5.4. Overall Bond Fund Performance
5.4.2. Conditional Models
become negative. This outcome is consistent with the findings of Elton, Gruber, Das and Hlavka (1993) in relation to the Ippolito (1989) study and with other studies on stock fund performance and reinforces the idea that single-index models might overestimate fund performance. Multiple factor benchmarks, in general, produce lower alphas. This happens because multiple factor benchmarks control for risk better, causing the risk-adjusted performance to be lower. In our sample, the number of funds that present statistically significant negative alphas increase from 388 to 442, representing a shift in 54 funds.
Table 5.4 – Estimates for the conditional single and multiple index models
For each country, we formed equally-weighted portfolios of bond funds for each fund category and for all funds. This table shows the results for both the conditional single and multiple index models. The predetermined information variables are the term spread (term), the IRW and a dummy variable for the month of January (jd). Term is the difference between the yield on a long- term government bond and a short-term bond rate (or the 3-month interbank offered rate). IRW is the ratio between the exponentially weighted average of past real wealth and current wealth. All these variables are stochastically detrended (by subtracting a 12-month moving average) and mean zero variables. Bindex, Sindex and Def as defined in table 5.3. We present the estimates for alpha (in percentage) and for the average conditional beta(s) and also the R2(adj.) for each of the equally-weighted portfolios of funds. The statistical significance of the estimates is based on heteroscedasticity and autocorrelation adjusted errors (following Newey and West, 1987). The number of individual funds presenting statistically significant positive, not different from zero and negative alphas, at the 5% level, is also reported (N +/0/-). Bonf.(+) and Bonf.(-) are the bonferroni p-values for the null hypothesis that all funds have alphas equal to zero against the alternative that at least one has a positive alpha and the same null hypothesis against the alternative that at least one has a negative alpha. The W(p-val) is the probability value for the Chi-square statistic of the Wald test for the restriction that the coefficients on the additional variables (the cross products between the factors and the predetermined information variables) are jointly equal to zero. The number of funds for which we reject that hypothesis, at the 5% level, are reported in brackets.
*** Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds αp β0p R2(adj.) N +/0/- alphas W(p-val) αp BIndex SIndex Def R2(adj.) N +/0/- alphas W(p-val) Germany
Renten Euro 59 -0.021 0.855*** 83.3% 2/54/3 0.478 [ 8] -0.069 0.885*** 0.024*** 0.182** 86.5% 0/49/10 0.703 [19]
Renten Europa 14 0.066 0.958*** 49.1% 0/14/0 0.284 [ 2] -0.082 1.009*** 0.107*** 0.372* 73.9% 0/14/0 0.000 [10]
Renten Kurz 11 -0.009 0.353*** 64.7% 0/10/1 0.180 [ 3] -0.033 0.368*** 0.010** 0.127*** 66.3% 0/9/2 0.001 [ 5]
Renten IZB 6 -0.042 0.430*** 77.7% 0/4/2 0.000 [ 2] -0.053 0.450*** -0.002 0.116** 77.8% 0/4/2 0.000 [ 5]
All Funds 90 -0.008 0.781*** 79.3% 2/82/6 0.324 [17] -0.065 0.812*** 0.033*** 0.200** 86.3% 0/76/14 0.263 [39]
Bonf.(+) 0.867 7.592
Bonf.(-) 0.005 0.000
France
Obl.Euro CT 60 -0.065*** 0.262*** 84.8% 0/24/36 0.022 [29] -0.079*** 0.272*** -0.002 0.134*** 87.6% 0/15/45 0.016 [44]
