Portfolio Boss

Predicting the Next Bank to go Bankrupt

Corona Del Mar, CA

Howdy Friend,


A long-time member was very concerned about bank solvency. That concern even spread to worries about his broker going bankrupt.




He had the unfortunate experience of stumbling upon a website with bankruptcy scores where they give you the probability of a company going bankrupt.


The problem is that they are wildly inaccurate.


According to the Zmijewski Score, Google should have been bankrupt in 2004.

"Scores less than .5 represent a higher probability of default."


Then there are Altman scores, Piotroski F Score, Fulmer H Factor, Ohlson Score, and Springate Scores.


Here's the problem: Theses are all from the 70's and 80's, and they don't ever show their performance.


In other words, there's no backtest or forward test.


I strongly believe they over-fit their backtests to come up with these scores.


You just have to take their word for it that these number represent something useful.


News flash: THEY DON'T.

You know what's a great predictor of bankruptcy?


A small market cap.


For proof, being listed on the NASDAQ Composite has been a death sentence for many companies...that's why the NASDAQ composite A/D line has been in decline since the 70's.


One of the scores listed Interactive Brokers as a high likelihood of going bankrupt (as the score has for several years... which they don't tell you on that website).


Meanwhile back in reality: IBKR is close to hitting new highs. There's a reason I use ZERO fundamental data to predict anything: It doesn't help. I have access to something like 300 data-points per stock.


Practically none of it can beat price behavior analysis.


I know because I've been programming trading strategies since 1997... and over the past three years we've fed a bunch of data to The Boss machine learning supercomputer...and we've hit dead end after dead end.


Sentiment is garbage... price behavior forms sentiment not the other way around. Index put/call ratios were a big yawn. Short interest had some alpha, but it's not updated frequent enough to be worthwhile.


COT data only seems to work with high retail participation like the S&P 500 and 10-year bonds. There are a few exceptions -- namely True Asset Pricing and ETF Fund Flow data.


That's where we struck pay dirt.


Then there's the discovery of Cycle Reversals when you're trading multiple strategies together. We were seeing backtests with annual gains in the hundreds of percent.

It's wild.


And of course it works with real money not just a backtest. Member Josh placed in the top 5 out of 18,000 traders at Fundseeder...plus members have been sharing their brokerage statements with wild gains.


That's why we've been focusing on dialing back these strategy of strategies (what I call Meta Ai). With the advent of all these new 2x and 3x funds, who needs to trade futures?


Want to learn how it's done?


Since you're a subscriber, for the next 72 hours, I'm granting you full access to my new Meta Ai course ($997 value).


All you have to do is click this link for full access >>


You'll learn all about combining strategies together for maximum gains, and hyper-consistency.


Click here for your 72-hour access pass >>

Trade smart,

Dan "Prince of Proof" Murphy


Disclaimer: The results listed herein are based on hypothetical trades. Plainly speaking, these trades were not actually executed. Hypothetical or simulated performance results have certain inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Also, since the trades have not actually been executed, the results may have under (or over) compensated for the impact, if any, of certain market factors such as lack of liquidity. You may have done better or worse than the results portrayed.

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