►
From YouTube: Governance and Risk Meeting: Ep. 86
Description
# Agenda
## Risk Segment
Vishesh: Overview of Risk Model
Cyrus: Overview of Vaults and Risk Parameters
## General Q&A
We'll open the floor for any questions about Scientific Governance and Risk.
Please join us and help shape the future of the MakerDAO.
## Links
- [Video/Voice](https://zoom.us/j/697074715)
- [Dial-in](https://zoom.us/u/acRbIMDvK)
- [Calendar](https://calendar.google.com/calendar/embed?src=makerdao.com_3efhm2ghipksegl009ktniomdk@group.calendar.google.com&ctz=America/Los_Angeles)
A
Where's
robot
lady
there
she
is
hello.
Everyone
welcome
to
a
special
April
14th
edition
of
the
scientific
governance
and
risk
meeting.
This
one
is
late
on
the
governance
heavy
on
the
risk
we're
going
to
hear
from
Cyrus
and
vishesh
today,
as
they
drop
science
there's
a
significant
huge
amount
of
work.
It's
been
happening
in
the
background
from
the
wrist
team
over
the
course
of
the
last
few
months
and
years
years,
almost
and
today
we're
going
to
start
walking
through
that
stuff
I'm
going
to
fade
into
the
background.
B
A
A
B
So
thanks
everybody
for
joining
governance
call
outside
of
the
regular
circuit
think
we
may
see
more
of
this
type
of
thing
in
the
coming
months,
as
we
start
to
tackle
a
whole
bunch
of
new
initiatives,
so
today,
I
think
we're
just
going
to
quickly
discuss
a
minor
sed
shutdown
topic
and
then
afterwards
we're
gonna
get
back
into
some
risk
discussions.
A
few
weeks
ago,
we
started
some
collateral
risk
presentations.
I
think
we
gave
one
presentation
before
Black
Thursday
happened
and
things
got
a
little
bit
sidetracked.
B
B
B
Essentially,
this
would
set
the
actual
shutdown
to
occur
at
a
specific
time
stamp,
and
this
would
make
it
significantly
easier
for
the
ecosystem
for
the
community
for
integration
partners
to
manage
their
their
you
eyes
and
and
so
forth,
and
help
ensure
a
smoother
wind
down.
I
think
there's
a
maybe
a
quick,
five
minute
discussion
that
should
go
into
this.
A
To
sit
it
over
myself,
you
know.
Basically,
the
idea
is
just
that
whenever
the
executive
goes
out
the
the
code
that
implements
that
will
have
some
like
you
know
this
can't
be
cast
say
you
know
before
May.
First,
whatever
you
know
pick
well,
you
know.
The
idea
here
is
to
pick
that
date,
which
you
know
some
consideration
should
go
into.
Maybe
how
long
the
delay
should
be.
A
A
And
response
to
a
comment
in
the
chat
where
it
says
if
this
part
doesn't
pass
it
one
welcome
the
whole
time
thing
and
make
maker
look
really
bad
from
your
perspective.
We're
referring
to
you
know
if
we
say
the
system
is
going
to
shut
down
at
X
date,
but
then
the
spell
to
actually
shut
it
down
a
next
date
doesn't
pass.
It
looks
a
little
weird
I
think
that
the
answer
that
is
you
just
do
the
messaging
of
say:
okay,
hey
here's
an
executive
spell
to
shut
down.
A
You
know
at
this
date
that's
a
month
and
a
half
in
the
future,
and
then
you
only
announce
the
shutdown
is
happening
if
that
passes
so
I
think
that's
just
a
matter
of
order
of
operations.
Have
it
how
you
announce
stuff,
which
is
another
good
argument
for
having
you
know,
a
fairly
long
play
so
that
after
you,
you
know
once
you've
gotten
condenses
consensus
and
actually
passed
the
vote,
then
you
can
still
announced
it
with
plenty
of
lead
time
for
people
to
prepare.
B
Are
sorry
about
that
guys,
I,
don't
know
where
I
cut
off
but
shush
if
you're,
if
you're
there
do
you
want
to
do
the
screen
share.
B
B
C
B
B
B
All
right
we're
gonna
start
off
by
quickly
reviewing
the
few
slides.
We
did
a
few
weeks
ago,
probably
just
easier
to
start
fresh,
but
first
we
are
going
to
read
a
little
bit
of
a
disclaimer
which
is
likely
to
be
a
becoming
standard
on
these
risk
calls
just
something
the
the
folks
at
the
foundation
would
like
me
to
read:
can
you
jump
to
the
next
slide
all
right,
so
this
communication
is
provided
for
information
purposes.
B
Only
the
views
expressed
here
are
those
of
the
individual
maker
foundation,
maker
personnel
quoted
or
who
present
said
materials
and
are
not
the
views
of
maker
or
its
affiliates.
The
communication
has
been
prepared
based
upon
information,
including
market
prices.
Data
and
other
information
from
sources
believed
to
be
reliable.
The
maker
has
not
independently
verified
such
information
and
makes
no
representations
about
the
enduring
accuracy
of
the
information
or
its
appropriateness
for
a
given
situation.
This
content
is
provided
for
informational
purposes
only.
It
should
not
be
relied
upon
as
legal
business,
investment
or
tax
advice.
B
You
should
consult
your
own
advisers
as
to
those
matters
references
to
any
digital
assets
and
the
use
of
finance
related
terminology
or
for
illustrative
purposes
only
and
do
not
constitute
any
recommendation
for
any
action
or
an
offer
to
provide
investment
advisory
services.