Obl.Euro MT 83 -0.086*** 0.589*** 92.5% 0/32/51 0.003 [39] -0.097*** 0.595*** 0.001 0.125*** 92.8% 0/25/58 0.229 [46]
Obl.Euro LT 114 -0.085*** 0.905*** 96.3% 0/56/58 0.003 [49] -0.085*** 0.905*** 0.003 0.066* 96.5% 0/64/50 0.001 [81]
Obl.Europe 9 -0.060 0.843*** 73.5% 0/9/0 0.063 [ 5] -0.060 0.806*** 0.035*** 0.023 75.8% 0/9/0 0.133 [ 6]
All Funds 266 -0.080*** 0.659*** 95.2% 0/121/145 0.002[122] -0.086*** 0.662*** 0.003 0.098*** 95.6% 0/113/153 0.087[177]
Bonf.(+) 7.972 70.805
Bonf.(-) 0.000 0.000
Conditional single-index Conditional multi-index
Table 5.4 – Estimates for the conditional single and multiple index models (continued)
*** Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds αp β0p R2(adj.) N +/0/- alphas W(p-val) αp BIndex SIndex Def R2(adj.) N +/0/- alphas W(p-val) UK
Gilt 26 -0.168*** 0.992*** 93.6% 0/8/18 0.000 [17] -0.164*** 0.966*** 0.023 0.078 93.7% 0/10/16 0.000 [20]
Corporate 13 -0.031 0.799*** 75.6% 0/12/1 0.001 [10] -0.124* 0.721*** 0.124*** 0.189 83.8% 0/12/1 0.000 [10]
Other Bond 6 0.190 0.488*** 41.3% 0/6/0 0.000 [ 5] 0.081 0.403*** 0.146*** 0.353 53.7% 0/6/0 0.013 [ 5]
All Funds 45 -0.081 0.869*** 88.9% 0/26/19 0.000 [32] -0.120** 0.820*** 0.069*** 0.147 91.2% 0/28/17 0.000 [35]
Bonf.(+) 2.546 1.143
Bonf.(-) 0.000 0.003
Spain
RentaFija CP Euro 108 -0.177*** 0.278*** 90.7% 0/6/102 0.006 [20] -0.181*** 0.275*** 0.003* 0.050** 90.9% 0/5/103 0.000 [40]
RentaFija Euro 49 -0.171*** 0.514*** 93.2% 0/3/46 0.001 [44] -0.185*** 0.520*** 0.003 0.067* 93.5% 0/2/47 0.001 [93]
All Funds 157 -0.175*** 0.352*** 92.6% 0/9/148 0.016 [64] -0.182*** 0.352*** 0.003 0.055** 92.9% 0/7/150 0.000[133]
Bonf.(+) 51.310 31.510
Bonf.(-) 0.000 0.000
Italy
Short-Term Euro 26 -0.198*** 0.278*** 72.7% 0/1/25 0.596 [ 5] -0.192*** 0.265*** 0.002 0.034 73.3% 0/1/25 0.000 [25]
M/L Euro 25 -0.220*** 0.640*** 93.8% 0/1/24 0.608 [ 6] -0.214*** 0.614*** 0.008** -0.001 94.3% 0/0/25 0.000 [18]
Europa 7 -0.214*** 0.530*** 67.5% 0/1/6 0.434 [ 1] -0.213*** 0.506*** 0.007 0.008 66.5% 0/1/6 0.191 [ 4]
All Funds 58 -0.210*** 0.465*** 89.1% 0/3/55 0.419 [12] -0.204*** 0.445*** 0.005 0.015 89.5% 0/2/56 0.000 [47]
Bonf.(+) 31.616 19.992
Bonf.(-) 0.000 0.000
Portugal
Euro Fixed Rate 6 -0.189*** 0.595*** 82.5% 0/1/5 0.001 [ 5] -0.181*** 0.601*** 0.008 -0.040 81.8% 0/1/5 0.000 [ 4]
Euro Floating Rate 16 -0.128*** 0.026*** 19.9% 0/0/16 0.010 [ 8] -0.129*** 0.029*** -0.001 0.009 18.9% 0/0/16 0.072 [11]
All Funds 22 -0.144*** 0.181*** 78.7% 0/1/21 0.000 [13] -0.143*** 0.185*** 0.001 -0.005 76.8% 0/1/21 0.001 [15]
Bonf.(+) 0.878 2.054
Bonf.(-) 0.000 0.000
All Sample 638 2/242/394 [260] 0/227/411 [446]
Conditional single-index Conditional multi-index
The effects on the estimates of alphas are, however, somewhat mixed, as revealed by the distribution of the funds’ alphas in Appendix 5.7 and Appendix 5.8. For some countries the alphas increase slightly, in particular in the context of the multi-index model. This is the case for German, UK and French bond funds with more 11, 6 and 17 funds (in comparison with the unconditional multi-index model), respectively, presenting alphas not statistically different from zero. In an opposite direction, the alphas on Spanish and Italian bond funds decrease slightly. We have 3 and 1 more funds, respectively, with statistically significant negative alphas. Overall, comparatively to the unconditional multi-index model, the number of funds that present either a positive or not statistically different from zero alpha is higher (196 funds with zero alphas against 227 funds with zero alphas, which represents an increase in 31 funds).
