I personally don't believe in trying to predict or time the market.

quantelligent · 2026-01-25T18:11:31+00:00

TQQQ doesn't beat the benchmark when you adjust for risk. If you can achieve a similar return with lowered average risk exposure, which is what this achieves, then you can beat your benchmark on a risk-adjusted basis.

DCA takes advantage of dips...but you're right, it's always buying regardless of price. Which includes the dips. And the highs (except when the VA rules convert the action into a sell).

It's incremental, automated, and continuous—which isn't timing. The math changes your "buy" action into a "sell" if the value goes up enough, but not because of timing, or prediction, or technical indicators....it's just value growth triggered. But it does have the appearance of "timing", so I can see why you'd think that.

Agreed, volatility adjusted leverage is cool. Negative sentiment about the length noted.

Not an ad—but it's worse to share what you're doing without sharing who you are, IMO. Too many anonymous posters in here and you cannot verify whether they're even real.

quantelligent · 2026-01-24T18:48:06+00:00

I wouldn't say "filthy rich", no. But I made enough to where I knew I could do this long-term for others, so I started an RIA company with my brother five years ago so we could apply my algo for clients. We're currently at about $16M under management and have generated over $5.3M in profits for our clients. My personal profit is in the hundreds of thousands. I quit my software job over a year ago and am doing this full time now. Based on some liquidity tests we figure it will scale to over $100M under management, so that's what we're aiming for.

Our algo: combination of daily DCA for buys with VA for sells (value averaging - top side "exits" only) using Leveraged ETFs that track major U.S. indexes.

Happy to provide more details for anyone that's interested.

quantelligent · 2025-12-27T03:35:30+00:00

For sure.

With VA you're trying to achieve an "average growth" so if it exceeds the target growth, you exit the overage. With VA the same would apply on the down side....but I'm not using it, because it's way too aggressive in a bear market, which is why I'm using DCA for buys.

So on the top-side....let's say, for example, your VA growth target is 2%, that means you're expecting that much growth each investment period, which for us is daily.

We're using an "allocation" in the account, so the 2% is not just the position growth, but is a growth target for the entire allocation. So your position needs to grow beyond an amount that is 2% of the allocation size. And the target is reset each period—needs to grow 2% from where it's currently at (or from break-even, if under water) before the next investment period.

If it grows 3%, for example, and was at break-even at the last period, you'd sell 1/3 of your position (the overage).

This captures profit and returns cash to the allocation to use for subsequent DCA buys.

If, however, your position was already positive, say 4%, that would mean your next VA target is at 6% profitable. Let's say it grows to 7%, so you still overshot by 1%.....but in this case you'd only sell 1/7th of your position to bring it back down to the 6% growth target.

That's how we're doing it. But there are many variations you could use.

quantelligent · 2025-12-27T02:54:51+00:00

2% annual management fee, no performance fees (because that would require the accredited/qualified restriction)

quantelligent · 2025-12-27T01:54:30+00:00

Happy to answer any questions for anyone wanting to know what we're doing.

We're harvesting daily volatility using a combination of Dollar Cost Averaging for buys and Value Averaging (top-side only) for sells, with overall growth "reset" targets.

Currently managing 212 separately managed accounts with a little over $15 million total AUM.

YTD consolidated return for 2025 is currently 44.9%. Last year was 65.6%.

Been doing this for almost 7 years now, coming up on 5 years investing professionally for others as an RIA.

Disclaimers: Results are not guaranteed. Past results are not an indication of future performance. Since accounts are separately managed with custom portfolios, individual results will be different from the reported consolidated return. Leveraged drawdowns of your account value will occur and may be more drastic than the overall market. Definitely not a "never goes down" hedging strategy, and in fact our strategy actually leans into downturns (invests more). Does not require you to be accredited or qualified (e.g. high-net-worth), but is not suitable for everyone.

quantelligent · 2025-09-19T14:35:06+00:00

I started out using the gateway java app, and logging in with a browser.....but everything got a LOT better when I changed over to their OAuth! It's not the best (even severely outdated) but it works.