This
content
is
not
directed
at
nor
intended
for
use
by
the
maker
dog
community
and
we
not
under
any
circumstances
being
relied
upon
when
making
a
decision
to
purchase
any
other
digital
asset
referenced
here
in
the
digital
assets.
B
Reference
here
and
currently
face
an
uncertain
regulatory
landscape,
and
not
only
the
United
States,
but
also
in
many
foreign
jurisdictions,
including,
but
not
limited
to
the
UK
European
Union
Singapore,
Korea,
Japan
and
China.
The
legal
and
regulatory
risks
inherent
in
reference.
Digital
assets
are
not
the
subject
of
this
content
for
guidance.
Regarding
the
possibility
of
said
risks,
one
should
consult
with
his
or
own
his
or
her
own,
appropriate
legal
and/or,
regulatory
counsel,
charts
and
graphs
provided
within
our
for
informational
purposes
solely
and
should
not
be
relied
upon.
When
making
any
decision.
B
B
B
B
Our
goal
is
to
create
tooling
that
can
hopefully
integrate
well
with
the
community
and
that
governance
can
basically
help
drive
this
whole
thing
forward
and
we
can
start
adding
new
collateral
types.
We
can
start
working
with
the
MIPS
process
and
we
can
just
start
helping
maker
pro
and
scale
and
all
that
fun
stuff.
Next
slide.
B
Just
a
few
things
that
community
can
expect
from
us
in
terms
of
deliverables,
primarily
a
quantitative
framework
for
evaluating
risk.
This
is
in
conjunction
with
monetary
policy.
It's
not
it's
really
an
extension,
not
a
replacement
of
any
sort.
So
basically
I'm.
You
know
up
till
now
a
lot
of
the
risk
course
the
community
has
been
doing
for
the
past
couple
years
has
been
primarily
focused
on
monetary,
monetary
policy
and
there's
now
going
to
be
a
collateral
risk
portion
as
well.
B
It's
fair
to
say
that
there
are
a
number
of
assumptions
baked
into
any
risk
model,
really
and
makers
no
exception.
So
there
isn't
really
going
to
be
a
magic
8-ball
on
what
policy
should
look
like
and
in
fact
some
decisions.
It's
not
really
even
appropriate
for
the
risk
team
to
to
call
the
shots.
A
lot
of
these
a
lot
of
these
trade-offs
are
don't
have
clear,
clear
answers
and
there
will
need
to
be
a
bit
of
community
input
in
terms
of
direction.
B
D
D
B
D
A
D
So
yeah
I
was
just
saying:
there's
two
portions
to
the
system,
so
the
the
dye
token
and
the
bolts
as
far
as
the
dye
token.
Obviously
the
goal
is
to
maintain
a
target
price
pegged
at
a
dollar
the
risks
associated
with
it.
So
dye
holders
bare
some
degree
of
monetary
policy
risk
as
well
as
some
degree
of
credit
risk,
because
the
revolt
system
is
sort
of
backing
the
functionality
of
the
dye
token,
the
vaults
of
the
audience,
so
they
are
able
to
generate
dye
and
they're
able
to
get
access
to
leverage
using
that.
D
But
in
turn
the
mkr
holders
are
bearing
a
credit
risk
for
these
vaults
and
they
also
govern
this
risk
by
having
control
over
the
ability
to
set
risk
parameters
and
if
a
bolt
is
liquidated,
then
the
system
will
attempt
to
recover
dye
through
a
collateral
auction
or
if
that
doesn't
work,
then
MKR
dilution.
So
we
have
multiple
parties
at
play
here:
they're
all
sort
of
connected
in
the
ecosystem
that
is
make
er
down.
D
So
in
general,
I
think
you
know.
When
managing
the
system,
you
try
to
identify
your
targets
and
goals
and
you
identify
the
problems
that
you
need
to
solve
in
order
to
achieve
those
goals.
So
for
the
dye
token,
you
know,
as
it's
kind
of
been
stated
before,
the
goal
is
to
grow
the
usage
and
the
overall
supply
of
dye,
but
do
it
in
a
sustainable
way
where
it's
scaling
to
demand
and
you're
maintaining
meaningful
transaction
value.
D
So
you
have
to
balance
that
equation
as
well,
which
means
the
most
important
and
biggest
missing
step
in
all
of
this,
at
least
in
terms
of
a
lot
of
the
conversations
that
have
been
had
so
far
about
maker
are
those
risks,
and
so
that's
part
of
the
goal
of
some
of
this
work
is
to
quantify
and
ideally
minimise
the
risks
associated.
So
one
you
have
to
figure
out
what
is
an
appropriate
debt
ceiling?
You
have
to
quantify
MKR
dilution.
D
What's
the
risk
associated
there,
you
saw
a
lot
of
this
with
the
auctions
and
sales
that
occurred
previously,
you
have
to
figure
out
what's
an
appropriate
surplus
buffer
for
the
for
the
surplus
itself
and
then
also
buffer
for
things
like
debt
ceilings,
you
have
to
identify.
You
know
collateral
types,
what's
an
appropriate
collateral
to
add
how
much
risk
is
associated
with
that
collateral
and
what
parameters
you
need
to
set
in
order
to
appropriately
adjust
for
risk
was
obviously
just
considering
macro-level
risks
as
well
in
terms
of
diversifying
your
collateral
asset
portfolio,
etc.
D
So
you
don't
have
just
a
bunch
of
tail
risk
correlated
assets,
for
example,
so
yeah,
where
does
this
risk
specifically
come
from?
So
when
you
talk
about
gains
and
losses
for
MPR
holders,
one
thing
is,
so
these
vaults
are
generating
value
from
care
holders
through
stability
fees
and
the
these
liquidation
penalties,
as
well,
can,
in
an
ideal
system,
serve
to
to
add
to
the
the
surplus
buffer.
