It's quite hard to find good resources on the internet for this purpose; what helped me was scouring Wikipedia [1] for the buzzwords (check out 'see also') and searching on Google if necessary beyond that. There's also lots of free lectures from places like KhanAcademy or Coursera that likely cover these parts of business.
One small tip my cofounder learned in business school: I don't remember the exact terminology, but analyses that go from the inside outwards are more respected by investors than ones that go from the outside inwards. Don't take huge figures like "Number of Americans" and multiply by "Percent of Americans that do 'x'", but rather find localized, small figures, and extrapolate those up/outwards.
[1] https://en.wikipedia.org/wiki/Total_addressable_market https://en.wikipedia.org/wiki/Market_segmentation https://en.wikipedia.org/wiki/Target_market
An example of top-down analysis is to go to e.g. Gartner or similar research firms and read that they estimate the ridesharing market to be say $100B.
An example of bottom-up is to say, based on data from this and this article or data source, we estimate there are 1M cars doing ridesharing every year in the US. We will sell each of them a gadget for $10 so our market is $10M if we capture all of it.
Not sure if it could be considered the same, but in physics there's a concept of "from first principles" where you obtain something starting from laws which you know are true (within the domain of applicability of a theory). "From first principles" is in contrast to making comparisons for example reasonings like "I know the answer in that other situation, so in my situation of interest I'm going to estimate the answer is X% more".
Calculations from first principles are tipically more robust but harder to do.
Also, check out some of the common frameworks like Porter's 5 Forces, SWAT analysis, BCG Growth-Share matrix, and the GE-McKinsey matrix. There are a lot of free educational materials on these. I'd take it slow and steady, and try to focus on orienting your thinking to the questions asked by these frameworks.
Also, consider reading the Form 10Ks for some companies whose products you like. They have a section where they explain their market and their role in it.
Good luck!
Typically these kinds of books take one of two extremes:
1. Markets are psychology and TA patterns will unlock profits
OR
2. Markets are mathematics and algorithms will unlock profits
Books in #1 will tell you all about Ichimoku clouds, fibonacci levels, fractal patterns, and how to read tea leaves.
Books in #2 tend to ignore the (real) psychological aspects of trading and don't give you much edge beyond a random walk.
Grimes book holds a special place in this dynamic: He discusses price action as psychology, but applies statistical tests to common trader folklore.
As a programmer and beginning trader/quant, Grimes book was exactly what I was looking for.
My personal take on TA is that Markets are psychology and TA is a slowly evolved form of feature engineering that has been finely tuned to be used by the most advanced visual pattern recognition algorithm we have, our brains. Many of these features can be tested and proven statistically, but they require additional feature engineering work to convert them from their visual pattern recognition purpose into something more suited to statistical inference. And just like any form of feature engineering, a lot of it doesn't work, but when you find what does work, it's pretty awesome.
5Cs, STP, 4Ps
5Cs: Just list out a bunch of facts to get acquainted - Context: what are the wider trends (e.g. millennial habits, etc.). This is where you start wide
- Customer: what 'job' is your customer trying to do? Who could that be? What is your unit of analysis: a person, an occasion, a ___ ??
- Company: what are you good at?
- Competitors: Who else is trying to serve that job?
- Collaborators: Who could be a partner? (Vendor, complementary service, channel partner, etc.)
STP:
- Segmentation: What are the different customer segments? What are the dimensions that make two {people, occasions, etc.} different in a meaningful way
- Targeting: Which are the viable and nonviable segments? Who's your target?
- Positioning: What is your:
-- POP/POD: point of parity/point of difference
-- Frame of reference: who are you stealing share from?
-- Reasons to believe: why would someone believe that you can deliver?
4Ps/marketing mix:
- Product/brand: what is your product? what's it's functionality? what's your brand?
- Price: level and structure.
- Place: distribution channels. Pull vs. push.
- Promotion: where will you advertise? What's your message?
https://stratechery.com/concepts/
I've found his Aggregation Theory to be a very useful lens to understand the largest tech companies. Arguably this particular theory isn't as useful if you're trying to find a niche to start your own company, but he explains a lot of his working in a way that I feel is transferrable/generalizable.
These traders also told me that do not know anybody at the trading desk that has not quickly felt out of love for TA.
TA will work when nothing major is affecting the market.
Special events will affect the price is a way that TA cannot predict. Who has enough money or influence can also manipulate the prices. Changes in fundamentals can also affect the price in a way that TA cannot predict.
If you're referring to financial markets, I personally learned a lot from Trading and Exchanges: Market Microstructure for Practitioners, although I didn't finish it. But it explains the basic characteristics of financial markets, and why they are set up the way they are. It isn't necessarily going to be obvious and financial markets are based on hundreds of years of accumulated knowledge.
There's many ways to approach market analysis and taking it all in at once can be overwhelming, with "Analysis Paralysis" quick to set in.
I'll follow through and write/dump in an article all I know based on my experience and books I've read if anyone is interested.
One of the ways people do their research is by creating a landing page and driving traffic via google/facebook/linkedin ads. The amount of signups for beta is supposed to be an indicator of the product's demand.
~70% in 2012 of the market trades on computers/algorithms.
I recommend reading some finance books, but at the end of the day, you probably going to want start to build a financial trading algorithm.
I recommend Black Swan or Fooled by Randomness
Blue Ocean Strategy
Thinking in New Boxes: A New Paradigm for Business Creativity
Both aren’t entirely scientific and obviously downplays the effort to make success happen, the theories are quite interesting and applicable.
I recommend 'A new trading for a living'. Great intro to trader psychology and non-BS technical indicators