Toomas Laarits NYU Stern Eesti Pank, Avatud Seminar 6/2/2020.

1. Precautionary Savings and the
Stock-Bond Covariance
Toomas Laarits
NYU Stern
Eesti Pank, Avatud Seminar 6/2/2020.

2. Stock-Bond Covariance
−8
−6
−4
−2
0
2
1990/1 2000/1 2010/1 2020/1
Cov(Tr 10y, St.) Cov(TIPS 10y, St.)=⇒ Correlations
=⇒ Long History 1 / 28

3. International Evidence
−2
−1
0
1
2
3
1990m1 1995m1 2000m1 2005m1 2010m1 2015m1
USA Cov JPN Cov GBR Cov
ESP Cov DEU Cov
2 / 28

4. Stock-Bond Covariance
What accounts for the high-frequency time variation in the risk exposure of a long
safe bond?
Inflation dynamics? For instance, Campbell, Sunderam and Viceira (2017). But note
calculation with TIPS.
Here: a shock to the price of risk affects stock and bond returns in
opposite directions.
Therefore, times when price of risk is volatile see a more negative
stock-bond covariance.
3 / 28

5. Mechanism: Precautionary Savings and Risk Premium
Consider asset pricing models where log SDF can be represented by
mt,t+1 = −at − γtσ t+1.
The log risk-free rate is
rf
t,t+1 = at −
1
2
γ2
t σ2
.
Risk premium on a payout that depends on σd t+1 is
RPt,t+1 = γtσ σd.
Change in γt moves risky and safe asset prices in opposite directions.
4 / 28

6. Model Intuition
Two state variables: 1) aggregate dividend growth rate 2) price of risk process.
Price of risk follows a CIR process, meaning its volatility is proportional to the square
root of the level.
The share of return volatility stemming from the two distinct sources
varies over time.
Both the aggregate stock market and long Treasury have constant risk loadings in the
model.
Yet their covariance changes with the price of risk process.
5 / 28

7. Empirics Overview
In the recent data, the stock-bond covariance:
1. Has a level effect on the term structure of safe rates.
2. Accounts for the contemporaneous level of credit spreads.
3. Predicts with a negative sign excess stock and bond returns going forward.
4. Is low when risk-neutral probability of FTQ in Treasuries is high.
5. Predicts issuance of investment grade corporate bonds; accounts for sectoral holdings
of Treasuries.
6. Co-moves with covariance calculated in other developed economies.
6 / 28

8. Calibration Overview
Data generated according to the model solution:
1. Matches the empirical moments of stock-bond covariance and bond beta—assuming
an SDF that can match the aggregate equity risk premium.
2. Exhibits a two factor term structure with level and slope factor reflecting empirical
counterparts.
Risk compensation determines level of interest rates while dividend growth rate
determines the slope of interest rates.
Just like in the data, negative stock-bond covariance times see lower interest rates.
7 / 28

9. Roadmap
Introduction
1. Empirical Facts
Rates, Spreads
Return Predictability
Issuance, Holdings
Treasury Risk-Neutral Distribution
2. Term Structure Model
Setup and Solution
3. Model Simulation
Stock-Bond Covariance
Term Structure of Safe Rates
Literature

10. Treasury Yields
D.yield 1y D.yield 3y D.yield 5y D.yield 10y D.yield 30y
D.Cov(Tr 10y, St.) 0.0533∗∗∗
0.0557∗∗
0.0543∗∗
0.0546∗∗
0.0793∗∗∗
(3.80) (2.85) (2.58) (2.59) (4.70)
D.VIX -0.00683∗∗
-0.0128∗∗∗
-0.0117∗∗∗
-0.00729∗
-0.0114∗∗∗
(-2.86) (-3.97) (-3.38) (-2.07) (-4.03)
Constant -0.0110 -0.0127 -0.0133 -0.0137 -0.0129
(-0.54) (-0.80) (-0.95) (-1.12) (-1.24)
Observations 264 264 264 264 264
R2
0.069 0.087 0.070 0.044 0.137
Monthly data 1997-2018.
=⇒ Forward Curve
8 / 28

