How was 2022 for you?

I always think it’s interesting for users to share their performance with P123-derived strategies. 2022 was a pretty bad year for investors, but my own performance was good, thanks to P123, and I’d love to hear about yours.

Altogether, including some options trades, I made just over $1 million, with a 22% return. I do use some margin, so you can attribute some of the performance to that. If you look only at my long stock positions, I made a 20% return.

The stocks that made me the most money were Valhi (VHI), RCM Technologies (RCMT), Obsidian Energy (OBE), Journey Energy (JRNGF), and Silvercrest Asset Management (SAMG). The stocks that lost me the most money were Cumulus Media (CMLS), Medical Facilities (MFCSF), Computer Task Group (CTG), Itafos (MBCF), and Euroseas (ESEA).

Besides investing in the above losers, I made three other big mistakes in 2022. I tried to arbitrage a tender offer for Cumulus Media, I tried out a factor-momentum strategy during the summer, and I bought out-of-the-money call options. If I hadn’t done those three things I would have come out even farther ahead.

I’m eager to discover how you did this year, what your successes and mistakes were, and what you might have learned. I’m working on a few blog posts about the things I learned in 2022 . . .

As a user that started using Porfolio123 in June this year, I have to say I’m pretty happy with my results so far. I made about a 12% return during the last 7 months, even though the broad US market did not do too well.

But more importantly: I (feel like I) learned a TON about investing in equities in general. Mostly due to the Portfolio123 system and its community, but also due to my conversations with other investors in real life (that I think I actually had a chance to meet because of the knowledge I got from using Portfolio123!).

One of my biggest winners was Limbach Holdings Inc (LMB) that I bought almost straight when I started using Portfolio123 and survived my ranking systems revamps during the last few months. My biggest mistake up untill now was probably to wait so long with live trading. I think looking back I could have started at the start of the year and yes, maybe I would have made some mistakes with a ranking system that would have been more rough on the edges, but the learning experience that live trading gives has been on another level for me. Just the engagement is so worth it.

One of the things I have been enthusiastic about in recent days is to look for data that might be a nice add-on when evaluating a company. For example, a company called Thinknum has alternative data from Glassdoor and other sources that might a value-add to the rich dataset that Portfolio123 already is.

But of course, I don’t think I will ever really ran out of the ideas that can be applied with the Portfolio123 data alone. I have been thinking about trying to quantify some other metrics that might usually be seen as qualitative. See for example the metrics below.

I hope to add more of these ideas to my ranking systems the coming year!

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Overall, 2022 made me poorer. However that was my fault. I stayed in an options playing strategy too long and that hurt my account. The good news is I now have a large options DB to mine.

Consequently, I made a market indicator to signal bearish market turns. It would have taken me into a defensive posture by Dec 03, 2021. It’s still looks rather poor today, so I remain defensive. And, yes, I know what the general consensus is about market timing but I’m still optimistic the indicator has value.

Finally, my book of micro/small cap stocks had a reasonable year - up 14%.

The strategy for 2023 is to watch the macro environment and once it turns more bullish return to a more systematic and less discretionary trading system.

Overall happy with p123. Not so happy with my discretionary trades.

My main small/microcap strategy was up 15% for the year. Around May it became obvious this was going to be a rocky year and the Fed was raising rates, I put a similar microcap live portfolio in a Book with some managed futures/trend following ETFs (DBMF, KMLF) and short term bonds (SHY) to try to smooth volatility and did even better (18%). After P123 went live with European Data, I started a North Atlantic Strategy in late August and it’s up 17% in 4 months. Needless to say, very happy with my results and Portfolio123’s product.

My worst blunder of the year is I have a stray tax advantaged retirement account from a job a long, long time ago with just a little money in it that I pretty much set aside for outright market gambling and fun. I sunk it all into CAAS after it had melted up, pretty much perfectly timed the top and it’s gone straight down ever since. This is pretty much the norm when I pick stocks with just my discretion and hunches.

