Venture Portfolio Research Articles

Explore or exploit? A process view on entrepreneurial decision-making in venture portfolio formation

This study explores the decision-making processes of portfolio entrepreneurs (PEs) regarding their exploration and exploitation strategies. It investigates how PEs’ expectations and eventual realizations affect their intentions and actions in forming portfolio ventures. In addition, this research highlights the dynamic nature of entrepreneurial decision-making in the context of portfolio formation to understand how intentions for portfolio formation are related to exploration and exploitation strategies. It presents evidence from in-depth interviews with 21 PEs (collectively owning 132 companies). This study classifies the structures of the venture portfolios held by the interviewed entrepreneurs into five novel categories to identify the nuanced interplay between intentionality and external influences in shaping PEs’ decisions. It introduces the concept of “emerging bounded agency” to characterize the complex nature of decision-making in portfolio entrepreneurship, challenging traditional notions of intentionality. This research advances the categorization of emerging portfolio structures and supports future research on entrepreneurial decision-making in venture portfolio development.

Process Alpha: How to Construct and Manage Optimized Venture Portfolios

The author provides a specific strategy to design and manage an optimal venture investment strategy, regardless of the venture thesis. The author first discusses the contributing factors that have contributed to the consistent underperformance of the median venture capital fund performance and highlights the recent research findings and actions taken by Sequoia Capital to frame the direction of the innovation in the venture fund model. He then offers specific examples of how an optimal fund would be structured and managed, presuming there is proper reporting and analytics available on the individual portfolio companies. Last, the author makes a case for professionalizing the venture industry with recognized training, curriculum, and a certification and continuing education requirements to parallel other recognized professions.

Stock Market Prediction Algorithm

Abstract: Lately, numerous institutional financial backers utilize algorithmic exchanging to finish their speculation choices. This technique decreases the exchange costs, and further develops the venture return. Algorithmic exchanging is another exchange mode. This paper presents the algorithmic exchanging and the improvement cycle, presents the advancement interaction of exchanges costs, audits the most recent exploration literary works of algorithmic exchanging technique, and presents the writings of venture portfolio choice. In light of the current exploration and the ongoing circumstance of algorithmic exchanging our country, this paper fosters the application and idea for algorithmic exchanging Keywords: Neuron-Fuzzy systems, LSTM, Artificial neural network, Hidden Markov model, Data mining, Stock market prediction, TSLM and RNN.

Stock Market Prediction Algorithm

Abstract: Lately, numerous institutional financial backers utilize algorithmic exchanging to finish their speculation choices. This technique decreases the exchange costs, and further develops the venture return. Algorithmic exchanging is another exchange mode. This paper presents the algorithmic exchanging and the improvement cycle, presents the advancement interaction of exchanges costs, audits the most recent exploration literary works of algorithmic exchanging technique, and presents the writings of venture portfolio choice. In light of the current exploration and the ongoing circumstance of algorithmic exchanging our country, this paper fosters the application and idea for algorithmic exchanging Keywords: Neuron-Fuzzy systems , LSTM, Artificial neural network, Hidden Markov model, Data mining, Stock market prediction, TSLM and RNN.

Optimization of venture portfolio based on LSTM and dynamic programming

<abstract><p>A rational investor always pursues a portfolio with the greatest possible return and the least possible risk. Therefore, a core issue of investment decision analysis is how to make an optimal investment choice in the market with fuzzy information and realize the balance between maximizing the return on assets and minimizing the risk. In order to find optimal investment portfolios of financial assets with high volatility, such as gold and Bitcoin, a mathematical model for formulating investment strategies based on the long short-term memory time series and the dynamic programming model combined with the greedy algorithm has been proposed in this paper. The model provides the optimal daily strategy for the five-year trading period so that it can achieve the maximum expected return every day under the condition of a certain investment amount and a certain risk. In addition, a reasonable risk measure based on historical increases is established while considering the weights brought by different investment preferences. The empirical analysis results show that the optimal total assets and initial capital obtained by the model change in the same proportion, and the model is relatively stable and has strong adaptability to the initial capital. Therefore, the proposed model has practical reference value and research significance for investors and promotes a better combination of computer technology and financial investment decision.</p></abstract>

Why Do Some Entrepreneurs Develop Venture Portfolios? And how do they Do So? A Meso-Level Analysis