11. Corporate Spreads
D.Aaa-Tr D.Baa-Aaa D.HY-Tr D.HY-Aaa D.GZ Spread
D.Cov(Tr 10y, St.) -0.0788∗∗∗
-0.0723∗∗∗
-0.483∗∗∗
-0.404∗∗∗
-0.150∗∗∗
(-4.88) (-4.12) (-11.22) (-10.49) (-7.08)
D.VIX 0.0134∗∗∗
-0.00135 0.0360∗∗∗
0.0226∗∗∗
0.0367∗∗∗
(5.12) (-0.45) (4.68) (3.30) (8.78)
Constant 0.000857 0.00236 0.00334 0.00248 0.00596
(0.08) (0.20) (0.07) (0.07) (0.25)
Observations 264 264 264 264 165
R2
0.174 0.062 0.334 0.295 0.440
Monthly data 1997-2018.
=⇒ Graph
9 / 28

12. Corporate Bond Returns
Aaa-Tr. 12m R Baa-Tr. 12m R HY-Tr. 12m R
Cov(Tr 10y, St.) -1.462∗∗∗
-1.029∗
-6.388∗∗∗
(-3.87) (-2.54) (-3.54)
Constant -0.861 -0.667 -3.721
(-1.63) (-1.16) (-1.45)
Observations 263 263 263
R2
0.180 0.091 0.168
Monthly data 1997-2018.
=⇒ Treasury Returns
=⇒ Equity Returns
10 / 28

13. Issuance of Safe Corporates
D.IG share D.A-rated share D.IG mat D.IG Fin/GDP
D.Cov(Tr 10y, St.) -0.0286∗
-0.0348∗
-0.0272 -0.216∗
(-2.13) (-2.29) (-0.07) (-1.97)
Constant 0.00106 0.00153 -0.0741 -0.00576
(0.33) (0.43) (-0.88) (-0.29)
Observations 264 264 264 264
R2
0.021 0.024 0.000 0.019
Monthly data 1997-2018.
11 / 28

14. Who Buys Treasuries?
Share of total Treasuries held by sector. Sectors that increase holdings during negative
stock-bond covariance episodes.
D.Broker-Dealer D.Households D.MMF
D.Cov(Tr 10y, St.) -0.369∗∗∗
-0.0988 -0.213∗∗∗
(-3.64) (-0.67) (-3.56)
Constant 0.00754 -0.133 0.0177
(0.08) (-1.02) (0.33)
Observations 76 76 76
R2
0.152 0.006 0.146
Quarterly data 1997-2018.
=⇒ Who sells?
12 / 28

15. Treasury Implied Volatility and Jump Probabilities
Cov(Treasury 10y, Stocks)
Implied Volatility 10y -0.169∗
-0.476∗∗∗
-0.346∗∗∗
-0.281∗∗
(-2.22) (-4.48) (-3.45) (-3.02)
Jump Probability Calls (LT) -1.767∗∗
-2.091∗∗∗
-1.754∗∗∗
(-3.23) (-3.90) (-3.56)
Jump Probability Puts (RT) 0.578 0.998∗
1.118∗∗
(1.32) (2.43) (2.98)
VIX -0.0479∗∗∗
(-4.09)
Constant 0.984∗
2.483∗∗∗
1.698∗∗
2.124∗∗∗
(2.04) (4.47) (3.21) (4.32)
Observations 217 217 217 217
R2
0.446 0.402 0.471 0.543
Monthly data 1997-2014.
=⇒ Graph 13 / 28

16. Roadmap
Introduction
1. Empirical Facts
Rates, Spreads
Return Predictability
Issuance, Holdings
Treasury Risk-Neutral Distribution
2. Term Structure Model
Setup and Solution
3. Model Simulation
Stock-Bond Covariance
Term Structure of Safe Rates
Literature

17. Model Setup
Setup follows Lettau and Wachter (2007): work with exogenously specified
price of risk process.
Log changes in the aggregate endowment process follow
∆dt+1 = g + zt +
√
xtσd t+1 −
1
2
σ2
dxt.
Log SDF is given by
mt,t+1 = a − ρ(g + zt) − γ
√
xtσc t+1.
ρ is akin to 1/EIS.
γ
√
xt is akin to risk aversion.
14 / 28

18. Price of Risk Process
xt evolves according to a Cox, Ingersoll Jr. and Ross (1985) process
xt+1 = (1 − φx)¯x + φxxt +
√
xtσηηt+1,
Dividend growth rate zt evolves according to an AR(1) process
zt+1 = φzzt + σξξt+1.
The ηt+1 and ξt+1 shocks are not directly priced by the SDF—only t+1 is.
15 / 28