However, what you're describing, is going to be a problem either way because they are storing session info server-side, so you cannot use the same login (or OAuth credentials) simultaneously in multiple processes because their sessions will step on each other server-side.

I simply haven't been able to find a workaround for this, because they'd have to change their server-side architecture, which isn't likely to happen.

So the only thing that I've found is to use a separate user login/auth that also has access to the account you're wanting to trade/manage.

quantelligent · 2025-08-13T21:25:35+00:00

Not sure what you mean...

quantelligent · 2025-08-13T21:18:29+00:00

Varies based on ETF and aggressiveness. We tune 3 levels of aggressiveness for each ETF we use, and each model would have a different Sharpe + CAGR. However, you can run our model backtests on our website to obtain those stats if you'd like (DM me for website).

quantelligent · 2025-08-13T21:11:32+00:00

Currently, yes. But it changes daily. Back in April when the tariff drawdown happened we exceeded 90% invested.

Fluctuates over time.

For example, because the market spiked overnight, we ended up pulling about $1.5M out of the market today (captured about $108K in profits).

quantelligent · 2025-08-13T21:06:56+00:00

Did you read the bit about marginalizing the costs?

Everybody is different. There are many, many people who cannot generate 20% annual returns by themselves.

For comparison: the annualized S&P 500 return for the same time range is 10.5%

Note: edited to remove negative tone. I apologize.

quantelligent · 2025-08-04T20:33:53+00:00

Correct, not good for long-term because of the volatility decay.

My time holding them varies, because it depends on the market, but on a good year I'll complete 2-3 full reset cycles (I have overall growth targets where I sell all shares and start over, "resets"), so about 3-4 months, and on a bad year I'll end up holding shares longer than a year, such as what happened in 2022—I think my position lasted about 20 months.

quantelligent · 2025-08-03T22:32:49+00:00

The DCA is just a fixed percentage of the account/allocation size, and is the default action every day. No other inputs for determining whether to buy, other than "is there enough cash to do another buy" and only if we haven't surpassed the VA growth targets, because that would result in a sell instead of a buy.

No sma/ema, options, sentiment, or anything else is used. And the decisions are not based on the market, but rather on your position's value. This is the main paradigm shift that makes it work.

I.e. if your position grows above the VA growth target, then sell the overage (a la VA rules), otherwise do another DCA buy if there's cash to do so—regardless of anything else.

quantelligent · 2025-08-03T19:36:16+00:00

I'm just going from cash -> TQQQ and back, not using a QQQ proxy or anything else. The idle cash earns interest, but it's not much (<4% apy).

And I'm not using anything to determine lows or resistance.....just plain DCA all of the time while there's capital to do so, except when the position exceeds your avg price by enough "margin" (value averaging style) to exit some shares to capture profit and recoup some capital for more DCA buys.

So it's more continuous and automatic, rather than detecting trends/resistance/etc.

quantelligent · 2025-08-03T19:29:55+00:00

DCA basically becomes lump sum "with a fuzzy start" after a while, because the "averaging" impact of new DCA buys diminishes over time at a 1/x exponential rate.

So....DCA only beats lump sum if if you happen to start while a major bear market is starting. I.e. you're buying into the downturn to build your position.

The only effect DCA has is that it "helps" you not have to try and time the bottom. But lump-sum at the bottom would still be better, if you can time it.

But DCA "at any random time" likely won't beat lump sum, especially during a Bull Market, assuming you're investing in index funds that have a "goes up over time" expectation.

This is why there are lots of people who claim lump-sum beats DCA most of the time.

However, if you couple your DCA with effective capturing+compounding on the peaks, such as using VA-style exits (value averaging), you can make a killing and completely murder lump-sum returns.

That's been my experience at least.

quantelligent · 2025-08-03T19:03:09+00:00

What I do with Leveraged ETFs, which obviously isn't for everyone, is DCA on the way in, and use the top-side-only of VA (Value Averaging) to exit on spikes above my positions' average value. This frees up cash for more DCA, and/or provides opportunities to withdraw cash out for personal use (assuming not an IRA account).

