5. Result
5.7. The relationship between country risk and the momentum excess return 34
with high or low country risk, so we double-sort the currencies into two portfolios. We first sort currencies into two group depending on whether the individual country risk is higher or lower than the U.S.’s country risk and then we form these two groups of currencies into three portfolios depending on their lagged excess return. That is, we treat the one-third of the currencies with the highest lagged return as the winner currencies, and the one-third of currencies with the lowest lagged return as the loser currencies. Here we also use formation period for 1, 3, 6, 9 and 12 month, but we only consider 1 month holding period.
Table 11. Momentum excess return sorting by country risk.
This table present the average return of the Winner-loser portfolio using 64 currencies against U.S. dollar for whole
sample periods, first classed with the CRISK, then calculated by winner minus loser and use 1, 3, 6, 9, 12 month as
formation period and one month holding period. The excess return is calculated by 𝑟𝑥𝑡+1𝑘 = 𝑓𝑡𝑘− 𝑠𝑡+1𝑘 . Means and
standard deviation are annualized and in percent. T-stat are based on HAC standard error. ***, ** and * are
significant at 1%, 5% and 10%, respectively.
Formation period M(L) M(M) M(H) ∆M
1 CRISK(L) Mean 0.39% 2.82% 3.82% 3.44%**
T-stat [0.23] [1.82] [2.51] [2.42]
CRISK(H) Mean -5.32% 2.44% 10.89% 16.23%***
T-stat [-2.23] [1.76] [6.01] [5.46]
∆CRISK Mean -5.59%* 0.34% 7.20%** 12.79%***
T-stat [-1.97] [0.16] [3.00] [5.12]
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3 CRISK(L) Mean 0.50% 2.63% 2.98% 2.47%*
T-stat [0.32] [1.75] [1.89] [1.84]
CRISK(H) Mean -3.09% 3.03% 8.50% 11.66%***
T-stat [-1.46] [2.25] [4.28] [4.02]
∆CRISK Mean -3.59% 1.52% 5.59%** 9.18%***
T-stat [-1.37] [0.14] [2.18] [3.74]
6 CRISK(L) Mean 2.68% 2.51% 1.31% -1.35%
T-stat [1.66] [1.54] [0.81] [-0.99]
CRISK(H) Mean 1.81% 2.64% 6.09% 4.33%
T-stat [0.90] [1.87] [2.97] [1.49]
∆CRISK Mean -0.79% 0.45% 4.89%* 5.68%**
T-stat [-0.34] [0.12] [1.83] [2.36]
9 CRISK(L) Mean 1.84% 1.08% 3.01% 1.15%
T-stat [1.16] [0.63] [1.83] [0.88]
CRISK(H) Mean 1.52% 1.80% 8.20% 6.53%**
T-stat [0.85] [1.23] [4.20] [2.54]
∆CRISK Mean -0.11% 0.52% 5.28%** 5.38%**
T-stat [-0.14] [0.38] [2.04] [2.44]
12 CRISK(L) Mean 2.81% 2.37% 1.97% -0.81%
T-stat [1.81] [1.39] [1.21] [-0.61]
CRISK(H) Mean 4.85% 2.75% 5.01% 0.27%
T-stat [3.22] [1.74] [2.48] [0.06]
∆CRISK Mean 2.06% -0.16% 3.14% 1.08%
T-stat [0.95] [-0.20] [1.17] [0.53]
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We divide the whole sample currencies into two group, high CRISK and low CRISK, and make the momentum portfolios in each group. In the table 11, we show the result of the momentum excess return sorting by country risk. ∆M is the return of momentum strategy portfolio (that is M(H)’s return minus M(L)’s return) and ∆CRISK is CRISK(H)’s return minus CRISK(L)’s return. In the group of low country risk, we find that differences between winner and loser are smaller, and the momentum excess returns are not significant at 10% confidence level. However, in the group of high country risk, the momentum excess returns are larger and positively significant.
Furthermore, the return of ∆CRISK have significant difference from zero as well. These results indicate that the returns are significant difference between the group of low and high country risk and excess returns of momentum portfolio on high country risk are larger and more significant than the excess returns on low country risk.