19. Solving Recursively for Risky Asset Prices
In order to solve for stock prices let’s define the price dividend ratio of a
maturity n dividend strip and guess the functional form
Fn,t =
Pn,t
Dt
= exp A(n) + B(n)xt + C(n)zt .
Stock prices have to satisfy
Fn,t = Et exp{mt,t+1}
Dt+1
Dt
Fn−1,t+1 .
The pricing equation implies
exp A(n) + B(n)xt + C(n)zt =
= E exp {a − ρ(g + zt) − γ
√
xtσc t+1} exp g + zt +
√
xtσd t+1 −
1
2
σ2
dxt
exp A(n−1) + B(n−1)xt+1 + C(n−1)zt+1 .
16 / 28

20. Closed-form Expressions for Risky Asset Prices
Can recursively solve the pricing equation to derive closed form
expressions:
=⇒ A(n) = a − ρg + g + A(n−1) + B(n−1)(1 − φx)¯x +
1
2
C2
(n−1)σ2
ξ
=⇒ B(n) = B(n−1)φx − γσcσd +
1
2
B2
(n−1)σ2
η +
1
2
γ2
σ2
c
=⇒ C(n) = C(n−1)φz − ρ + 1.
Boundary condition implies A(0) = B(0) = C(0) = 0.
The market return is calculated as
Rt,t+1 =
P m
t+1
Dt+1
+ 1
P m
t
Dt
Dt+1
Dt
.
=⇒ Safe Asset Prices
=⇒ Solution Graph 17 / 28

21. Roadmap
Introduction
1. Empirical Facts
Rates, Spreads
Return Predictability
Issuance, Holdings
Treasury Risk-Neutral Distribution
2. Term Structure Model
Setup and Solution
3. Model Simulation
Stock-Bond Covariance
Term Structure of Safe Rates
Literature

22. Calibration
Description Variable Value
Time Discount a -0.041
Risk Aversion γ 3.000
One over IES ρ 1.200
Consumption Growth Rate g 0.020
Consumption Volatility σc 0.013
Dividend Volatility σd 0.026
Average Price of Risk Squared ¯x 50.000
Price of Risk Squared Volatility ση 2.500
Price of Risk Squared Persistence φx 0.890
Dividend Growth Rate Volatility σξ 0.002
Dividend Growth Rate Shock Persistence φz 0.800
Parameters roughly follow Lettau and Wachter (2007). Preference parameters are
unitless. All other parameters reported in annualized terms. The model is simulated daily.
18 / 28

23. Main Model Moments
Variable Mean S.D. p10 p90 Skew
Instantaneous risk premium 5.017 3.928 1.134 10.191 1.618
Annualized Sharpe ratio 0.251 0.097 0.130 0.382 0.451
Instantaneous risk-free rate 2.871 4.594 -3.193 8.669 -0.177
Precautionary savings component -3.520 2.583 -7.020 -0.842 -1.359
10-year yield 2.421 2.264 -0.608 5.110 -0.544
1,000,000 days of simulated data.
19 / 28

24. Main Model Moments
Variable Mean S.D. p10 p90 Skew
Monthly market return, model 0.431 7.248 -8.515 9.640 0.282
Monthly market return, data 0.575 4.558 -5.660 6.110 -0.677
Monthly 10y bond return, model 0.062 3.550 -4.381 4.594 0.135
Monthly 10y bond return, data 0.138 2.696 -2.964 3.440 0.000
Stock 10y bond covariance, model -0.063 0.432 -0.584 0.363 -1.134
Stock 10y real bond covariance, data -0.332 0.589 -1.064 0.148 -2.488
Stock 10y nominal bond covariance, data -0.514 1.086 -1.833 0.482 -2.422
10y bond stock beta, model 0.026 0.194 -0.156 0.214 3.677
10y real bond stock beta, data -0.082 0.146 -0.262 0.079 0.312
10y nominal bond stock beta, data -0.088 0.263 -0.385 0.286 0.756
1,000,000 days of simulated data.
20 / 28