The question how decisions made by entrepreneurs affect their individual business ventures is essential to research in entrepreneurship. While knowledge on the role of entrepreneurial learning and habits (Aldrich and Yang 2014), the influence of uncertainty on organizing entrepreneurial activities (Alvarez and Barney 2005) and the role of past career practices on entrepreneurial decision making (Engel, van Burg, Kleijn and Khapova 2017) is widely established, yet little is known on how this applies to entrepreneurs “simultaneously owning and engaging in a portfolio of entrepreneurial interests” (Carter and Ram 2003, p. 374). As such, portfolio entrepreneurs are a distinctive group of habitual entrepreneurs whom received increased and sustained scholarly attention over the recent years (Wiklund and Shepherd 2003 and 2008, Baert, Meuleman, Debruyne and Wright 2016, Lechner, Kirschenhofer and Dowling 2016, and Cruz and Justo 2017). However, yet little empirical evidence exists to explain variation within this group of entrepreneurs (Kutzewski, Bahlmann and Stam 2020); nor do we know how and through which practices the formation of business portfolios is affected. We conducted research asking why, how and with what effect, portfolio entrepreneurs engage in their activities. To answer these questions, a comparative multi-case study design was chosen. The research unit comprised management decisions made by individual portfolio entrepreneurs. Based on a case sample comprising the explorative and exploitative activities of 21 portfolio-entrepreneurs with a combined portfolio of 129 companies, this research found ample evidence that various forms of intention (Why?), decision making and coordination (How?) exist simultaneously within the same portfolio (With what effect?). The result of this research contributes to our understanding of how entrepreneurial principles through which portfolio-entrepreneurs organize their activities affect the structure of venture portfolios.

Entrepreneurial Hiring Strategies in Standalone and Portfolio Ventures

Acquiring talent is a central decision for new ventures. Yet recruiting decisions are made under demand uncertainty, making the optimal hiring strategy unclear. We argue that such strategy depends on the type of entrepreneurship pursued: whether entrepreneurship entails founding a standalone venture or a portfolio of ventures. We predict that standalone ventures will prioritize size flexibility by minimizing the number of initial hires. By contrast, portfolio ventures will make greater investments because they can redeploy unused labor within the portfolio. Thus, portfolio entrepreneurs will prioritize resource flexibility by hiring non-specialized workers, who are easier to redeploy. Finally, we expect differences between hiring strategies to diminish with labor market flexibility. We test our predictions on the population of Finnish entrepreneurs between 2007 and 2017.

How Proper Information, Effective Risk Management, and Legacy Capital Can Solve the Funding Gap

One of the articles in the Spring Edition of <i>The Journal of Private Equity</i> explores why positive risk-adjusted returns, namely alpha, has been limited to a select group of venture funds and investors. That article recommends possible causes and proffered solutions. This article explores in greater detail the (potential) answers to the chronic “negative alpha” typical of the venture asset class. The author also presents the most recent thinking on venture portfolio construction, and shared investment selection philosophies and practices from the public securities market (hint: picking stocks does not work). Included are insights from institutional investors that have heretofore avoided the venture asset class due to the chronic “negative alpha,” and how a new approach using Smart Beta filtering could attract more institutional capital earlier in the startup lifecycle. The interests and motivations of the modern Impact investor today are remarkably similar with the original roots, and could represent the next wave of capital flowing into early-stage entrepreneurial companies. Success may come with a lowering of the cost of capital for entrepreneurs seeking funding and the equity risk premium applied by investors, moving the efficient frontier on the asset class up and to the left. <b>TOPICS:</b>Private equity, portfolio construction, risk management, performance measurement

Partly risky, partly solid – Performance study of public innovation loans

In this paper I attempt to measure the ability of a Norwegian publicly subsidized loan program to identify innovative firms that are victims of market imperfections. I apply three complementary control groups, which all have in common that they address specific unobservable characteristics of the program participants. The program participants perform better on a variety of growth measures compared to the firms rejected by the program. Compared with firms that receive private credit financing, I do not find that the program participants perform better in the upper quantiles of the contingent performance distribution despite a lower survival rate. The latter result suggests that the program does not seem to succeed in identifying a target group of firms with a sufficiently high growth potential. Firms with innovation loans are not outperformed by venture portfolio companies with respect to sales growth. The venture portfolio companies do, however, have higher survival rates as well as stronger growth in employment and assets. The latter result possibly indicates that the venture portfolio companies are more likely to succeed in the long run. The overall results indicate that the selection competency of the bureaucrats administrating the program is at level with that of private banks, and possibly also of that of venture funds. Still, in order for the program to provide the same level of welfare improvement as regular business credit provided by the private market, I find that the positive externalities from the program must be sufficiently large to compensate for the direct public subsidy element including risk adjusted return on equity and social costs of public funds.

