples of applied research.

17. Applied vs. Fundamental:
Thus, the central aim of applied research is to discover a solution for some pressing practical problem, whereas basic research is directed towards finding information that has a broad base of applications and thus, adds to the already existing organized body of scientific knowledge.

18. Quantitative vs. Qualitative:
Quantitative research is based on the measurement of quantity or amount. It is applicable to phenomena that can be expressed in terms of quantity.
Qualitative research, on the other hand, is concerned with qualitative phenomenon, i.e.,phenomena relating to or involving quality or kind. For instance, when we are interested in investigating the reasons for human behaviour (i.e., why people think or do certain things), we quite often talk of ‘Motivation Research’, an important type of qualitative research.

19. Conceptual vs. Empirical:
Conceptual research is that related to some abstract idea(s) or theory. It is generally used by philosophers and thinkers to develop new concepts or to reinterpret existing ones.
On the other hand, empirical research relies on experience or observation alone, often without due regard for system and theory. It is data-based research, coming up with conclusions which are capable of being verified by observation or experiment.
In empirical research, the researcher must first provide himself with a working hypothesis or guess as to the probable results. He then works to get enough facts (data) to prove or disprove his hypothesis.

20. Conceptual vs. Empirical:
Empirical research is appropriate when proof is sought that certain variables affect other variables in some way.
Evidence gathered through experiments or empirical studies is today considered to be the most powerful support possible for a given hypothesis.

21. Types of data Time Series Data
Macroeconomic data measures phenomena such as real gross domestic product(denoted GDP), interest rates, the money supply, etc. This data is collected at specific points in time (e.g. yearly).
Financial data, on the other hand, measures phenomena such as changes in the price of stocks. This type of data is collected more frequently than the above, for instance, daily or even hourly.
In all of these examples, the data are ordered by time and are referred to as time series data.
Time series data can be observed at many frequencies. Commonly used frequencies are: annual (i.e. a variable is observed every year), quarterly (i.e. four times a year), monthly, weekly or daily.

22. Years
GDP (m.$)
DC /GDP
2007
225,2
0.75
2008
226,4
0.66
2009
227,8
0.45
2010
225,4
0.60
2011
229,5
0.70
2012
240,0
0.31
2013
234,1
0.40
2014
285,9
0.62
2015
262,4
0.94

23. Cross-sectional data
Data that is characterized by individual units are called cross-sectional data.
These units might refer to people, companies or countries. A common example is data pertaining to many different people within a group, such as the wage of all people in a certain company or industry.
With such cross-sectional data, the ordering of the data typically does not matter (unlike time series data).
For example, a labor economist might wish to survey N = 1,000 workers in the steel industry, asking each individual questions such as how much they make or whether they belong to a union.

24. Country
GDP (m.$)
(Year: 2015)
DC /GDP
Nigeria
315,2
0.65
Cyprus
306,4
0.86
Turkey
417,8
0.75
Azerbaijan
515,4
0.60
Tajikistan
219,5
0.90
Kazakhstan
220,0
0.81
Jordan
324,1
0.66
Iran
650,9
0.68
Chad
432,4
0.78

25. Panel Data
Some data sets will have both a time series and a cross-sectional component. This data is referred to as panel data.
For example, GDP for many countries from1950 to the present is available. A panel data set on Y= GDP for 12 European countries would contain the GDP value for each country in 1950 (N = 12 observations), followed by the GDP for each country in (another N = 12 observations), and so on. Over a period of T years, there would be T times N observations on Y.

26. Country
Years
GDP (m.$)
DC /GDP
Nigeria
2002
315,2
0.65
2003
406,4
0.66
2004
517,8
0.75
Cyprus
115,4
0.70
219,5
320,0
0.79
Turkey
424,1
0.80
550,9
0.82
632,4
0.84

27. The distinction between quantitative and qualitative data
The microeconomist’s data on sales will have a number corresponding to each firm surveyed (e.g. last month’s sales in the first company surveyed were £20,000). This is referred to as quantitative data.
The labor economist, when asking whether or not each surveyed employee belongs to a union, receives either a Yes or a No answer. These answers are referred to as qualitative data. Such data arise often in economics when choices are involved(e.g. the choice to buy or not buy a product, to take public transport or a private car, to join or not to join a club).