D
The
stability
fees
accrue
over
time
and
are
collected
of
hundred
to
die,
so
that's
sort
of
a
time-based
function
and
when
vaults
are
liquidated
at
above,
a
hundred
percent
collateralization
there's
a
liquidation
penalty
that
is
extracted
from
from
that
sale
and
losses
occur
when
vaults
are
liquidated
below
100
percent
collateralization
so
effectively.
If
there's
not
enough
money
to
back
the
debt
and
MKR
at
the
last
resort
is
diluted
to
pay
for
that
difference.
D
So
how
do
you
start
to
think
about
this?
What
does
this
all
mean?
How
do
you
organize
this
information?
Basically
there's
two
sides
of
the
coin:
man,
monetary
policy
and
managing
collateral
risk.
The
vaults
themselves
as
well
pose
a
degree
of
credit
risk,
though
that's
primarily
derived
from
collateral
risk.
What
are
the
questions
that
you
know
this?
This
type
of
work
is
seeking
to
answer.
Well,
one.
You
want
to
try
to
identify
an
appropriate
civility
fee,
given
a
set
of
parameters.
D
You
want
to
try
to
identify
sustainable
debt
ceilings,
and
you
want
to
set
the
parameters
such
that
you
know
it's
conducive
to
the
growth
of
the
system
as
well.
So
in
general,
how
do
you
go
about
doing
this
work
and
starting
to
answer
these
questions?
Well,
one!
You
can
simulate
what
how
you
expect
these
liquidations
to
occur
and
how
you
expect
them
to
occur.
So
you
know,
is
in
a
stressed
time
period
would
the
whole
collateral
asset
portfolio
get
liquidated
at
one
hundred
and
forty
percent,
one
hundred
thirty
percent
one
hundred
twenty
percent.
D
Ninety
percent
forty
percent:
these
are
the
kinds
of
questions
that
you
can
start
to:
try
to
model
an
answer,
and
basically
that
is
the
prime
step
in
in
identifying
gains
or
losses
for
mkr
holders
in
terms
of
the
value
that's
recovered
from
vault
collaterals,
post
liquidation,
and
then
you
also
want
to
produce
basically
a
distribution
of
these
gains
or
losses
over
time.
And
then
you
use
that
distribution
to
identify.
Basically,
your
worst
tale
cases
and
sort
of
your
average
cases
and
then
basically
there's
a
bunch
of
traditional
finance
methodology
that
goes
into
identifying.
D
What
do
you
do
with
that
information
once
you
have
it?
When
you
know,
okay,
you
roughly
expect
to
lose
X
amount
on
average
and
in
your
worst
cases
you
probably
expect
to
lose.
You
know
Y
amount
in
total
sum
and
those
basically
help
identify
your
degree
of
exposure
and
then
the
goal
is
to
appropriately
set
parameters
to
adjust
for
that
degree
of
exposure.
D
The
driver
that
sort
of
causes
these
fluctuations
in
collateralization
ratios
over
time
is
primarily
asset
price.
So,
in
simple
terms
with
eath
is
collateral
when
eath
goes
up
and
down,
collateralization
ratios
go
up
and
down,
and
that
leads
to
liquidations
there's
a
lot
more
nuances
to
it
than
that,
but
that's
the
basic
idea
so
just
running
through
a
couple
specific
examples
of
where
these
kinds
of
losses
and
gains
can
come
from.
D
D
So
this
is
a
case
where
this
generates
gains
now
consider
a
case
where
same
thing
happens,
similar
vault,
setup,
I
need
to
make
sure
I,
don't
say
CDP
and
that
vault
is
initially
safe.
Instantaneously
drops
to
$60
eath
price,
which
means
now
it's
below
150%,
but
it's
also
under
collateralized.
So
when
the
entire
1e
is
sold,
even
in
the
best
case
scenario,
which
assumes
no
slippage,
you
would
only
obtain
60
die,
which
means
there's
no
liquidation.
D
Penalties
to
be
collected
for
the
system
and
MKR
holders
actually
have
to
be
diluted
to
make
up
if
there's
no
buffer
to
cover
it
and
care
holders
have
to
be
diluted
to
make
up
for
the
shortfall.
So
this
is
a
case
where
you
generate
losses
from
purely
dipping
below
into
that
red
area.
Now
consider
a
third
case,
which
is
a
bit
more
of
a
gray
area,
so
same
set
up
price
drops
by
50%
overnight.
D
It
goes
into
this
where,
when
you
sell
$1
worth
of
eath,
how
many
dollars
do
you
actually
recover
in
dye?
And
that
is
not
necessarily
a
one-to-one
like
I
said,
there's
a
lot
of
factors
that
go
into
where
additional
losses
can
come
from.
So
in
this
particular
example,
you
sold
$100
worth
of
ease,
but
due
to
inefficient
auctions
or
due
to
price
movements
during
auction,
you
only
obtained
80
died.
In
this
case,
you
don't
have
enough
dye
to
cover
the
debt
and
you
obviously
don't
have
enough
to
generate
any
liquidation
penalties.
D
So
in
reality
the
MKR
holders
have
to
make
up
the
shortfall.
So
this
is
a
case
where
you
would
have
been
in
the
green
area,
but
due
to
reality
and
market
conditions
you
dip
into
the
red
area.
So
as
an
example
of
where
I'd
say,
there's
nuances
to
this
stuff,
so
yeah
like
I,
said:
asset
price
is
the
prime
independent
variable
that's
driving
this
so
as
each
price
fluctuates,
what
you're
going
to
see
is
fluctuations
in
collateralization
ratios.
