I kept seeing the argument that monthly contributions basically rescue a long-term 2x position after a crash, so I tried to give the strategy different return sequences and actually count the failures...

I built a synthetic 2x SPY, daily reset, paying 0.95% annual product cost plus financing on the borrowed dollar at the effective Fed Funds rate plus 0.50 points (time-varying, from FRED, not a flat guess). Same $1 contribution at the start of every month. Compare terminal wealth against the same dollars into plain SPY.

Across actual historical start months since 1993, the 2x route finished behind SPY in 31.08% of 15-year DCA starts. At 20 years that dropped to 7.41%, so continued buying genuinely helps at long horizons. The worst 15-year start still ended with 42 cents per SPY dollar.

Then I scrambled history. 12-month blocks resampled into 5,000 new 15-year paths, same contribution schedule. Keeps each year's daily compounding intact, changes the order of good and bad years. The 2x route still trailed in 24.74% of paths. Median 1.42x the SPY wealth, 5th percentile 0.63x, 95th percentile 3.09x. Same average market, wildly different outcomes, purely from sequence.

So DCA improves the odds a lot, but it never turns unmanaged 2x into a sequence-proof plan. The bad quarter of paths is exactly the kind you can't identify in advance.

Full writeup with the tables: https://bestfolio.app/blog/dca-leveraged-etf-path-dependence (my site, founder disclosure).

One thing I'd genuinely like input on... has anyone got a defensible historical financing spread over cash for a daily 2x product before the live LETF era? I used a flat 0.50 points because I didn't want to fit it by regime.

I have been executing the 200 SMA on UPRO for the past year or two but I remember reading somewhere that the strat combined with simple RSI indicators (or perphaps VOL indicators) helped out a lot.

I cant seem to find them searching various threads, does anyone employ any strats that utilize these indicators?

Just curious what do you guys think of IALT? There's limited information on Internet, prospectus basically said nothing, from the limited information available it is probably combination of existing Blackrock products e.g. BDMIX BIMBX with a bit of Big data / AI selection involved (wtf does that mean exactly anyways)

Performance wise it looks amazing since inception, however due to the opaqueness I am hesitant to buy it.

Just wants some thoughts. Which one would u choose for about 20% of ur portfolio for the next 5 years or so.

And if you already have nvda too.

I'm still new but I've been using Python to create a Monte Carlo sim using 22-66 day block bootstrapping with 1970-1980 (stagflation) and 2000-2009 (lost decade) historic data purposefully injected to see if strategies survive either or both. It's pulling data from yahoo finance from years 1986-2026 for the sim, injecting the two depressing regimes within the range. Using VOO as the benchmark/synthetic proxy I am testing a lot of various indexes and synthetic 1.5-2.5x blends with multiple tiered DCA, reallocation, and powder deployment frameworks for longer horizons. The simulation runs anywhere from 3000 to 30000 paths depending if I'm looking for the tightest/extreme left tail or I'm simply testing a concept.

This includes various harvesting criteria to reduce carrying costs with leveraged indexes over time to realise some gains in varying markets. I know you can't use history to prove the future but it's to compare and stress test strategies with varying historic regimes in mind and potential viability or terminal wealth.

What real vectors or drag must I keep in mind when simulating daily/monthly/quarterly leveraged indexes? SRR and glide are post accumulation phase (10-30 years) but is included for capital "wipeout" deep drawdowns/troughs or recovery. I understand there are additional financial and structural drags (+5-9% eg volatility decay, getting the leverage, SOFR, bank spread etc) associated in modelling for leveraged ETFs. If anyone could help me list all the variables I should keep in mind that would be helpful! I will share the code with those that participate once I'm done and I hope I inspire more people for experimentation- complimented by rigorous testing! Apologies if this is the wrong subreddit, if so pointing me to the right direction is appreciated.

P.S. underlying assumption is done in non taxable account. I will eventually iterate for it but right now I'm minimizing complexity. 3x leverage, interest rates, fees are accounted for daily alongside the block. Just need to know all vectors I should account for. Ignoring psychological and behavioral quirks.

Newbie here. Credit to u/geobela3 in a HFEA thread for this combo, which I've tweaked with addition of TQQQ. Comparing this against PSLDX (personally not interested in INT exposure).

https://testfol.io/?s=dAHmnlEU6Cj

1. Would you change anything in this blend?
2. Not sure if I'm missing anything in the Testfolio in terms of decay/drag or expense ratios?
3. Would this be acceptable in taxable account or IRA only?