Overview:
After studying various investment philosophies over the past 20 years with varying degrees of success, I decided to develop an algorithm for generating long-term returns. I personally believe that beating the market over the long term (i.e. generating returns greater than the return of the S&P 500 a.k.a. alpha) is hard to do. Clearly some money managers have generated alpha for their clients over an extended period of time, but theoretically it is harder and harder to do as information is quickly and readily available to all market participants these days. This is an attempt at publishing my thoughts and work on the subject, publicizing my results in a systematic way, and seeing if I can start to generate wealth faster than the average market participant who simply invests in the S&P 500.
The Basics:
Benjamin Graham has a simple formula for calculating the Intrinsic Value of an investment:
V= the value expected from the growth formulas over the next 7 to 10 years
EPS= the company’s last 12-month earnings per share
8.5= P/E base for a no-growth company
g= reasonably expected 7 to 10 year growth rate
4.4= the average yield of AAA corporate bonds in 1962 (Graham did not specify the duration of the bonds, though it has been asserted that he used 20 year AAA bonds as his benchmark for this variable[4])
Y= the current yield on AAA corporate bonds.
(Source: Wikipedia)
For any company, it's pretty easy to plug-and-chug into the formula and arrive at the Graham Value for any stock. I'll ignore the fact that I must have reliable data to have good results for now.
Generating a Value Ratio:
For any company, I calculate its Value Ratio accordingly:
VR = V* / CP
VR = Value Ratio
V* = Intrinsic Value calculated according to Benjamin Graham's formula
CP = Current Stock Price
Once I have this ratio, I can easily compare one stock to another.
As of May 1, 2018, you can see my results, ranked by this Value Ratio for most of the companies in the Russell 3000 here: www.operative.cc/stocks_20180501.htm
Scrutinizing The Data:
There are several pieces of data that I accept as input. In order to feel confident in any investment, I have to have some degree of confidence in the numbers I am using.
First, I have to get the Earnings Per Share (EPS) for the company. The EPS number for any company is highly scrutinized by the public, and absent the possibility of accounting fraud (hopefully defended against through diversification), I generally accept these numbers at face value. As far as EPS is concerned though, on any company I identify as a prospective investment, I look for one-time boosts or hits to earnings that can distort my results. It'd be fairly involved to do this manually for every stock in the list, although I have some todos on how to detect this programmatically. For right now, the process I've been following is that I throw out "outliers" in my manual analysis.
The second piece of data I rely on is (g) or the rate at which I expect the company to reasonably grow over the next 7-10 years. First off, I must rely on information from financial analysts. We can get this information from www.finviz.com. How accurate is this data? Projected growth rates are usually provided by analysts of respected Wall Street firms. The numbers provided by www.finviz.com are likely the average of all of these analysts, also known as the consensus. As a basis for the accuracy of these numbers, we can compare them to actual growth rates for the past five years. We do this manually for any prospective investment.
Subjective Selection Criteria:
There are many reasons, which in full are not the subject of this blog, as to why we shouldn't just blindly buy stocks that are ranked highly on our list. We have to trust that market participants sometimes have a reason for not paying up for a company. It's primarily our job to identify companies that we believe the Market may be over-discounting. Here is my attempt at describing my subjective approach:
Brand Recognition and Favorability
I like to invest in companies that I recognize. Just like a nice car from a respectable brand, I like putting my money in companies with a name that I at least recognize and a business that I have at least some understanding of.
Temporary Events
I like to invest in companies that have demonstrated long-term earnings power with short term issues. An example of this is BP. During the Gulf Oil Disaster, BP's cleanup costs were a tiny fraction of its long-term earnings capacity. In the short term, BP looked like an unmitigated disaster, but long term its earnings potential was only modestly affected.
