Estrategias basadas en momentum

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Estrategias basadas en momentum

Mensajepor Dalamar » 29 Mar 2015 07:33

Vamos a analizar este interesantisimo estudio sobre momentum, que nos trae Mahdi Heidari de la Stockholm School of Economics.
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Re: Estrategias basadas en momentum

Mensajepor Dalamar » 10 May 2015 03:26

The simple Momentum Investing portfolios are formed monthly as follows:

MOM Decile EW MR = Highest decile of firms ranked on Momentum. Portfolio is equal-weighted and rebalanced monthly.
MOM (19/20) EW MR = Split the top decile ranked on Momentum in two. Keep the the 90%-95% highest Momentum firms. Portfolio is equal-weighted and rebalanced monthly.
MOM (20/20) EW MR = Split the top decile ranked on Momentum in two. Keep the the 95%-100% highest Momentum firms. Portfolio is equal-weighted and rebalanced monthly.
SP500 EW = S&P 500 equal-weight Total return

Takeaways:

Momentum investing has outperformed over the past 41 years.
Buying the “highest” momentum stocks (top 5%) has marginal effects (higher CAGR, lower Sharpe ratios).
ImageUploadedByTapatalk1431221136.337560.jpg
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Estrategias basadas en momentum

Mensajepor Dalamar » 10 May 2015 03:40

Combining Value and Momentum:

Here we want to combine Value and Momentum by sequentially sorting on the two variables.

First we will split the Momentum decile by Value.

Specifically, here are the 4 portfolios we will examine:

MOM Decile, high EBIT EW MR = Highest decile of firms ranked on Momentum, then split on Value (EBIT/TEV). We keep the top half when sorted on Value. Portfolio is equal-weighted and rebalanced monthly.
MOM Decile, low EBIT EW MR = Highest decile of firms ranked on Momentum, then split on Value (EBIT/TEV). We keep the bottom half when sorted on Value. Portfolio is equal-weighted and rebalanced monthly.
MOM (20/20) EW MR = Split the top decile ranked on Momentum in two. Keep the the 95%-100% highest Momentum firms. Portfolio is equal-weighted and rebalanced monthly.
SP500 EW = S&P 500 equal-weight Total return
Results are gross of management fees and transaction costs. All returns are total returns and include the reinvestment of distributions (e.g., dividends).

Here are the returns (1/1/1974-12/31/2014):

Momentum (and then Value) Investing Portfolio Results:

ImageUploadedByTapatalk1431221886.252888.jpg


Takeaways:

Taking the top decile on Momentum and splitting on Value (EBIT/TEV) improves Sharpe and Sortino ratios (Comparing Column 1 to Columns 2 and 3).
On a CAGR basis, the best bet is simply buying the top 5% of firm on Momentum.
Overall, this sequential sort (Momentum and then Value) does not drastically improve simple Momentum Investing returns.

Next we focus on splitting the Value decile by Momentum.

Specifically, here are the 4 portfolios we will examine:

EBIT Decile, high MOM EW MR = Highest decile of firms ranked on Value (EBIT/TEV), then split on Momentum. We keep the top half when sorted on Momentum. Portfolio is equal-weighted and rebalanced monthly.
EBIT Decile, low MOM EW MR = Highest decile of firms ranked on Value (EBIT/TEV), then split on Momentum. We keep the bottom half when sorted on Momentum. Portfolio is equal-weighted and rebalanced monthly.
EBIT (20/20) EW MR = Split the top decile ranked on Value (EBIT/TEV) in two. Keep the the 95%-100% cheapest firms. Portfolio is equal-weighted and rebalanced monthly.
SP500 EW = S&P 500 equal-weight Total return
Results are gross of management fees and transaction costs. All returns are total returns and include the reinvestment of distributions (e.g., dividends).

Here are the returns (1/1/1974-12/31/2014):

Value (and then Momentum) Investing Portfolio

ImageUploadedByTapatalk1431221833.669228.jpg


Takeaways:

Taking the top decile of Value firms and splitting on Momentum improves returns in general. This improves the CAGR, Sharpe and Sortino ratios (Comparing Column 1 to Columns 2 and 3).
Results are similar to other studies.
Overall, it appears that splitting Value by Momentum is a good strategy to follow!

However, such a strategy does require frequent rebalancing, as momentum works best if rebalanced more frequently. This will cause higher transaction costs relative to a long-term buy-and-hold Value strategy.

