Куда ИНВЕСТИРОВАТЬ 10 млн, 100 млн и 1 млрд рублей? | Айрат Ямаев

Finance-focused summary (real estate investing, tourism hospitality)

Core thesis / “where to invest”

The speaker argues that tourism-focused real estate—specifically 4–5 star hotels and tourist cluster locations—is a “blue ocean” within Russia because:

• Tourist arrivals are rising
  • Russia: ~60m tourists 4 years ago → 96m last year (+55% in 4 years).
• Growth is ongoing
  • Annual increases are described as approximately ~5–12% (varying by year/region and seasonality).
• Demand is uneven at the micro-market level
  • Investors should not buy “the whole market,” but target specific locations where high-quality hotel supply is scarce.

He also highlights selective caution toward glamping:

• Despite visual appeal and claims of possible state support (mentioned possible 50% subsidy), operating costs are high.
• Claim: ~70% of revenue may go to operations.
• Small properties struggle to reach operational profitability without hotel-scale “critical mass.”

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Markets, sectors, and instruments mentioned

Sector focus

• Real estate (primary development and hospitality)
• Tourism real estate / hotel clusters
• Glamping (treated as higher risk due to operational difficulty)
• Commercial real estate (mentioned historically as less attractive post-COVID)

Macro / investment context

• Post-COVID shift away from commercial real estate demand
• Inflation as a key macro driver (real estate/land framed as an inflation hedge)

Assets / financing structures (non-ticker)

• Russia 214-FZ / escrow accounts
  • Construction under Federal Law 214, with bank financing and funds held in escrow
• Sberbank (bank financing referenced)
• SRO accounts (escrow-type protection referenced)
• Special economic zone (SEZ) mentioned as relevant for tax privileges, with clarification that the “sale” aspect differs from “exploitation” (as stated)

No public-market tickers, ETFs, bonds, or FX instruments were explicitly named.

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Key numbers, metrics, and valuation/profit claims

Macro tourism growth

• Russia tourists: ~60m → 96m (last year), +55% over 4 years
• Annual growth noted as ~5–12% (with seasonality and regional variation)

Tourism real estate pricing and performance (Shergesh example)

Hotel accommodation price claim

• ~20,000–25,000 RUB/day for the 4–5 star segment in Shergesh.

Example “unit rent” / income assumptions

• Starting “current” rent: ~14,000 RUB per room/day
• Occupancy modeled: ~60% of nights across the year
• Seasonality framing: roughly 50% retained as “service/rent coverage” after costs, then ~30–40% remaining as “clean” (netting described as management/service-related)

Yield / profitability claim

• Modeled owner net income: ~1,200,000 RUB per year clean for a ~25 m² “standard unit” in the 4-star category
• Implied yield: ~8%
  • Compared as higher than apartments, with a view that hotels outperform apartments in his framework

Capitalization / development valuation (Shergesh example)

• Bank-model capitalization price:
  • ~450,000–470,000 RUB/m² (with renovation)
• Expected at delivery:
  • ~620,000 RUB/m²
• Development horizon:
  • Delivery around end of 2028 (Shergesh; “start in 2028 season”)

Development scale and investments

Company pipeline scale (One Company)

• Projects simultaneously: ~40–50 (exclusive sales of residential complexes)
• Total square meters launched: ~200,000 m² → ~300,000 m²
• Group size: 500+ employees

Shergesh and other project references

• Shergesh:
  • Presented as “the largest project in Siberia within one project”
• Another Novosibirsk project (“Moscow City” reference):
  • ~5 towers / 190,000 m²
• “Freedom Village”:
  • 220 hectares (cluster concept)
• Total planned investment for Shergesh:
  • Later discussed as ~250 billion RUB (valuation mentioned “by year 2030”)
• Speaker’s share estimate:
  • ~20% (approx.)

Altai / Manzherok

• Altai total “first queue” area: ~200,000 m²
• First phase timeframe:
  • 10–12 years
• Residential staff housing concept:
  • Starting cost: ~180,000 RUB/m²
  • Avg unit size mentioned: 55–60 m²

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Methodology / framework described (step-by-step logic)

1. Find “blue ocean” micro-markets

   • Analyze regional tourist demand vs hotel supply
   • Target areas where tourist flow is strong but 4–5 star quality accommodations are scarce

2. Validate with operating reality

   • Check existing operating hotels’ fill/price (“cost shown on the check”)
   • Estimate achievable seasonal rent + occupancy

3. Build a bank-style investment model

   • Two-part appeal:
     • Capitalization growth (modeled RUB/m² at delivery; inflation considerations)
     • Operational income (modeled net income after service/management assumptions)

4. Prefer structures with reduced buyer risk

   • Use construction via 214-FZ / escrow accounts / bank financing
   • Escrow reduces consumer/developer counterparty risk

5. Apply a risk filter for operational profitability

   • Hospitality size/critical mass matters
   • Caution: glamping may be operationally unprofitable due to high opex share

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Explicit recommendations / cautions

Recommendation

• Consider tourism resort real estate (clusters/hotels), especially 4–5 star assets in high-traffic but under-supplied locations.

Caution (glamping)

Be careful with glamping because:

• ~70% of revenue may be operating expenses
• Reinvestment/maintenance and major repairs can materially damage profitability
• Lack of scale may prevent operational profitability

General risk caution

• Infrastructure/airport completion risk mentioned (e.g., “airport won’t be completed…” as an example)
• Emphasis that demand can be partly “wild placement”—i.e., may persist even if some infrastructure is delayed or incomplete

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Disclosures / disclaimers

• No explicit “not financial advice” disclaimer was observed in the provided subtitles.

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Presenters / sources mentioned

• Айрат Ямаев (Airat Yamaev) — founder of One Company; main speaker.
• Company references:
  • One Company
  • MR Group (partner model referenced)
  • Sberbank (bank financing referenced)
  • Montera (consulting/development master plan referenced; brand naming discussed)
• Illustrative/external references:
  • A Chinese entrepreneur (mentioned via a “Dyson-vacuum” style humorous comparison; no clear name)
  • “GPT chat” referenced humorously (no direct link)

No other clearly named presenters/sources were indicated beyond Airat Yamaev and the company references above.