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Get Started with the Venture Investor Model

An overview of the structure and assumptions in the Venture Investor Model.

The Venture Investor Model is used by investors — venture funds, angels, incubators, accelerators — to forecast investments and proceeds for a portfolio of venture investments, using assumptions for fund size, average check size, follow-ons, timing from investments to exits, and more. 1

If you are looking to track and create performance reports for an existing and ongoing portfolio, use the Venture Portfolio Model ›

It summarizes key economics for LPs and GPs and calculates key performance metrics over the fund’s lifetime, including IRR, ROI, gross and net multiples, Residual Value, Paid In Capital (PIC), Distributed to Paid in Capital (DPI), Residual Value to Paid in Capital (RVPI), and Total Value to Paid in Capital (TVPI).

How it works

The model’s inputs are on two sheets:

  • Dashboard, where you can set the distribution of gross multiples expected from your investments
  • Assumptions, where you can set the parameters of investments, timing to proceeds, management fees, carry, and other inputs


The dashboard sheet provides an overview of the fund performance, which is valuable as a first look at the fund’s performanace, and also contains an important input that creates the overall gross multiple used to forecast the total proceeds of the fund’s investments.

The chart of the distribution of gross exit multiples expected by the portfolio’s investments has an input line where you can set the % of the fund’s investments (initial checks) that will achieve a gross exit multiple within each of the ranges above (you can also set these ranges using the respective input line if desired).

This curve is a valuable way to communicate a fund’s investment strategy, and you will want to adjust this curve to communicate the strategy you are pursuing and set the overall gross exit multiple for the fund.


The remainder of the assumptions are located on the Assumptions sheet. Here the assumptions are a little more detailed, and they cover more about fund construction, investment performance, and the operating costs of the fund.

Fund Assumptions

The key fund constrution assumptions include:

  • Fund size - the total size of the fund, before fees
  • General partner commitment - how much the GPs contribute to the fund
  • Organizational Fees - fees paid by the fund out of the fund commitment, one-time in the first period of the model
  • Operating Fees - fees paid by the fund out of the fund commitment, recurring for all periods in the investment horizon
  • Management Fees - the % of the fund that the operating company takes to manage and pay expenses for operating the company that operates the fund
  • Management Fees Recycling - the % of the management fees that are recycled from proceeds back into investments instead of immediately distributing. This will only occur during the investment horizon when new and follow-on investments are being made, and the total recycled may not reach the % goal based on the actual timing and performance of the fund

Investment Areas

In this section you can optionally define up to 4 different “areas” to allocate investments to. An area can be an industry - say tech, retail, etc. - or a country - USA, UK, France, etc. - or stage - Seed, A, B, etc. - and allows you to set a portfolio allocation, average initial check size, and follow on allocation separately by each area.

This structure is not to allocate follow on capital across different stages, only to represent different areas of initial checks. If you are going to allocate all initial checks to A and reserve for follow on investments in B and C rounds, you will want to only use 1 area, and use the A initial check size. If you are going to lead A and B rounds, i.e. write your first checks into A and B rounds, then you would want to define two areas for A and B, and then set fund and follow on allocation for each area appropriately.

Investment Timing

The investment timing has a few options here which are not obvious but allow you some flexibility in how the proceeds are distributed over the periods where you are earning proceeds.

  • The investment horizon, when you start investing (for the future investments)
  • The time from investment (and follow-on) to exit, which sets the timing in the model for follow-on and exits
  • Average Time from Initial Investment to Exit, with inputs for an Average, Min, and Max

You have a choice of three options for creating a distribution of proceeds over the time periods:

  1. Straight-line, over investment period. If you set average = a number and min = max = “na”, then it will create a straight-line distribution of proceeds over a time-period of proceeds that matches the investment horizon.
  2. Triangular distribution. If you set min, mode and max to represent the minimum, maximum, and most likely time period of exits, it will create a triangular distribution for each period of investments.
  3. Straight-line, over variable period. If you set min and max as numbers and average time = “na”, then it will create a straight-line average distribution of proceeds over a period that is from the minimum time from first investment to maximum time after last investment.

Investment Performance

This section has two inputs which are rarely altered, but I’ll explain what they do in case you want to make adjustments.

  • The assumptions here cover two things that require a bit of explanation. The assumptions are the “% of Initial investment capital allocated to non-zero investments”, and “% of Follow-on capital allocated to non-zero investments”. What does that mean?
  • Essentially, this is an estimate of how much initial and follow-on investment capital is invested into deals that return > 0. This is a way to assume that you write larger initial checks into better deals, or allocate more capital in follow-ons to better deals. There’s no need to change these assumptions as the default assumption is taken from the exit multiples we created, but if you want to add an extra factor to assume the impact of variation in check sizes in better deals, feel free to edit these assumptions.

Fund Management

These assumptions refers to the fees and arrangements between LPs and GPs:

  • Carried interest - % of gains, above the preferred return and return of capital, that the operating company earns from the proceeds of sales of investments
  • Preferred return rate - the % that the fund has to return before collecting carried interest fees. Note, this is not a European-style hurdle rate, just a preferred return rate
  • Management Fees - % of committed capital, per year annually. If you need to calculate this based on Called or Managed Assets, contact
  • Capital calls - the % of committed capital called each period. Capital called will deviate from assumptions if necessary in order to have enough capital to make investments, as the investment schedule takes priority over the capital call schedule.