D
These
collateralization
ratios
also
fluctuated
over
time,
not
quite
one
to
one
like
I,
said:
there's
nuances
associated
with
this
I'll
touch
on,
but
they
fluctuate
and
when
that
eath
price
drops
significantly
some
of
them
dip
below
into
the
under
collateralized
category,
and
this
would
generate
liquidations.
So
there
you
precisely
see
a
spike
in
liquidations
at
that
particular
drop.
D
Now,
obviously,
this
is
a
sample
eath
price.
This
is
not
the
actual
lease
price
history
in
case
somebody
in
the
back
of
their
head
was
thinking.
Eath
is
not
worth
$20
so
to
to
just
touch
on
how
this
translates
into
gains
and
losses,
then
so,
like
I
said
these
particular,
if
you
consider
these
particularly
liquidations,
some
of
these
are
below
that
100
mark.
So
some
of
these
are
generating
very
real
losses
for
MKR
holders.
D
Some
of
these
are
liquidated
above
and
are
not
generating
losses
and
potentially
liquidation
penalties,
and
so
essentially,
the
net
value
during
that
liquidation
event
would,
in
this
case,
have
been
pretty
significant
losses.
So
this
is
generally
the
the
process
that
we're
looking
at,
where
you
start
with
the
asset
price
back
your
way
into
the
collateralization
ratios
use
those
collateralization
ratios
to
determine
the
amount
of
debt,
that's
liquidated
and
then
based
on
the
amount
of
that
that's
liquidated
at
the
particular
collateralization
ratios.
D
It's
a
trivial
calculation
to
say
what
are
roughly
the
gains
or
losses
from
that
liquidation
event.
The
general
approach
that
we're
taking
here
is
a
Monte
Carlo
simulation.
There
is
not
a
huge
long.
You
know
ten-year
robust
price
history
for
eath,
as
there
are
for
some
traditional
assets,
so
you
have
to
take
different
approaches
when
stress
testing.
Crypto
lends
itself
well
to
Monte
Carlo
simulations,
particularly
because
these
are
complex
systems,
there's
a
lot
of
nuances
to
them,
and
also
because
there's
not
strong,
robust
histories
to
just
do
simple
historical
analysis
on.
D
So
you
use
those
lines.
You
determine
a
distribution
over
a
number
of
different
simulations.
This
particular
graph
shows
just
a
hundred.
You
figure
out
your
average
percentage
losses
for
each
of
those
simulations.
Look
at
the
distribution
of
them
slice
it
up
differently
and
you
learn
different
things
from
say:
the
mean
versus
the
tail
etc.
But
this
is
the
main
unit
of
data
that
you're
using
to
get
your
learnings
off
oh
yeah,
and
then
you
can
start
to
talk
about
how
to
analyze
that
distribution.
D
B
All
right
so
yeah
that
that
last
slide
or
also
the
chart
here
is
a
picture
of
a
hypothetical
probability
distribution
of
losses.
It
simply
says
how
likely
a
particular
losses.
Generally
speaking,
the
majority
of
losses
are
small,
and
then
you
have
some
extreme.
You
have
some
extreme
losses
at
the
end,
the
shaded
region,
which
are
large
losses
that
are
very
infrequent
people,
tend
to
call
these
tail
losses
and
and
so
forth.
B
You
can
do
a
couple
cool
things
with
it
with
a
distribution
like
this
are
a
few
basic
metrics,
the
most
simplest
one
is
just
nearly
the
average
or
the
mean
of
this
distribution,
which
is
called
the
expected
loss.
This
one,
the
expected
loss,
is
important
because
well
it's
a
it's.
What
your
so
it's
your
expected
to
lose
and
see.
You
have
to
be
sure
that
you
can.
You
can
cover
these.
B
These
are
losses
that
are,
by
definition,
not
a
surprise
to
anybody
and
keep
in
mind
that
these
losses
are
after
the
collateral
has
been
taken
into
account.
So
these
losses
represent
what
would
either
have
to
come
out
of
the
die
surplus,
buffer
or
mkr
dilution.
B
So,
as
I
said,
the
average
of
this
distribution
is
what
you
almost
assuredly
should
be
prepared
for
and
then,
given
that
there's
a
lot
of
randomness
and
uncertainty
in
various
risk
factors
such
as
asset
price
or
liquidations
I-
you,
you
know,
you
might
have
larger
losses
than
you
might
expect.
These
are
just
quite
simply
called
unexpected
losses,
and
the
upper
limit
of
these
unexpected
losses
is
basically
the
entire
die
supply
right.
B
If
every
single
collateral
type
simultaneously
goes
to
0,
then
maker
has
a
shortfall
of
what
the
entire
die
supply
is,
and
it's
not
really
feasible
to
have
the
entire
outstanding
dye
supply
in
your
buffer
either
in
the
dye
surplus
or
in
the
expected
MKR
issuance
or
delusion.
So
kind
of
a
rule
of
thumb
is
to
just
pick
a
pick.
B
Some
cutoff
point
where
you
say
we
can
handle
losses
up
to
this
amount,
but
anything
beyond
well
that
that
could
be
quite
disastrous
right
and
so
there's
kind
of
like
a
fairly
standard
heuristic
for
what
this
threshold
should
be.
It's
called
the
Value
at
Risk
Value
at
Risk
metric
I'm.
Essentially,
you
choose
a
probability
with
which
you're
you're,
okay
you're,
okay,
with
the
likelihood
of
suffering
losses
greater
than
this
amount.