25. Stock-Bond Covariance in the Model
0
10
20
30
40
50
Percent
−.5 0 .5 1 1.5 2
10y Bond Stock Market Beta, Model
0
10
20
30
Percent
−3 −2 −1 0 1 2
Stock−10y Bond Covariance, Model
0
10
20
30
Percent
−.5 0 .5 1
10y Bond Stock Market Beta, Data
0
5
10
15
20
25
Percent
−4 −2 0 2 4
Stock−10y Bond Covariance, Data
21 / 28

26. Stock-Bond Covariance in the Model
Cov(Stocks, 10y Bond) Model
Price Dividend Ratio 0.0117∗∗∗
0.0159∗∗∗
(44.20) (10.57)
Price of Risk -0.0574∗∗∗
0.00741
(-51.87) (1.39)
Dividend Growth Rate 1.144 30.56∗∗∗
(1.48) (10.63)
Constant -2.541∗∗∗
0.306∗∗∗
-0.0632∗∗∗
-3.473∗∗∗
(-44.38) (51.24) (-31.91) (-9.85)
Observations 47620 47620 47620 47620
R2
0.094 0.110 0.000 0.115
=⇒ Bond Beta
22 / 28

27. Term Structure in the Model
yield 1y yield 5y yield 10y yield 20y Level Slope
Cov(Tr 10y, St.) 2.106∗∗∗
1.710∗∗∗
1.372∗∗∗
0.962∗∗∗
3.418∗∗∗
-0.282∗∗∗
(29.31) (32.90) (36.27) (39.94) (37.72) (-27.81)
Constant 2.982∗∗∗
2.775∗∗∗
2.508∗∗∗
2.121∗∗∗
0.216∗∗
-0.018∗
(49.51) (63.76) (79.32) (105.45) (2.86) (-2.10)
Observations 47620 47620 47620 47620 47620 47620
R2
0.046 0.057 0.068 0.081 0.073 0.042
Level and Slope refer to the first two principal components of the simulated term structure.
=⇒ Price of Risk
23 / 28

28. Yield Curve Factors in the Model
Model.
−.5
0
.5
1
FactorLoading
0 10 20 30
Maturity
Level Slope
Model Factor Loadings
Data.
−.5
0
.5
1
FactorLoading
0 10 20 30
Maturity
Level Slope
Data Factor Loadings
24 / 28

29. Yield Curve Factors in the Model
Level Factor Slope Factor
Cov(Stocks, 10y Tr.) 3.418∗∗∗
-0.282∗∗∗
(37.72) (-27.81)
Price of Risk -1.663∗∗∗
0.143∗∗∗
(-81.26) (52.09)
Dividend Growth Rate 1.350∗∗∗
0.188∗∗∗
(54.01) (87.53)
Constant 0.216∗∗
10.70∗∗∗
0.124 -0.0178∗
-0.923∗∗∗
0.0172∗∗
(2.86) (75.59) (1.93) (-2.10) (-48.45) (3.13)
Observations 47620 47620 47620 47620 47620 47620
R2
0.073 0.581 0.380 0.042 0.362 0.617
Level and Slope refer to the first two principal components of the simulated term structure.
25 / 28

30. Literature
Bekaert and Grenadier (1999) study joint pricing of stocks and bonds in affine
economies. Don’t address time variation in stock-bond covariance, however.
Kozak (2015) proposes an explanation using a purely real, production-based model.
Two-tree model intuition.
Campbell et al. (2017) attribute the stock-bond covariance dynamics to a change in
the covariance between nominal rates and the real economy.
Campbell et al. (2018) explore the implications of a changing covariance between
inflation and output using a habits based model of investor preferences.
Pflueger et al. (2018) show that the relative valuations of volatile stocks have a strong
relationship with the real interest rate.
Main measure—difference between average book-to-market ratios of high and low
volatility stocks—is strongly correlated (.48) with the stock-bond covariance studied
here.
26 / 28

31. Other Measures in the Literature
1.3
1.4
1.5
1.6
1.7
BondQ
−6
−4
−2
0
2
1995q1 2000q1 2005q1 2010q1 2015q1
Cov(Tr 10y, St.) PVS Bond Q
Stock-Bond Covariance. PVS measure from Pflueger et al. (2018). Bond
Market’s Q from Philippon (2009) Quarterly data 1990-2015.
27 / 28