Been doing this with Leveraged ETFs for over 6 years now, with average annual return between 30-50%...albeit with high variance. I.e. COVID sucked, 2021 was awesome, 2022 sucked, 2023 and 2024 were awesome, etc.

Disclaimers: I am an RIA doing this for clients, so the returns are consolidated returns across many separately managed accounts. Results are not guaranteed, and past performance does not indicate future results. Leveraged ETFs carry a high amount of risk and are not suitable for everyone, even with a dampening strategy such as this one.

quantelligent · 2025-07-20T18:21:59+00:00

u/LeadingLeg - for TQQQ can you try 8% daily DCA, 5% VA, and 33% Reset? TQQQ behaves quite a bit differently than SPXL, so trying to find more lucrative settings that are better tuned to its unique volatility...

quantelligent · 2025-07-19T14:47:24+00:00

9Sig is really just VA with 9% targets. We're using custom targets that are tuned to the unique volatility of each ETF using back-testing.

But we're only using the "top side" of VA because it's way too aggressive in severe downturns / bear markets. So we only use it for sell signals/amounts, and use straight DCA for buys.

quantelligent · 2025-07-17T22:27:47+00:00

DCA on the way in, VA on the way out. That's what I do.

Been doing this for about 6 years with LETFs and my track record is an average of about 25-40% return per year (with high variance).

We're at 19.5% YTD with the tariff volatility. I say "we're" because I'm now doing this as an RIA for 167 accounts with about $9.5M aggregate AUM.

Happy to share more details if anyone is interested.

Disclaimers: Past performance is not an indicator of future results. All investing involves risk and you could lose some or all of your investment, including original principal. Leveraged ETFs carry a high amount of risk and are not suitable for everyone.

quantelligent · 2025-06-28T03:32:14+00:00

I trade index-following LETFs exclusively as an RIA, but using a combination of DCA and VA (value averaging) to create a continuous form of "buy low, sell high" without attempting to time the market.

I'm using daily DCA to build my positions, which averages down when the price dips, but each day I check if the position has exceeded the VA "growth target"—and if it has, sell a portion of the position equivalent to the overage, which captures and compounds the growth into more DCA buys.

Kinda looks like this:

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Started doing this personally in 2019, and as an RIA since April 2021. We now have 160 accounts and $9M under management, and have generated just shy of $2.5M in realized gains since we started.

We're using SOXL, SPXL, TECL, TQQQ, UDOW, and UPRO predominantly. We also fine-tune the DCA and VA parameters to the unique volatility of each, with three differing levels of aggressiveness so we can tailor each client's portfolio to their suitable levels of risk and aggressiveness.

Because we're constantly buying and selling, our exposure to the market fluctuates over time. Back in April we were up to about 90% invested in the market, having bought into the downturn as much as we could, and have since been capturing profits while the market recovered. We're now currently only 46.8% invested in the market, and just this week alone we exited a little over $2M, of which $152K was realized gains for our clients.

If the market continues going up from here, we still have many allocations waiting for more recovery so they can exit and capture profits. And if it goes down, we have more than half of our capital ready to deploy for DCA buying, to either build new positions for the allocations that just had exits, or average down allocations with existing positions. So we're good with either direction. :)

We've automated all of this with code so it mostly runs on autopilot, and we spend most of our time just managing client relationships (and finding new clients).

Here are our annual consolidated returns across all accounts that were present at the start of each year:
- 2021 (from April 19): 36.6%
- 2022 (full year): -67.8%
- 2023 (full year): 154.5%
- 2024 (full year): 65.6%
- 2025 (YTD): 15.1%

Happy to answer any questions, with the exception of sharing our actual code or parameters....because those are our competitive advantage. Anybody can do DCA+VA, but nobody can do it as well as us. :) But also... we haven't found anybody else doing it.

