Market Fantasy #6 – Beta Max

Hello all, and welcome to Market Fantasy. To recap the last few weeks’ episodes, so far we have created a market index of fantasy players – the FOW. This has been tracked mostly weekly. Then, after a short history of the Dow Jones Industrial Index, we kicked out two players from the original FOW—out with Albert Pujols and Ryan Braun and in with Chris Davis and Carlos Gonzalez. After that, I got an adorable Keeshond puppy named Ash so the updates came less frequently causing the tens of people that read this blog to go into serious panic withdrawal, I’m sure.

Well, I’m back now. Today’s blog post is kind of the reason I started this blog in the first place. I wanted to take a look at Beta in terms of fantasy sports players. Besides being Sony’s first failed attempt at dominating a media format, in investing terms, Beta measures systematic risk based on how returns co-move with the overall market. Got it? What that means in plain English is that Beta measures the swing in returns of a stock compared to the swing in returns of an index. The index in question is usually the S&P. To calculate Beta, we take the covariance of rates of return of the stock and rates of return of the index.  This is divided by the variance of the rate of return of the index. The formula is as follows:

This calculation will give us a number. This number is the Beta of the stock. So what does this number mean, other than that you can do advanced calculations correctly? Like I said above, this number measures the volatility of an asset compared to the index. But what does that mean? The following chart from Wikipedia will help decipher Beta:

Value of Beta	Interpretation	Example
β < 0	Asset generally moves in the opposite direction as compared to the index	An inverse exchange-traded fund or a short position
β = 0	Movement of the asset is uncorrelated with the movement of the benchmark	Fixed-yield asset, whose growth is unrelated to the movement of the stock market
0 < β < 1	Movement of the asset is generally in the same direction as, but less than the movement of the benchmark	Stable, "staple" stock such as a company that makes soap. Moves in the same direction as the market at large, but less susceptible to day-to-day fluctuation.
β = 1	Movement of the asset is generally in the same direction as and about the same amount as the movement of the benchmark	A representative stock, or a stock that is a strong contributor to the index itself.
β > 1	Movement of the asset is generally in the same direction as but more than the movement of the benchmark	Volatile stock, such as a tech stock, or stocks which are very strongly influenced by day-to-day market news.

At this point, I’m sure most of you are thinking “Alright nerd, enough math, how does this help me in my fantasy league brosephus?” Well, let me tell you. As stated above, Beta is a measure of volatility. The way this relates to fantasy sports is to try to find the players with Betas that match your style. You can identify consistent performers week in and week out with this formula. If you want to cut out some risk on your team, try to go after players whose Beta is close to one. These are players who will be the most likely to perform on a consistent level. Conversely, if you’re a gambler, maybe a player with a high Beta is more up your alley. These are the feast and famine players you can ride to glory one week and who will flush your team straight down the toilet the next.

This can be very helpful when constructing your roster. Use players whose Beta is close to one to offset players with higher or lower Betas. Fantasy managers do this all the time when constructing their fake rosters for individual stats (holding Adam Dunn for HR? you better have a safe batting average guy like Mauer to offset Dunn’s BA torpedo), why not broaden that strategy to include overall performance? Portfolio managers look at a stock’s Beta, so why not use it to construct your imaginary dynasty? With that in mind, here are some position-by-position examples of consistent and extreme Beta cases. Note, some players are listed in a different position than their natural position, but they are eligible there in most leagues.

Catcher:

Value of Beta	Player	Beta
β < 0	Posey, Buster SF Molina, Yadier  STL	-2.98    -2.42
β = 0
0 < β < 1
β = 1
β > 1

1st Base

Value of Beta	Player	Beta
β < 0	Carter, Chris  HOU Carpenter, Matt  STL	-0.40 -0.23
β = 0	Votto, Joey  CIN	0.00
0 < β < 1	Freeman, Freddie  ATL Dunn, Adam  CHW	0.23 0.51
β = 1
β > 1

2nd Base

Value of Beta	Player	Beta
β < 0	Altuve, Jose  HOU Carpenter, Matt  STL	-1.14 -0.81
β = 0	Gonzalez, Marwin  HOU	0.00
0 < β < 1	Murphy, Daniel  NYM Kipnis, Jason  CLE	0.22 0.47
β = 1
β > 1

3rd Base

Value of Beta	Player	Beta
β < 0	Longoria, Evan TB Machado, Manny BAL	-0.48 -0.14
β = 0	Encarnacion, Edwin TOR	0.00
0 < β < 1	Dominguez, Matt HOU Alvarez, Pedro PIT	0.36 0.49
β = 1
β > 1

Shortstop

Value of Beta	Player	Beta
β < 0	Cozart, Zack CIN Cabrera, Asdrubal CLE	-0.61 -0.35
β = 0	Escobar, Yunel TB	0.00
0 < β < 1	Ramirez, Alexei CHW Aybar, Erick LAA	0.08 0.65
β = 1
β > 1

Outfield

Value of Beta	Player	Beta
β < 0	Choo, Shin-Soo CIN Holliday, Matt STL	-0.45 -0.41
β = 0	Eaton, Adam ARI	0.00
0 < β < 1	Bautista, Jose TOR Werth, Jayson WAS	0.66 0.75
β = 1
β > 1

Pitcher

Value of Beta	Player	Beta
β < 0	Harvey, Matt NYM   Tillman, Chris BAL   Soriano, Rafael WAS	-1.36 -1.28                                  -0.85
β = 0	Alvarez, Henderson MIA   Chapman, Aroldis CIN	0.00 0.00
0 < β < 1	Scherzer, Max DET   Wilson, C.J. LAA     Rodney, Fernando TB	0.47 0.67 0.55
β = 1	Fernandez, Jose MIA	1.00
β > 1	Lohse, Kyle MIL     Marquis, Jason SD Cishek, Steve MIA	1.48 1.58 2.03

So there you have it. Unfortunately there weren’t any hitters with Betas over 1, but there were pitchers with Betas all over. As we learned about Beta, negative Beta and Beta over one can have similar effects in that they are both more volatile, just moving in different directions. Combining hitters with negative Betas (those who tend to have big swings in the opposite direction as the index) with those Beta is closer to one (those who tend to move closer to the index) can help you create a team of players that both performs consistently while having enough upside to give you those big weeks.

Thanks for reading! Please leave me any comments!