pyrrhotech

It's a freemium subscription service to the algorithmic trading models / hedging systems I've been developing over the last few years. 2022 performance:

SPX (benchmark): -18.77%

Free models:

TA - Mean Reversion Basic (https://grizzlybulls.com/models/ta-mr-basic): -9.93%

TA - Trend Basic (https://grizzlybulls.com/models/ta-trend-basic): -17.79%

Vix Basic (https://grizzlybulls.com/models/vix-basic): -20.45%

Premium models:

Vix Advanced (https://grizzlybulls.com/models/vix-advanced): -17.9%

Vix - TA Advanced (https://grizzlybulls.com/models/vix-ta-advanced): -16.14%

Vix - TA Macro Advanced (https://grizzlybulls.com/models/vix-ta-macro-advanced): -3.15%

Vix - TA Macro Monetary Policy Extreme (https://grizzlybulls.com/models/vix-ta-macro-mp-extreme): +0.56%

The models use no leverage and are always either 100% long the S&P 500 or 0% long (in cash). These are not HFT, averaging one trade per 2-4 weeks on average depending on the model. You can see active signals for the free models by checking the site frequently, or if you subscribe to one of the premium plans you'll get email or text notifications as well.

In 2022, all but one of the models beat the SPX on an absolute performance basis, some substantially so with the top model returning positive absolute returns with a +19.33% outperformance gap. However, it was still a much worse year than 2021 as the unprecedented reversal of Fed policy in response to 40 year high inflation proved to make a challenging backdrop.

Full 2022 performance report: https://grizzlybulls.com/blog/models-performance-update-q4-2...

My take on the EMH, in short I believe in the 95% EMH, but that 5% makes all the difference and perfectly explains how legendary traders like RenTech, TwoSigma and David E Shaw have been able to outperform the market consistently for decades: https://grizzlybulls.com/blog/time-in-the-market-vs-timing-t...

This sort of attitude is exactly what makes left coast limousine liberal tech workers so insufferable to the rest of the country. Thanks for living up to the stereotype

No one ever became wealthy from buy and hold index funds. The returns are relatively low because most people are lazy and it's the easy thing to do. That's why I split my time between active investing (https://grizzlybulls.com) and working on my private business ventures.

How long have you been running it live, and how far back does your backtest data run? How closely are you seeing real returns match backtest? After running live for over 2 years, I've seen up to 6 month periods where the model outperformed the backtest, but overall the models have underperformed to varying degrees as expected. Though I have spent hundreds of hours dedicated to removing noise and overfit bias, I've come to the conclusion it isn't possible to 100% remove it, which combined with expected market regime changes where legitimate patterns become unprofitable means that in the long run every model is essentially guaranteed to underperform its backtest, the question becomes simply to what degree. However, with a strong enough model, even underperforming the backtest can lead to substantial alpha which is what I and our members have experienced so far this year.

People often think beating the market is impossible, and for an unaided human, it may be. But just like Magnus Carlsen cannot come close to defeating Stockfish at chess, sophisticated algorithms that analyze far more data than possible for a human are on an entirely different playing field. The ironic thing is the growth in the belief in the EMH and passive investing has actually made beating the market easier in recent years as there's simply much less competition and more money buying no matter what the economic conditions or monetary policy are to exploit. I've written a blog post on my take in depth on the subject here: https://grizzlybulls.com/blog/time-in-the-market-vs-timing-t...

I can assure you that there's no conspiracy to start the models right at the start of the last bull market, and I'd be elated to get my hands on the data for this as well as a couple other indicators that don't stretch back as far. Though there is no guarantee, market volatility, bear markets and general downturns are actually the conditions that enable the models to outperform. During buy signals which can be quite lengthy in periods of low volatility during bull markets, the returns are exactly equivalent to buy & hold.

1. Vix Futures are a huge part of all the VIX based models. Vix Futures came out in 2004 but the earliest intraday per-contract data publicly available is in 2009 which is needed to calculate the futures curve.

2. Slippage is included in the modeled returns but taxes are not, as mentioned in the tooltip. Taxes are not included because they vary widely by location, account type and implementation method. I've also written at large about how to minimize taxes on the blog. As a conservative estimate, feel free to multiply returns by 0.75x to get equivalent after-tax CAGR, but in most cases you'd beat this in real life.

