Amazing paper related to several momentum strategies Thursday, 28 May, 2015

#2 - Asset Class Momentum - Rotational System
#3 - Sector Momentum - Rotational System
#8 - FX Momentum

#14 - Momentum Effect in Stocks

#15 - Momentum Effect in Country Equity Indexes

Authors: Geczy, Samonov

Title: 215 Years of Global Multi-Asset Momentum: 1800-2014 (Equities, Sectors, Currencies, Bonds, Commodities and Stocks)

Link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2607730

Abstract:

Extending price return momentum tests to the longest available histories of global financial asset returns, including country-specific sectors and stocks, fixed income, currencies, and commodities, as well as U.S. stocks, we create a 215-year history of multi-asset momentum, and we confirm the significance of the momentum premium inside and across asset classes. Consistent with stock-level results, we document a large variation of momentum portfolio betas, conditional on the direction and duration of the return of the asset class in which the momentum portfolio is built. A significant recent rise in pair-wise momentum portfolio correlations suggests features of the data important for empiricists, theoreticians and practitioners alike.

Notable quotations from the academic research paper:

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"We set out to create and examine the longest possible history of the global asset momentum effect to better understand its time-series properties, and to better explain the general characteristics already discovered in more recent history. In addition, observation of momentum “crashes” (Daniel and Moskowitz (2013)) in any given asset class would be useful since, while they appear in recent experience, they do so rarely. We find that they are relatively more frequent before the second half of the 20th century, creating a potential underestimation of the inherent risk associated with the premia if only 1950 - present be considered.

The first contribution of this study is the creation of a long-run dataset of global financial asset return histories back to 1800. Using Global Financial Data databases and additional data available through Bloomberg, we create an expanded dataset going back to 1800 which includes 47 country equity indices, 48 currencies (including Euro), 43 government bond indices, 76 commodities, 301 global sectors, and 34,795 U.S. stocks from Geczy and Samonov (2013).

The second contribution of this study is the extension of the price momentum factor history back to 1800 for this broad and extended sample of assets, both within and across six asset classes. We test for the cross-sectional momentum effect on the mostly untested monthly data from 1800 to 2014.

We document that on average, since 1800, momentum effect appears significant in all asset classes, except in commodity spot prices where it is significantly opposite.2 We plot the average of six intra-asset class (country equities, currencies, country government bonds, commodities, global sectors, U.S. stocks) plus one cross-asset class (incorporating stocks, currencies, bonds, and commodities) momentum top- and bottom-third portfolios’ 10-year rolling and log-cumulative excess returns. Generating a 215-year history of global multi-asset class price momentum (Figure III), we document that the momentum return is consistently significant in each asset class, across asset classes, and in combination.

The third contribution of this study is the replication of the dynamic beta property of momentum portfolios. We confirm that the long/short momentum portfolios exhibit significant variation of beta to the average return of the corresponding asset class from which portfolios are formed, consistent with Grundy and Martin (2001) and Daniel and Moskowitz (2013). This effect is present in each of the six asset classes and in the cross-asset class momentum. Further, we explore the relation between momentum portfolio betas and the sign and duration of the trailing market state, resulting in conclusions consistent with Geczy and Samonov (2013) and generalized to the six asset classes. Specifically, the longer an up or down market state persists, the larger the absolute value of the momentum portfolio beta, creating a dynamic risk profile of momentum over a given market cycle.

Finally, a number of additional observations become possible from the long-run data. First, we observe strong mean reversion in commodity spot prices, an effect which is very persistent over the entire sample. The effect is especially strong in the commodities that do not have futures data, while it deteriorates in the commodities that do have a futures contract – adding evidence to the research on financialization of commodity markets (Hamilton and Wu (2012), Basak and Pavloval (2013), Corbet and Twomey (2014), Van Hemert (2014)). Second, we test for the short-run and long-run reversal effects and find consistent evidence of long-run reversion and short-run continuation, with the exception of the U.S. stocks, which experience a short-run reversal (consistent with Asness, Moskowitz and Pedersen (2013)). Third, we are able to compare momentum to its time-series cousin, the trend indicator, which is gaining increasing popularity in institutional and retail portfolios (Han and Zhou (2012), Clare et al. (2012), Hurst et al. (2012), Faber (2013), Antonacci (2014), Lemperiere et al. (2014)).We find that when a comparable definition is used, momentum outperforms trend, yet both remain highly significant. Finally, we document two additional versions of momentum effects: first we observe momentum in the momentum time-series themselves, consistent with style-timing literature (Chen De Bondt (2004) and Kim (2010)); and second, we observe that country bond momentum is cross-sectionally priced not only it the bond market but also in the country equity market, similar to Lee, Naranjo and Sirmans (2014)."


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