AVUV QMOM 1:1 左右
仲係AVGV, 表現暫時差過VT少少
VFMF同AVGV差唔多
兩者都可以考慮
全市場指數投資/因子投資討論區 (2)
津路茶
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想問下如果想vt+因子，投資20-30年
係咪avdv+imom 好過avuv+qmom
Avdv估值更低，同要avuv升都要美國大型成長跌先大機會avuv 升？如果美國大型成長跌，會唔會avdv有更好報酬？
如果我覺得美國估值過高20-30年內一定有美國大回調（均值回歸），咁係咪直接買imom而唔買qmom，等美國動能反轉，資金有機返到imom？
呢個美國高估值嘅時機係咪買imom+avdv比較好？
謝謝
係咪avdv+imom 好過avuv+qmom
Avdv估值更低，同要avuv升都要美國大型成長跌先大機會avuv 升？如果美國大型成長跌，會唔會avdv有更好報酬？
如果我覺得美國估值過高20-30年內一定有美國大回調（均值回歸），咁係咪直接買imom而唔買qmom，等美國動能反轉，資金有機返到imom？
呢個美國高估值嘅時機係咪買imom+avdv比較好？
謝謝
Abstract:
We document and explain the sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about -0.50% to -1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests.
We document and explain the sharp performance deterioration of smart beta indexes after the corresponding smart beta ETFs are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about -0.50% to -1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests.