What to know about trading stocks

Compiling some useful analysis to help newbies and as a reference for others.

What drives a stock's price? I'll use Macy's as an example.

tl;dr -- most of a stocks return comes from what's going on at the market level (SPX) or industry level (XLY for example). The "alpha" or idiosyncratic return is typically driven by changes in estimates for a stocks performance (revenue or margins). Paying attention to which companies are seeing positive/negative surprises to their outlook can help you identify how the stock will trend in the near-term. Analytical techniques, such as pricing the impact (e.g. a 1% chg to revenue estimate might result in a 5% increase to EPS, which is a 5% increase in the stock price), can help you create more relative price targets. Overlaying that with positioning and liquidity data (ownership, average volumes, open interest at certain strikes) can help improve your risk/return.


Capital asset pricing model (CAPM) tells you where your returns are coming from: 4700-07-Notes-CAPM.pdf (columbia.edu)

E.g. about ~50% of Ms daily returns can be described by moves in SPX.
upload_2023-6-28_17-9-58.png


At the industry level this rises. Here, SPX is explaining about ~80% of XLYs moves:
upload_2023-6-28_17-10-54.png


Macy's relationship to XLY is greater than it's relationship to SPX:
upload_2023-6-28_17-10-25.png


Macy's also has a relationship to non-sector factors (value, growth, quality, momentum, etc.) -- using the Bloomberg GS US Equity Factor index we can see this relationship:
upload_2023-6-28_17-10-38.png


So now we can come up with a basic model to understand Macy's stock price.

Expected return = risk free rate + beta(SPX) + beta(XLY-SPX) + beta(factors) + idiosyncratic return

As traders, you can use this to estimate where you think the return will come from.

Idio returns primarily come from estimate revisions to earnings (company specific improvements) and liquidity/market structure (large holdings impact), though other things can impact a stock too.

For example, Macy's tends to trade higher when estimates for its EBITDA are higher:
upload_2023-6-28_17-16-57.png


News that impacts estimates of the company's revenues and margins will have a significant effect on the stock price. A greater primer on anomalies that drive such behavior is this review of the Post-Earnings Announcement Drift (PEAD): main.pdf (sciencedirectassets.com).

A pretty good paper put out by Tradestation covering stock ranking using estimate revisions: Web-Stock-Ranking-Based-on-Earnings-Estimate-Revisions.pdf (tradestation.com)
 
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longandshort said:
Compiling some useful analysis to help newbies and as a reference for others.
  1. Capital asset pricing model (CAPM) tells you where your returns are coming from: 4700-07-Notes-CAPM.pdf (columbia.edu)
More...
A few other suggestions:

Asset Pricing -- Cochrane
Continuous Time Finance -- Merton
Into to Math Finance, Discrete Time Models -- Pliska

These are foundational. Also, even before reading these, a few undergrad level math courses (lin alg, diff eq, real analysis...) would be helpful.

I think, in today's markets, you probably want familiarity with the above before you try evaluating actual published strats like, e.g, intraday momentum or even standard 12-1 momentum.
 
Kevin Schmit said:
A few other suggestions:

Asset Pricing -- Cochrane
Continuous Time Finance -- Merton
Into to Math Finance, Discrete Time Models -- Pliska

These are foundational. Also, even before reading these, a few undergrad level math courses (lin alg, diff eq, real analysis...) would be helpful.

I think, in today's markets, you probably want familiarity with the above before you try evaluating actual published strats like, e.g, intraday momentum or even standard 12-1 momentum.
More...
Cochrane's book is great. Have you read any Adam Iqbal? He wrote Volatility (Wiley Finance): Iqbal, Adam S.: 9781119501619: Amazon.com: Books and Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory: 9783030935542: Economics Books @ Amazon.com

Appreciate any other books & papers you think would be beneficial.
 
longandshort said:
Have you read any Adam Iqbal? He wrote Volatility (Wiley Finance): Iqbal, Adam S.: 9781119501619: Amazon.com: Books and Foreign Exchange: Practical Asset Pricing and Macroeconomic Theory: 9783030935542: Economics Books @ Amazon.com
More...

I own* both books, and have read through the latter pretty thoroughly. In fact I recommended it here on ET in this thread:

Another “what’s your edge” thread

And in at least one more post that I can't seem to find now (maybe I misspelled the name?).