3. Correct, and I make no guarantee that they will always be available. As of now, selling access to them in no way negatively impacts my own returns. I've met a lot of people in this journey and I enjoy leading a community and making an impact. I also make a significant amount of MRR that has grown substantially from the start of the year that gets reinvested into the models in my own account. I consider Grizzly Bulls to be a win-win alternative to the hedge fund industry for those interested in alternative investments. We've only ever had one Platinum member cancel, and given the model's underperformance in Q1 it was understandable. Since Q1, the model has been crushing the market, and it makes me happy to see our customers happy as well. Finally, as I mention several places, no one should ever expect any model to achieve 100% of its backtest performance, but there's enough leeway in the performance and drawdown figures to underperform the backtest and still generate substantial alpha, which has been my experience running them live for over 2 years now.

My system is down -1.58% this year compared to -17.39% for the SPX for a nearly 16% outperformance margin. I've documented the results and information about it here: https://grizzlybulls.com/models/vix-ta-macro-mp-extreme

Being worried about very low or even negative real returns over the next 10-15 years (as has happened many times in the past, most recently 2000-2013) led me to start building sophisticated algorithmic trading models that can produce positive absolute returns in any market context in early 2020. While there have been ups and downs, I've turned 525k into 1.4M since deploying live in April 2020. I've recently decided to publish 7 of them at https://grizzlybulls.com, 3 totally free and 4 premium.

It's the best of both worlds to me, I don't have to pick stocks or worry about the markets because the models tell me when it's time to hedge. My strongest model (https://grizzlybulls.com/models/vix-ta-macro-mp-extreme) has returned > 70% ROI since April 2020, and 60% ROI longer term in the backtest with much lower volatility than the market as a whole.

The next 10-15 years for investors are likely to be much more challenging than the last. How do you navigate such a climate with extreme overvaluation in all asset classes? That's why I'm building sophisticated algotrading models at https://grizzlybulls.com to help determine when to hedge and produce positive absolute returns regardless of market environment.

1. Internally, the model does work on a sort of weightings / probability system but it's not so simple as boiling down to a single probability figure, i.e. if it hits over 60% we trigger buy or less than 40% trigger sell. Instead there are a few phases in signal change identification starting with an attempt to classify overall fundamentals and market move and moving down to the more granular indicators based on each level of abstraction. Certain low level indicators mean very different things based on the higher level classifier output. However, I could feasibly attempt to boil down to some sort of confidence or probability figure and expose it. I'll need to do some rigorous internal testing to ensure that it conveys accurate information first, but it's a good suggestion.

2. I think the fairest way to report the results is with a 1x/0x (long with no leverage on buy signal, market neutral on short) and then let the users decide whether to use leverage or to short the market during sell signals. Personally I have used leverage here and there and I tend to dial it up or down based on how well the model seems to be performing at a given time. However, I think it's important to note that no model can ever be 100% free from overfitting, and while a great deal of effort has been made to generalize and widen params and heuristics, there's bound to still be some and even I don't know to what degree. This, plus the fact that algotrading becomes more competitive every year means that I think it's prudent to conservatively expect returns somewhere in the 50-100% wide range of the past, which could also mean drawdowns a bit larger than the backtest shows. And of course, black swan risk is ever present. Finally, the models only go back to 2009, so we don't have great data to indicate how they might perform in a more harsh bear market such as 2007-2009 or 2000-2003. This is an unfortunate coincidence as one of the key indicators, Vix Futures, only came to be in late 2004 and the earliest I could find intraday data broken into distinct contracts (not just continuous front month) was early 2009.

As far as my occasional contradictory past reporting of my own financial position. There's a couple reasons this could be--at times I've included less liquid assets (private company shares, family business interest, 401k, home equity, etc), and at others I've only reported what's immediately available to me and highly liquid (bot account + emergency fund, etc). I feel I've probably erred on the side of sharing too much personal financial details over the years, but it is what it is. Secondly, I've not always been a stable investor. I hate to admit that back in the day I was a bit of a WSBer at times. Never consistently, but sometimes I'd get caught up in the FOMO and make a rash (and often too large) bet on an earnings report or something and (though I won a few times) usually end up losing my ass. As such my net worth was pretty volatile between 2013-2018. I've since given that all up and the bot has helped assuage my inner gambler. I also used to follow some other folks' timing systems back then and learned the hard way that most don't work, so all skepticism is warranted. Even I like to keep a skeptical mind about the future of my own models which is why I reported the wide range of expected outcome above