peggychen711
2007-04-30, 12:46 AM
請麻煩英文不錯的朋友幫我看一下該怎麼翻比較通順，我之前有自己翻了，但翻的2266，讓我看不太懂在說什麼~~:|||:
可挑會翻的來翻就好了~
原稿在此==>https://webstaging.lse.ac.uk/ubs/pdf/dp17.pdf
1.The idea is to apply a standard quantile formula over the long-term horizon and then estimate VaR using estimates of the horizon-average values of the parameters on which the VaR depends.(P3倒數第二行)
2.we also suggest that the estimation of long-term VaR should not involve the square-root rule, which can be misleading , even for relatively short horizons , and especially misleading for longer ones.
(p4上面第三行)
3. the best approach is simply to take a view about the values of the mean long -term parameters involved. (p4)
4.positive return observations correspond to profits, and negative ones to losses. (p4倒數第二行)
5.ploughed back into (p4最後一行)
6.if we make the alternative assumption that log-returns are studnent-t distributed. (p5 上面第五行)
7.Pcl is the (1-cl) percentile(or critical percentile)of the terminal value of the portfolio after a holding period of h days.(p5 倒數第三行)
8.and thereafter remains negative and moves further and further away from zero(p6 倒數第八行)
9.the VaR peaks slowly and stays at or near its maximum value? which is bounded above by,and sometimes close to the value of the investment itself? (p6 倒數第五行)
10. The VaR approaches its ceiling asymptotically , and stays in that region indefinitely (p7倒數第四行)
11. the compounding of the mean return ..(P7最後一行)
12.this error rises with μ, becasuse the square-root formula makes no proper allow ance for the impact of the compounding of μ in the VaR.
(p10上面第四行)
13.and eventually changes sign(p11上面第一行)
14.the longer the time horizon on which the VaRs are based (p11 上面第二行)
15.if the variable concerned has a trend? how ever small? then the forecasted variable will eventually become implausible high or low.(p13f上面第三行)
16.and we may as well impose arbitrary values in the first place.(p13上面第九行)
17.they move around a zero trend(P13倒數八行)
18.perhasps some typical recent value?(P13倒數六行)
19.as the forecasted variable keeps returning toward its zero trend;
a horizon-average of day-to-day forecasts would give us much the same result as projecting some recent value over our horizon period and particularly so over longer horizons where the averaging-out process has more scope.(P13 倒數第五行)
可挑會翻的來翻就好了~
原稿在此==>https://webstaging.lse.ac.uk/ubs/pdf/dp17.pdf
1.The idea is to apply a standard quantile formula over the long-term horizon and then estimate VaR using estimates of the horizon-average values of the parameters on which the VaR depends.(P3倒數第二行)
2.we also suggest that the estimation of long-term VaR should not involve the square-root rule, which can be misleading , even for relatively short horizons , and especially misleading for longer ones.
(p4上面第三行)
3. the best approach is simply to take a view about the values of the mean long -term parameters involved. (p4)
4.positive return observations correspond to profits, and negative ones to losses. (p4倒數第二行)
5.ploughed back into (p4最後一行)
6.if we make the alternative assumption that log-returns are studnent-t distributed. (p5 上面第五行)
7.Pcl is the (1-cl) percentile(or critical percentile)of the terminal value of the portfolio after a holding period of h days.(p5 倒數第三行)
8.and thereafter remains negative and moves further and further away from zero(p6 倒數第八行)
9.the VaR peaks slowly and stays at or near its maximum value? which is bounded above by,and sometimes close to the value of the investment itself? (p6 倒數第五行)
10. The VaR approaches its ceiling asymptotically , and stays in that region indefinitely (p7倒數第四行)
11. the compounding of the mean return ..(P7最後一行)
12.this error rises with μ, becasuse the square-root formula makes no proper allow ance for the impact of the compounding of μ in the VaR.
(p10上面第四行)
13.and eventually changes sign(p11上面第一行)
14.the longer the time horizon on which the VaRs are based (p11 上面第二行)
15.if the variable concerned has a trend? how ever small? then the forecasted variable will eventually become implausible high or low.(p13f上面第三行)
16.and we may as well impose arbitrary values in the first place.(p13上面第九行)
17.they move around a zero trend(P13倒數八行)
18.perhasps some typical recent value?(P13倒數六行)
19.as the forecasted variable keeps returning toward its zero trend;
a horizon-average of day-to-day forecasts would give us much the same result as projecting some recent value over our horizon period and particularly so over longer horizons where the averaging-out process has more scope.(P13 倒數第五行)