Decision Theory (Quantitative Techniques)

1. WELCOME TO My
PRESENTATION

2. Special thanks to
Kazi Md. Nasir Uddin
Assistant Professor
Department of Accounting & Information Systems
Faculty of Business Studies
Jagannath University, Dhaka

3. Presentation Topic:
“Operational research is a very powerful
tool and analytical process that results in
and offers an optimal solution, in spite of
its limitations.”

4. MD.SHAMSURRAHMANHEERA
IDNO.:B-150201187

5. DECISION THEORY

6.  What is Decision Theory?
Decision theory is an analytic and systematic approach to
decision making.
***A good decision is based on logic***
 Implications of Decision Theory:
Is used whenever an organization or an individual faces a
problem of decision making or dissatisfied with the existing
decisions or when alternative selection is specified.

7.  Importance of Decision Theory:
 It is a body of methods helpful to decision makers to select
wisely one course of action (strategy) from amongst the
alternatives plan of action.
 It provides a meaningful conceptual framework for improved
decision theory.
 Elements Related to Decision Theory:
1. Goals to be achieved
2. The decision maker
3. Courses of action
4. States of nature
5. Payoff
6. Payoff table

8.  Types of decision making environment:
Type 1
• Decision
making
under
certainty
Type 2
• Decision
making
under risk
Type 3
• Decision
making
under
uncertainty

9. Rules/ techniques for decision making under risk situation:
• EMV criterion
• EOL criterion
1. Expected payoff criterion
2. Decision Tree
3. Utility curves
4. Marginal Analysis
5. Posterior Analysis

10.  Expected Monetary Value (EMV)
EMV is the weighted sum of possible payoffs for each alternatives.
Formula:
Expected monetary value (EMV) = probability × impact
If this were expanded, it would become:
EMV (alternative) = (payoff in first state of nature) ×
(probability of first state of nature) + (payoff
in second state of nature) × (probability of
second state of nature) +…….+ (payoff in last
state of nature) × (probability of last state of
nature).
***The alternative of maximum EMV is then chosen***

11. Example of EMV
An Investor is given the pay-offs of three investment alternatives and the
states of nature are given below:
Alternatives Growing Stable Declining
Bonds 40 45 5
Stocks 70 30 -13
Mutual funds 53 45 -5
Probabilities 0.20 0.50 0.30
Requirement:
Tabulate the expected monetary values for the above data and state
which can be chosen as the best investment alternative.

12. Solution:
Alternatives Growing Stable Declining EMV
Bonds 40 45 5 32.00
Stocks 70 30 -13 25.10
Mutual funds 53 45 -5 31.60
Probabilities 0.20 0.50 0.30
EMV (Bonds) = (0.20×40) + (0.50×45) + (0.30×5) = 32.00
EMV (Stocks) = (0.20×70) + (0.50×30) + (0.30×-13) = 25.10
EMV (Mutual Funds) = (0.20×53) + (0.50×45) + (0.30×-5) = 31.60
Decision: Invest in Bonds.

13.  Expected Opportunity Loss (EOL):
An alternative approach to maximizing expected monetary value
(EMV) is to minimize expected opportunity loss (EOL). EOL is
calculated in the same manner as the EMV criterion discussed
earlier.
According to the EOL criterion the decision maker should choose
the strategy with the minimum expected opportunity loss.
Decision Tree:
A decision tree is a graphical representation of various
alternatives and sequence of events in a decision problem.
It is extremely useful in multistage situations which involve a
number of decisions, each depending on the preceding one.

14.  A decision Tree consists of 3 types of nodes:-
1. Decision nodes - commonly represented by squares (⧠)
2. Chance nodes - represented by circles (○)
3. End nodes - represented by triangles (optional)
 Create the tree from left to right
 Solve the tree from right to left

15. Basic rules and conventions in drawing decision tree
8. Select the action
7. Calculated of expected value
6. Obtain estimates of consequences
5. Obtain probability
4. Develop a tree diagram
3. Identify the chance events
2. Identify all alternatives
1. Identify all decisions