B
The
percentage
or
the
confidence
interval
is
chosen,
such
that
it's
just
extremely
extremely
unlikely
that
you
would
suffer
a
loss
greater
than
that
and
then
the
goal
would
be
to
make
sure
that
loss
is
less
than
that
can
be
absorbed
either
by
the
die
surplus
buffer
or
the
M
care
dilution.
So
the
goal
is
so
just
to
recap:
you
run
a
simulation.
B
You
create
a
hypothetical
distribution
of
what
your
losses
might
look
like
you
pick
a
threshold
beyond
which
losses
are
extremely
unlikely,
and
then
you
you
ensure
that
you
can
absorb
losses
up
to
that
point.
So
then,
the
governance
decisions
become
well.
What,
if
the
number
that
you've
chosen
is
still
greater
than
your
greater
than
your
buffer?
So,
let's,
let's
explore
that
concept?
Perfect
next
slide!
Okay,.
B
B
So
to
pick
apart,
these
two
individually,
the
surplus
die
buffer
is
first
netted
against
is
the
first
kind
of
line
of
defense
that
is
netted
against
protocol
losses.
We
saw
this
on
Black
Thursday.
The
die
surplus
was
drained
prior
to
dime
care
dilution.
Beginning
dye
surplus
is
likely
to
be
the
preferable
form
because
it's
the
it's
literally
the
the
precise
unit
of
account
that
you
need
to
offset
protocol
liabilities
or
protocol
losses
right.
There's,
a
shortfall
of
a
hundred
thousand
die
and
the
protocol
has
a
hundred
thousand
die
in
hand.
Then
Matt.
B
So
if
you
think
about
it,
you
could
wait
for
the
market
to
crash
the
protocol
sustains
a
bunch
of
losses,
and
then
at
that
moment
the
protocol
would
need
to
mint
MKR
and
sell
for
dyeing
or
governance
in
the
community
could
preemptively
do
that
process
either
by
just
collecting
stability
fees
and
just
putting
in
a
surplus
buffer
which
is
okay.
So
that's
not
technically
preprinting.
That's
just
abstaining
from
the
burning
event
here,
but
I
think
in
theory,
governments
could
actually
preemptively
mint
MKR
to
raise
dye
for
the
surplus
puzzle.
B
There's
some
good
heuristics
for
that
as
well.
This
kind
of
gets
heavy
into
some
corporate
finance
theory
like
what
is
the
cost
of
the
trade-off
between
minting
MKR
for
dye
at
the
current
price
of
300
or
or
not
just
some
fairly
I'm
gonna
take
fairly
standard,
but
definitely
if
any
corporate
finance
experts
out
there.
This
is
super
interesting
conversation
to
have,
although
probably
outside,
of
the
scope
for
this,
for
today's
call
there's
also
a
another
few
considerations
so
well,
one
is
that
one
is
an
investor.
B
This
is
precisely
one
of
those
that
I
was
referring
to
it's
not
really
risks
job
to
say
how
much
dyes
should
go
in
the
surplus
versus
how
much
should
go
to
the
surplus
auction,
although
we
can
help
quantify
the
sum
of
these
two,
the
sum
of
these
two
sources
of
so
that
at
least
the
from
the
risk
management
side.
It's
it's
it's
handled
well
and
then.
Secondly,
there's
like
potentially
some
game
theoretic
issues
with
having
large
died
reserves.
B
Governance
needs
to
think
carefully
about
how
how
a
large
died
buffer
could
be
exploited
or
taken
advantage
of
somehow,
for
example,
an
emergency
shutdown.
What
would
happen
to
the
surplus
buffer?
How
would
I
get
distributed
who's
kind
of
the
rightful?
Who
does
that
I
rightfully
belong
to
what?
If
the
I
think
the
specific
issue
could
be?
B
Something
like,
let's
say,
there's
a
catastrophic
loss
and
now
die
is
trading
at
a
at
a
hair
at
a
discount
and
then
potentially
there's
some
scenarios
where
the
die
in
the
surplus
buffer
would
not
necessarily
go
to
recapitalizing
the
system.
So
yeah
there's
some
kind
of
edge
cases
that
that
governance
should
work
through
before
just
dramatically
increasing
the
surplus
buffer.
B
Secondly,
there's
M
care
issuance
right.
We
experienced
this
a
few
weeks
ago
in
the
wake
of
Black
Thursday
right-
and
this
is
this
is
probably
quite
it's
quite
risky
to
at
least
depend
on
this
preemptively,
because
you
know,
even
when
the
m
care
prices
say
$300,
which
represents
a
market
cap
of
roughly
300
million
I.
Think
everybody
is
well
aware
that
you
cannot
actually
mint.
Three
hundred
million
died
out
of
this
MKR
right
because
they're,
just
a
liquidity,
isn't
there
for
that.
B
So
what
is
the
true
amount
of
dye
that
could
be
raised
in
a
MKR
auction
like
what
is
the
absolute
maximum
amount?
And
actually
the
first
thing
I
want
to
say
is
that
there
is
some
maximum
amount
and
there
is
a
hard
limit
to
dilution,
a
lot
of
people,
not
a
lot
of
people,
but
from
time
to
time.
I
hear
this.
This
idea
that
Emma
card
dilution
is
almost
like
an
infinite
money
bag
or
you
could
just
every
time
you
have
an
issue.
B
You
can
just
dip
your
hand
into
this
bag
and
and
reach
out
and
create
some
dye,
and
it
doesn't.
It
doesn't
actually
work
like
that,
so
we
need
to
come
up
with
a
methodology
to
quantify
how
much,
how
much
dye
we
expect
to
raise
from
MKR,
and
that
number
is
important,
because
if
we
miss
estimate
that
number-
and
we
do
suffer
a
large
well
and
we
do
suffer
a
loss
larger
than
that
dilution
capacity,
then
maker
would
I
think
effectively
just
be
insolvent
right
and
we'll
we'll
discuss
one
methodology
that
we
devised.
