Definition

Pivot meaning in business, refers to a strategic shift where a company changes its business model, product focus, or market strategy to better meet customer needs or respond to market conditions.

Description 

Pivot levels in business typically involve several stages or aspects:

1. Customer Feedback: Analyzing and incorporating feedback to improve products or services.
2. Market Research: Studying market trends and competitor strategies to identify new opportunities.
3. Product Development: Modifying or redeveloping products to better align with market demands.
4. Business Model Adjustment: Changing the revenue model, cost structure, or value proposition to enhance business viability.
5. Operational Shifts: Streamlining operations or altering processes to increase efficiency and reduce costs.
6. Target Market Change: Redirecting efforts towards a different customer segment or geographic market.
7. Strategic Partnerships: Forming new alliances or collaborations to gain a competitive edge or enter new markets.

Importance of pivot in stock market 

This is why pivot in stock market is important:

Support and Resistance Identification: Pivot points help traders identify potential support and resistance levels, guiding entry and exit decisions.

Trend Analysis: They assist in determining the overall market trend, helping traders align their strategies with market direction.

Risk Management: By highlighting key price levels, pivot points aid in setting stop-loss orders and managing risk.

Market Sentiment: Pivot points reflect market sentiment and can indicate potential market reversals or continuations.

Trading Strategies: They provide a basis for various trading strategies, including range trading, breakout trading, and trend following, enhancing decision-making.

How to do pivot analysis?

To perform pivot analysis in the stock market, follow these steps:

1. Calculate Pivot Point (PP):
   • Use the previous day's high (H), low (L), and close (C) prices.
   • Formula: PP=H+L+C3PP=3H+L+C​
2. Calculate Support and Resistance Levels:
   • First Resistance (R1): R1=(2×PP)−LR1=(2×PP)−L
   • First Support (S1): S1=(2×PP)−HS1=(2×PP)−H
   • Second Resistance (R2): R2=PP+(H−L)R2=PP+(H−L)
   • Second Support (S2): S2=PP−(H−L)S2=PP−(H−L)
   • Third Resistance (R3): R3=H+2×(PP−L)R3=H+2×(PP−L)
   • Third Support (S3): S3=L−2×(H−PP)S3=L−2×(H−PP)
3. Plot Pivot Levels on Chart:
   • Mark the calculated pivot point (PP), support levels (S1, S2, S3), and resistance levels (R1, R2, R3) on your stock chart.
4. Analyze Price Movements:
   • Observe how the stock price interacts with these levels.
   • Use them to identify potential support and resistance, guide entry and exit points, and confirm trends or reversals.
5. Incorporate into Trading Strategy:
   • Combine pivot levels with other technical indicators (e.g., moving averages, RSI) to enhance decision-making.
   • Use pivot points to set stop-loss orders and target prices, manage risk, and plan trades.

By following these steps, traders can effectively use pivot points to analyze market movements and make informed trading decisions.

Emerging Trends in Pivot Table 

Three key trends that can affect pivot table analysis are:

1. Data Volume and Complexity:
   • Increasing amounts of data and its growing complexity can influence how pivot tables are structured and analyzed. As businesses gather more data, pivot tables must handle larger datasets and more intricate relationships, requiring more advanced analysis and visualization techniques.
2. Business Intelligence Tools:
   • Advancements in business intelligence (BI) tools and software can significantly impact pivot table functionality. Modern BI tools offer enhanced features, such as real-time data processing, integration with multiple data sources, and advanced visualization options, making pivot table analysis more powerful and insightful.
3. Data Quality and Accuracy:
   • The quality and accuracy of data used in pivot tables are crucial for reliable analysis. Trends in data governance, data cleansing, and data validation practices ensure that the data feeding into pivot tables is accurate, consistent, and trustworthy, which directly affects the validity of the insights derived from the analysis.

Example 

Let us assume Starbucks uses pivot tables to analyse seasonal beverage sales data across various regions.

Pivot Table Setup:

• Rows: Different regions (North America, Europe, Asia)
• Columns: Types of beverages (Coffee, Tea, Seasonal Specials)
• Values*: Sales figures

Insights Gained:

• Starbucks identifies that Seasonal Specials like Pumpkin Spice Latte have higher sales in North America during the autumn months.
• They observe that Tea sales are particularly strong in Asia throughout the year.

Action Taken:

• Based on these insights, Starbucks decides to increase the stock of seasonal specialties in North American stores during fall and promote tea more aggressively in Asian markets to boost sales.

This example illustrates how Starbucks could use pivot table analysis to make strategic decisions about product distribution and marketing based on regional sales trends.

FAQ

What is pivot analysis?

Pivot analysis is a data summarization tool that helps in transforming extensive data sets into organized summaries through pivot tables, enabling quick analysis of patterns and trends across different dimensions such as time, region, or product categories.

What are pivot levels?

Pivot levels are key prices determined using the previous day’s high, low, and close to calculate support and resistance levels for the current trading day, helping traders make informed decisions about entry and exit points.