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Dhochak, M., Pahal, S., & Doliya, P. (2022).

Predicting the Startup Valuation: A deep learning

approach. Venture Capital, 1-25.

The investment and funding decisions of a new venture are based on the startup valuation, which remains an
inconclusive and disputable subject matter. For this purpose, well-established strategic management theories

such as resource-based view (RBV), industrial structure effect, and network-based theory have been leveraged
as inputs. This study uses 757 Indian startup deals dataset during the period from January 2012 to December 2019

to develop a predictive model based on the Artificial Neural Network (ANN) technique, which is a deep learning
approach to predict the startup valuation. The ANN-based model predicts the startup pre-money valuation, and

we also compares the ANN model to a linear classifier, linear regression, in this study. The result shows that the
application of the ANN model can be used as a supplementary method to predict the pre-money valuation, if

not an alternative to the traditional valuation models depending on its adaptability and accuracy. This model
provides a competitive advantage by building a strong foundation during the negotiation between VCs and

entrepreneurs. This study provides managerial and theoretical implications to VCs, entrepreneurs, and policy-
makers for upgrading the startup ecosystem.

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