Macro Issues and Cyclicality
I try to avoid companies that are late in their business cycle and prefer companies that are early. Steel and construction companies always look the best when the economy is strong, and always look the worst when the economy is weak. It's important to understand where we are at in the cycle to avoid getting in at the proverbial top and to avoid selling at the bottom. It's broadly believed right now that we're late in the business cycle. That's also one of the biggest reasons why Steel companies seem so highly ranked, and one of the biggest reasons I'm avoiding them right now.
Things I want to own
I like boring things that make money. I once considered starting a laundromat business. The curse of the value investor is that you nearly NEVER should buy high flying growth stocks. There is a place for growth in a portfolio, but that's not what this algorithm will find.
All this being said and as the market has started to fall this year, I've been more interested in identifying value investments. Here are some that I've started to take interest in and have opened positions:
So what is my process? I go through the list from top to bottom over time, identifying companies that I'm interested in investing in that have a compelling Value Ratio as calculated above on any given day. I make a list, and invest on days when the market gives me a compelling entry price. So far this year my portfolio is up around 2.13% YTD while the S&P 500 is down around 1%.
GS - Goldman Sachs (this week)
LMT - Lockheed Martin (this week)
FLR - Fluor Corporation (this week)
CAT - Caterpillar Inc.
WM - Waste Management
UNP - Union Pacific
FCX - Freeport Mcmoran
PHM - Pulte Group
EBAY - eBay
XOM - Exxon Mobil
AOBC - American Outdoor Brands Corp.
T - AT&T (last two weeks)
Some themes to I'd like to explore in upcoming blog entries:
Happy Investing!
Robinhood is one of the greatest financial innovations of the past 100 years. No longer do you need to buy 100 shares in order to moderate the cost of commissions on each trade. Robinhood transactions have absolutely no commissions, allowing small investors to dollar cost average with as little as 1 share at a time. This is amazing!
If you like this post, consider signing up for a Robinhood account at https://share.robinhood.com/nathanl801
After studying various investment philosophies over the past 20 years with varying degrees of success, I decided to develop an algorithm for generating long-term returns. I personally believe that beating the market over the long term (i.e. generating returns greater than the return of the S&P 500 a.k.a. alpha) is hard to do. Clearly some money managers have generated alpha for their clients over an extended period of time, but theoretically it is harder and harder to do as information is quickly and readily available to all market participants these days. This is an attempt at publishing my thoughts and work on the subject, publicizing my results in a systematic way, and seeing if I can start to generate wealth faster than the average market participant who simply invests in the S&P 500.
The Basics:
Benjamin Graham has a simple formula for calculating the Intrinsic Value of an investment:
V= the value expected from the growth formulas over the next 7 to 10 years
EPS= the company’s last 12-month earnings per share
8.5= P/E base for a no-growth company
g= reasonably expected 7 to 10 year growth rate
4.4= the average yield of AAA corporate bonds in 1962 (Graham did not specify the duration of the bonds, though it has been asserted that he used 20 year AAA bonds as his benchmark for this variable[4])
Y= the current yield on AAA corporate bonds.
(Source: Wikipedia)
For any company, it's pretty easy to plug-and-chug into the formula and arrive at the Graham Value for any stock. I'll ignore the fact that I must have reliable data to have good results for now.
Generating a Value Ratio:
For any company, I calculate its Value Ratio accordingly:
VR = V* / CP
VR = Value Ratio
V* = Intrinsic Value calculated according to Benjamin Graham's formula
CP = Current Stock Price
Once I have this ratio, I can easily compare one stock to another.
As of May 1, 2018, you can see my results, ranked by this Value Ratio for most of the companies in the Russell 3000 here: www.operative.cc/stocks_20180501.htm
Scrutinizing The Data:
There are several pieces of data that I accept as input. In order to feel confident in any investment, I have to have some degree of confidence in the numbers I am using.