My P123 goals for this year … I would like to streamline my main ranking system, as it’s become quite a Frankenstein’s monster of factors over the years. I’m also interested in seeing if I can try to create a more tax friendly system that minimizes my capital gains without impacting total return too much for my taxable accounts. I would also like to see if I could create more sector /industry specific ranking systems that I could rotate in and out of based on timing sector specific ETFs. And of course, I’m looking forward to seeing the P123 Machine Language release.

I’m overall pretty happy about 2022. My main US/Canadian microcap strategy returned -3 %, a focused version of the same strategy returned 6 %. My utility strategy returned 8 %, and my European strategy (started in late august) returned 1 %. I guess none of the results are very impressive, but they all beat their benchmark, with enough excess return to pay for P123 many times over.

I found a few small ideas that worked, for example that insider buying in stocks with poor momentum is a small source of alpha. I worked a lot on robustness and optimization, but I’m not sure how to summarize the results, if anything my confusion about the subject is deeper now than a year ago.

It was fun to get access to European data, and nice to see that my models from the US works works in Europe as well (except for utilities). Momentum seems to work much better in Europe & Canada vs the US (for me), I don’t know why.

Thanks for sharing all, and Happy New Year!

A difficult year, to be sure. I was fortunate to achieve 29% between my various strategies (long only, no leverage).

Here’s my annual write-up:

I currently run 5 strategies, summarized below.

One item that I did not specifically cover in the piece above, is that I stuck to the plan (my current strategies), other than the experimental strategy #8. I’ve been running these strats, unchanged, since Jan 2020. Easier said than done, many times I looked at changing things, increasing quality, removing energy, adding energy, etc…but instead just kept them the way they were, as it seemed very little new things were adding value (at least for this year).

In 2023 I’ll be revisiting strat #6, and potentially #3, as it has lagged the other strategies 1, 2 & 4, which are similar.

HRTG was hands down the most significant loser. Classic example of buying high, selling low, it lost 90% (!!!) between buy and sell. I’ve been running this strategy for nearly 3 years, and it has not picked a stock like this. It’s on my list to see if I can add some rules to my strategy to avoid this particular situation.

Positive holdings included RCM, NPK:CA, SCL:CA, etc.

I’ve been experimenting with day and swing trading as well (look up “Episodic Pivots”, or see my section in the link above), with limited success so far. Not sure that it’s my cup of tea though; may dabble further this year with very small trades, if/when the market becomes more bullish.

Similar to Yuval, I looked at factor momentum, and did my own research on the subject (see link in year-end article above if interested). I wasn’t able to find any real robust trends though, and have not put funds live towards this strategy. The idea is very appealing, so I hope to revisit at some point.

In the above I also had good exposure to biotech, mostly net-nets (which I posted about on the forum earlier in the year). Some of these names can make significant intra-day moves, but they often do not stick. What I’d like to do this year is better understand biotech, and develop a strategy to find those stocks that can maintain their returns, after a major milestone (FDA approval, etc).

Let’s see how 2023 goes, wishing you all the best of luck!



I made a 6% return.
More importantly it was a third in row year when I achieved higher return than iwm or voo etf.

Top performers: RCMT, LMB, CAAS, DPSI, AGFS
Worst performers: SIEB, DLHC, AXAS, INLX

I’m very happy user. Big thanks for Yuval, Marco and the whole p123 team!

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Return for the entire year was 4.15% with drawdown registering at 15.35%. Limiting drawdown is a focus.

The more interesting part is the year is divided into three parts (details below) divided by the approaches taken.

The first portion (1/1/2022 - 7/7/2022) returned -2.09% with a 10.72% drawdown. This was a volatility weighted relatively high yield and low valuation portfolio that I had developed using the Morningstar stock screens – until they gutted them and made them unusable for my approach.

The second portion (7/8/2022 - 9/12/2022) returned 3.57% with a 7.16% drawdown. It started with four of the model portfolios with Build for Stability dominating which I decided was too stable for my purposes.

The third portion (9/13/2022 - 12/31/2022) returned 2.71% with a 11.55% drawdown. I had accumulated five screens totaling 37 positions that I decided to run live as an Ensemble portfolio along side two of the original models. I’ve relaxed the limiting drawdown focus with a switch paying more attention to alpha. I’ve tweaked one of the screens and replaced one in late December to leave the year with 39 positions.