32. Precautionary Savings
Inherent non-linearity in the precautionary savings term makes it cumbersome to
work with.
Here a particular functional form assumption allows to solve for both PS and RP in
closed form.
Underlines tight connection between risk dynamics and the safe term structure. Thus
escapes the separation between macro quantities and risk premia studied in Tallarini
(2000).
Safe rates are currently low. How much on account of µc, how much on
account of γt?
Thank You!
28 / 28

33. Citations I
Bekaert, Geert and Steven R Grenadier, “Stock and bond pricing in an affine economy,” 1999.
Working Paper.
Campbell, John Y., Adi Sunderam, and Luis M. Viceira, “Inflation bets or deflation hedges? the
changing risks of nominal bonds,” Critical Finance Review, 2017, 6 (2), 263–301.
, Carolin E. Pflueger, and Luis M. Viceira, “Monetary policy drivers of bond and equity risks,”
2018. Working Paper.
Cox, John C., Jonathan E. Ingersoll Jr., and Stephen A. Ross, “An intertemporal general
equilibrium model of asset prices,” Econometrica, 1985, pp. 363–384.
Kozak, Serhiy, “Dynamics of Bond and Stock Returns,” 2015. Working Paper.
Lettau, Martin and Jessica A. Wachter, “Why is long-horizon equity less risky? A duration-based
explanation of the value premium,” The Journal of Finance, 2007, 62 (1), 55–92.
1 / 15

34. Citations II
Pflueger, Carolin, Emil Siriwardane, and Adi Sunderam, “A measure of risk appetite for the
macroeconomy,” 2018. Working Paper.
Philippon, Thomas, “The bond market’s q,” The Quarterly Journal of Economics, 2009, 124 (3),
1011–1056.
Tallarini, Thomas D., “Risk-sensitive real business cycles,” Journal of Monetary Economics, 2000, 45
(3), 507–532.
2 / 15

35. Historical Stock-Bond Covariance
−1
−.5
0
.5
1
Cov(Stocks,LongTreasury)
1880 1900 1920 1940 1960 1980 2000 2020
=⇒ Back
3 / 15

36. Stock-Bond Correlation
−1
−.5
0
.5
1
1990/1 2000/1 2010/1 2020/1
Tr 10y Stock Correlation TIPS 10y Stock Correlation
=⇒ Back
4 / 15

37. Treasury Forward Curve Factors
D.Level D.Slope D.Curvature
D.Cov(Tr 10y, St.) 0.109∗∗∗
-0.0202 0.0200
(3.68) (-1.65) (1.87)
D.VIX -0.0118∗
-0.00286 -0.00597∗∗∗
(-2.41) (-1.45) (-3.32)
Constant -0.0222 0.00201 0.000477
(-1.32) (0.22) (0.09)
Observations 264 264 264
R2
0.076 0.017 0.058
Monthly data 1997-2018.
=⇒ Back
5 / 15

38. Corporate Spreads
−8
−6
−4
−2
0
2
Cov(Tr10y,St.)
0.00
5.00
10.00
15.00
20.00
HY−Tr
1995/1 2000/1 2005/1 2010/1 2015/1 2020/1
HY−Tr Cov(Tr 10y, St.)
=⇒ Back
6 / 15

39. Treasury Bond Returns
5y 12m ER 10y 12m ER 20y 12m ER 30y 12m ER
Cov(Tr 10y, St.) -0.00203 0.000126 0.0206 0.0500∗
(-0.43) (0.01) (1.43) (2.33)
Constant 0.0238∗∗∗
0.0442∗∗∗
0.0720∗∗∗
0.0953∗∗
(3.53) (3.65) (3.58) (3.18)
Observations 261 261 261 261
R2
0.003 0.000 0.029 0.073
Monthly data 1997-2018.
=⇒ Back
7 / 15

40. Equity Returns
ER 12m ER 24m ER 36m ER 48m ER 60m
Cov(Tr 10y, St.) -0.00353 -0.0426 -0.0751 -0.104∗
-0.143∗∗
(-0.16) (-1.14) (-1.71) (-2.27) (-3.28)
Constant 0.0737∗
0.116 0.148 0.179∗
0.212∗
(2.28) (1.83) (1.85) (2.04) (2.30)
Observations 253 241 229 217 205
R2
0.000 0.031 0.078 0.138 0.249
Monthly data 1997-2018.
=⇒ Back
8 / 15

