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Analyzing Institutional Investor Demand

ASecurity

Maps institutional investor targeting with AUM analysis, sector allocation preferences, and historical participation patterns. Use when targeting investors, analyzing demand profiles, or building investor marketing lists.

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Added 9/20/2026
content-marketinggoapiperformance

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api

Security Analysis

A100/100

Scanned 9/20/2026

Install to Claude Code

$npx -y skills add lev-os/agents --skill analyzing-institutional-investor-demand --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: analyzing-institutional-investor-demand
description: Maps institutional investor targeting with AUM analysis, sector allocation preferences, and historical participation patterns. Use when targeting investors, analyzing demand profiles, or building investor marketing lists.
tags:
  - analysis
  - equity-capital-markets
metadata:
  author: casemark
  practice_areas:
    - ECM
    - IPO Advisory
    - Equity Origination
  document_types:
    - Analysis Report
  skill_modes:
    - Analysis
---
# Analyzing Institutional Investor Demand

## When To Use

- Building an investor target list for an IPO, follow-on, block trade, or convertible offering
- Evaluating likely demand depth and price sensitivity ahead of bookbuilding
- Profiling anchor, cornerstone, or strategic investor candidates
- Assessing sector rotation trends to time equity offerings
- Comparing investor participation patterns across comparable recent transactions

## Inputs To Gather

- **Issuer profile**: sector (GICS), market cap range, geography, index eligibility
- **Deal parameters**: offering type (IPO/FO/block/convert), estimated size, structure, use of proceeds
- **Comparable transactions**: 5–15 recent deals in same sector/size bracket with allocation data if available
- **Investor universe**: institutional holders from 13F filings, beneficial ownership reports, or syndicate desk data
- **Existing shareholder register**: current top holders, recent buying/selling activity, lock-up status
- **Market context**: current volatility, sector ETF flows, recent deal performance (aftermarket returns)

## Workflow

1. **Define the targeting universe**
   - Filter institutional investors by AUM tier (mega-cap >$100B, large $20–100B, mid $2–20B, emerging <$2B)
   - Screen by investment style: long-only, GARP, deep value, growth, index/quasi-index, hedge fund (L/S, event-driven, quant)
   - Narrow by sector allocation — identify funds with existing overweight or underweight in the issuer's GICS sector
   - Flag geographic constraints (US-only mandates, global, EM-focused) [VERIFY against each fund's prospectus or ADV]

2. **Analyze historical participation patterns**
   - Pull allocation data from recent comparable offerings (same sector, similar deal size)
   - Rank investors by frequency of participation and average order size as % of deal
   - Identify "anchor" candidates — investors who consistently take 5%+ allocations in comparable deals
   - Note investors who participated in prior rounds or PIPE transactions for the issuer
   - Flag any investors with pattern of quick flipping (selling within 30–90 days post-pricing)

3. **Assess demand quality indicators**
   - **AUM capacity**: investor's total equity AUM vs. typical position size — can they absorb a meaningful allocation?
   - **Sector conviction**: recent 13F changes showing increased/decreased sector exposure
   - **Holding period**: median hold duration for comparable positions (long-term holders vs. tactical)
   - **Price sensitivity**: historical behavior at various discount/premium levels in bookbuilds
   - **Relationship strength**: prior deal participation with lead bookrunners, attendance at NDRs

4. **Build tiered target list**
   - **Tier 1 (High Priority)**: strong sector fit, proven participation history, long holding periods, large AUM capacity
   - **Tier 2 (Core)**: good fit on most criteria, moderate participation history, may need more marketing effort
   - **Tier 3 (Opportunistic)**: situational interest — event-driven funds, crossover investors, new entrants to sector
   - Assign estimated order size ranges per investor based on historical patterns
   - Calculate aggregate demand estimate vs. deal size to gauge potential oversubscription

5. **Map demand against deal structure**
   - Estimate total book coverage at various price points within the filing range
   - Identify concentration risk — if top 10 investors represent >50% of expected demand, flag for diversification
   - Assess sensitivity to greenshoe exercise and potential stabilization needs
   - Recommend marketing priorities: which investors need 1-on-1 meetings vs. group lunches vs. virtual-only

## Output

Deliver a structured **Institutional Demand Analysis** containing:

- **Executive summary**: headline demand assessment (strong/moderate/soft), key risks, and recommended actions
- **Investor target matrix**: tabular list with columns for investor name, style, AUM, sector allocation %, comparable deal participation count, estimated order size, tier ranking, and recommended marketing approach
- **Demand waterfall**: visual or tabular breakdown of estimated demand at low/mid/high price points, showing contribution by investor tier
- **Comparable deal benchmarks**: table of 5–10 recent transactions with pricing outcome, oversubscription level, aftermarket performance, and top allocatees
- **Risk flags**: concentration risk, flipper exposure, sector rotation headwinds, or calendar conflicts with competing offerings
- **Recommended roadshow strategy**: prioritized cities/meetings based on where highest-quality demand is concentrated

## Quality Checks

- Confirm all 13F data is from the most recent available filing period — stale data (>1 quarter old) must be flagged [VERIFY filing dates]
- Cross-check investor style classifications against multiple sources (eVestment, Morningstar, PitchBook) — self-reported styles often diverge from actual behavior
- Validate that comparable transactions are genuinely comparable (same sector, ±50% deal size, same deal type, within 18 months)
- Ensure estimated demand totals are internally consistent — sum of individual investor estimates should reconcile to aggregate demand figure
- Verify no restricted or wall-crossed investors are included in open-market targeting lists [VERIFY compliance status]
- Confirm that any fund-level data respects aggregation rules — separate accounts, sub-advised mandates, and fund-of-funds positions should not be double-counted

Attribution

lev-oslev-os
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3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

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