The inclusion of the information variables seems to add explanatory power to the model. Although the R2 (adj.) of the portfolios of funds remain similar, or even decreases slightly, at the individual fund level we can observe that for both models (single and multi-index), we reject the hypothesis, at the 5 percent level, that the coefficients for the additional variables are jointly equal to zero for a large number of funds. For the conditional multi-index model we reject that hypothesis for 39 German funds, 177 French funds, 35 UK funds, 133 Spanish funds, 47 Italian funds and 15 Portuguese funds (a total of 446 representing approximately 70 percent of the funds). In the case of the conditional single index model we reject the null hypothesis for 260 funds (41 percent of the funds).
The evidence suggests that the measures of risk are time-varying, being stronger for the conditional multi-index and weaker for the conditional single-index model.
Table 5.5 shows, in more detail, the estimates for the slope coefficients of the
conditional beta function.83 The variable IRW is the most significant one in the conditional single-index model, namely for the UK and French markets. This variable also appears as one of the most significant one in the conditional multi-index model.
There seems to exist a significant negative relation between the conditional beta and IRW. This is contrary to what we found in the analysis of bond return predictability, as higher IRW tends to forecast higher excess bond returns. The fact that the sign of this relation is the opposite of what should be expected can be due to the same reasons pointed out by Ferson and Schadt (1996) for the case of stock funds. Possible explanations are the impact of new cash flows into the funds and the fact that the betas of the underlying securities change through time. We think that the latter is, probably, the most reasonable explanation as we are dealing with bond funds.
83 Regression estimates for each individual fund are reported in Appendix 5.9.
Table 5.5 – Estimates of conditional betas
This table presents the coefficients’ estimates for the conditional beta function for the equally-weighted portfolios of funds and for both the single and multiple index models. The predetermined variables Term, IRW and Jd are as defined in table 5.4. The conditional beta for the Bindex is designated by b1, b2 identifies the conditional beta for Sindex and b3 the conditional beta for the Def. Bindex, Sindex and Def as defined in table 5.3. The number of funds with positive (N+) or negative (N-) coefficients with respect to the lagged information variables are also reported, with the number of those which are statistically significant, at the 5% level, reported in brackets.
*** Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds term irw jd b1term b1irw b1jd b2term b2irw b2jd b3term b3irw b3jd
Germany
Renten Euro 59 0.073 0.092 0.020 0.051 0.158 -0.141 -0.002 0.007 0.028 0.059 -0.522 -0.066
Renten Europa 14 0.100 -2.017 0.042 -0.016 -1.508* -0.442*** -0.006 0.000 0.034 0.175 1.559 0.299
Renten Kurz. 11 0.032 0.179 -0.121 0.034 0.176 -0.177*** 0.002 0.020 0.014 0.095 0.023 -0.139
Renten IZB 6 0.137*** 0.502 -0.011 0.150*** 0.464 -0.124** -0.004 -0.010 0.029*** 0.031 -0.211 0.033
All Funds 90 0.077 -0.198 0.004 0.045 -0.078 -0.191* -0.002 0.006 0.027 0.080 -0.111 -0.011
N+ 64 50 47 60 53 9 39 38 74 69 36 47
[14] [4] [0] [13] [4] [0] [0] [3] [17] [1] [0] [2]
N- 26 40 43 30 37 81 51 52 16 21 54 43
[1] [6] [4] [2] [4] [18] [0] [1] [0] [0] [0] [2]
France
Obl.Euro CT 60 0.004 -0.298 0.091*** 0.001 -0.317 0.116*** -0.001 0.004 -0.011* 0.013 -0.463 0.032 Obl.Euro MT 83 0.001 -0.608* 0.116*** 0.003 -0.509 0.084** -0.003 -0.052 0.003 0.003 -0.351 -0.064 Obl.Euro LT 114 -0.016 -0.973*** 0.091** 0.003 -0.715** -0.016 -0.008 -0.143** 0.023** 0.005 -0.282 -0.183 Obl.Europe 9 0.033 -1.932** -0.084 0.043 -1.152* -0.374** -0.014 -0.293** 0.019 -0.085 2.576 0.582 All Funds 266 -0.005 -0.739*** 0.093*** 0.004 -0.576* 0.033 -0.005 -0.086 0.009 0.003 -0.248 -0.072
N+ 116 39 229 136 42 184 80 78 155 154 91 110
[27] [0] [67] [29] [2] [46] [3] [9] [35] [9] [2] [13]
N- 150 227 37 130 224 82 186 188 111 112 175 156
[27] [72] [2] [16] [45] [16] [12] [43] [23] [6] [7] [14]
UK
Gilt 26 -0.031 -1.891*** 0.009 -0.041 -1.720*** -0.137 0.025* -0.295 0.021 0.161 -0.031 -0.137 Corporate 13 0.099 -4.154*** 0.102 -0.017 -2.491** -0.337*** 0.017 -0.255 0.028 -0.060 -0.884 0.863**
Other Bond 6 0.137 -7.013*** 0.804 -0.040 -5.260*** 0.537** 0.012 -0.352 -0.042 -0.551 0.410 0.850*
All Funds 45 0.029 -3.227*** 0.142 -0.034 -2.415*** -0.105 0.021 -0.291 0.015 0.002 -0.219 0.284
N+ 21 1 21 33 19 3 13 34 7 28 30 24
[1] [0] [5] [3] [2] [0] [2] [7] [2] [1] [0] [2]
N- 24 44 24 12 26 42 32 11 38 17 15 21
[6] [33] [0] [0] [6] [23] [4] [1] [6] [1] [1] [1]
Conditional single-index Conditional multi-index
Table 5.5 – Estimates of conditional betas (continued)
***Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds term irw jd b1term b1irw b1jd b2term b2irw b2jd b3term b3irw b3jd
Spain
RentaFija CP Euro 108 0.018* -0.448*** 0.045 0.017 -0.405** -0.285*** 0.000 0.008 0.047*** 0.010 -0.024 0.366***
RentaFija Euro 49 -0.033** -0.081 0.069** -0.032* -0.068 -0.290** -0.002 0.046* 0.052** 0.063* -1.020* 0.328**
All Funds 157 0.002 -0.334** 0.053* 0.002 -0.300** -0.287*** -0.001 0.020 0.049*** 0.027 -0.335 0.354***
N+ 83 56 110 80 59 30 66 97 131 110 62 138
[19] [4] [25] [23] [6] [2] [0] [26] [58] [17] [3] [60]
N- 74 101 47 77 98 127 91 60 26 47 95 19
[26] [21] [0] [20] [27] [52] [4] [1] [3] [1] [15] [5]
Italy
Short-Term Euro 26 0.014 -0.396 0.007 0.015 -0.604* 0.059 0.005 0.035 -0.012* 0.092 1.470* -0.006 M/L Euro 25 0.029 -0.299 0.018 0.020 -0.345 0.094* 0.009* 0.013 -0.013** 0.054 1.226** -0.095
Europa 7 0.040 -1.312 0.102 0.050 -1.267 0.105 -0.006 0.012 0.018 0.200 1.609 -0.193
All Funds 58 0.024 -0.465 0.023 0.021 -0.572 0.080* 0.005 0.023 -0.009 0.089 1.382** -0.067
