KEI based Strategy

Just a sample strategy, inspired and created in collaboration with Strongs

Wanted to start a collaboration thread and to spark your creativity on adding whatever ideas you're fancy to add on top of this framework.
As tips/ideas we were thinking to add:

Add a momentum-based ETF selection for the bull days (to select best mom etf from QQQ, FDN, etc.)
Add a momentum-based ETF selection for the bear days (to select best mom etf from TLT, TLH, etc.)
Try adding IN&OUT switch (with wait days)
Replace bull days with a Stock selection strategy

Below few info about the KEI indicator
Key Short—Term Economic Indicators. The Key Economic Indicators (KEI) database contains monthly and quarterly statistics (and associated statistical methodological information) for the 33 OECD member and for a selection of non—member countries on a wide variety of economic indicators, namely: quarterly national accounts, industrial production, composite leading indicators, business tendency and consumer opinion surveys, retail trade, consumer and producer prices, hourly earnings, employment/unemployment, interest rates, monetary aggregates, exchange rates, international trade and balance of payments. Indicators have been prepared by national statistical agencies primarily to meet the requirements of users within their own country. In most instances, the indicators are compiled in accordance with international statistical guidelines and recommendations. However, national practices may depart from these guidelines, and these departures may impact on comparability between countries. There is an on—going process of review and revision of the contents of the database in order to maximise the relevance of the database for short—term economic analysis.
For more information see: http://stats.oecd.org/OECDStat_Metadata/ShowMetadata.ashx?Dataset=KEI&Lang=en

Reference Data Set:

Hi Nicolas,

Both orders are filled because the data feed resolution is set to daily. Here you have two limit orders at 1.49 and 1.41, and the daily bar is most likely wide enough such that it contains both prices. Therefore, before you could cancel the other limit order, the algo would have already filled the other limit order since the price conditions have been met.

We suggest changing the data resolution to 'minute', which would result in a much narrower data bar, and this issue should disappear.

Hope this helps! Thanks for your support!

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Simone Pantaleoni INVESTOR

LesFlex Quantitative Nerd | June 2021

Here the framework algo

Upvote

2 people upvoted this

Peter Guenther INVESTOR

June 2021

Interesting project, looking forward to the discussion. Well done, Simone Pantaleoni and Strongs!

1 person upvoted this

Strongs INVESTOR

Mirko Vari | June 2021

Hi all guys, this is just a base from which to start. The starting idea is to also exploit the concept of in & out and the intersection of ROC by Vladimir . The LEI could actually be exploited for a dynamic selection of ETFs, essentially identifying phases of the economic cycle and then selecting groups of ETFs that perform best in that specific phase of the cycle.

New version with the fixes from Vladimir 😊

Vladimir INVESTOR

Simone Pantaleoni,
Completed as requested!

The second problem is that you have initialized the position in QQQ,
which is contrary to the main logic at the beginning of backtest.

To solve this. I define

	initial_asset = self.stock if self.mom.Current.Value > 0 else self.bond 
        if self.init:
            self.SetHoldings(initial_asset, 1)

To make self.mom visible on the chart changed self.MOM to self.MOMP

Here is "SIMON LesFlex" modified by Vladimir
with changes I mention above and some cosmetic changes.

Enjoy.

4 people upvoted this

The idea would be to turn the indicator like that

.ekz. INVESTOR

ThePrinters.io | June 2021

First of all, great work :)

I've had some time to look at this, and I want to be sure i'm interpreting it correctly...

We run our rebalancing logic every week, 30 mins after market open
If the Quandl KEI indicator is trending upward (positive MOMP), then we liquidate Bonds and go long Stocks
If the Quandl KEI indicator is trending downward (negative MOMP), and the KEI under 100, then we liquidate Stocks and go long Bonds

Questions:

I see we are tracking the SMA of 1 period, so we arent actually calculating a moving average. We're just plotting the value. Is this intentional, just for plotting sake? or should we actually be trying to smooth out the KEI with an SMA?
The KEI seems to be recalculated every Month (at most). So, do we actually need to check for rebalancing every week? Or are we using a weekly frequency just to make sure we catch the monthly change as soon as it happens?
How, exactly, does one interpret the KEI? i've read the description on the page, but it isn't very helpful. For example, why do we want KEI to be under 100? What does that value represent?

Hi .ekz. ! many thanks for appreciating it. :)

Let me try to answer your questions:
Questions:

I see we are tracking the SMA of 1 period, so we arent actually calculating a moving average. We're just plotting the value. Is this intentional, just for plotting sake? or should we actually be trying to smooth out the KEI with an SMA?
1. KEI is already pretty smoothed. I just use the SMA 1day trick to quickly address the value in the code easily (but indeed, isn't really “clean”)
The KEI seems to be recalculated every Month (at most). So, do we actually need to check for rebalancing every week? Or are we using a weekly frequency just to make sure we catch the monthly change as soon as it happens?
1. Exactly, just to be sure to catch every change (which occurs anyway montly)
How, exactly, does one interpret the KEI? i've read the description on the page, but it isn't very helpful. For example, why do we want KEI to be under 100? What does that value represent?
1. take a look at the link below :)

Perfect, Simone Pantaleoni. Thanks for this.

Hi guys!

