{"id":672,"date":"2016-05-02T13:09:32","date_gmt":"2016-05-02T13:09:32","guid":{"rendered":"http:\/\/quantpedia.com\/?p=672"},"modified":"2019-08-22T05:48:06","modified_gmt":"2019-08-22T05:48:06","slug":"quantpedia-update-2nd-may-2016","status":"publish","type":"post","link":"https:\/\/vvv.quantpedia.com\/es\/quantpedia-update-2nd-may-2016\/","title":{"rendered":"Quantpedia Update – 2nd May 2016"},"content":{"rendered":"

\n\tNew strategies:<\/u><\/strong><\/p>\n

\n\t#305 – Multi-Asset Market Breadth Momentum<\/strong><\/p>\n

\n\tPeriod of rebalancing:<\/strong> monthly
\n\tMarkets traded: <\/strong>equities, commodities, bonds, REITs
\n\tInstruments used for trading:<\/strong> ETFs
\n\tComplexity:<\/strong> Simple strategy
\n\tBactest period:<\/strong> 1993-2015
\n\tIndicative performance:<\/strong> 10.50%
\n\tEstimated volatility:<\/strong> 7.90%
\n\tSource paper:<\/strong><\/p>\n

\n\tKeller, Keuning: Protective Asset Allocation (PAA); A Simple Momentum-based Alternative for Term Deposits<\/strong>
\n\thttp:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2759734<\/a>
\n\tAbstracto:
\n\tSince the financial crisis of 2008 and the recent (end of 2015) pull back, investors are searching for less risky investments. Therefore, there is a growing demand for low risk\/absolute return portfolios. In this paper we describe a simple dual-momentum model (called Protective Asset Allocation or PAA) with a vigorous “crash protection” which might fit this bill. It is a tactical variation on the traditional 60\/40 stock\/bond portfolio where the optimal stock\/bond mix is determined by multi-market breadth using dual momentum. We backtested the model with several global multi-asset ETF-proxies. Starting from Dec 1970 allows us to investigate the behavior of PAA in periods with rate hikes as well. The in-sample (Dec 1970-Dec 1992) and out-of-sample returns of the most protective variant of our PAA strategy satisfy our absolute return requirement without compromising high returns. This makes PAA an appealing alternative for a 1-year term deposit.<\/p>\n

\n\t#306 – Trading VIX ETFs v2<\/strong><\/p>\n

\n\tPeriod of rebalancing:<\/strong> daily
\n\tMarkets traded: <\/strong>equities
\n\tInstruments used for trading:<\/strong> ETFs
\n\tComplexity:<\/strong> Simple strategy
\n\tBactest period:<\/strong> 2006-2014
\n\tIndicative performance:<\/strong> 69.00%
\n\tEstimated volatility:<\/strong> 39.00%
\n\tSource paper:<\/strong><\/p>\n

\n\tBordonado, Molnar, Samdal: VIX Exchange Traded Products: Price Discovery, Hedging and Trading Strategy<\/strong>
\n\thttp:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2753300<\/a>
\n\tAbstracto:
\n\tThis paper investigates the most traded VIX exchange traded products (ETPs) with focus on their performance, price discovery, hedging ability and trading strategy. The VIX ETPs track their benchmark indices well. They are therefore exposed to the same time-decay (high negative expected returns) as these indices. This makes them unsuitable for buy-and-hold investments, but it gives rise to a highly profitable trading strategy. Despite being negatively correlated with the S&P 500, the ETPs perform poorly as a hedging tool; their inclusion in a portfolio based on S&P 500 will decrease the risk-adjusted performance of the portfolio.<\/p>\n

\n\tNew research papers related to existing strategies:<\/strong><\/u><\/p>\n

\n\t#1 – Asset Class Trend Following
\n\t#137 – Trendfollowing in Futures Markets
\n\t#143 – Momentum and Trendfollowing in Country Equity Indexes
\n\t#144 – Trendfollowing Effect in Stocks<\/strong><\/p>\n

\n\tHaghani, McBride: Return Chasing and Trend Following: Superficial Similarities Mask Fundamental Differences<\/strong>
\n\thttp:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2718428<\/a>
\n\tAbstracto:
\n\tReturn chasing is often cited as one of the primary behavioral foibles of investors, resulting in sub-par returns. Surprisingly, the literature does not provide a generally accepted and testable description of return chasing. This paper proposes a simple definition. It then describes how return chasing so defined differs from trend following and how return chasing explains the shortfall of the returns of active, market timing investors compared to static asset allocation strategies. Finally, it shows that if the trading flows of return chasers are large enough to impact prices, then return chasing provides a powerful explanation of the positive returns earned by trend following strategies, which alternative descriptions of return chasing, such as it is trend following but with too long of a horizon, do not provide.<\/p>\n

