1. Derivatives and, in particular, options, have always fascinated me: modeling is mathematically interesting involves numerical estimation methods non-intuitive nonlinear behavior leveraged its role as a financial instrument 2. My approach to options trading was inspired by "tastytrade" and "option alpha": it sounds good it's supported by "backtests" looking at panels with indicators and managing positions based on what-if scenarios seems professional "I run my own casino!" 3. My "equity curve" was upwards and smooth. Until the "six sigma events" appeared. I kept saying to myself: "theoretically you know those losses were possible" "you could have avoided that if you had a protection on that leg" "look what happened afterwards: if you managed the position this way..." 4. The fact is that, in the end, everything was perfect balanced ("as all things should be"): exposition to losses = chances to profit 99.99% of the time right = 0.01% of the time wrong expected value = 0$ (let's pretend trading is free...) 5. Then I moved to day trading futures (CL) and got lucky: no strategies ("pure price action... just feel the market flow" lol) oil prices dropped almost everyday for 3 months, all I had to do was to keep shorting more and more contracts (of course I didn't know that at the time) After +$40k in the first month I could absorb losses and keep reverting the wrong positions (adding more contracts) and surfing the big wave down +$50K total in the 2nd month and trading 500 contracts (a couple of millions in notional value) and posting everyday in a thread (in another futures famous forum) +$50k total in the 3rd month and people started to calling me a fraud and threatened me, so I stopped posting when I was already a millionaire (at least in my country's currency), the big loss happened... about -$90k in a single trade So I decided to end my short "career" as a trader and kept ~$50k in profits (net) The end 6. Post scriptum: Recently I started researching (as a hobby) the impact of fat-tails in option pricing, more generally: what happens when we plug a non-gaussian, asymmetric and fat-tailed distribution of prices/returns and account for volatility clustering I'm a frustrated trader and now I have a "anti-risk taking approach" in life (whatever it means...) I think trading derivatives is totally worth it, as long as you avoid been kicked out of the market (don't ask me how) Q:"What the hell are you doing in an options trading forum?" A:"I just like the atmosphere... maybe I can learn a thing or two from the pros"
how does it feel to be chewed up and spit out by randomness? like a lotto winner you will never be able to replicate your results because you don't understand how you hit the lotto in the first place. when you have lost everything you had multiple times then you are learning..
4. The fact is that, in the end, everything was perfect balanced ("as all things should be"): exposition to losses = chances to profit 99.99% of the time right = 0.01% of the time wrong expected value = 0$ (let's pretend trading is free...) great realization & place to start to dig deeper. If you like fat tail and are good at scalping, maybe it wouldn't be a bad idea to take the other side of the thetagang strategy
Imagine that percentage is a parameter p that you want to optimize. So you'll get some historical data and run montecarlo simulations. Letting the data show us the way is the obvious way to go, but we are assuming a lot of things without even knowing. We already know that returns do not follow a normal distribution. The problem is to find a suitable distribution to fill this gap. If the tail is "too heavy", the option market couldn't even exist at all (at least without another pricing model), and the past wouldn't inform us enough (the sample average is not an unbiased estimator for the population mean in some cases, for instance). So finding the "right tail" (goldilocks principle) is one option. Remember the p parameter? We could take the worst event ever (in the backtest) and plug some value p0 in order to survive a two-fold drawdown (damn it, let's make it ten-fold). If Mandelbrot was right in the 60's, for example, and the prices do follow some kind of "stable Paretian distribution", we're screwed anyway... in the long run (it's important to mention). But I'm speaking from a theoretical point of view... the things I'm saying works only asymptotically. In the "real world", people trade for some years and some get rich exploiting market "inefficiencies" (the person in the right place and time with the right approach "almost surely" exists).
Trading is actually quite easy if you can identify a trend, be patient and don’t over leverage. The problem is everyone thinks you need to trade every day.