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A couple of my humble observations about this post: - true odds can never be known in financial markets due to not knowing all the factors which effect price levels. - the metric one should maximize in a trading system is payoff = (profit factor x winning percent).

The problem with EW is that it isn't based on any fundamental scientific or engineering principles, just the observation that prices seem to behave like waves. If you think prices have wave and cycle like behavior, then you should apply digital signals processing (DSP) methods. At least DSP is...

Since March 1st!? Not a big enough N. Backtest this simple strategy from 1960 and report back on percent up and down days. Then let us know if it would be positive expectancy. I seriously doubt that this simple strategy is viable.

The obvious action to a stock you have identified as being pumped is to wait for the dump and quickly pull the trigger. Assuming you can find shares to short of course.

I hope this article can help give you some ideas: https://falkenblog.blogspot.com/2020/02/simple-vol-estimators.html

Truth, as always, in financial markets is relative. The market is always moving in its' search for "true" valuation. There is always instability at every point. Your search for cause and effect will melt your brain, so don't take market movements personally.

TastyTrade has a good series on options math. Only one new episode in a while, but the math doesn't change. https://www.tastytrade.com/tt/shows/the-skinny-on-options-math/episodes/probability-of-profit-08-06-2015

Delta approximates the probability of finishing ITM. The probability of touching the strike during contract lifetime is approximately twice the probability of finishing ITM.

How do you then monetize your time and efforts? Are you expecting to get it back through inheritance?

This code uses the method of bisection to find IV #include <cmath> #include "fin_recipes.h" double option_price_implied_volatility_call_black_scholes_bisections(const double& S, const double& K, const double& r, const double& time, const double& option_price){ if...

Except in trading the odds of a given event occurring are never known with fixed certainty. Whereas in gambling they are fixed and known (largely.) Vanilla option delta is about the closest we can get to fixed odds, and even then it is only an approximation. I'm not familiar with other...

Absent any other information, low and going lower.

Lag is why MAs don't work, at least the traditional way people view and use them. I've written a few posts in this thread about how to deal with lag. You have to be willing to treat a MA as a lowpass filter. That means you have to learn a bit of math and physics to learn how to engineer lowpass...

The problem with that logic is that what is low can always go lower (down to zero of course), and what is high can always go higher. That's why you have momentum traders.

To measure fear in the broader equity markets, why not just use the VIX or possibly the VIX/VIX3M ratio?

Have you all read about rescaled range (R/S) analysis, with values between 0 and 1. A value of 0.5 means a random walk. A value greater than 0.5 means some nonrandom movement is present. A value less than 0.5 means movement is more reverting than even a random process would suggest. Daily...

J.M. Hurst did his work and by analyzing cycles of floods from the Nile river. Cycle analysis from the physical world applied to finance is only a model or approximation. How well that approximation works is shown by your pnl curve. So, I'm not saying Hurst analysis is wrong when applied to...

That is the philosophical debate everyone needs to have with themselves. If price evolves as a random walk, then all of TA is bullshit. If price was purely Gaussian, that would be easy to deal with. However price and return distributions are not perfect and have skew and kurtosis, as well as...

If you want to filter data, look at the work of John Ehlers, and specifically his zero-lag filter for a lowpass. If you want a stationary series you can highpass or bandpass the data, again Ehlers is the man. He even has a paper on linear prediction. More in the ML realm, there is something...

Correlation is the wrong metric to be looking at in the first place. Cointegration is the proper metric. Now down that rabbit hole you go.