Operating Assumptions

These assumptions refer to the management company operating the fund, and allow you to forecast the necessary expenses to run the fund.

  • Fairly self-explanatory, but the assumptions include a hiring plan and a set of assumptions tied to operating the fund (rent, travel, marketing, PR, legal, administration, etc.)
  • The key to the hiring plan and salary forecasts is to just manually type in the salary for the first year the person joins, and then it will calculate future salaries.
  • The model used the fund management horizon assumption on this page to set how long to estimate the operating expenses
  • If the fund earns any income, those can be estimated, and you can choose to offset them against LP fees if desired

Existing Investments

This is explained in detail at Rolling existing investments into the Venture Investor Model ›

Calculating Proceeds, Returns and IRRs

The model actually calculates the proceeds twice: once on the Portfolio sheet, where you can see all the details around the fund construction, and second, on the Operating Forecast sheet. Why?

Venture fund construction

Essentially, on the Portfolio sheet it’s calculating the aggregate proceeds and gains, while in the Operating Forecast sheet it’s allocating the aggregate investments, proceeds, and cash flows over the investment and management timeframes. The fact is that building a model that forecasts aggregate returns is actually fairly simple, but building a model that calculates returns based on timeframes (IRRs) is quite harder, and involves some thinking about what you’re forecasting.

You’ll notice that the model forecasts investments and proceeds at an overall fund level, not an individual company level. So how can we forecast the aggregate portfolio without forecasting each investment?

Think about how funds make their money - a small set of outsized exits drive the vast majority of overall returns. So, the existance of large multiple exits, 25x or greater, are incredibly important to a fund’s overall performance. But how can you forecast the timing and distribution of highly infrequent and random events, and what kind of impact will it have on your return estimates?

In an earlier version of this model I created a forecast of individual investments using probability distributions of exits, follow-ons, and going out of business, as well as the timing and exit multiple of exits at different stages, and one could use the model to run a set of observations of portfolio performance to create an average of the results. But I eventually simplified the approach by stripping out the random generation and creating a methodology to forecast the distribution of returns. My goal was to make it easier for people to use the model for running a business (and not just generating numbers and forecasts). In this version I took that a step further and essentially removed the events to focus just on the aggregate. And the result is something that is simpler to understand and audit and surely easier to use.

On the Operating Forecast sheet you’ll see the forecasted fund operations. The model uses a semi-annual time-period (H1 for first half of the year and H2 for second half of the year) to map the time period simple to use. Since the distribution of deals done can be somewhat seasonal and bunchy over smaller time periods, I chose semi-annual periods as the best blend of calculation accuracy and detail meaningfulness.

The existing investments (investments already made) are shown over time, and then below the forecasted investments are estimated over the future time period. Excluding any already-invested follow-on rounds, the follow-on capital is allocated separately from the new investments so that the timing of follow-on rounds can be allocated separately, as well as any difference in returns from follow-on v. new invested capital (see how-to part 1 for explanation).

Venture fund capital forecasts

After the fund’s investments and proceeds are estimated, the model breaks down the cash flows for the limited partners (LPs) and general partners (GPs). The model doesn’t distinguish between or calculate specific returns for invidual LPs or GPs, but that can be done easily by adding lines at the end of the model using your own breakdown of fund ownership by LP and GP.

Note: when forecasting proceeds, the model offers three different distribution timing options:

  • Straight-line distribution over a harvesting period that matches the investing period
  • Straight-line distribution over a harvesting period of your choice (independent of investing period)
  • Triangular distribution over a harvesting period of your choice.

Instructions are on the Assumptions sheet in the model in how to use the inputs to choose your preferred proceeds distribution.

Performance Metrics

In addition to cash flow, multiples and IRR, the model also calculates a number of standard fund metrics to help gauge the fund’s performance. In addition to tracking investments and proceeds (i.e. distributions), the model calculates residual value (i.e. net asset value) of the portfolio over time and differentiates between realized and unrealized gains.

This chart on the Performance tab shows how the cash flows map out over time:

Venture fund capital forecasts

The model also calculates metrics such as Paid In Capital, Distributed to Paid in Capital, Residual Value to Paid in Capital, and Total Value to Paid In in order to provide a deeper picture of fund performance.

Venture fund capital forecasts

Financial Statements

The model forecasts the income statement, statement of financial condition, statement of cash flows, and statements of partner’s capital, in order to provide the full financial outlook for the fund. In addition, there is a statement of operations (income statement) generated for the management company.

Venture fund capital forecasts

There’s a lot of detailed, complicated formulas in these sheets; my goal has been to make the model very flexible based on the different use-cases of the model and the range of assumptions that you can input, thus there are many deep formulas to account for the range of possibilities. I’ve built a number of these models for venture funds and worked to make the template applicable for as many cases as possible, but funds can have interesting structures and require some edits. Contact me with any comments or questions.

  1. Fund structures the mdoel does not work for: evergreen funds where proceeds are recycled, venture debt, revenue-sharing, and other arrangements where proceeds are not through one-time exits. 

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