I.
B
Think
on
tomorrow's
call,
honestly,
though
this
is,
this
is
going
to
be
like
one
of
the
few
subjective
components,
because
there's
a
number
of
different
ways
to
estimate
what
this,
how
much
dye
can
be
raised
and
I'm
care
issuance
event
and
that
variance
and
that
uncertainty
is
kind
of
what
throws
the
the
favor
towards
the
surplused.
Ibuffer
is
just
being
much
cleaner
and
easier.
B
Are
there
any
comments
in
the
sidebar
that
actually
I
think
at
this
point
we
should
address
the
comments
slide
by
slide,
because
so
Akiva
asks
talk
about
how
a
higher
surplus
buffer
will
attract
more
dye
buyers
from
hedge
funds,
right
so
I
mean
die.
Is
this
surplus
dye
is
definitely
a
more
robust
form
of
protection?
It
doesn't
rely
on
investors
coming
to
the
table
in
a
crisis.
B
We're
very
I
mean
the
community
should
feel
very
grateful
and
thankful
that
that
did
happen
with
quite
with
almost
no
hesitation
in
the
wake
of
Black
Thursday,
but
that
may
or
may
not
be
a
luxury
that
is
always
is
always
there,
and
so,
if,
in
terms
of
dye
adoption
from
large
institutional
buyers
conceivably,
they
would
want
to
see
large
dye
surplus
surplus
buffer.
Oh
yeah
I
forgot
to
mention
one
other
game.
B
Theoretic
issue
that
I
was
considering
is
that
I
think
it'd
be
kind
of
weird
to
have
like
a
significant
portion
of
the
dye
supply
sitting
inside
the
the
surplus
buffer.
So
imagine
if
there
was
a
hundred
million
die,
but
in
a
hundred
million
die
outstanding,
but
thirty
million
of
them
were
in
the
end
of
surplus
buffer,
I,
think
that
could
kind
of
create
some
weird,
some
weird
edge
cases
and
potentially
impact
growth
as
well.
So
one
kind
of
third
idea-
that's
not
listed
on
this
slide-
is
some
sort
of
on
chain
reserve.
C
Not
gonna
take
too
long
either
so
I
advocated
for
a
surplus
buffer,
at
least
two
to
three
percent
on
some
time
ago.
So
a
lot
of
these
points
are
pretty
good.
The
whole
point
of
having
that
surplus
buffer
is
then
it
doesn't
remove
liquidity
from
the
market,
so
it
kind
of
has
a
negative,
but
when
times
are
good,
you
kind
of
want
to
do
that
when
times
are
bad
and
you
have
this
kind
of
large-ish
buffer,
we
can
debate
what
largest
30
million
out
of
sixty
million
fifty
percent-
that's
pretty
large
too
much.
C
But
if
you
have
something
like
ten
percent,
then
basically,
what
you
can
do
is
during
the
bad
time
you
can
actually
go
and
buy
maker
at
a
depress
price
and
release
dye
into
the
market,
and
so
it's
kind
of
a
clean
mechanism
actually
for
our
cleaner
mechanism
actually
for
liquidity,
removal
and
supply
and
so
having
that
surplus
buffer
and
having
that
mechanism
to
do
lots
of
things
with
it.
I
think
is
a
good
idea
really
and
something
to
be
think
about
the
level
of
it.
That's
a
whole
different.
C
B
So
I
think
I
I
think
that
the
key
theme
here
is
this
is
where
skin
in
the
game.
Governance
is
most
critical
apparent
right.
This
is
where
prudent
risk
management
needs
to
take
center
stage,
and
people
have
to
realize
that
if
things
go
south,
they
want
to
be
adequately
prepared,
and
this
is
probably
going
to
be
the
subject
of
many
conversations
kind
of
this,
this
the
quantity
of
the
dye
surplus
buffer,
a
starting
point
could
just
be
based
off
the
off
the
lost
distribution,
but
there's
really
a
number
of
directions
to
go
with
this.
A
C
There's
another
bonus
here:
I
mean
I,
don't
hate
using
dye.
I
think
is
good
because
of
the
liquidity
thing,
but
there's
an
idea
of
having
like
assets
in
our
our
surplus
buffer.
To
that
we
can
manage
as
well,
and
so
you
know,
the
other
thing
is
that
companies
are
valued
on
multiple
things
assets.
You
know
revenue
streams,
the
growth
thereof
or
not.
You
know
how
much
debt
they
have
and
the
idea
that
you
know
we
have
to
burn
maker
to
actually
give
it
value.
That's
all
wrong.
That's
totally
wrong!
Thinking.
C
B
B
B
The
way
to
think
about
the
liquidation
ratio
is
that,
if
you're
requiring
more
collateral
upfront,
then
your
losses
will
be
we'll
be
lower,
and
so
therefore,
if
you're,
in
a
situation
where
your
your
value
at
risk
is
larger
than
your
than
your
total
buffer,
then
you
kind
of
have
two
options:
one
is
you
can
either
just
lower
your
risk
altogether
by
just
lowering
the
debt
ceilings
and
and
the
dye
supply,
or
you
can
increase
the
collateral
requirement,
and
so
this
is
maybe
like.
This
is
one
reason
why
such
a
high
I
mean
I.
B
Think
a
relatively
high
collateral
was
a
liquidation
ratio
for
eath
has
been
in
in
production
from
the
beginning.