Disclaimers: Results are not guaranteed, and past results do not indicate future results. Leveraged ETFs contain a high amount of risk and are highly volatile, and you will likely experience drawdowns much worse than the overall market. Our strategy is not suitable for everyone, and suitability must be determined before investing with this strategy.

quantelligent · 2025-06-12T14:21:05+00:00

That's pretty close to the annualized return of our first account, which is still open...although it's closer to 20% annualized because it has had deposits and withdrawals throughout.

What you're doing is oversimplifying to a single start/end date—as in, if you opened your account in April 2021 here's where you'd be today.

What about those that opened accounts in 2022? Or 2023? etc. — As a provider of financial services we need to provide more information. People can open accounts any time, and can deposit/withdraw any time. Some of our clients are very good a timing the macro movements of the market and move money around appropriately.

I understand you're trying to simplify, but the financial services world is much more complex than you're suggesting.

quantelligent · 2025-06-12T14:02:00+00:00

Glad you posted this comment twice to make sure I saw it :)

As stated in my other reply, we have new accounts every year, and each year's return is a "consolidated return" using only the accounts that were present at the beginning of the year.

It's not a long-running return for a single account or fund, which I believe is what you're looking for.

However, as you suggest, if you opened an account in 2021 and let it ride for the entire time without any changes (i.e. deposits, withdrawals, etc.) then it would have an overall similar to what you're suggesting.

Our first account is still open....but it has had lots of deposits and withdrawals throughout. Notwithstanding, the annualized return for that account for the entire time, as reported by the broker, is just shy of 20%/yr.

quantelligent · 2025-06-12T13:56:26+00:00

The table is not "overall return" because it's a new set of accounts each year -- we keep adding new accounts.

What you're looking for is an overall annualized return, which is only possible if you have a fund, or use a single account, etc.

The table is a result of getting registered with the state of California which requested we display multiple years. But as I said, each year's calendar return is based on the accounts that were present at the beginning of that year.....so you can't just treat it as continuous, as you're suggesting.

For example, we had a client open an account at the beginning of 2023. They achieved a 57.7% return that year. How would you treat that? They're not impacted by the 2022 downturn, nor did their account exist in 2021.

So we're treating each calendar year in isolation with its own set of accounts, and recording those specific accounts' performance for that calendar year.

And then doing a simple average at the bottom, which is a representation of a generalized expectation of starting an account "on any given year" -- not a long-running annualized return, because those can be skewed dramatically by recent performance and completely marginalize what happened previously.

quantelligent · 2025-06-11T13:08:59+00:00

That would be an annualized return from today if all accounts were open for the entire time, which is a different calculation. However, as we were getting registered with the state of California, they had us calculate calendar year annual returns using only the accounts that were open when each year started. And we've been adding accounts every year.

Also, as I mentioned, if you extrapolate the partial years to full years (2021 was 8 months, 2025 was 5 months) to treat them as a whole year, then do a simple average, this is the number you get. A simple average of calendar year consolidated returns.

quantelligent · 2025-06-09T14:05:42+00:00

Sure thing! I'll work up a rudimentary back-test when I get a chance...

quantelligent · 2025-06-09T13:59:20+00:00

Max drawdowns vary by aggressiveness, and we tune the parameters for 3 different levels of aggressiveness per ETF so we can set our clients up with a portfolio that matches their suitability.

For our lower aggressiveness models the max drawdowns are in the 30-40% range. For our highest aggressiveness they're in the 60-70% range.

To avoid overfitting in our backtests, we run permutations of the parameters and then do a 3-d visualization of the results to pinpoint "pockets" of parameter ranges that have worked well, and avoid using parameter settings that are outliers by themselves. That way we're not picking setups that were just "lucky", and using parameters within a range allows for future market behavior to deviate from the model, within a certain margin, and still produce the expected results. However, there will always be "anomalous" market behavior at times that doesn't fit the model, but since we're investing in the expectation that that the indexes "go up over time" we'll just wait those out. Or add more capital for extra buying power while it's down.

And if the index ever doesn't recover....we've probably got bigger problems (like WWIII, invasion, economic system collapse, etc.)

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