N+ 41 11 34 40 6 45 47 42 12 45 52 22
[6] [0] [2] [7] [0] [9] [6] [2] [2] [7] [9] [3]
N- 17 47 24 18 52 13 11 16 46 13 6 36
[1] [6] [2] [1] [9] [0] [2] [0] [22] [0] [0] [4]
Portugal
Euro Fixed Rate 6 -0.057 1.395*** 0.126 -0.061 1.366*** 0.321 0.009 -0.014 -0.019 -0.071* 0.557 -0.373 Euro Floating Rate 16 -0.003 -0.062 0.050*** -0.004 -0.087 -0.023 -0.002 -0.002 0.006 -0.003 0.362 0.053 All Funds 22 -0.018 0.335** 0.071*** -0.019 0.309* 0.071 0.001 -0.006 -0.001 -0.021 0.415 -0.063
N+ 9 12 19 9 10 8 9 9 14 10 17 12
[1] [4] [10] [1] [5] [2] [1] [0] [5] [1] [1] [2]
N- 13 10 3 13 12 14 13 13 8 12 5 10
[2] [0] [0] [3] [2] [2] [4] [1] [2] [1] [0] [1]
All Sample 638
N+ 334 169 460 358 189 279 254 298 393 416 288 353
[68] [12] [109] [76] [19] [59] [12] [47] [119] [36] [15] [82]
N- 304 469 178 280 449 359 384 340 245 222 350 285
[63] [138] [8] [42] [93] [111] [26] [47] [56] [9] [23] [27]
Conditional single-index Conditional multi-index
The dummy for the month of January is another variable with some significance and, in general, for all countries. However, the evidence is mixed. For several funds there seems to exist a negative relation between the conditional betas and the month of January, while for others that relation is positive.
It would be important to investors in bond funds to know when they are most likely to present superior performance. Is it better in up markets or when the market is expected to enter into recession? The analysis of the sign of the estimates for the conditional alpha function, resulting from equation [5.5] and reported in Table 5.6, can help us answer this question. This table shows that there is a relationship between the predetermined information variables and bond fund performance for both the single and the multi-index conditional models.84
The variable term spread appears significant for several funds, mainly for Spanish, German and French bond funds, and with a negative sign. The negative sign indicates that abnormal performance is above average when term spread takes on low values.
According to the results obtained in the previous chapter, as a low term spread predicts higher bond returns, we may therefore conclude that bond funds seem to present above average abnormal performance in up bond markets. The January dummy is also significant for several funds, in particular for German, French and UK bond funds, and also with a negative sign. It appears that bond funds have below average alphas in the month of January. The IRW seems to have a weak relation with bond fund performance, although with some significance in the UK, Spanish and Portuguese markets. For those cases in which it appears as significant, its sign is not clear: for the UK market it has a negative sign while for the Spanish market some funds present a positive sign.
84 The estimates for the conditional alpha function for each individual fund are presented in Appendix 5.10.
Considering all funds of the sample, most of them have a positive sign. If IRW reflects wealth-dependent RRA, it should peak during cyclical contractions and be low in expansions. A positive sign of the IRW is consistent with a higher performance in an up bond market.