\n\t#14 – Momentum Effect in Stocks<\/strong><\/p>\n

\n\tSchmidt: Trading Strategies Based on Past Returns – Evidence from Germany<\/strong>
\n\thttp:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2721800<\/a>
\n\tAbstracto:
\n\tAmong the various strategies studied, only momentum investing appears to earn persistently non-zero returns. Over the total time period from 1965 to 2014, the classical momentum strategy based on performance over the past two to twelve months earned an average return of 1.57% per month (excluding microcap stocks and value-weight returns). In the most recent ten-year time period, it has been even larger: 2.27%, which is much larger than in the U.S. However, the profitability net of transaction costs appears weak because the strategy involves trading in disproportionately small stocks with high transaction costs, especially observed for the loser portfolio. A strategy that only concentrates on the winner portfolio and thus avoids potential problems associated with (short) selling the costly loser portfolio appears to earn strong and persistently abnormal profits, even after transaction costs.<\/p>\n

\n\tTwo additional related research papers have been included into existing free strategy reviews during last 2 week:<\/strong><\/u><\/p>\n

\n\t#129 – Dollar Carry Trade<\/strong><\/p>\n

\tShehadeh, Erdos, Li, Moore: US Dollar Carry Trades in the Era of 'Cheap Money'<\/strong>
\n\thttp:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=2765552<\/a>
\n\tAbstracto:
\n\tIn this paper, we employ a unique dataset of actual US dollar (USD) forward positions against a number of currencies taken by so-called Commodity Trading Advisors (CTAs). We investigate to what extent these positions exhibit a pattern of USD carry trading or other patterns of currency trading over the recent period of the ultra-loose US monetary policy. Our analysis indeed shows that USD positions against emerging market currencies are characterised by a pattern of carry trading. That is, the USD, as the lower yielding currency, is associated with short positions. The payoff distributions of these positions, moreover, are found to have positive Sharpe ratios, negative skewness and high kurtosis. On the other hand, we find that USD positions against other advanced country currencies have a pattern completely opposite to carry trading which is in line with uncovered interest parity trading; that is, the lower (higher) yielding currency is associated with long (short) positions.<\/p>\n

\n\t#21 – Momentum Effect in Commodities<\/strong><\/p>\n

\tBianchi, Drew, Fan: Microscopic Momentum in Commodity Futures<\/strong>
\n\thttps:\/\/www120.secure.griffith.edu.au\/research\/file\/0a572b95-132b-419d-9a71-310420fad143\/1\/2015-10-microscopic-momentum-in-commodity-futures.pdf<\/a>
\n\tAbstracto:
\n\tConventional  momentum strategies  rely  on 12 months of past returns for  portfolio formation. Novy-Marx  (2012)  shows that the intermediate  return  momentum strategy formed  using only twelve to  seven  months  of returns prior  to  portfolio  formation significantly outperforms the recent return momentum formed using six to two month returns  prior. This  paper proposes a more granular strategy  termed  ‘microscopic momentum’, which further decomposes the intermediate and recent return momentum into  single-month  momentum components. The  novel  decomposition  reveals that a microscopic  momentum  strategy  generates  persistent  economic profits  even  after controlling   for   sector-specific   or month-of-year   commodity   seasonality   effects. Moreover, we show that the intermediate return  momentum in the commodity  futures must  be  considered largely  illusory, and all 12  months of  past  returns play  important  roles in determining the conventional momentum profits.<\/p>","protected":false},"excerpt":{"rendered":"

\n\tTwo new strategies have been added:<\/p>\n

\n\t#305 – Multi-Asset Market Breadth Momentum
\n\t#306 – Trading VIX ETFs v2<\/strong><\/p>\n

\n\tTwo new related research papers have been included into existing strategy reviews. And two additional related research papers have been included into existing free strategy reviews during last 2 weeks.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-672","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/672","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/comments?post=672"}],"version-history":[{"count":0,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/posts\/672\/revisions"}],"wp:attachment":[{"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/media?parent=672"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/categories?post=672"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vvv.quantpedia.com\/es\/wp-json\/wp\/v2\/tags?post=672"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}