Research on Strategic Analysis and Decision Modeling of Venture Portfolio

The value of risk project is usually uncertain, so venture investor must make investment decision based on prior estimation of future value of risk projects. This paper constructs a portfolio optimization model of risk projects considering the psychological characteristics of venture investors, and proposes a Bayesian method to deal with the uncertainty of value estimation in project portfolio selection, and utilizes Monte Carlo method to simulate the model as a linear integer programming problem. The study finds that, compared with portfolio selection based directly on ex ante value estimation, Bayesian modeling of project estimates of project value uncertainty can provide more accurate value estimates and use the resulting revised estimates to make portfolio decisions can help to select a project portfolio with a higher expected utility, eliminate the expected interval between the expected pre-expected utility and the expected utility of post-implementation, and reduce the degree of disappointment of venture investor's expected decision-making.

Portfolio Entrepreneurship and Resource Orchestration

Research summaryThis study examines the role of resource orchestration for the exploration and exploitation of opportunities through portfolio entrepreneurship. Adopting a single‐case study approach, we identify eight distinctive resource orchestration subprocesses that we group into three aggregate resource orchestration processes that enable the development and exploitation of a set of resources and capabilities across a portfolio of ventures. Our findings extend the literature on enduring entrepreneurship by building theory on how resource orchestration across a portfolio of ventures facilitates the emergence of synergies when exploring and exploiting opportunities.Managerial summaryThis study examines the processes through which an entrepreneur structures and rearranges resources and capabilities across multiple firms as he/she grows a portfolio of firms to engage in the exploration and exploitation of market opportunities. Entrepreneurs can obtain insights for building their businesses from the eight processes we identify; these processes allow entrepreneurs to develop synergies as they create and put to use a set of resources and capabilities across their businesses. Through these synergies, entrepreneurs can share, transform, and harmonize resources and capabilities across their firms. This can enable them to continuously and simultaneously explore and exploit market opportunities, which ultimately facilitates the sustainability of their businesses. Copyright © 2016 Strategic Management Society.

International Analysis of Venture Capital Programs of Large Corporations and Financial Institutions

In this article, we investigate what drives large companies (nonfinancial corporations and financial institutions) worldwide to run venture capital (VC) programs, specifically targeting Fortune Global 500 companies. Such a decision involves trade–offs between expected strategic and financial benefits and costs of managing and financing a portfolio of ventures, which are influenced by the institutions and regulations that affect innovation–oriented entrepreneurship. We determine that companies are more likely to run a program if they are based in countries in which the market for early–stage investments is well developed and innovation–related resources are more widely available. Moreover, companies based in countries with costly personal bankruptcy regulations are less likely to run a VC program, which is consistent with the prediction that these regulations discourage entrepreneurial initiatives. These findings emphasize the importance of favorable local conditions for an affiliated VC program. We observe no evidence, however, that unfavorable local conditions affect the degree of internationalization of programs, suggesting that running international programs entails significant extra costs. Finally, no significant difference emerges between U.S.–based and Western European–based companies.

International Analysis of Venture Capital Programs of Large Corporations and Financial Institutions

In this article, we investigate what drives large companies (non-financial corporations and financial institutions) worldwide to run venture capital (VC) programs, specifically targeting Fortune Global 500 companies. Such a decision involves trade-offs between expected strategic and financial benefits and costs of managing and financing a portfolio of ventures, which are influenced by the institutions and regulations that affect innovation-oriented entrepreneurship. We determine that companies are more likely to run a program if they are based in countries in which the market for early-stage investments is well-developed and innovation-related resources are more widely available. Moreover, companies based in countries with costly personal bankruptcy regulations are less likely to run a VC program, which is consistent with the prediction that these regulations discourage entrepreneurial initiatives. These findings emphasize the importance of favorable local conditions for an affiliated VC program. We observe no evidence, however, that unfavorable local conditions affect the degree of internationalization of programs, suggesting that running international programs entails significant extra costs. Finally, no significant difference emerges between U.S.-based and Western European-based companies.

Enhancing Innovation through International Joint Venture Portfolios: From the Emerging Firm Perspective

Anecdotal evidence continues to suggest that many firms in emerging economies (EEs) lack innovation. To investigate how these firms might improve their innovation, the authors integrate resource dependence theory with network theory and the resource-based view to theorize that EE firms can advance their innovation by configuring their international joint venture (IJV) portfolio characteristics at the network and focal firm levels. The results indicate that an EE firm's innovation improves when structural hole positions in its IJV portfolio increase but decreases when network centrality increases. Such relationships are further contingent on two focal firm-level IJV portfolio characteristics: IJV portfolio size and IJV portfolio resource commitment.

