The “Should we get rid of the GRE?” conversation and the “Should we pay undergrad RAs $15/hour?” conversation have three things in common that I think are really unfortunate — 🧵
Some musings about graduate admissions, standardized testing, etc while I wait for my coffee.... these are things that seem obvious? but are maybe not obvious?
— Dr. Paige Harden (@kph3k) December 2, 2020
More from Economy
1/ Trend Factor: Any Economic Gains from Using Information over Investment Horizons? (Han, Zhou, Zhu)
"A trend factor using multiple time lengths outperforms ST reversal, momentum, and LT reversal, which are based on the three price trends separately."
https://t.co/udkvsdw2Lz
2/ This resembles combining multiple measures of ST reversal, momentum, and LT reversal (forecasts determined by walking forward rather than using signs from the full sample).
Unlike normal moving average signals, these are *cross-sectional.* More below:
https://t.co/wkIFLg9jtK
3/ Unsurprisingly, the Trend factor formed by this approach outperforms benchmarks in terms of both Sharpe ratio and tail metrics. It's combining momentum with two factors that are negatively correlated to it AND using multiple specifications.
More here:
https://t.co/x8Tloz3iyL
4/ "Average return and volatility of the trend factor are both higher in recession periods. However, the Sharpe ratio is virtually the same.
"Interestingly, all of the factors still have positive average returns.
"Momentum experiences the greatest increase in volatility."
5/ "In terms of maximum drawdown and the Calmar ratio, the trend factor performs the best.
"The trend factor is correlated with the short-term reversal factor (35%), long-term reversal factor (14%), and the market (20%) but is virtually uncorrelated with the momentum factor."
"A trend factor using multiple time lengths outperforms ST reversal, momentum, and LT reversal, which are based on the three price trends separately."
https://t.co/udkvsdw2Lz

2/ This resembles combining multiple measures of ST reversal, momentum, and LT reversal (forecasts determined by walking forward rather than using signs from the full sample).
Unlike normal moving average signals, these are *cross-sectional.* More below:
https://t.co/wkIFLg9jtK

1/ Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference? (Goyal, Jegadeesh)
— Darren \U0001f95a (@ReformedTrader) June 18, 2019
"The difference between the performances of TS and CS strategies is largely due to a time-varying net-long investment in risky assets."https://t.co/CSIn3ujN2R pic.twitter.com/XHnVmIart4
3/ Unsurprisingly, the Trend factor formed by this approach outperforms benchmarks in terms of both Sharpe ratio and tail metrics. It's combining momentum with two factors that are negatively correlated to it AND using multiple specifications.
More here:
https://t.co/x8Tloz3iyL

1/ An Executive Summary (in Tweet form) of our new paper
— Adam Butler (@GestaltU) March 27, 2019
Dual Momentum \u2013 A Craftsman\u2019s Perspective
Download here: https://t.co/Y9GlGNohBg
Everything that follows in this thread is based on HYPOTHETICAL AND SIMULATED RESULTS. pic.twitter.com/9m5YJnTdtq
4/ "Average return and volatility of the trend factor are both higher in recession periods. However, the Sharpe ratio is virtually the same.
"Interestingly, all of the factors still have positive average returns.
"Momentum experiences the greatest increase in volatility."

5/ "In terms of maximum drawdown and the Calmar ratio, the trend factor performs the best.
"The trend factor is correlated with the short-term reversal factor (35%), long-term reversal factor (14%), and the market (20%) but is virtually uncorrelated with the momentum factor."
