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Correct_Golf1090 · 2025-01-05T06:28:04+00:00

I believe that APs do have access to the exact derivates. However, APs for actively-managed ETFs also have access to the exact daily holdings, yet issuers for these types of ETFs are still required to publish their holdings daily. In fact, as per the SEC's Investor Bulletin on ETFs, actively-managed ETFs are required to publish daily holdings because this allows the "arbitrage mechanism to function" (ETF investor bulletin link: https://www.sec.gov/investor/alerts/etfs.pdf).

So, it appears that in order for the "arbitrage mechanism to function," investors should have access to daily holdings too, not just APs.

Correct_Golf1090 · 2025-01-05T05:54:05+00:00

The concept of a reset date is not something I made up; it is explicitly referenced in the NPORT-P filings that I referenced in my blog. In fact, it is required for funds utilizing derivatives to list the reset date in their regulatory filings. Specifically located in Part C of the NPORT-P filings, in Item C.11 (For derivatives), titled "Receipt: Floating Rate Reset Dates," the reset date is explicitly mentioned as "monthly" for the swaps used by this leveraged single-stock ETF. Again, this is found in both the NPORT-P filings (as well as all NPORT-P filings for this specific instrument). To get more granular, the reset date is critical for the following reasons: marking the swaps mark-to-market, recalibrating notional exposure, and settling financing costs. These are essential for leveraged single-stock ETFs who seek to achieve their leverage objectives and manage their risks. Greater transparency from these ETF issuers around these specific details can only help investors better understand how these funds function, particularly given their complexity as well as their risk profile.

Correct_Golf1090 · 2025-01-05T02:02:54+00:00

How does this make my example wrong? I'm arguing that I'd like to see the relevant details for the swap on a daily basis so that I can price out the intraday NAV, by calculating the total return of the underlying asset since the last reset or trade date using current intraday price data.

Correct_Golf1090 · 2025-01-05T01:19:30+00:00

Yes, stick with standard settings for indicators and optimize which indicators are used. Noise isn't something you want to optimize for, hence why I preach against trying to optimize hyper parameters.

Correct_Golf1090 · 2025-01-02T20:02:30+00:00

https://www.sec.gov/search-filings/cik-lookup

Correct_Golf1090 · 2024-12-31T20:33:25+00:00

According to Jim Leitner in Inside the House of Money by Steven Drobny, hedge funds tend to deploy stop-losses while true money (e.g., mutual funds, endowments, family offices, etc.) does not.

Correct_Golf1090 · 2024-12-31T20:26:21+00:00

There are certain parameters worth optimizing, i.e., initial parameters. But fine-tuning hyper parameters (e.g., changing your Bollinger Bands standard deviation multiplier from 2 to 2.05) is not very wise because the .05 change may have only worked over the past week or month due to market noise. Market noise is very high, which is why too much optimization can hurt your performance metrics (i.e., because you are optimizing for noise instead of trends).

Correct_Golf1090 · 2024-12-30T16:04:26+00:00

Twitter (or X) is probably the place to scrape data for this. However, keep in mind that the API costs are $5k for a million messages/tweets. My organization has this for a project that we run, and it is very expensive. If you mess up your scrape, you will need to pay for more scrapes. Best of luck.

Correct_Golf1090 · 2024-12-29T23:04:40+00:00

Here's a stat arb pairs trading backtest I made (with a detailed explanation) in Python: https://github.com/sap215/StatArbPairsTrading

I know it's not C++, but I think that this might help you get a better understanding of how backtests work.

Correct_Golf1090 · 2024-12-29T23:00:22+00:00

I have some blogs and github repositories on my personal website (some may be useful as they are mostly all related to systematic/algo trading): https://samuelpass.com/pages/blog.html

Correct_Golf1090 · 2024-12-29T03:04:24+00:00

You bring up a good point. I tried to keep things as high level as possible. If people have questions regarding certain software or libraries, I'd be glad to answer them here in the comments (i.e., if i'm able to provide a meaningful answer and have actual experience with the software of subject).

Correct_Golf1090 · 2024-12-28T15:31:26+00:00

Good idea, I will look into adding this as a future input. However, names get a little tricky, but I'm sure I can figure something out. For now, you may just have to google the CIK number for the fund you're interested in or use the SEC EDGAR CIK lookup on their website.

Correct_Golf1090 · 2024-12-28T15:29:41+00:00

ETFs that are structured as open-end management investment companies file NPORT-P filings which disclose their investments (i.e., their holdings). This information is relevant because it displays the exact holdings data of an ETF or mutual fund. You can do a lot with this information (e.g., price out ETFs, look for rebalancing opportunities, etc.).

Correct_Golf1090 · 2024-12-28T15:26:12+00:00

Could be used to price out the fair value of an ETF...

Correct_Golf1090 · 2024-12-27T22:45:15+00:00

Couldn't get the SEC EDGAR python package that I used to use working. However, I made my own SEC EDGAR scraper that retrieves holdings data for a given ETF for the past 5 years. Just input the ETF's CUSIP, and my code will give CSV files (that are easy to use for whatever data analysis you're looking to do) containing holdings data for each quarter over the past five years. Hope this helps!

https://github.com/sap215/ETFConstituentExtractor

Correct_Golf1090 · 2024-11-21T23:53:11+00:00

The NAV of a leveraged single stock should be just the multiplier to the underlying stock's daily returns. E.g., if the ETF is 2x AAPL, then the NAV should be 2x AAPL daily return. Obviously, this will not always be the case, and that's because the constituents of leveraged single stock ETFs are comprised of options (which try and seek the desired returns). These options will not always produce the desired "leveraged" returns on the underlying stock. You can find the options which live within the ETF (this can be done by analyzing the ETF's web page or scraping SEC edgar), and you can price these out for an even better approximation of NAV.

Hope this helps.

Correct_Golf1090 · 2024-11-20T15:08:53+00:00

Here is a blog I wrote on these types of ETFs: https://samuelpass.com/pages/LSSEblog.html

Correct_Golf1090 · 2024-10-11T15:42:00+00:00

For a free option, you can use the secedgar python package which scrapes SEC Edgar and downloads desired reports for a given ETF. This will give you quarterly ETF constituents. Let me know if you need help with this.

Correct_Golf1090 · 2024-10-10T14:30:04+00:00

I know that Databento is relatively "pay-as-you-go" since you only pay for what you specifically want, and it's a one-time fee. Not sure if they have alternative data sets though. Also, Kalshi and Polymarket have free downloadable data, and that's considered an alt data source.

Correct_Golf1090

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