Going into the new year I sold out of one of the models on Wednesday. A switch out of one of the screens next Monday will reduce volatility, reduce beta, lower turnover, and up alpha (all projected) while increasing positions to 44.

In conclusion, it has been an interesting year with the changes and it has taken some time to work up some possibilities. The current year will be more incremental developments as I learn more.

Best of luck to all,


Start End Security Return Drawdown Sharpe Sortino Days + Days -
1/1/2022 7/7/2022 SPY -17.49% 23.01% -1.55 -1.98 65 69
1/1/2022 7/7/2022 IWM -20.69% 26.92% -1.54 -1.99 67 67
1/1/2022 7/7/2022 Account -2.09% 10.72% -0.53 -0.70 68 66
7/8/2022 9/12/2022 SPY 5.65% 9.06% 1.44 2.26 23 24
7/8/2022 9/12/2022 IWM 8.01% 11.32% 1.79 2.80 24 23
7/8/2022 9/12/2022 Account 3.57% 7.16% 1.23 1.89 26 21
9/13/2022 12/31/2022 SPY -6.12% 12.88% -0.85 -1.26 31 48
9/13/2022 12/31/2022 IWM -7.17% 12.99% -0.85 -1.24 40 39
9/13/2022 12/31/2022 Account 2.71% 11.55% 0.32 0.48 41 38
1/1/2022 12/31/2022 SPY -18.17% 24.50% -0.88 -1.20 119 141
1/1/2022 12/31/2022 IWM -20.48% 26.92% -0.82 -1.13 131 129
1/1/2022 12/31/2022 Account 4.15% 15.35% 0.09 0.12 135 125
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Yuval -

Congrats on another successful year in 2022. You are an inspiration to many of us.

My stock trading was essentially flat in 2022, but I wasn’t necessarily using P123 portfolios for most of my trading. My active trading over the past several years has been in systematic managed futures, and my futures portfolio (and my client’s account) was up 40% in 2022.

In order to provide diversity and another uncorrelated return stream, I am planning to really to focus on P123-style trading in 2023. I have 50 pages of notes from Yuval’s recorded presentations … so, that is a start.

Best luck to you all in 2023.

Hi Yuval - congrats on your success this year (as well as others).

One interesting point you made here is that you made $1M trading stocks that have very low volume/price/liquidity. I’ve got some good performing microcap / smallcap type systems but worry that since I have more capital rather than less I would run into a lot of slippage /inability to trade these stocks that only trade 20,000 to 80,000 shares per day.

Can you share what your personal experience is with this and at what size account you think trading these smaller stocks will become difficult?


The key here is to trade only a small amount per day. Here’s a formula that’s pretty close to the one I use, but a bit easier to use. 0.42*S^(2/3)*V^(1/3) where S is the ideal amount you want to trade overall and V is the daily dollar volume. So let’s say you want to trade $100,000 worth of a stock that only trades $30,000 per day. The formula tells you that you should buy no more than $28,000 worth per day, so you split up your buy into 4 days. And each of those days you should split up your buy into 5 more or less equal trades placed at different points through the day–either that or use a VWAP order. So altogether you’d be placing 20 orders of about $5,000 each. You’ll still get market impact costs, but this way they’re lessened.

Right now I’m investing an average of about $75,000 per stock. My lower limit for liquidity is based on both daily volatility and on median daily dollar volume. It’s a bit of a complicated formula, but an approximation might be: volatility/(mddv^0.5) < 0.0125 where volatility = 100*loopstddev("(hi(ctr)-low(ctr))/close(ctr)",100) and mddv = mediandailytot(126). But if you’re using this guideline, you have to take into account all the stocks for which hi-low = 0 because we don’t have trading data (all Y-shares, for instance). You also might want to exclude stocks with a high ratio of median bid-ask spread to price.

I also adjust the amount I buy of a stock depending on its estimated transaction costs. So I’m going to buy a LOT more of a stock that trades $750,000 per day than one that trades $15,000 per day if they have the same rank.

I’m gradually moving toward a system with longer holding periods, in which case transaction costs won’t matter quite as much. I’m always fiddling with these things, which might really be a big waste of time . . .

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Thanks for the info!