The Causes and Consequences of Churn in Entrepreneurs’ Personal Networks

This study examines the causes and consequences of churn in technology entrepreneurs’ (ego) core personal networks. Churn refers to the change in the composition of an entrepreneur's core personal network due to the entry of new network contacts (alters) or exit of existing network contacts. We draw on recent research describing networking styles to examine how a focal entrepreneur's networking actions affects churn in his/her core personal network and thereby increases his/her venture's portfolio of exchange partners. We find that entrepreneurs whose networking actions involve establishing greater interpersonal knowledge when interacting with strangers or relationally embedding ties with existing alters experience lesser network churn. In contrast, entrepreneurs whose networking actions involved greater time pacing of interactions with existing alters experienced greater network churn. The longitudinal empirical analysis on a sample of Indian high technology entrepreneurs operating business‐to‐business ventures provides support for our theoretical framework. We contribute to the entrepreneurial networks literature by systematically examining the dynamics of technology entrepreneurs’ core personal networks and their venture‐level consequences. Copyright © 2012 Strategic Management Society.

Propagation of Financial Shocks: The Case of Venture Capital

This paper investigates how venture-backed companies are affected when others sharing the same investor suffer a negative shock. In theory, companies may be helped or hurt in this scenario. To examine the topic empirically, I estimate the impact of the collapse of the technology bubble on non-information-technology (non-IT) companies that were held alongside IInternet companies in venture portfolios. Using a difference-in-differences framework, I find that the end of the bubble was associated with a significantly larger decline in the probability of raising continuation financing for these non-IT companies in comparison to others. This does not appear to be driven by unobservable company characteristics such as company quality or IT relatedness; for the same portfolio company receiving capital from multiple venture firms, investors with greater Internet exposure were significantly less likely to continue to participate in follow-on rounds. This paper was accepted by Itay Goldstein, operations management.

Research on portfolio optimization of agricultural intellectual property promotion engineering projects

Venture capital which supports the commercialization of agricultural S&T achievements is a new type of investment mode. High earning of agricultural intellectual property venture capital coincides with high risk. How to balance the return on investment against the risk of investment and how to decide the compositions of investment portfolios are what the investment companies most concern. From the perspective of venture capital companies, this paper, which applies expert evaluation method, mean-variance portfolio theory and quadratic programming, studies optimization of intellectual property venture portfolio, proves rationality and feasibility of the model through case analysis, and provides a theory for venture capital companies to optimize their investment portfolios.

Corporate Venture Capital and the Returns to Acquiring Portfolio Companies

A prominent motive for corporate venture capital (CVC) is the identification of entrepreneurial-firm acquisition opportunities. Consistent with this view, we find that one of every five startups purchased by 61 top corporate investors from 1987 through 2003 is a venture portfolio company of its acquirer. Surprisingly, our analysis reveals that takeovers of portfolio companies destroy significant value for shareholders of acquisitive CVC investors, even though these same investors are “good acquirers” of other entrepreneurial firms. We explore numerous explanations for these puzzling findings, which seem rooted in managerial overconfidence or agency problems at the program level.

Corporate venture capital and the returns to acquiring portfolio companies

A prominent motive for corporate venture capital (CVC) is the identification of entrepreneurial-firm acquisition opportunities. Consistent with this view, we find that one of every five startups purchased by 61 top corporate investors from 1987 through 2003 is a venture portfolio company of its acquirer. Surprisingly, our analysis reveals that takeovers of portfolio companies destroy significant value for shareholders of acquisitive CVC investors, even though these same investors are “good acquirers” of other entrepreneurial firms. We explore numerous explanations for these puzzling findings, which seem rooted in managerial overconfidence or agency problems at the program level.

Simulating the Effects of Fund Valuation Policies on the Measurement of Risk in Venture Capital

The common venture capital adage that there is “too much money chasing too few good deals” is in essence an indirect criticism that limited partners are not demanding sufficient risk premia from their venture portfolios. But the lack of objective, regular pricing data for venture fund assets makes this a difficult charge to evaluate even with the benefit of historical hindsight. How risky is a well diversified portfolio of venture funds and what kind of mean returns should LPs demand? This article explores that question indirectly by using computer simulations to estimate how much underlying asset risk may be masked by venture firms9 portfolio valuation policies. <b>TOPICS:</b>Private equity, VAR and use of alternative risk measures of trading risk, simulations