So an obvious question is the following — Why don’t we integrate momentum in to our Quantitative Value strategy?

The answer is simple: momentum doesn’t increase QV performance, in expectation.

Below, we explain why we do not incorporate momentum into our value algorithm.

Quantitative Value Index Universe Results:

Here we examine how splitting a Value portfolio by Momentum compares to the Quantitative Value results.

As explained here, the Quantitative Value process involves 5 steps. Step 4 requires us to sort firms based on their quality. However, what happens if we replace this step and sort firms by their past Momentum?

We answer this below. It is important to understand that the universe for the results above is slightly different than the results below, as the Quantitative Value process requires firms to have 8 years of data (which is not required above).

Specifically, here are the 4 (annually rebalanced) portfolios we will examine:

QV EW = Portfolio formed using the Quantitative Value process. Portfolio is equal-weighted and rebalanced annually.
QV (High MOM) EW = Portfolio formed using the first three steps of the Quantitative Value process. However, step 4 is changed to pick the top half of firms ranked on Momentum. Portfolio is equal-weighted and rebalanced annually.
QV (Low MOM) EW = Portfolio formed using the first three steps of the Quantitative Value process. However, step 4 is changed to pick the bottom half of firms ranked on Momentum. portfolio is equal-weighted and rebalanced annually.
SP500 EW = S&P 500 equal-weight Total return
Results are gross of management fees and transaction costs. All returns are total returns and include the reinvestment of distributions (e.g., dividends).

Here are the returns (1/1/1974-12/31/2014):

Quantitative Value Index Investing Portfolio Results (Annual Rebalance):

ImageUploadedByTapatalk1431221789.159674.jpg


Takeaways:

Similar to the results above, splitting the top 10% Value firms by Momentum is a good strategy (Comparing Column 2 to Column 3).
However, splitting firms by quality and keeping the top half (QV EW) is optimal when comparing CAGRs, Sharpe and Sortino ratios.
These portfolios are highly correlated.
However, since we know Momentum works best at a monthly rebalance frequency, let’s examine the same portfolios which are rebalanced monthly.

Specifically, here are the 4 (monthly rebalanced) portfolios we will examine:

QV EW MR = Portfolio formed using the Quantitative Value process. Portfolio is equal-weighted and rebalanced monthly.
QV (High MOM) EW MR = Portfolio formed using the first three steps of the Quantitative Value process. However, step 4 is changed to pick the top half of firms ranked on Momentum. Portfolio is equal-weighted and rebalanced monthly.
QV (Low MOM) EW MR = Portfolio formed using the first three steps of the Quantitative Value process. However, step 4 is changed to pick the bottom half of firms ranked on Momentum. portfolio is equal-weighted and rebalanced monthly.
SP500 EW = S&P 500 equal-weight Total return
Results are gross of management fees and transaction costs. All returns are total returns and include the reinvestment of distributions (e.g., dividends).

Here are the returns (1/1/1974-12/31/2014):

Quantitative Value Index Investing Portfolio Results (Monthly Rebalance):

ImageUploadedByTapatalk1431221688.862478.jpg


Takeaways:

Rebalancing the Value portfolios monthly increases returns. This has been found in other studies. However, this should increase trading costs (which are not included here), and does increase drawdowns.
Similar to the results above, splitting the top 10% Value firms by Momentum is a good strategy (Comparing Column 2 to Column 3).
However, splitting firms by quality and keeping the top half (QV EW MR) is optimal when comparing CAGRs, Sharpe and Sortino ratios.
The last reason we prefer the QV strategy is shown in the table below:

QV and Mom correlations

ImageUploadedByTapatalk1431221740.249343.jpg


As is shown in the table, the correlation between QV and a generic Momentum portfolio is 57.40%, while the cheap firms split by Momentum have a slightly higher correlation (63.44%). All else being equal, we would prefer to have a lower correlation to Momentum.

