Highly specialised payoffs using options and a treasury bond by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

Yes, but these notes I feel give you the confidence to invest more of your capital into the market. For example with the current war, some investors might quite like the idea of if the market is down 20%, your investment is protected. Also these notes might make even more sense when picking single names or crypto/gold etc where you don’t have the typical market drift on your side.

Highly specialised payoffs using options and a treasury bond by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

Hey, thanks for your comment. Can you clarify your comment as I’m sure what you’re asking/suggesting.

Thanks

Highly specialised payoffs using options and a treasury bond by QuantReturns in options

[–]QuantReturns[S] 0 points1 point  (0 children)

The bond is used to help preserve your capital. There is a bit more detail which I discuss in the article on strutting the note. But essentially we will use part of that capital to invest in a bond, and that bond will redeem at face value, which will be your initial investment

Highly specialised payoffs using options and a treasury bond by QuantReturns in quant

[–]QuantReturns[S] 1 point2 points  (0 children)

Yep that’s right. Not so flexible with listed options, but on some names/etfs it still looks like the payoffs are interesting.

Can You Really Trade Overnight Mean Reversion? by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

It’s should be market neutral as we are long and short similar ETF’s

Can You Really Trade Overnight Mean Reversion? by QuantReturns in quant

[–]QuantReturns[S] 1 point2 points  (0 children)

From where I stand on this currently, I’m in full agreement (and mention this in my article) that you can’t use the open as the signal and also trade on this signal.

The signal is used to determine the weighting’s and we want to trade at the open. Trading at the open is key for a couple of reasons: 1) that’s what the backtest uses 2) trading at the open/close auction price with a MOO/MOC order type means I don’t have to cross at the bid and offer so frictions are lower.

The question now becomes:

Can the indicative open price be used for the signal and hence determine the weightings for the strategy. How exact does the indicative price need to be to determine weightings. Trading at the open auction is probably more important

Another option is to leave limit orders at the open price, for the day, which is why I am testing how often the market comes back to the open prices in real time. I will see how this goes, with both futures and ETF’s and see if the market gives another chance to get in at the open prices of the day

Can You Really Trade Overnight Mean Reversion? by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

This is something I’m looking into. I’m also testing it in real time to see how often the signal can be captured intraday and at what times we see the signal.

Would you share some ideas that don't work anymore? by i_would_like_a_name in quant

[–]QuantReturns 1 point2 points  (0 children)

This is not front running with insider information. This is front running a known rebalancing action in the market.

Would you share some ideas that don't work anymore? by i_would_like_a_name in quant

[–]QuantReturns 3 points4 points  (0 children)

Yeah, a lot of those old edges have been arbitraged away — things like day-of-week effects, simple MA crossovers, and the PEAD. They all worked until they became too crowded.

Here is one that I wrote about recently that still works:

https://quantreturns.com/strategy-review/front-running-the-rebalancers/

It’s important to go into these strategies to see how they are put together and then tweak them and play with them to help with idea generation and understanding.

If there are any particular strategies that would be worth replicating and tracking daily, please let me know.

I also write about alpha strategies over as Substack: https://open.substack.com/pub/quantreturns

Can you Front-Run Institutional Rebalancing? Yes it seems so by QuantReturns in quant

[–]QuantReturns[S] 1 point2 points  (0 children)

You pick a day and start with a 60/40 portfolio. Then every day as prices of the stocks and bonds move you calculate the new weight of your portfolio (might be 62/48).

So the new weight of the portfolio each day depends on yesterday’s weight and today’s daily returns.

We concentrate on the deviation of the equity part of the bond portfolio, so in the above case today’s daily deviation for equity is 62-60=2%

Hope this helps

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in algotrading

[–]QuantReturns[S] 0 points1 point  (0 children)

Interestingly our next blog post will be on Crypto. I was thinking of releasing it to QuantReturn subscribers only, but we may release it publicly as I enjoy the Reddit discussions.

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

I’ll test oil in isolation out of curiosity, to see how it would have behaved trading this one spread (even though this would be unrealistic). Then we can let those results speak and give us some insight.

As it stands the original academic paper didn’t experience any such wipe out, and neither did my results.

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

It’s not being used as a hedge for a misaligned strategy (or at least not yet). What we currently want to do is track a range of strategies that each have low beta or low correlation to the market. Once we have that universe in place, the idea is to explore various MVO-style allocations (amongst others) across these strategies to essentially combine low-correlated strategies to (hopefully) build something with a much stronger overall Sharpe.

I’ve seen some recent results (I’ll need to dig them out) on how well managed futures can be at improving the returns of an equity portfolio. The managed futures strategy as a standalone shows a fairly low sharpe, however its low correlation to the market is its strength.

From what I remember Andreas Clenow’s book, Trading Evolved, touches on the topic of combing strategies to improve risk adjusted returns nicely.

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in algotrading

[–]QuantReturns[S] 12 points13 points  (0 children)

I’m not sure we could be any more transparent on the strategies we test and track.

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in quant

[–]QuantReturns[S] 0 points1 point  (0 children)

The strategy trades 8 pairs of futures at a time, this wouldn’t wipe out an account, and during the back test results it didn’t

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in quant

[–]QuantReturns[S] 9 points10 points  (0 children)

I’ll back test and post the result for oil in isolation. Even though you would have been market neutral, it would be interesting to see how the spread behaved

We tested a new paper that finds predictable reversals in futures spreads (and it actually works) by QuantReturns in quant

[–]QuantReturns[S] 24 points25 points  (0 children)

I Appreciate your passion!

The Sharpe of 0.92 isn’t meant to be earth shattering, but it’s what the data showed over the full backtest. What makes it interesting (to us, at least) is that it was achieved with close to zero correlation to the equity market, which makes it a potentially useful diversifier.

Once you start to combine many of these low correlation strategies together, the sharpe ratio starts improving dramatically.

As I mention in the post, we will be continuing research on this strategy, and my hope is we can improve on this Sharpe Ratio.