The Investment Process -- How to find and develop good ideas (discretionary l/s equity)

I initially posted this on twitter -- reposting it here because it's applicable for students interested specifically in the discretionary long/short equity. This style is what you should expect at MMs (podshops) like Baly/citadel/p72/etc. and sector focused SMs with a low net strategy. High net funds (viking) will benefit from this style too.

1. Your job is to find attractive trade ideas. Doing so in a repeatable way requires a strong process. This means you need to focus on a coverage group you can maintain through many earnings cycles. Some industries are a coverage group, but most need to be broken down into a specific verticals. For example, breaking up "Media" into "ad tech" and "streamers". When you build your coverage list, include companies from other sectors and industries if they compete in your vertical. E.g. AMZN should show up in coverage of e-commerce, hyperscale/csp, and streaming. Yes, companies exist in multiple verticals. Do this in excel --> list your stocks, briefly describe them, and organize them into verticals (direct competitors). You'll also create comp tables for each vertical (market cap, EV, sales/ebitda/eps est for FY / NFY / NTM, & calculate their valuation e.g. ev/ebitda on a FY, NTM, and NFY basis)
2. Limit your initial coverage to 25-30 companies within 2-3 verticals to start. You will expand coverage into adjacent verticals as your understanding of the industry and its dynamics evolve. "Getting deep" into an industry is hard and is "bi-directional" -- you need to complete both a bottom-up and top-down process. The top-down part is done by reading industry research, industry surveys, gathering a list of key words, etc. The bottom-up part requires an initiation on each stock you cover. This is labor intensive and is your "ramp" process, where you need to read (at minimum) item 1 & 7 on the 10-k, last 4 earnings press releases & call transcripts, guidance commentary, and investor day presentations. Your goal is to understand what the business does (where you can describe it in 1 sentence) and what the goalpost for the company is. E.g. A company's investor day deck states "we are targeting $10bn in ARR by 2027" or "we plan to increase production to 100k units by 2030". This is a must have -- it's the "fundamental bet" of a company. Beyond that, analyze the company's product-market fit (how good is the product, what makes it different), industry dynamics (how exposed is it to competition, themes, its value chain, etc.), and the strategic operating plan of management (company's goals/opportunity and how management plans to get there). Use OneNote and Alphasense to help speed up the process and organize your information.
3. After industry (and company) initiations, you can move on to an "earnings recap" note.. In your earnings recap, describe how each company did (vs. their own guidance and vs. the street at minimum), what drove performance (commentary from management), guidance (including what assumptions are baked in, e.g. "our guidance of $200mn sales next quarter assumes macro remains soft"), and your updated view metrics (through the forecast period). Try to draw "themes" you are seeing e.g. "coffee chains are seeing higher coffee bean prices but have been successful at passing it through to consumer". 
4. Now let's get to modeling. Before you do an individual company model, build a "vertical dashboard" to track KPIs, things that impact companies across the vertical, and important industry trends. E.g. Smartphone shipments, market dare data, coffee bean prices. For individual company modeling focus on 2 primary things: an earnings process that allows for a quick update and assessment, and a valuation module. Yes, you need a 3 statement model because you need to do all sorts of analysis for scenarios (more on this later). The more data you have the better, but starting off with 3-yr historical annual data + last 2 full years of quarters is fine. Your forecast period at minimum should be 5 years out. Both alphasense and bamsec have great tools to speed up this process (takes me about 3 min per period per statement, so for 3yr = ~30min, for 8 quarters ~70 min). Your earnings section needs to be set up to make a forecast and quickly assess actual data when it comes in. I always compare my forecast to guidance and the street for each period I forecast-- you should do the same. Include analytics such as q/q, y/y, average q weight, seasonality (ave q %), and 2-year stack. I typically start forecasting at the annual level and then calibrate to the quarterly level. E.g. "company's strategy means they can realize 15% y/y.. seasonally most of their growth happens in q4". Valuation needs to be simple and useful. No DCFs; use multiples. Valuation does not happen in a vacuum -- the multiple is a proxy for the denominator in the Gordon growth/DCF model "(r-g)". To understand how r and g have changed, compare the chg in rates for r, for g you should look at the trend of estimate revisions through the period. Also compare the chg to your peer estimates vs. your co's. If there's no chg to the premium/discount your company is trading on vs. peers, is the multiple really telling you something about a view on earnings? Don't try to trade the multiple-- see it as the money weighted view of the metric. When the multiple is trading below the average, since the last report period, it may suggest the market is expecting a lower metric and vice versa. This tends to be true unless there has been material changes intraperiod. Remember to compare vs. peers (if your co's multiple is higher in the quarter, and so too is all the co's peers, then is that really a strong idio signal? Probably not). Keep your analysis focused on the metric (sales, ebitda, earnings) and try to stick with the average multiple or simply the last print as your baseline.
5. Okay now that you generally know the process, how do you find trade ideas? Step 1: Go back to your framework of product-market fit, industry dynamics, and strategic operating plan. With those in mind, read sell side research. Pay close attention to the arguments per sell side analyst and their metric forecast (don't worry about the price target). Lay out the information to understand the spectrum of views. I use a spreadsheet for this (a sheet in my company model excel workbook). Identify the critical factors and what you think would make the sell side analyst change their view. E.g. Bofa Analyst thinks Snowflake billings will reaccelerate because of improving SMB trends. Now you know if SMB trends get worse, that analysts estimates will likely move lower. Step 2: Get hyperfocused on those critical factors -- do everything you can to understand them at the same level or better than the sell side analyst. Step 3: Conduct scenario analysis to understand how changes in the critical factors would roll up into sales, ebitda, eps. Consider the change to growth rates and what that would imply on a multiples basis (look at historical context and spread vs. peers). Step 4: Determine what scenario (or mix of scenarios) is the most likely outcome and what the "path of monetization" looks like. The stock will tend to trade around the midpoint  the most likely outcomes. You buy at value when the stock is underestimating the odds of your outcome, but ultimately your payoff is in being right about the actual outcome. The path of monetization is when you look at the calendar and identify the upcoming events that will provide the information that will prove your thesis correct. That could be the upcoming earnings, an investor day event, 2-3 quarters down the line ("factory won't come online until next year, so it's a q4 story"), or even years out. Step 4 requires good judgement -- read @PTetlock's book Superforecasting.

And that's it for the general process! Some additional tips are to write up ideas in memo format to get feedback, have a routine for checking news, and to use a set date during the week testimate revision updates. Can analysts incorporate more into the process? Yes - what I laid out should be seen as the bare minimum. Let me know what you think and this has been helpful.

Quick comment re: sell side -- you are not "trading" vs. sell side, however, they're a useful proxy for the "arguments" and "math" (the scenarios) that the buy side are considering too. It's not so simple as just having a view vs. consensus, but it should start there.