Using the heteroscedaticity and autocorrelated-consistent Wald test we conclude that, for a large number of funds, in particular for the conditional multi-index model, we reject the hypothesis that the coefficients on the lagged information variables are jointly equal to zero (for a total of 348 funds, representing approximately 55 percent of the sample).
Table 5.6 – Estimates of time-varying alphas
This table presents the coefficients’ estimates for the conditional alpha function for the equally-weighted portfolios of funds and for both the single and multiple index models. The predetermined variables Term, IRW and Jd are as defined in table 5.4. The number of funds with positive (N+) or negative (N-) coefficients with respect to the lagged information variables are also reported, with those which are statistically significant, at the 5% level, included in brackets. The W(p-val) is the probability value for the Chi-square statistic of the Wald test for the restriction that the coefficients on the lagged information variables are jointly equal to zero. The number of funds for which we reject that hypothesis, at the 5% level, are reported in brackets.
*** Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds α 0p term irw jd R2(adj.) W(p-val) α 0p term irw jd R2(adj.) W(p-val)
Germany
Renten Euro 59 -0.007 -0.119*** 0.167 -0.262* 84.2% 0.000 [47] -0.057 -0.133** 0.214 -0.521*** 88.5% 0.000 [59]
Renten Europa 14 0.069 -0.231* -0.272 0.158 49.2% 0.339 [ 4] -0.081 -0.257* -0.403 -0.204 75.6% 0.019 [ 7]
Renten Kurz. 11 -0.003 -0.003 0.562 -0.065 64.8% 0.019 [ 6] -0.026 -0.012 0.701** -0.093 67.3% 0.000 [ 4]
Renten IZB 6 -0.040 -0.025 0.479 0.067 77.6% 0.255 [ 3] -0.048 -0.030 0.662** -0.004 78.2% 0.002 [ 5]
All Funds 90 0.003 -0.116** 0.168 -0.150 80.0% 0.012 [60] -0.057 -0.131** 0.207 -0.385*** 88.1% 0.000 [75]
N+ 35 8 55 23 30 10 38 19
[3] [0] [4] [4] [2] [1] [3] [2]
N- 55 82 35 67 60 80 52 71
[5] [42] [0] [28] [5] [37] [0] [52]
France
Obl.Euro CT 60 -0.063*** -0.011 0.049 -0.018 84.3% 0.893 [15] -0.074*** -0.021 0.228 -0.090 87.8% 0.005 [30]
Obl.Euro MT 83 -0.078*** -0.047** 0.114 -0.090* 92.7% 0.001 [44] -0.086*** -0.061** 0.419 -0.128 93.4% 0.000 [58]
Obl.Euro LT 114 -0.077*** -0.045* -0.183 -0.159** 96.4% 0.000 [58] -0.076*** -0.058** 0.169 -0.138** 96.7% 0.000 [61]
Obl.Europe 9 -0.061 -0.081 -1.296 0.020 73.8% 0.520 [ 0] -0.059 -0.100 -0.961 -0.061 76.1% 0.626 [ 1]
All Funds 266 -0.074*** -0.039* -0.076 -0.099** 95.4% 0.000[117] -0.078*** -0.052** 0.222 -0.121* 96.0% 0.000[150]
N+ 13 49 129 79 14 33 202 74
[0] [1] [2] [8] [0] [1] [14] [13]
N- 253 217 137 187 252 233 64 192
