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Momentum Investing Strategy (Strategy Overview)

Allocations for June 2020 (Final)
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Momentum Investing

Do financial market prices reliably exhibit momentum? If so, why, and how can traders best exploit it? These blog entries relate to momentum investing/trading.

Combining Momentum and Roll Return Signals for Commodity Futures

Does combining two commodity futures trading signals shown to be effective in prior research, momentum and roll return (term structure), improve on both? In the May 2008 version of their paper entitled “Tactical Allocation in Commodity Futures Markets: Combining Momentum and Term Structure Signals”, Ana-Maria Fuertes, Joelle Miffre and Georgios Rallis measure the combined value of momentum and roll return signals in the design of commodity futures trading strategies. They test combinations that iteratively buy backwardated (positive roll return) winners and short contangoed (negative roll return) losers. Using daily closing prices on the nearby, second nearby and distant contracts for 37 commodities as available over the period January 1979 through January 2007, they find that: Keep Reading

Momentum Returns for Large Caps

Are momentum trading strategies reliable and economically significant after trading frictions for large-capitalization stocks? In his November 2006 paper entitled “Alpha Generating Momentum Strategies”, Gregor Obrecht test 32 momentum trading strategies on large-capitalization U.S. stocks. The strategies encompass all combinations of: formation periods of three, six, nine and 12 months; wait periods of zero months and one month; and, holding periods of three, six, nine and 12 months. Using monthly returns for S&P 100 stocks over the period 12/85-8/06, he concludes that: Keep Reading

Exploiting Industry Momentum Via ETFs?

Industries arguably follow multi-month cycles of outperformance and underperformance. Can investors use industry/sector Exchange Traded Funds (ETF) to capture abnormal returns from industry momentum? In their June 2008 paper entitled “Can Exchange Traded Funds Be Used to Exploit Industry Momentum?”, Laurens Swinkels and Liam Tjong-A-Tjoe analyze the profitability of industry momentum strategies based on two sets of industry/sector ETFs. Using monthly ETF return data for the period July 2000 through November 2007, they conclude that: Keep Reading

Returns of High-Momentum Stocks Around Earnings Announcements

Do the attention-grabbing past returns of high-flying stocks produce pre-earnings announcement buying frenzies? In the April 2008 version of their paper entitled “Limited Attention and the Earnings Announcement Returns of Past Stock Market Winners”, David Aboody, Reuven Lehavy and Brett Trueman examine whether the limited time and resources of small investors explains a striking return pattern around the earnings releases of firms with extremely strong prior year price momentum. Using daily stock return data and earnings release/forecast news from the beginning of 1971 through the third quarter of 2005 for a broad sample of companies, they conclude that: Keep Reading

Classic Paper: Physical Inventories and Commodity Futures Returns

We occasionally select for retrospective review an all-time “best selling” research paper from the past few years from the General Financial Markets category of the Social Science Research Network (SSRN). Here we summarize the June 2007 paper entitled “The Fundamentals of Commodity Futures Returns” (download count over 2,500) by Gary Gorton, Fumio Hayashi and Geert Rouwenhorst. Commodity futures are derivative, short-maturity claims on real assets. In this paper, the authors apply the theory of storage to investigate relationships between the physical inventories of these assets and the returns to traders in the associated commodity futures. Using monthly data for over 30 commodity futures and associated physical inventories as available between 1969 and 2006 and data from the weekly Commodity Futures Trading Commission Commitments of Traders (COT) reports, they conclude that: Keep Reading

Momentum and Contrarian Commodity Futures Returns

Do commodity futures exhibit short-term momentum and long-term reversion, as do stocks? In the August 2006 version of their paper entitled “Momentum Strategies in Commodity Futures Markets”, Joelle Miffre and Georgios Rallis examine the profitability of 32 momentum (short-term continuation) and 24 contrarian (long-term reversal) strategies in commodity futures markets. The momentum strategies buy (sell) recently outperforming (underperforming) commodity futures and hold resulting long-short portfolios up to 12 months. The contrarian strategies buy (sell) the commodity futures that underperformed (outperformed) in the distant past and hold resulting long-short portfolios for periods of two to five years. All strategies trade liquid futures contracts with nearby maturities involving 31 commodities, unimpeded by short-selling restrictions often encountered in equity markets. Using futures contract price data spanning 1/31/79-9/30/04, they conclude that: Keep Reading

Institutional Trading, Returns and Strength of Anomalies

Are there exploitable differences in returns for stocks with heavy versus light institutional trading activity? In his March 2008 paper entitled “Trader Composition and the Cross-Section of Stock Returns”, Tao Shu analyzes the impact of institutional trading activity on the returns of individual stocks and on the strength of the momentum effect, post earnings-announcement drift (PEAD), the value premium and the investment effect. He calculates institutional trading activity at a quarterly frequency by dividing the aggregate absolute change in reported institutional holdings of a stock by the contemporaneous total quarterly trading volume for the stock. Using holdings data as reported via SEC Form 13F and associated stock trading volume and return data for the period 1980-2005, he concludes that: Keep Reading

The Pervasiveness and Persistence of Momentum

Is the momentum effect pervasive across different equity markets and persistent through different time periods? The overview of Chapter 3 in “Global Investment Returns Yearbook 2008: Synopsis”, which summarizes annual work performed by by Elroy Dimson, Paul Marsh and Mike Staunton for ABN AMRO, provides “findings from the longest momentum study ever undertaken.” Applying a 12-1-1 strategy (rank returns over the past 12 months, wait one month and then hold for one month until rebalancing) to very long-run UK data and more recent data for each of 17 country stock markets, they conclude that: Keep Reading

Fama and French Dissect Anomalies

Which stock return anomalies are trustworthy, and which are not? In the June 2007 draft of their paper entitled “Dissecting Anomalies”, Eugene Fama and Kenneth French apply both sorts and regressions to examine the robustness of the momentum, net stock issuance, accruals, profitability and asset growth anomalies. They note that sorts on an anomaly variable offer a simple picture of how average returns vary, but microcaps (a few big stocks) can dominate the performance of a sort-based equal-weighted (value-weighted) hedge portfolio. In addition, sorts are ill-suited to determinations of: (1) the exact relationship between an anomaly variable and returns, and (2) relationships among anomalies. They note also that extreme behavior by microcaps and outliers generally can distort inference from regressions. Using a robust set of firm data for a broad set of U.S. stocks allocated to three size groups (microcap, small and big) over the period 1963-2005, they conclude that: Keep Reading

Combined Value-Momentum Tactical Asset Class Allocation

Are value and momentum anomalies reliably present across international asset classes? If so, can investors exploit them to generate abnormal returns? In the December 2007 version of their paper entitled “Global Tactical Cross-Asset Allocation: Applying Value and Momentum Across Asset Classes”, David Blitz and Pim van Vliet examine global tactical asset allocation strategies across a broad range of asset classes based on both value (asset yield or earnings yield) and momentum (both short-term and long-term). These strategies weight asset classes according to volatility, with higher (lower) weights assigned to classes with lower (higher) volatilities. Using price and yield data for 12 international asset classes spanning January 1985 through September 2007, they conclude that: Keep Reading

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