5.8.The result from time-series regression
In this part, we want to test whether illiquidity risks or country risk will have significant impact on momentum excess return by running a time-series regression. Our proxy variable for illiquidity risks are TED and term spread for time period of November 1863 to October 2014. The time-series regressions are as follows:
𝑀𝑂𝑀1,1 = 𝛼𝑡+ 𝛽𝑇𝐸𝐷,𝑡𝑇𝐸𝐷𝑡−1+ 𝛽𝑡𝑒𝑟𝑚,𝑡𝑇𝑒𝑟𝑚𝑡−1+ 𝛽𝐶𝑅𝐼𝑆𝐾,𝑡𝑟𝑒𝑡(𝐶𝑅𝐼𝑆𝐾)𝑡−1 ( 7 )
Where 𝑇𝐸𝐷𝑡−1 is lagged TED spread, 𝑇𝑒𝑟𝑚𝑡−1 is lagged term spread and ret(𝐶𝑅𝐼𝑆𝐾)𝑡−1 is lagged conditional return which is calculated by lagged return on high CRISK minus lagged return on low CRISK.
TED Spread is the difference between the LIBOR (London Interbank Offered Rate) and the 3 Month Treasury bill. The LIBOR is Europe's equivalent to the United States
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Federal Funds Rate. A high TED Spread indicates higher perceived risk in lending, as interbank rates rise against risk-free treasury rates, and it is also an evidence that liquidity is being withdrawn from the financial markets. The term spread is the difference between yields on 10 year Treasury bill and 3 month Treasury bill. The higher the yield spread, the greater liquidity premium is, implying there is illiquidity risk. If we have positive 𝛽𝑇𝐸𝐷,𝑡 or 𝛽𝑡𝑒𝑟𝑚,𝑡, it means the larger spread (less liquidity on currency market) would cause larger momentum excess return.
We double-sort the currencies into two portfolios. We first sort currencies into two group depending on whether the individual country risk is higher or lower than the U.S.’s country risk and then we form these two groups of currencies into three portfolios depending on their lagged excess return. That is, we treat the one-third of the currencies with the highest lagged return as the winner currencies, and the one-third of currencies with the lowest lagged return as the loser currencies. Then, we construct the high-minus-low momentum portfolio. From this variable, we can easily realize that if we have positive 𝛽𝐶𝑅𝐼𝑆𝐾,𝑡, it means the larger difference between lagged return on high CRISK and lagged return on low CRISK would cause higher momentum excess return.
Table 12 shows results from time series regression of momentum returns on liquidity and country risk variables. We include the ted and term spread as our liquidity risk variables, and CRISK as country risk variable. The first three rows are coefficients from univariate regression and others are coefficients from multivariate regression.
Numbers In the brackets are t-statistic based on Newey and West (1987) standard errors.
The column of right is shown F-statistic for testing whole regression.
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Table 12. Liquidity risk and momentum excess return.This table shows results from time series regression of momentum returns on liquidity and country risk variables.
Ted and term spread are represented liquidity risk variables. retCRISK is country risk variable, calculated by
lagged return on high CRISK minus lagged return on low CRISK. Numbers In the brackets are t-statistic based
on Newey-West (1987) standard errors. ***, ** and * are significant at 1%, 5% and 10%, respectively.
constant ted termspread retCRISK F-test
0.02 -0.01
[4.70] [-1.65] [2.74]
0.01 0.00
[3.08] [1.52] [2.32]
0.01 0.41***
[6.05] [3.21] [10.29]
0.02 -0.01 0.00
[2.70] [-1.40] [1.06] [2.76]
0.01 0.00 0.44***
[-0.59] [-0.59] [3.29] [5.86]
0.01 0.00 0.41***
[2.75] [0.44] [3.17] [7.37]
0.01 0.00 0.00 0.44***
[1.92] [-0.50] [0.23] [3.26] [4.13]
In the univariate regression, coefficients of country risk variables are significant at 5% confidence level and coefficients of liquidity risk variables are just significant at 10% confidence level. In the multivariate regression, we find that ted and term spread are not significant anymore, indicating that there is little evidence that liquidity risk
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help to explain the momentum excess returns. However, the retCRISK are all positively significant, implied that the larger difference between the high and low CRISK return, the higher momentum excess return we will earn in next period. That is, we will more possibility to earn larger momentum excess return if country risk is higher in last period.