I
don't
know
if
this
was
the
original
reasoning,
but
if
you
think
about
it,
the
the
over
collateralization
buffer
provides
significantly
such
a
large
buffer
that
the
protocol
losses
are
well
as
if
a
few
weeks
ago
were
or
non-existent
right.
B
So
essentially,
liquidation
ratio
can
be
used
as
a
as
a
risk
management
tool
to
balance
the
to
balance
your
losses
versus
how
much
how
much
buffer
you
have
in
your
in
your
protocol.
A
couple
of
interesting
notes,
one
is
that
a
lot
of
people
tend
to
think
that
the
liquidation
ratios
are
fixed,
which
they
have
been
up
until
now,
but
there
are
some
weird
edge
cases
where
collateralization,
where
liquidation
ratios
might
have
to
be
changed
in
an
emergency
situation.
Of
course,
this
is
not
a
popular.
B
This
is
not
a
popular
decision
by
any
by
any
metric,
but
I
think
we
need
to
start
making
clear
that
this
is
technically
a
possibility
and
there's
actually
there's
actually
some
precedent
for
things
like
this.
B
B
If
you
end
up
in
a
situation
where
your
risk
is
too
high,
then
again
you
have
like
a
few
different.
You
have
a
few
different
policy
tools.
You
can
either
increase
your
buffer
somehow
or
you
can
increase
the
liquidation
ratio
or
you
would
have
to
essentially
just
curtail
the
dye
supply
so
to
lower
your
exposure
risk.
So
there's
there's
like
a
few
trade
offs
here
that
that
governance
should
be
aware
of.
B
B
But
then
the
balance
of
the
the
balance
of
the
stability
fee
is
what's
typically
called
the
risk
premium,
and
this
risk
premium
can
be
kind
of
subdivided
or
broken
down
in
a
few
different
ways.
This
is
just
kind
of
for
ease
of
understanding.
This
breakdown
is
it
strictly
important,
but
one
way
to
think
about
it
is
to
divide
the
risk
premium
itself
into
two
components.
One
is
compensation
for
your
average
expected
losses.
This
basically
says
if
you
already
know
you're
going
to
lose
this
amount
of
die
from
a
certain
collateral
type.
B
You
may
as
well
bake
in
a
stability
feed
that
will
just
cover
that
one
to
one
and
then.
Secondly,
you
likely
or
governance
would
likely
want
to
add
an
additional
component
to
cover
both
the
the
die
surplus
buffer
and,
however
much
when
I
say
the
die.
Servos
I
mean
the
opportunity
cost
or
the
die
surplus
buffer
and
any
additional
stability
fee
that
would
want
to
go
to
the
and
care
surplus
auction.
B
Cool
yep
and
then
tomorrow
and
then
it's
a
preview,
tomorrow's
call
we're
gonna,
actually
discuss
all
of
the
model
inputs
that
go
into
creating
those
those
charts
and
graphs
that
Bish's
showed
in
his
presentation.
We'll
talk
about
some
of
the
methodologies
behind
calculating
some
of
the
risk
factors
and
so
on,
with
the
ultimate
goal
being
to
create
that
loss,
distribution
and
from
that
loss
distribution.
We
can
use
a
few
heuristics
to
calculate
our
desired
risk
parameters.
B
Once
we
do
that
over
the
coming
weeks,
we
can
start
I,
think
that'll,
be
it
and
then
I
think
on
Thursday.
It's
call
there
will
be
a
demo
of
this
process
applied
directly
to
beef,
for
example,
and
then,
in
the
coming
weeks,
we
can
kind
of
start
messing
around
with
the
with
the
model
and
start
applying
it
to
other
collateral
types
that
we
might
be
interested
in.
B
There'll
be
some
documentation
coming
out
next
week.
The
shuttle
I
think
also
be
releasing
the
code
along
with
some
technical
documentation
next
week,
as
well,
so
yeah
I
think
over
the
next
few
weeks
it's
a
little
bit
of
a
governance
work.
We
should
be
able.
We
should
be
in
a
good
position
to
start
them
start
adding
new
collateral
types.
A
B
You
depends
what
you
mean
by
technical
risk,
so
if
we're
so
technical
risk
at
the
collateral
level,
we
do
I
mean
we
do
our
best
to
factor
in
a
premium
for
say
if
the
token
has
very
poor
solidity
code
or
under
the
underlying
protocol
is,
is
unsound
or
maybe
you
have
like
a
really
awesome,
incompetent
team,
but
the
platform
is
like
30,000
lines
of
solidity
code
right
you
can,
or
we
do,
attempt
to
bacon
premiums
for
these
kinds
of
things.
I.
B
B
A
B
So
here's
yeah,
actually
here's
one
interesting
thought
for
the
surplus
buffer
is
that
if
it
gets
set
significantly
higher
right,
it's
not
actually
gonna
get
filled
for
a
while
and
that's
kind
of
a
yeah.
It's
kind
of
well
that's
kind
of
one
of
the
tricky
things
there
and
so
there's
a
few
options
for
that.
One
is
to
preprint
mkr
to
fill
the
surplus
buffer,
although
that's
something
that
would
I
think
definitely
require
a
significant
amount
of
technical
work
and
I'm,
not
even
again,
I'm,
not
even
sure,
if
that's
even
desirable
or
not
by
the
community.
B
A
Yeah
I
think
at
this
stage,
I'm
gonna
I,
guess:
let's
consider
how
it's
actually
gonna
get
filled
up
in
the
short
term
and
more
just
like
I
feel
like
we
should
have
a
good
target
for
her
and
and
just
maybe
I,
don't
know.
If
there's
any
like
a
good
way
for
us
to
like
speed
up
filling
it
don't
need
to
think
about
it.
Some
more
I.
