- Trending Categories
- Data Structure
- Operating System
- MS Excel
- C Programming
- Social Studies
- Fashion Studies
- Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Decision Tree Analysis for Sequential Investment Decisions
Sequential analysis deals with the sequence of events an investment process follows instead of just accept or reject a process. Sequential analysis is more relevant in practice because it shows all the probable events in terms of a decisions tree that constitutes the probability of an outcome generated in the process.
Decisions trees are not a perfect measure of a future event, but they represent quite a close approach to the original outcome in general. However, some steps must be followed while constructing a decision tree which are explained below.
Defining the Investments
The investment for which the sequential investment has to be made should be defined at first.
It must contain the true facts about the investment because the whole decisions tree would be dependent on this.
The proposal for an investment may be made by any department of the organization such as production, marketing, or any other department.
The investment should be made for a unique purpose such as entering a new market or producing a new product.
Identifying the Decision Alternatives
Once an investment is defined, the next step is to identify the various alternatives that may follow the investment. It is a crucial step because all independent decision alternatives must be considered while identifying the decisions.
For example, a company may want to enter a new market, and it should identify the channels to market its products. Each of the channels would represent an alternative, as the outcomes of each alternative would be different.
Drawing the Decision Tree
The next step is to draw a decision tree, indicating the decision points, chance events, and other relevant data. One must be careful in drawing the decision tree because it is the most important part of the whole process, and no alternative should be missed from the whole business tree.
Relevant data such as probability distributions, projected cash flows and expected present values should be included in the branches of the tree to get the complete picture of the investment.
Analyze the Data
The final part is to analyze the data according to the business policies and check the utilities of each decision to be taken by the organization. The decision tree should make analyzing clear and succinct. It is for the better use of the department that sponsored the proposal initially. The business tree is now complete and subject to given assumptions to an analysis of data.
Decision Tree Analysis for Sequential Investment Decisions follows an 'ifthen' philosophy and it is dependent on the permission of the decision-making team. Therefore, the whole responsibility to construct a decision tree free from errors lies with the relevant departments.
- Related Articles
- What are Sequential Investment Decisions?
- Types of Financing Decisions - Investment Decisions, Dividend Policy Decisions
- What is the utility of Decision Tree Analysis?
- Rules to be followed while making Investment Decisions
- Utility Theory and Decision Analysis
- What are some of the important features of Investment Decisions?
- Decision tree implementation using Python
- What is a Decision Tree?
- How to construct a decision tree?
- What are the characteristics of Decision tree induction?
- Framework for Efficient Decision Making
- How can decision tree be used to implement a regressor in Python?
- How can decision tree be used to construct a classifier in Python?
- How can the data be visualized to support interactive decision tree construction?
- How are decision trees used for classification?