[132] [52] [6] [72] [134] [67] [3] [70]
UK
Gilt 26 -0.149*** -0.053 0.524 -0.269 93.6% 0.262 [ 5] -0.160*** -0.093** 0.575 -0.311* 93.7% 0.046 [ 8]
Corporate 13 -0.025 -0.024 -3.712*** -0.199 76.8% 0.001 [ 3] -0.156* -0.012 -5.579*** -0.184 86.6% 0.002 [ 8]
Other Bond 6 0.182 -0.250** -6.179*** -0.008 48.8% 0.000 [ 4] 0.017 -0.223** -8.795*** -0.075 63.9% 0.000 [ 4]
All Funds 45 -0.069 -0.071 -1.594* -0.214 89.3% 0.006 [12] -0.135** -0.087** -2.452** -0.243* 92.1% 0.023 [20]
N+ 13 13 21 14 6 6 20 12
[0] [0] [0] [0] [0] [0] [1] [2]
N- 32 32 24 31 39 39 25 33
[18] [3] [7] [12] [18] [6] [7] [11]
Conditional single-index Conditional multi-index
Table 5.6 – Estimates of time-varying alphas (continued)
*** Statistically significant at 1% ** Statistically significant at 5% * Statistically significant at 10%
Nº of
Funds α 0p term irw jd R2(adj.) W(p-val) α 0p term irw jd R2(adj.) W(p-val)
Spain
RentaFija CP Euro 108 -0.174*** -0.056*** 0.170 0.039 92.3% 0.018 [20] -0.177*** -0.058*** 0.247 0.068** 92.7% 0.032 [28]
RentaFija Euro 49 -0.165*** -0.064*** -0.099 -0.021 94.2% 0.000 [50] -0.180*** -0.061** -0.133 -0.064 94.5% 0.006 [57]
All Funds 157 -0.172*** -0.059*** 0.086 0.020 93.9% 0.012 [70] -0.178*** -0.059*** 0.128 0.027 94.1% 0.056 [85]
N+ 0 25 91 91 0 25 95 94
[0] [0] [8] [14] [0] [0] [22] [26]
N- 157 132 66 66 157 132 62 63
[149] [68] [2] [14] [151] [63] [17] [15]
Italy
Short-Term Euro 26 -0.196*** 0.020 0.250 -0.031 72.4% 0.401 [ 1] -0.192*** 0.014 0.180 0.012 72.5% 0.821 [ 1]
M/L Euro 25 -0.214*** -0.008 0.032 -0.119** 93.6% 0.025 [ 5] -0.211*** 0.003 -0.180 -0.136* 94.1% 0.219 [ 6]
Europa 7 -0.227*** 0.052 0.263 0.248 67.3% 0.371 [ 0] -0.218*** 0.034 0.324 0.164 65.6% 0.395 [ 1]
All Funds 58 -0.207*** 0.012 0.157 -0.035 88.8% 0.523 [ 6] -0.203*** 0.012 0.042 -0.034 89.1% 0.928 [ 8]
N+ 1 40 37 17 1 37 30 22
[0] [2] [0] [1] [0] [1] [0] [1]
N- 57 18 21 41 57 21 28 36
[55] [0] [0] [9] [56] [0] [1] [9]
Portugal
Euro Fixed Rate 6 -0.170*** -0.044 0.139 -0.248* 82.9% 0.007 [ 4] -0.170*** -0.057 0.275 -0.155 81.6% 0.066 [ 4]
Euro Floating Rate 16 -0.127*** -0.022 0.202*** 0.037 25.5% 0.007 [ 7] -0.127*** -0.026 0.247*** 0.005 26.2% 0.033 [ 6]
All Funds 22 -0.139*** -0.028* 0.185** -0.040 79.4% 0.000 [11] -0.139*** -0.034* 0.255** -0.038 77.5% 0.010 [10]
N+ 0 3 19 14 0 3 19 9
[0] [0] [5] [2] [0] [0] [8] [1]
N- 22 19 3 8 22 19 3 13
[21] [1] [0] [2] [21] [2] [0] [3]
All Sample 638 [276] [348]
N+ 62 138 352 238 51 142 385 230
[3] [3] [19] [29] [2] [3] [48] [45]
N- 576 500 286 400 587 496 253 408
[380] [166] [15] [137] [395] [175] [28] [160]
Conditional single-index Conditional multi-index