As suggested, we have been working behind the scene on applying the concepts shared above about the different phases of the market. Based on that, we apply ETF-selection accordingly, out of a basket of sectorial ETFs (we kept a similar switch to shift to bond in case of possible market downturn using the leading indicator)

Some improvement on Total Return, sharpe and so on.
Feel free to work on this release, fix it in case I've made mistakes (here I rely on Vladimir as PeerReview :P ) and improve it (there's still something to optimize - but don't want to share all in once so… work on it and share your outcomes with us! :) )

KEI Leading Indicator Phases

Surely there is still a lot of work to be done, but this is definitely a great start. Levels for identifying the phases of the business cycle with associated ETF groups was presented. We await more ideas from you to improve it.

Frank Giardina INVESTOR

Great stuff Guys thanks for sharing. I have a question and a comment. I have a Quandl free account have not used it much. I plugged in my key and started looking at the algo. My question is how does the self.history statement get the Quandl data to sync up with the start of the algo? i see the request for the 1400 bars, so does the Quandl request use the start date of the algo as it start retrieval date? I see the data frame adjusting to the different start dates I tried. Any clarification greatly appreciated.

My comment is i have been following a youtube channel Hedgeeye. The gentleman who runs the channel is an ex-Hedge fund manager who also uses a macro view of investing. He uses inflation and gdp rates of change for his strategy much like this algo uses the KEI data as leading indicators.. He uses ETFs like this algo but also uses different styles based on his macro view of 4 Quadrants. Depending on the Quads as he calls them he picks the ETFs and the investment style (Momentum, V:alue, High Beta, Low Beta etc.)

GrowthInflationQuad 1acceleratingslowingQuad 2acceleratingacceleratingQuad 3slowingacceleratingQuad 4slowingslowing

A full explanation of his approach is on Hedgeeye.com, but here is a link to his strategy

https://app.hedgeye.com/insights/77156-chart-of-the-day-what-works-in-which-quad?type=macro

Frank

Sorry, the grid got messed up when i pasted it

Quad 1 Growth accelerating Inflation slowing
Quad 2 Growth accelerating Inflation accelerating
Quad 3 Growth slowing Inflation accelerating
Quad 4 Growth slowing Inflation slowing

Varad Kabade INVESTOR

July 2021

Hi Frank,
History method takes the StartDate as the anchor retrieves data before it for the requested period. Refer to the following source code.

keihist = self.History([self.kei], 1400)

returns the last 1400 bars of history but we have the option to pass start and end dates to the History method.

keihist = self.History([self.kei],self.StartDate-timedelta(100),self.StartDate-timedelta(10))

returns the historical data for custom 90 day period.
Refer to the attached backtest, which demonstrates both approaches just comment out any one.
Best,
Varad Kabade

Varad,

Thank you for the explanation now i understand

Frank Schikarski INVESTOR

August 2021

Hi there,

interesting stuff!!

Here are my 2 cents:

KEI data was Europe, is now Total to work together with US stocks.
The number of regimes is increased to 4 for rising and 4 for declining.
A regime plot is included: increasing = regime 1,2,3,4, and decreasing = regime 3.8, 2.8, 1.8, 0.8 so that the regime curve follows the momentum curve intuitively.
A benchmark bool is added using QQQ and TLT only.
The attached backtest does not include my personal Quandl code, so to reproduce you have to register yourself.

And the results using QQQ and TLT only:

Results using an amended version of Sector ETF's:

Results using an overfitted version of Sector ETF's:

Suggestions for the way forward:

Maybe the weighting of ETF could be done from a preselection based on the regime, plus a dynamic based on their actual performance.
Also, further ETF such as SPY growth / SPY value could be included.
I found a note that this KEI has a delay of 2 months, so it needs to be confirmed if it can be used for trading. Maybe an addition would be possible using High-Yield Spread:

Have fun,

Tom Penrose INVESTOR

Expanding on Frank's work, I've added to the number of assets allocated depending on the regime.

I've attempted to replicate an asset allocation chart that I have which tells you where you should put your money depending on the trajectory of the economy.

For example, in a scenario of better than expected growth forecasted, it suggests allocating to 37% US equities, 18% non-US equities, 25% US-fixed income, 3% non-US fixed income, 13% alternative investments, and keeping 4% cash.

This doesn't translate perfectly to this strategy but I've done a crude implementation that follows more ETF's weighted based on this chart. For the US-equities component I've maintained the same sectors suggested in the previous version, only with different weighting.

The optimal implementation of this version of the strategy in my opinion would be to use universe selection to choose the best companies in each index, rather than following a whole sector. I think this would increase performance dramatically. Unfortunately, I'm not advanced enough to do this sort of dynamic universe selection.

LesFlex Quantitative Nerd | August 2021

Thanks to Frank Giardina and Tom Penrose for the good work and for moving the thread forward!

You're going on the exact direction I was meant to drive this discussion, when we've started it :)
I've been a bit busy lately on other projects, but next step will be exactly as Tom outlined, about stock-selection to pick up best 4-5 stocks for each sector.
Challenge there is to make the code decently quick, so I think a quite strict pre-selection of stocks will be needed

I think we got the wrong Frank, I made some comments and certainly want to help but Frank Schikarski did more meaningful work with his post.

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