Given two possibilities,
A. Factor death (zero expected returns)
B. Factor reversion (high expected returns)

What could help in either scenario?

Initial thoughts:
* Better execution
* Less aggressive trading
* Thoughtful turnover management
* Harvesting tax losses
* Lower AUM
Applications might not be as obvious as they seem.

For example, long-dated options have optically high spreads but reduce the need for aggressive vol targeting when it's most expensive to trade the underlying. They also make it possible to rebalance into dislocated assets.
Momentum can become much lower turnover and more tax efficient when rebalanced differently:

Implementing Momentum: What Have We Learned?


Shorting is more tax-efficient than it looks:

Taxes, Shorting, and Active Management
Some strategies can actually reduce turnover while simultaneously increasing expected returns when carefully implemented.

This is especially advantageous because these strategies (e.g. momentum, ST reversal) may also be anticorrelated to each other.

Lower turnover also means more patient trading, which in turn can lead to lower slippage.

So portfolio construction can have an even larger effect than what shows up in the backtest. And this relative benefit exists even in the case of factor death.

In the cases above, careful implementation starts with intuition rather than a backtest.

Strategies that are hard to intuitively understand may be less amenable to this kind of philosophical tinkering.

Rob Carver is a master of "think first, then build:"
The more constraints there are, the harder this becomes.

You can't harvest tax losses when they're trapped inside an impenetrable wrapper.

Anticorrelated strategies can't reduce each others' turnover when they're in separate funds.

A skilled manager is worth his weight in 🪙.
Even if you're highly constrained (no leverage, no derivatives, no stocks), there are still interesting questions to consider:

* Mutual funds vs. ETFs vs. CEFs
* Tax efficiency
* Fund factor loadings
* Commodities or not?
* Asset class weights
* Bond tenor
* Rebalancing
You can only backtest what you think of. The more random your thinking, the greater the risk of p-hacking... but the more conventional your thinking, the less new information the tests will give you.

The key might be to be different but in a focused way.

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More from @ReformedTrader

23 Jan
One way to be a liquidity provider is to be an endowment: no leverage and infinite time to wait for convergence.

Another is to be simultaneously diversified/hedged, such that divergence has a payoff and allows you to hold on to convergence trades with very high expected returns.
Read 4 tweets
22 Jan
How would diversification have done in 2020?

#1: SPY: 18% CAGR (-19% dd, 0.76 Sharpe, 0.89√2 Sortino)

#2: SPY, TLT, DBC, and VXZ (inverse vol): 20% CAGR (-4% dd, 2.34 Sharpe, 4.38√2 Sortino)

#2 did FIVE times better (Sortino) due to lower drawdowns.

portfoliovisualizer.com/test-market-ti…
Read 7 tweets
21 Jan
1/ Implementing Momentum: What Have We Learned? (Ross, Moskowitz, Israel, Serban)

"Live momentum portfolios are capable of capturing the momentum premium, even after expenses, trading costs, taxes, & other frictions associated with real-life portfolios."

papers.ssrn.com/sol3/papers.cf…
2/ "We decompose the performance differences between the live momentum strategies and the theoretical AQR Momentum Indices.

"We expect that trading costs and expenses will always be a drag on performance, but ‘smarter’ portfolio construction decisions should offset this."
3/ "Momentum's historical excess return is 1.0-1.5%/yr. Even if transaction costs were twice as high as realized, they may only put a small dent in performance.

"These results contrast with papers that estimates costs based on liquidity-demanding orders for immediate execution."
Read 8 tweets
21 Jan
...
2020's winners included
* Benn Eifert’s QVR Advisors (+77% ret/-12% dd)
* Covenant Total Volatility (+21%)
* Rotella Long Biased Vol (+20% ret/-1.5% dd)
* Artemis Vega (+15% ret/-10% dd)
* Logica (+15% ret/-7% dd)
* Quadriga (+13% ret/-35% dd)
...
Read 5 tweets
21 Jan
Pandemic-related papers (2021)
(I haven't read these yet, but the abstracts look interesting.)

Safety and Efficacy of the BNT162b2 mRNA Covid-19 Vaccine
nejm.org/doi/full/10.10…

Coronavirus vaccine-associated lung immunopathology-what is the significance?
ncbi.nlm.nih.gov/pmc/articles/P…
Nonlinear Effects of Mobility on COVID-19: Implications for Targeted Lockdowns
papers.ssrn.com/sol3/papers.cf…

Empirical Assessment of Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19
papers.ssrn.com/sol3/papers.cf…
COVID-19 ‘Immunity’ in Dhaka Slums: Do Genes Matter?
papers.ssrn.com/sol3/papers.cf…

Vaccine Clinical Trials and Data Infrastructure
papers.ssrn.com/sol3/papers.cf…

Monthly Suicide Rates During the COVID-19 Pandemic: Evidence from Japan
papers.ssrn.com/sol3/papers.cf…
Read 14 tweets
17 Jan
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."

papers.ssrn.com/sol3/papers.cf…
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:
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:
Read 22 tweets

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