%% TSLA?? Looks like the buyers & sellers& sellers think mr musk may get fired/SEC $40,000.000 fine...………………………………………………………………………………………………………………. Actually I would rather trade UDOW/TZA/TQQQ than junk like TSLa. NOT a prediction or insult, I still like junk silver coins/some coins.LOL
interesting ... thanks. on TZA (like UVXY) since it a perpetual decaying stock - last reverse split when it was $9 back in 6/28/2019, its likely going back down sometime this year to its early 2020 low (even lower) sub $35, so right now there is a potential $15 drop from its current price at $50 https://www.splithistory.com/tza/ how or what would your trade/play be on this?
Thanks. I'm familiar with the Gaussian Statistical Model (sometimes called a Bell Curve) . You have shown me a 25 year SPY price distribution model which measures mean, median, and mode. The mean, which is simply an average, is obtained by adding all prices and dividing by the number of prices. The median is obtained by adding the two middle numbers of an ordered sample and dividing by two (in case of an even number of data values), or simply just taking the middle value (in case of an odd number of data values). The mode is the most frequent of the numbers in a distribution of values. However, the past movement or trend off a stock price or market cannot be used to predict its future movement. Gaussian distribution is a statistical concept that is also known as the normal distribution. It doesn't predict where prices may move in the future. For a given set of data, the normal distribution puts the mean (or average) at the center and standard deviations measure dispersion around the mean. In a normal distribution, 68% of all data fall between -1 and +1 standard deviations of the mean, 95% fall within two standard deviations, and 99.7% fall within three standard deviations. In the options world we know that 68% (1 SD) equals about 16 Delta. Investments with high standard deviations are considered higher risk compared to those with low standard deviations which gives us opportunities to sell Put and Calls for symbols strikes that have high IV and buy the low IVs. Standard deviation measures volatility and determines what performance of returns can be expected. Smaller standard deviations imply less risk for an investment while higher standard deviations imply higher risk. Traders can measure closing prices as the difference from the mean; a larger difference between the actual value and the mean suggests a higher standard deviation and, therefore, more volatility. Prices that deviate far away from the mean tend to revert back to the mean so that we can take advantage of these situations, and prices that trade in a small range might be ready for a breakout. For my personal style of trading that means selling puts and calls with high IV in anticipation that the price will revert back to the mean in which case I will buy back the option for a profit. I use thinkorswim's Trade tab, Probability Analysis tab and Risk Profile tab to determine where the probable price range for a 1SD (68%) move and 1.5SD (85% ) move. On the trade tab I pick a pair of strikes that fall between 16 Delta (1SD) and 7 Delta (1.5SD). Fortunately the ToS platform makes it easy to do all that. To cover my butt in case things become even more volatile I always buy a farther OTM put or call to protect myself. Normally that creates a 10 wide or 20 wide vertical credit spread. That limits my profit potential but also limits a potential loss. But in any case moving averages, keltner channels, MACD and bollinger bands, etc. don't occupy any space on my chart. I do use the ToS Probability Cone to give me a visual of where the 1SD and 2SD prices are. But, as I said previously it's my opinion that the past movement or trend off a stock price or market cannot be used to predict its future movement. As an aside I think that it's important for a new options trader to be familiar with Friedrich Gauss' Gaussian normal distribution models, Merton-Black-Scholes options pricing modeland the Cox, Ross and Rubinstein binomial model pricing theory. Best JB
[1] Never trade TNA, even though some years IT MAY MAKE A FORTUNE I like TWM better for now; even though jim rogers admitted he lost money on his bank shorts one year , but not much=good balance on his longs. Mainly I have to plan to sell TZA/SRTY, even though latter = less liquid; been trying to sell DDM all day with a nice limit/may have to use a market order next 20 minutes= I like to get paid every now/then...……………………………………………...……………………......
%% I was starting to get CONCERNED ON DDM ………………………………………………………………………………...ok NOW; hate the way so many limit orders get filled @ a worse price after you change them/limit, but that's trading/investing .
5 mins to go - if not already done so, close the position & be done, tomorrow is another day. be interested to know, did you do it, if so what was the % profit
Levy and Laplace are also statistical model describing the distribution of stock price change. Usually they signal the outcome is a combination of a Gaussian (random walk, Brownian motion) and something else. Any time the distribution is non Gaussian the process is not random and in principle one can find a model to profit from predicting the non random part of the process. An example is blackjack, the card distribution is random but if you can count cards, it becomes non random and one can profit by card counting. I am not a math or statistics guy, this is just what I read from asking Prof. Google.
I have a hard enough time understanding how to derive Black Scholes. The others are just Greek (no pun intended) to me. Even if I go back to college, I don't think I can ever derive and understand Friedrich Gauss, Ross and Rubinstein, binomial, trinomial...
IMHO Implied Vol is a derivative. It has nothing of a leading indicator. When market is going to break, THEN you will see IV spiking upwards.