Characteristics of Venture Capital Funding

Venture Capital Funding can be of different kinds. Early stage funding could be at the stage of ideation, initial production and marketing. Expansion funding is done during commercial production, marketing and growth (For more information refer to the article – Stages of Venture Capital Funding). Different funds focus on different types of funding and sectors. There are however some unifying characteristics of venture capital funds.

  • Illiquidity: Easy liquidity by cashing out in the short-term is not an option for venture capital funding. An IPO or buyout of a venture is how venture capitalists disinvest. A premature IPO could undermine an otherwise successful company. Alternatively an IPO released in a poor IPO market could also stall possibilities of cash out.
  • Long-term commitment: Venture capital funds need to be latched in for a period of few years before disinvestment. Investors who do not prefer illiquidity will attach a premium to their funds, also known as liquidity risk premium. Therefore an investor who can wait out the time horizon will benefit from this premium. University endowments who seek VC funds to invest in are an example of such investors.
  • Difficulty in determining current market values: It is difficult to evaluate the current market value of the portfolio of a VC.
  • Limited historical risk and return data and limited information: Venture capital funds more often than not invest in new and cutting edge industries of a sector, where there is little historical data or continuous trading data. It is also difficult to estimate cash flows or the probability of success.
  • Entrepreneurial/management mismatches: Entrepreneurs may face difficulties when there is dilution of ownership and control. Bad management choices may scuttle a good venture. Entrepreneurs sometimes find it difficult to step up as the venture gains size.
  • Fund manager incentive mismatches: Investors interested in well performing rather than large sized funds need to find managers who match their investment objectives.
  • Knowledge of competition: As we discussed earlier since most business’ that are funded are from nascent industries it is difficult to assess the competition, than say in established industries. A complete competitive analysis is therefore difficult to undertake for a VC fund.
  • Vintage Cycles: Economic conditions vary from year to year. During some years venture capital funding is plenty and therefore returns for them low. In poor or stressed market condition, even good firms find it difficult to find VC funding.
  • Extensive Operation Analysis and Advice: Venture capital funds that plan to invest in technology companies may not have the required expertise to assess them. Financial investment knowledge alone is not sufficient. Good fund managers therefore require both operating and financial analysis and advising skills. A fund manager who does not understand the business will impede rather than improve it.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.