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
|
|
|
||||
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
|
|
|
||||
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
|
|
-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
|
|
|
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.
So aim for zero? Did I get that correctly?
ReplyDeleteAlso your formula showed up blank for me
Zero means very consistent. You can use those type of players to offset players with a negative Beta who are more prone to ups and downs
ReplyDeleteBut over the course of a full roster 0 should field a competitive team?
ReplyDeleteGenerally yeah.
ReplyDeleteActually, I meant closer to one. Those are the ones that move with the index, which is made up of stars.
ReplyDeleteSo to expand, toy want to have a combination of one's and negatives. Since the ones move with the index, and the negatives opposite, they will act to cancel each other out and keep your team consistent
ReplyDelete