Thangavel PrasanthTP

Regret Analysis

4 min read

Regret analysis is a decision-making framework or technique used to evaluate the consequences of different choices by focusing on the potential regret associated with those decisions. It involves considering how much a person or organization might regret a decision if the outcome turns out to be less favorable compared to an alternative choice.

Key Concepts:

  1. Regret:
    • Regret is the emotional or cognitive discomfort experienced when realizing that a better decision could have been made in hindsight.
  2. Minimizing Regret:
    • Regret analysis helps decision-makers identify and choose options that minimize potential regret, especially in uncertain or risky situations.
  3. Comparison of Outcomes:
    • It involves comparing the outcomes of different decisions and assessing how much regret one might feel if a different choice had led to a better result.

Applications:

  • Business Decision-Making:
    • Companies may use regret analysis to evaluate investment options, product launches, or market strategies.
  • Personal Decisions:
    • Individuals might use regret analysis for life choices, such as career moves, financial investments, or relationships.
  • Policy and Risk Management:
    • Governments and organizations use it in designing policies or managing risks where outcomes are uncertain.

Examples

Example 1

Imagine a person deciding between two job offers:

  • Job A has a higher salary but requires relocation.
  • Job B has a lower salary but allows them to stay close to family. In regret analysis, they would consider:
  • How much regret they might feel if they choose Job A and later miss their family.
  • Conversely, how much regret they might feel if they choose Job B and later realize they could have earned more money.

The decision would aim to minimize the potential regret based on their priorities and values.

Example 2: Choosing Between Two Investments

A simple Python code example that implements regret analysis for a decision-making scenario:

Suppose you have two investment options:

  • Option A: High risk, high reward (potential profit: 5,000).
  • Option B: Low risk, moderate reward (guaranteed profit: $3,000).

The code will calculate the regret for each option based on possible outcomes and help you choose the one with the least regret: Github Gist

# Define possible outcomes for each option
option_a = {"profit": 10000, "loss": -5000}  # High risk, high reward
option_b = {"profit": 3000, "loss": 0}      # Low risk, no loss
 
# Define probabilities for each outcome
probabilities_a = {"profit": 0.6, "loss": 0.4}  # 60% chance of profit, 40% chance of loss
probabilities_b = {"profit": 1.0, "loss": 0.0}  # 100% chance of profit, 0% chance of loss
 
# Calculate expected regret for each option
def calculate_regret(option, probabilities, best_outcome):
    regret = 0
    for outcome, value in option.items():
        regret_interim = probabilities[outcome] * (best_outcome - value)
        print (f"outcome: {outcome:>10s} | regret_interim: {regret_interim:>5.0f}")
        regret += regret_interim
    return regret
 
# Best possible outcome (maximum profit)
best_outcome = max(option_a["profit"], option_b["profit"])
print (f"Best outcome possible: {best_outcome}")
 
# Calculate regret
print ("\nRegret for option a:")
regret_a = calculate_regret(option_a, probabilities_a, best_outcome)
print ("\nRegret for option b:")
regret_b = calculate_regret(option_b, probabilities_b, best_outcome)
 
# Print regret values for transparency
print(f"\nRegret for Option A: {regret_a}")
print(f"Regret for Option B: {regret_b}")
 
# Compare regrets and choose the option with the least regret
if regret_a < regret_b:
    print("Choose Option A (High Risk, High Reward)")
else:
    print("Choose Option B (Low Risk, No Loss)")
Best outcome possible: 10000
 
Regret for option a:
outcome:     profit | regret_interim:     0
outcome:       loss | regret_interim:  6000
 
Regret for option b:
outcome:     profit | regret_interim:  7000
outcome:       loss | regret_interim:     0
 
Regret for Option A: 6000.0
Regret for Option B: 7000.0
Choose Option A (High Risk, High Reward)

How It Works:

  1. Inputs:
    • Each option has possible outcomes (profit and loss).
    • Probabilities are assigned to each outcome.
  2. Regret Calculation:
    • Regret is calculated as the difference between the best possible outcome and the actual outcome, weighted by probabilities.
  3. Decision:
    • The option with the least regret is chosen.

Graph View