What are the most effective market research strategies for identifying potential investments?

Secondary research backed target identification has to be step 1 of any effective deal origination exercise, leveraging sources such as LinkedIn, Crunchbase, Pitchbook, etc. Every PE firm maintains a target list, often in an unorganized excel, however, this traditional practice needs to evolve with rise of data mining and analytics capabilities. Secondary research can help PE evolve from target identification to 'Dynamic Target Watch', wherein a live dashboard enables dissemination of potential targets across the firm (barring confidential ones) with dynamic updates of the target's KPIs such as Employee Growth, Product Launch, Expansion, Financials, New Investment, etc. This data can be the foundation, which is enhanced via other means.

A comprehensive secondary research metholody to collate investment targets involves screening different sources including: 1) Paid/unpaid databases: Databases such as Cap IQ, LinkedIn, PitchBook, Tracxn & Crunchbase allow users to create customized searches with filters for industry, geography, headcount, etc. 2) Screening Top X lists: Annual lists such as Inc. 5000, Forbes Top 100 & FI50 often yield fastest growing companies in different regions, industries, etc. 3) Tracking conferences/tradeshows & their attendees: Every industry hosts events that are attended by thousands of firms that can be tracked & added to an investment firm's pipeline 4) Tracking competitors of interesting companies

Secondary research is a great starting point, but as you dig deeper, remember the gold often lies in unconventional places. Talking to actual customers can unveil hidden gems that reports and articles might miss.

I tend to take the idea that the prices are "baked in" as a confirmed hypothesis, and so that makes finding "efficient portfolios" over any given amount of time relatively easy even with Simple Monte Carlo methods. I also like to use measures of probability distributions of log returns. For example stockr which are more than 50% likely to "go up" are those which are down and have a high excess kurtosis to absolute skewness ratio. These stocks also tend (not absolute) to have a strong lagging correlation to stocks which are up. So a potential score is ||(kurtosis/skewness)||*correlation to 5 day lag with say QQQ <--- could be any stock which is up recently.

Network and Relationships: Leveraging networks and industry relationships is invaluable. Insights gained through industry contacts, conferences, and networking events often provide early access to potential investment opportunities and a deeper understanding of market sentiment. Data-Driven Evaluation: Employing quantitative analysis to evaluate potential investments through financial metrics, market trends, and comparative analyses helps in objectively assessing opportunities and mitigating risks.

When performing searches and research, listing companies is not enough. Industries are big; there are so many nooks and crannies! You need to: 1) Understand your investment thesis and strategy of the target industry; what characteristics are you looking for? What risks are involved? 2) Consider the companies you select and dig deep. Utilize current/former target industry professionals who can "read" a company; using basic analysis from those without experience only goes so far, and we've seen it be ineffective. 3) Based on your investment goals, rank and benchmark them. It's better to have 30 quality targets than 300 random enterprises that say "we do target industry."

(a) Evaluate the regulatory landscape and its impact on potential investments. Changes in regulations can significantly affect market dynamics and profitability. Prior knowledge of impending regulatory changes allowed me to exit an investment just before it faced compliance issues. (b) Calculate the customer acquisition costs (CAC) for potential investments. Lower CAC indicates efficient marketing and can lead to higher margins. An e-commerce investment with a low CAC and a scalable customer acquisition model proved to be a wise choice

Competitive intelligence has the good, the bad, and the ugly. The good: When choosing the right peers, a thorough look at the competitor information is sound. Per definition, it is relevant to what you compare it to. The bad: With public information, you only see what the competitor wants you to see. Or where there are disclosure obligations, data can either be buried or be given a particular spin. The ugly: Overly focusing on competition hurts innovative thinking from first principles. This is not to say one should neglect competitive intelligence, though one cannot necessarily rely on it for leading the way.

If you're willing to look at a lot of options chains, you can glean what the market thinks is the actual move. For near the money options, the probability estimates of Black Sholes are pretty good, so looking at where the delta is "close" to 50, is a good place to look. If you can get good historical data, you can test this hypothesis for a single stock quite well. Correlative effects using options data is often more computationally expensive than anyone outside a trading firm would be willing to undertake.

(a) Stay updated on technological advancements and their potential to disrupt industries. Seek investments in companies that are at the forefront of innovation. Recognizing the potential of blockchain technology, we invested in a startup developing blockchain solutions for supply chain management (b) Consider the social and environmental impact of potential investments. ESG (Environmental, Social, Governance) factors can influence a company's long-term sustainability. Investing in a socially responsible agriculture company not only generated profits but also contributed positively to the environment and local communities.