Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for June 2022 (Final)

Momentum Investing Strategy (Strategy Overview)

Allocations for June 2022 (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.

Upside Down Beta Distributions for Value and Momentum?

Typically, value means unexciting low-beta stocks, and momentum means exciting high-beta stocks. Does “typically” mean always? In their September 2009 paper entitled “The Changing Beta of Value and Momentum Stocks”, Andrea Au and Robert Shapiro investigate the relationships between beta and value and between beta and momentum under varying stock market conditions. Using monthly beta distributions for value (based on book-to-market ratio) and momentum (based on prior 12-month return) sorts of the Russell 3000 stocks over the period December 1978 through March 2009, they conclude that: Keep Reading

Any Tools to Implement Value-Momentum Asset Class Allocation?

A reader asked: “Regarding ‘Combined Value-Momentum Tactical Asset Class Allocation’, have you developed any sort of screen or model that ranks value exactly as studied in the referenced paper (asset yield or earnings yield)?” Keep Reading

Why the Skip-period in Momentum Strategies?

A reader asked: “In reviewing your various posts on momentum-based trading, I noticed that many impose a one-month delay between momentum calculation and actual trade implementation. Is the effect/rational for this strategy adjustment referenced anywhere or is this something you can comment on?” Keep Reading

Have You Looked at ETFtradingstrategies.com?

A reader asked: “Have you ever looked at the work of David Vomund at ETFtradingstrategies.com?” Keep Reading

Mutual Fund Momentum Measure Fly-off

Which measure of mutual fund momentum best predicts future fund returns? In his August 2009 paper entitled “The 52-Week High, Momentum, and Predicting Mutual Fund Returns”, Travis Sapp examines the intermediate-term future performance of mutual funds ranked by: (1) nearness to the one-year high of the fund share net asset value; (2) prior six-month fund return; and, (3) fund sensitivity to stock return momentum. Using mutual fund returns for a broad sample of U.S. common stock funds and risk-adjustment data over the period 1970-2004, he concludes that: Keep Reading

Enhancing Asset Class Momentum with Downside Risk Avoidance?

A reader wondered about the value of combining momentum and downside risk avoidance for tactical asset class allocation, as follows:

“One of the methods described in The Ivy Portfolio by Mebane Faber is a simple momentum-based asset class rotation system that shifts monthly into the one, two or three highest performing asset classes based on their performance over an average of the prior 3, 6 and 12 months. Instead of using just the 3, 6 and 12 month prior returns, what if we used an asset class Ulcer Performance Index (UPI): UPI = average return over prior 3, 6 and 12 months / average Ulcer Index (UI) over prior 3, 6 and 12 months. Would this modification identify which asset classes are in low-volatility uptrends and therefore the biggest bang for the buck? Would this allow us to invest comfortably in the top two asset classes, or even the top one asset class, instead of the top three as recommended by Faber?”

Calculation of UI over a rolling interval across a long sample period is cumbersome. As a substitute for UI, we use a standard deviation of downside weekly returns over past intervals for three asset classes: S&P Depository Receipts (SPY), iShares Barclays 20+ Year Treasury Bond (TLT) and iShares Russell 2000 Index (IWM) , with historical data limited to July 2002 (by TLT). Every four weeks, we allocate funds to whichever of SPY, TLT or IWM has the highest ratio of prior return to prior downside standard deviation, or to 13-week Treasury bills (T-bills) if all three past returns are less than the T-bill yield. Using weekly adjusted closes for the asset class proxies over the period 7/31/02 through 8/21/09 (369 weeks or about 89 months), we find that: Keep Reading

Interplay of Beta with Momentum and Contrarian Investing

Does momentum trading (and its contrarian counterpart) work better for certain kinds of stocks? In their August 2009 paper entitled “Systematic Risk and the Performance of Mutual Funds Pursuing Momentum and Contrarian Trades”, Grant Cullen, Dominic Gasbarro, Gary Monroe and Kenton Zumwalt examine mutual fund trading activity and performance to measure the prevalence of and results for momentum and contrarian equity investing strategies. Using the quarterly stock holdings of 2,829 U.S. equity mutual funds and associated stock price data for the period 1991-2006, they conclude that: Keep Reading

A Few Notes on Quantitative Strategies for Achieving Alpha

In his 2009 book, Quantitative Strategies for Achieving Alpha, flagged by Jeff Partlow, author Richard Tortoriello “seeks to determine empirically the major fundamental and market-based drivers of future stock market returns” by testing over 1,200 alternative investment strategies. He believes “that the quantitative approaches outlined in this book can provide a proven way to generate investment ideas for the qualitative investor as well as a discipline that can help improve investment results.” Richard Tortoriello is an equity research analyst with Standard & Poor’s. The principal elements of the book are: Keep Reading

Momentum a Big Mistake?

Is chasing returns a bet on rational analysis or investor overreaction? In the June 2009 version of their paper entitled “Myopic Extrapolation, Price Momentum, and Price Reversal”, Long Chen, Claudia Moise and Xinlei Zhao compare expected and actual momentum returns and explore the detailed relationship between momentum/reversal returns and firm fundamentals. Using monthly stock return data and associated fundamentals for a broad sample of firms spanning 1985-2006, they conclude that: Keep Reading

Combining Momentum and Moving Averages for Asset Classes

A reader wondered about the value of combining momentum and simple moving average signals for asset class allocation, as follows:

  • Each month calculate the average momentum of each asset class over the prior 3, 6 and 12 months
  • Hold the top positions as long as they are also trading above their 10-month SMA (otherwise go to cash)

We test these rules using exchange-traded funds (ETF) as easily tradable asset class proxies. However, many ETFs have very short histories, greatly restricting any such test. We use S&P Depository Receipts (SPY), iShares Barclays 20+ Year Treasury Bond (TLT) and iShares Russell 2000 Index (IWM) as available asset classes, with historical data limited to July 2002 (by TLT). We use the 13-week Treasury bill (T-bill) yield as a proxy for the return on cash. Each month, we allocate funds to the one asset class with the highest average momentum over the prior 3, 6 and 12 months, unless the momentum leader is below its lagged 10-month SMA, in which case we put all funds into T-bills. Using monthly values for SPY, TLT, IWM and the T-bill yield over the period July 2002 through April 2009 (82 months), we find that: Keep Reading

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