Forecasting returns across a commercial real estate portfolio is a necessary discipline, but it is also a dangerous convenience. A consolidated model can make a collection of buildings look like a single smooth stream of cash flow. Yet the portfolio does not pay rent; each property does. It does not negotiate a lease extension; a specific tenant and landlord do. The moment an underwriter stops looking through the top-line forecast to the individual asset, the model becomes a summary of assumptions rather than a test of them. Returns are made at the property level, then assembled at the portfolio level.
The practical challenge is not just financial theory. It is a matter of process, data discipline, and knowing which property-level variables actually drive value. Public biographical materials for Mark Tersigni, a real estate investment professional and Certified Public Accountant, describe a career spanning public accounting, corporate finance, and commercial real estate investment. Those pages describe more than a decade of progression from auditing investment companies to underwriting and managing multibillion-dollar commercial real estate portfolios, with work centered on how assets are valued, financed, and positioned for sale. That trajectory is a reminder that forecasting returns is not a separate exercise from underwriting and asset management; it is the thread that connects them.
The Portfolio View Starts at the Property
A portfolio forecast should be built from the bottom up. Each property needs its own rent roll, lease expiration schedule, recovery structure, operating expense budget, capital plan, and financing assumptions. For retail assets, the details matter acutely. A forecast that uses a single market rent growth rate for every center can miss the difference between a grocery-anchored property with steady everyday traffic and a center with a few large-format vacancies. It can also miss the timing of rent commencements, tenant improvement allowances, leasing commissions, and free rent. Those items do not stay neatly inside annual averages. They arrive in lumps, and they change the shape of returns.
A property-level model also creates accountability. When a portfolio return shifts, the asset plan should explain why. Was it occupancy? Expense recovery? A refinancing assumption? A capital project? If the model cannot answer that question, the forecast is too aggregated. The same principle applies to disposition timing. A sale assumption is not simply an exit cap rate; it is a judgment about leasing status, tenant credit, capital needs, and buyer financing. Keeping those judgments visible at the asset level makes the portfolio view more credible, not less.
Open-Air Retail and Enclosed Malls Ask Different Questions
A September 2026 IBTimes article by Tom Robbins outlining the investment case for open-air retail centers summarizes the published argument of Mark Tersigni. The article discusses open-air centers versus enclosed malls, grocery and everyday-need tenants versus department-store malls, parking and common-area costs, occupancy versus lease expirations, expense sharing, capital needs, anchor-lease provisions, and the limits of broad “retail is dying” narratives. The point is not that one format always wins. It is that the same top-down retail assumption can produce very different asset-level outcomes depending on tenant mix, lease structure, and physical configuration.
Underwriting Is Only as Good as the Financing Assumptions
Debt can flatter or distort a return forecast. A property-level model should show the loan terms, maturity, amortization, interest rate, covenants, and refinancing risk alongside the cash flow. Public biographies describe his work managing more than $1 billion of property-level commercial mortgages, providing analysis for refinancing, extension, and maturity decisions. They also describe his contribution to the origination of a $1 billion single-asset, single-borrower CMBS loan—described as the largest open-air retail securitization of 2023—requiring property-level analysis across approximately forty assets. That kind of transaction work reinforces a basic underwriting rule: the collateral is not a portfolio abstraction. It is a set of specific properties with specific leases and specific capital needs. Public biographies also describe a corporate model used by the company’s private equity ownership to forecast investment returns, consolidating individual property plans into a corporate-level view.
Asset Management Turns Forecasts Into Feedback
Forecasting is often treated as a pre-acquisition exercise, but asset management is where the forecast meets evidence. Budgets, quarterly reporting, leasing updates, capital projects, and refinancing decisions all revise the original case. Public biographies describe earlier asset management experience at a private multifamily investment firm, including annual budgeting, quarterly KPI reporting, investor reporting, hold/sell analysis, and real estate tax appeal work. They also describe a role at a national retail company establishing annual budgets and monthly projections for international retail occupancy costs. Those experiences point to a simple discipline: compare actual property performance with the plan, document the variance, and update the forecast without losing the asset-level rationale. If the portfolio model changes, the property plan should change first. Otherwise the forecast becomes a reporting exercise rather than a management tool.
For owners and investors who need that discipline outside a full-time team, Complete Property Advisors, where Mark Tersigni is listed as founder, offers consulting and hourly analyst services. The site describes a commercial real estate analyst practice headquartered in Columbus, Ohio, with national expertise. Its listed focus areas include cash flow underwriting, hold/sell/refinance analysis, transaction due diligence support, Excel model creation and maintenance, comprehensive business planning, and existing employee training in tools such as Argus and Excel. Those services map closely to the asset-level work that keeps a portfolio forecast honest: build the property plan, test the financing, maintain the model, and train the people who use it.
Keeping the Model Honest at Every Level
A public profile can be useful for background, but it should not substitute for property-level diligence. An additional profile link for Mark Tersigni is available on Crunchbase; because the page itself was not retrievable, it is best treated simply as an additional profile pointer rather than a source for any factual claim in this discussion. The relevant point for underwriting is that credentials and biography may frame experience, but they do not replace rent rolls, lease abstracts, and debt terms.
For questions about commercial real estate, underwriting, asset management, finance, and investment strategy, the contact page for Mark Tersigni lists Columbus, Ohio. That detail is useful context, but the more important takeaway is procedural: keep the lines of communication open between acquisition, asset management, and finance. A forecast is more likely to hold up when the people closest to the property can explain the assumptions and when the portfolio team can trace every consolidated number back to a specific asset.
The hardest part of forecasting returns is not building the spreadsheet. It is resisting the urge to let the portfolio view erase the property view. A model can be internally consistent and still be wrong if the rent rolls, recovery assumptions, capital plans, and loan terms do not reflect what is actually happening at each asset. The better approach is to let the portfolio summary emerge from the property detail—not the other way around. When a return assumption changes, the asset plan should show why. When a financing decision moves, the property cash flow should show the effect. When a sale is contemplated, the lease schedule and capital needs should support the exit.
Raised amid Rome’s architectural marvels, Gianni studied archaeology before moving to Cape Town as a surf instructor. His articles bounce between ancient urban planning, indie film score analysis, and remote-work productivity hacks. Gianni sketches in sepia ink, speaks four Romance languages, and believes curiosity—like good espresso—should be served short and strong.