* as long as you consider having downloaded them from Lib Genesis as valid ownership

Edit: Here is an extended quote from the Iqbal FX book that I have shared with more than one correspondent, as it clarifies something that is often misunderstood:

"Much academic literature refers to the Q probabilities as risk-neutral probabilities rather than risk-adjusted probabilities. The reasoning is that, once the Q probabilities are known, then assets are priced as if investors are risk-neutral in that prices are Q-measure expected payoffs. However, Eq. 1.16 justifies the nomenclature of the Q probabilities as risk-adjusted probabilities.

In a specific state of the world, if investors were risk neutral, we say the risk-neutral probabilities coincide with physical probabilities. However, if it is not the case, [and] investors are risk-averse, then risk-neutral probabilities are risk-adjusted taking into account the price effect of investors’ risk preference (Siu, 2008; Carr and Yu, 2012, and Ross, 2015)."
 
Last edited:
longandshort said:
Compiling some useful analysis to help newbies and as a reference for others.

What drives a stock's price? I'll use Macy's as an example.

tl;dr -- most of a stocks return comes from what's going on at the market level (SPX) or industry level (XLY for example). The "alpha" or idiosyncratic return is typically driven by changes in estimates for a stocks performance (revenue or margins). Paying attention to which companies are seeing positive/negative surprises to their outlook can help you identify how the stock will trend in the near-term. Analytical techniques, such as pricing the impact (e.g. a 1% chg to revenue estimate might result in a 5% increase to EPS, which is a 5% increase in the stock price), can help you create more relative price targets. Overlaying that with positioning and liquidity data (ownership, average volumes, open interest at certain strikes) can help improve your risk/return.


Capital asset pricing model (CAPM) tells you where your returns are coming from: 4700-07-Notes-CAPM.pdf (columbia.edu)

E.g. about ~50% of Ms daily returns can be described by moves in SPX.
View attachment 317931

At the industry level this rises. Here, SPX is explaining about ~80% of XLYs moves:
View attachment 317934

Macy's relationship to XLY is greater than it's relationship to SPX:
View attachment 317932

Macy's also has a relationship to non-sector factors (value, growth, quality, momentum, etc.) -- using the Bloomberg GS US Equity Factor index we can see this relationship:
View attachment 317933

So now we can come up with a basic model to understand Macy's stock price.

Expected return = risk free rate + beta(SPX) + beta(XLY-SPX) + beta(factors) + idiosyncratic return

As traders, you can use this to estimate where you think the return will come from.

Idio returns primarily come from estimate revisions to earnings (company specific improvements) and liquidity/market structure (large holdings impact), though other things can impact a stock too.

For example, Macy's tends to trade higher when estimates for its EBITDA are higher:
View attachment 317935

News that impacts estimates of the company's revenues and margins will have a significant effect on the stock price. A greater primer on anomalies that drive such behavior is this review of the Post-Earnings Announcement Drift (PEAD): main.pdf (sciencedirectassets.com).

A pretty good paper put out by Tradestation covering stock ranking using estimate revisions: Web-Stock-Ranking-Based-on-Earnings-Estimate-Revisions.pdf (tradestation.com)
More...

Those relationships :banghead:
They don’t look strong enough.
 
I don't want to open a new thread so i ask my question here. Is there a big different between trading forex pairs and stocks?
 
Kevin Schmit said:
"Much academic literature refers to the Q probabilities as risk-neutral probabilities rather than risk-adjusted probabilities. The reasoning is that, once the Q probabilities are known, then assets are priced as if investors are risk-neutral in that prices are Q-measure expected payoffs. However, Eq. 1.16 justifies the nomenclature of the Q probabilities as risk-adjusted probabilities.

In a specific state of the world, if investors were risk neutral, we say the risk-neutral probabilities coincide with physical probabilities. However, if it is not the case, [and] investors are risk-averse, then risk-neutral probabilities are risk-adjusted taking into account the price effect of investors’ risk preference (Siu, 2008; Carr and Yu, 2012, and Ross, 2015)."
More...
I am going to highlight this in my copy! Rare for an author to be both a great practitioner and a great synthesizer.
 
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