C
I'll
just
can
say
one
thing
about
you
know:
selling
maker
to
buy
die,
you're
already,
gonna,
put
pressure
on
a
market,
that's
ill
liquid
and
die
it's
kind
of
not
a
great
option
right
now
that
I'm
with
long,
we
should
just
set
a
number
that
will
we
want
to
get
to
the
idea
of
like
hitting
the
market.
What's
a
few
million
more
first,
the
die
on
maker.
Just
doesn't
sound
appealing
for
lots
of
reasons
right
now,.
B
C
B
Yeah,
okay,
so
does
anybody
have
any
input
or
comments
on
either
on
value
at
risk
methodology?
Because
that's
that's
kind
of
that's
kind
of
an
interesting
one
over
the
past
couple
decades
of
financial
risk
management
right,
there's
kind
of
like
a
standard
way
to
do
risk,
and
then
a
lot
of
people
tend
to
say
that
we.
C
C
Listen
to
me
while
I
think
out
loud
and
so
I
think
this
was
a
really
good
thread
to
actually
just
have
start
up
a
discussion,
because
we
can
talk
in
there
about
the
surplus
buffer
and,
and
so
it
will
just
be
nice
if
the
risk
team
actually
started
a
thread
on
this
and
we
all
could
kind
of
chime
in
you
know.
Certainly
we
have
another
meeting
tomorrow.
B
C
Well,
I
was
gonna,
say,
don't
we
have
to
have
that
go
with
the
cadence
on
or
whatever
we're
gonna
do.
With
the
system
changes
you
know,
liquidation
all
the
numbers,
debt
ceilings
SS
all
that
jazz
I
mean
we
need
something.
It
doesn't
have
to
be
an
hour,
though
you
present,
you
know
the
dai
peg
and
I'd
literally
want
a
liquidation
report,
but
most
of
the
time
that's
gonna
be
like
not
much
happened.
I
think
it's
a
good
idea.
A
B
A
B
A
E
Guess
one
piece
of
wish
list
for
for
the
guidelines
for
new
collaterals
is
that
I'm
working
on
this
accounts,
receivables
and
the
problem
I
have
is
the
poor
availability
of
data
sets
when
it
comes
to
default,
risk
and
volatility.
So
from
this
perspective,
my
my
expectations
would
be
that
the
the
guidelines
and
the
various
models
considered
that
quite
a
few
collaterals
that
that
are
very
good
candidates
for
helping
balance
the
system
and
make
the
and
reduce
the
the
overall
correlation
between
prices
of
assets
is
that
some
of
these
collaterals
have
very
poor.
E
Data
sets
and
markets
that
are
proprietary
and
so
on
so
have
having
these
guidelines
and
risk
models
applicable
in
those
situation
is
would
be
my
like
success
criteria.
How
and
maybe
some
growth
hacks
around
solving
these
problems,
because
that's
what
I
think
the
issues
would
one
approach
that
is
recommended
is
that
it
not
gonna
be
applicable
in
winning
cases.
So
how
can
I
deal
with
that?
C
E
C
Know
I
was
just
saying
that
I'm
glad
you
brought
that
up
because
I
had
this
issue
of
like
what
data
do,
I,
throw
into
my
liquidation
analysis
and
there's
issues
with
getting
the
state
and
like
most
of
the
places
I
was
looking
for
buying
feeds
from
or
whatever
just
data
sets.
You
can't
distribute
them
to
other
people.
There's
like
restrictions
on
like
what
you
can
do
with
them.
So
the
question
is:
how
do
we
as
a
community
deal
with
the
data
sets
that
are
related
to
the
collateral
types
that
we're
dealing
with?
B
Right
so
to
answer
Ranaut's
question:
yeah
I
mean
when
the
risk
team
set
out
on
creating
a
risk
tool
for
maker.
We
definitely
targeted
collateral
types
that
are
public
and
liquid
and
have
market
prices
and
have
a
little.
You
know
they're
a
little
bit
more
tractable.
B
This
is
partly
why
this
is
mainly
why
things
like
the
MIPS
process
were
created
so
that
we
can
create
an
avenue
for
people
with
high
quality
collateral
that
may
not
be
able
to
be
simply
evaluated
by
an
existing
risk
team
would
create
a
structure
that
somebody
else
could
come
in
and
pick
up.
The
work
there
and
submit
to
governance
I
mean
all
I
can
say
is
it's
like
it
has
to
be
a
case-by-case
basis,
at
least
in
the
early
days
right.
E
E
An
understood
that
that
all
makes
sense,
it's
just
I've,
been
thinking
what
what
could
be
the
the
solution
to
this,
and
so
far
I
arrived
to
just
one
interesting
workaround,
which
is
the
debt
ceiling
in
many
of
these
cases.
Right
they
go
to
market.
There
are
some
collaterals
that
already
have
a
strong
origination
capabilities
right
and
then
there
are
types
of
collaterals
that
are
new
in
the
market
right
and
they're,
just
bootstrapping
their
demand
side
and
so
in
in
both
of
these
cases,
but
more
so
with
the
second
type.
E
They
not
necessarily,
they
don't
necessarily
care
about
about
how
big
the
amount
of
liquidity
they
can
access
right.
But
the
fact
that
it's
there
and
they're
bootstrapping
their
entire
demand
side
is
is
so
much
more
important.
So
what
leads
me
to
conclusion
is
that
imagine
we
have
a
sandbox
full
collaterals
right,
where
the
collaterals
can
have
much
less
strict
requirements
for
various
of
maturity
of
their
pieces,
not
necessarily
the
technical
pieces
right,
but
like
risk
models
and
studies
and
so
on.