41. Who Sells Treasuries?
Share of total Treasuries held by sector. Sectors that decrease holdings during negative
stock-bond covariance episodes.
D.Depository Inst. D.Mutual Funds D.Insurance
D.Cov(Tr 10y, St.) 0.0543 0.0147 0.00613
(1.94) (0.52) (0.40)
Constant -0.0207 0.0376 -0.0292∗
(-0.83) (1.48) (-2.16)
Observations 76 76 76
R2
0.048 0.004 0.002
Quarterly data 1997-2018.
=⇒ Back
9 / 15

42. Treasury Implied Vol and Jump Probabilities
0
.5
1
1.5
JumpPr.Calls(LT)
−8
−6
−4
−2
0
2
Cov(Tr10y,St.)
1990/1 2000/1 2010/1 2020/1
Cov(Tr 10y, St.) Jump Pr. Calls (LT)
=⇒ Back
10 / 15

43. Recursive Expressions for Safe Asset Prices
Can recursively solve the pricing equation to derive closed form
expressions:
=⇒ Af
(n) = a − ρg + Af
(n−1) + Bf
(n−1)(1 − φx)¯x +
1
2
Cf
(n−1)Cf
(n−1)σ2
ξ
=⇒ Bf
(n) = Bf
(n−1)φx +
1
2
Bf
(n−1)Bf
(n−1)σ2
η +
1
2
γ2
σ2
c
=⇒ Cf
(n) = Cf
(n−1)φz − ρ
Boundary condition implies A(0) = B(0) = C(0) = 0.
=⇒ Back
11 / 15

44. Model Solution
−6.00
−4.00
−2.00
0.00
A
0 500 1000 1500
months
−.002
−.0015
−.001
−.0005
0
B
0 500 1000 1500
months
−10
−8
−6
−4
−2
0
C
0 500 1000 1500
months
−2.00
−1.50
−1.00
−0.50
0.00
Af
0 500 1000 1500
months
0
.002
.004
.006
.008
Bf
0 500 1000 1500
months
−80
−60
−40
−20
0
Cf
0 500 1000 1500
months
=⇒ Back
12 / 15

45. Bond Beta in the Model
10y Bond Beta in Model
Price Dividend Ratio 0.00502∗∗∗
-0.0336∗∗∗
(67.01) (-89.45)
Price of Risk -0.0307∗∗∗
-0.167∗∗∗
(-93.85) (-107.44)
Dividend Growth Rate -0.254 -61.07∗∗∗
(-0.71) (-81.74)
Constant -1.036∗∗∗
0.223∗∗∗
0.0258∗∗∗
8.197∗∗∗
(-65.28) (98.96) (29.09) (91.93)
Observations 47620 47620 47620 47620
R2
0.086 0.156 0.000 0.277
=⇒ Back
13 / 15

46. Stock Return Predictability in the Model
1-year Returns 2-year Returns
Price Dividend Ratio -0.262∗∗∗
-0.478∗∗∗
(-29.53) (-20.32)
Price of Risk 0.0129∗∗∗
0.0229∗
(3.49) (2.35)
Stock-10y Bond Covariance -0.0209 -0.0387
(-1.92) (-1.55)
Constant 4.632∗∗∗
-0.0627∗
0.0186∗
8.460∗∗∗
-0.107 0.0376
(29.62) (-2.46) (1.98) (20.39) (-1.59) (1.49)
Observations 47608 47608 47608 47596 47596 47596
R2
0.165 0.003 0.000 0.151 0.002 0.000
14 / 15

47. Term Structure in the Model
yield 1y yield 5y yield 10y yield 20y Level Slope
Price of Risk -1.014∗∗∗
-0.828∗∗∗
-0.666∗∗∗
-0.470∗∗∗
-1.663∗∗∗
0.143∗∗∗
(-51.49) (-62.13) (-74.71) (-93.39) (-81.26) (52.09)
Constant 9.372∗∗∗
7.991∗∗∗
6.708∗∗∗
5.081∗∗∗
10.701∗∗∗
-0.923∗∗∗
(68.81) (86.74) (108.72) (146.10) (75.59) (-48.45)
Observations 47620 47620 47620 47620 47620 47620
R2
0.357 0.447 0.539 0.646 0.581 0.362
Level and Slope refer to the first two principal components of the simulated term structure.
=⇒ Back
15 / 15