Fuente: http://blog.alphaarchitect.com/2015/05/ ... ng-part-2/
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Re: Estrategias basadas en momentum

Mensajepor Dalamar » 16 May 2015 05:15

Enhanced Momentum basado en:

First, one notices that the regular momentum strategy turns $1 into $29,706 from 1927-2011, a large increase from a simple market return B&H portfolio ($2,107). The enhanced momentum strategy turns a $1 investment in 1927 into$9,685,301 in 2011, which is more than 325-fold the traditional momentum strategy. However, the enhanced momentum has relatively higher volatility than the traditional momentum (as sown in the Table 3 below). To address this issue the authors apply risk management methods by Daniel and Moskowitz (2014) and Barroso and Santa-Clara (2015), which generate even better performances. These techniques are described below:

Barroso and Santa-Clara (2015) - http://docentes.fe.unl.pt/~psc/MomentumMoments.pdf: scale the exposure of momentum to have constant risk/ target level of volatility over time. In their paper, the authors pick a target of an annualized volatility of 12%. This is labeled Enhanced Momentum*.

Daniel and Moskowitz (2014) - http://www.columbia.edu/~kd2371/papers/ ... /mom10.pdf: use the projected momentum premium and volatility to generate dynamic weights. This is labeled Enhanced Momentum**.
As we can see, using the risk management rules turns a $1 investment in 1927 into $69 million for Enhanced Momentum* and $116 million for Enhanced Momentum**. Not bad!
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Re: Estrategias basadas en momentum

Mensajepor Dalamar » 16 May 2015 08:09

Aqui tenemos una estrategia basada en Momentum que JP Morgan esta comercializando en su ETF: JPMORGAN US SECTOR ROTATOR INDEX ETF - http://www.globalxfunds.com/SCTO/IC

Podemos ver que la rentabilidad es un poco mejor que la del S&P 500 pero que si contamos dividendos ya no es tan buena (comisiones e impuestos extra...), la gran ventaja que tiene es que la Volatilidad Maxima es del 20%, por lo que podriamos hacer una variacion apalancada bastante interesante, pero tendriamos que hacer un backtesting con ETFs apalancados o ver como nos podemos apalancar nosotros.

US Dynamic Core Strategy: SCTO seeks to tactically participate in bullish markets through a momentum-based US sector rotation strategy, while defensively shifting up to 100% of its exposure to short-term treasuries in volatile or declining markets.


    strategy SPY
    Annualized Return 0.118 0.089
    Annualized Std Dev 0.125 0.193
    Annualized Sharpe (Rf=0%) 0.942 0.460
    Worst Drawdown 0.165 0.552
    Calmar Ratio 0.714 0.161
    Sortino Ratio (MAR = 0%) 1.347 0.763
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Re: Estrategias basadas en momentum

Mensajepor Dalamar » 05 Jun 2015 16:36

Vamos a ver la siguiente estrategia Momentum and Markowitz: A Golden Combination (2015) by Keller, Butler, Kipnis basada en el documento adjunto.

Mean-Variance Optimization (MVO) as introduced by Markowitz (1952) is often presented as an elegant but impractical theory. MVO is "an unstable and error-maximizing" procedure (Michaud 1989), and "is nearly always beaten by simple 1/N portfolios" (DeMiguel, 2007). And to quote Ang (2014): "Mean-variance weights perform horribly… The optimal mean-variance portfolio is a complex function of estimated means, volatilities, and correlations of asset returns. There are many parameters to estimate. Optimized mean-variance portfolios can blow up when there are tiny errors in any of these inputs...".

In our opinion, MVO is a great concept, but previous studies were doomed to fail because they allowed for short-sales, and applied poorly specified estimation horizons. For example, Ang used a 60 month formation period for estimation of means and variances, while Asness (2012) clearly demonstrated that prices mean-revert at this time scale, where the best assets in the past often become the worst assets in the future.

In this paper we apply short lookback periods (maximum of 12 months) to estimate MVO parameters in order to best harvest the momentum factor. In addition, we will introduce common-sense constraints, such as long-only portfolio weights, to stabilize the optimization.

We call our momentum-based, long-only MVO model Classical Asset Allocation (CAA) and compare its performance against the simple 1/N equal weighted portfolio using various global multi-asset universes over a century of data (Jan 1915-Dec 2014). At the risk of spoiling the ending, we demonstrate that CAA always beats the simple 1/N model by a wide margin.
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Re: Estrategias basadas en momentum

Mensajepor Dalamar » 07 Jun 2015 12:29

He encontrado unas cuantas estrategias basadas en Momentum que creo conviene analizar detalladamente y uno por una en su propio hilo, por lo que he creado un subforo para estrategias basadas en Momentum: momentum-f129/
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