First, I have to get the Earnings Per Share (EPS) for the company. The EPS number for any company is highly scrutinized by the public, and absent the possibility of accounting fraud (hopefully defended against through diversification), I generally accept these numbers at face value. As far as EPS is concerned though, on any company I identify as a prospective investment, I look for one-time boosts or hits to earnings that can distort my results. It'd be fairly involved to do this manually for every stock in the list, although I have some todos on how to detect this programmatically. For right now, the process I've been following is that I throw out "outliers" in my manual analysis.
The second piece of data I rely on is (g) or the rate at which I expect the company to reasonably grow over the next 7-10 years. First off, I must rely on information from financial analysts. We can get this information from www.finviz.com. How accurate is this data? Projected growth rates are usually provided by analysts of respected Wall Street firms. The numbers provided by www.finviz.com are likely the average of all of these analysts, also known as the consensus. As a basis for the accuracy of these numbers, we can compare them to actual growth rates for the past five years. We do this manually for any prospective investment.
Subjective Selection Criteria:
There are many reasons, which in full are not the subject of this blog, as to why we shouldn't just blindly buy stocks that are ranked highly on our list. We have to trust that market participants sometimes have a reason for not paying up for a company. It's primarily our job to identify companies that we believe the Market may be over-discounting. Here is my attempt at describing my subjective approach:
Brand Recognition and Favorability
I like to invest in companies that I recognize. Just like a nice car from a respectable brand, I like putting my money in companies with a name that I at least recognize and a business that I have at least some understanding of.
Temporary Events
I like to invest in companies that have demonstrated long-term earnings power with short term issues. An example of this is BP. During the Gulf Oil Disaster, BP's cleanup costs were a tiny fraction of its long-term earnings capacity. In the short term, BP looked like an unmitigated disaster, but long term its earnings potential was only modestly affected.
Macro Issues and Cyclicality
I try to avoid companies that are late in their business cycle and prefer companies that are early. Steel and construction companies always look the best when the economy is strong, and always look the worst when the economy is weak. It's important to understand where we are at in the cycle to avoid getting in at the proverbial top and to avoid selling at the bottom. It's broadly believed right now that we're late in the business cycle. That's also one of the biggest reasons why Steel companies seem so highly ranked, and one of the biggest reasons I'm avoiding them right now.
Things I want to own
I like boring things that make money. I once considered starting a laundromat business. The curse of the value investor is that you nearly NEVER should buy high flying growth stocks. There is a place for growth in a portfolio, but that's not what this algorithm will find.
All this being said and as the market has started to fall this year, I've been more interested in identifying value investments. Here are some that I've started to take interest in and have opened positions:
So what is my process? I go through the list from top to bottom over time, identifying companies that I'm interested in investing in that have a compelling Value Ratio as calculated above on any given day. I make a list, and invest on days when the market gives me a compelling entry price. So far this year my portfolio is up around 2.13% YTD while the S&P 500 is down around 1%.
GS - Goldman Sachs (this week)
LMT - Lockheed Martin (this week)
FLR - Fluor Corporation (this week)
CAT - Caterpillar Inc.
WM - Waste Management
UNP - Union Pacific
FCX - Freeport Mcmoran
PHM - Pulte Group
EBAY - eBay
XOM - Exxon Mobil
AOBC - American Outdoor Brands Corp.
T - AT&T (last two weeks)
Some themes to I'd like to explore in upcoming blog entries:
- Small Caps vs. Mid Caps vs. Large Caps
- Dividends and Payout Ratios
- Individual Stock Analysis
- Macro Factors that I pay attention to
- How to be smart about investing in "growth"
- Being contrarian
Happy Investing!
Robinhood is one of the greatest financial innovations of the past 100 years. No longer do you need to buy 100 shares in order to moderate the cost of commissions on each trade. Robinhood transactions have absolutely no commissions, allowing small investors to dollar cost average with as little as 1 share at a time. This is amazing!
If you like this post, consider signing up for a Robinhood account at https://share.robinhood.com/nathanl801
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