So im at this stage of my trading path where I’m familiar with the concepts of volatility. Yet I don’t know how to value it. for example I see advanced traders always saying you need a “model” that can value etermine if it’s cheap/expensive.. okay, but the only way that I look/view/see vol is through thinkorswim. That’s it. I look at the vol numbers the thinkorswim platform gives me. but I want to obviously expand and dig into these “models”. I can’t code so please don’t tell me to code some model. I’m just wondering how do YOU analyze vol?
Solely looking at ATM IVOL you can view it in a few ways. I usually look at vol in either absolute terms or relative terms. Relative: For example you might use SPY IVOL to help you price an illiquid security. You can also compare SPY IVOL with XYZ IVOL to find rich/cheap trades. Thirdly, you can compare SPY IVOL to a basket of its constituents (dispersion trading). These methods are looking at the world in relative terms. Partial pooling/multilevel models can be of great help here. Absolute: When we look at the world in absolute terms, we might try to find a fundamental/news driven trade. For example, you know that company XYZ has a court case coming up in 3 months and the market is not pricing in elevated vol. You might be able to construct a calendar spread to isolate that event. You can also use things like the GARCH family to help you out. I like the TGARCH for one day look ahead periods. I have not found much use of the standard GARCH (1,1) for a 1 month look ahead period. Margrabe's formula has been of high value for my current strategy (relative value stuff). https://en.wikipedia.org/wiki/Margrabe's_formula Moving outside of the ATM realm it gets quite furry. @PoopyDeek is a good reference to learn from if you want to go that route. P.s. programming is really helpful. It's tough to get clients if you are using a screw driver and all your competition are using drills. p.p.s. I might not have fully answered your question. You can not calculate volatility you can only estimate it. There are many models for estimating vol, Yang.zhang is my favourite on the daily time frame. Of course, the more data the better so looking at intraday tick data would be an even better estimate of stat vol. You can construct a trade by looking at it through a risk reward lens. "If I am right how much will I make and if I am wrong how much will I lose". If stat vol (historical vol) has a range of 20%-50% and current IVOL is 25% than you might have a great risk reward trade on your hands - If you are wrong, you will most likely not lose more than 5 points but if you are right....
volatility is how different the price change like 5% is the max the index should change overnight. in stocks it can be as high as 50% in options its 50% etc. is the change in price or trading range...currencies barely change in price in terms of percentages the delta , vega. or something. options always value the options based on volatility. or the VIX the market even would halt if 'volatility' and liquidity 's too HIGH or low. no bidders they shut down the exchange and nobody can sell. you put a market order and no bid just not enough cash to even settle the trades at end of day
There are different kinds of model. There are pricing models, like Black-Scholes. These can translate volatility quoted in different units, so for example given an option price in $ and some other inputs you can work out the "implied volatility". You can also do this calculation in the other direction, so if you have an idea of what implied vol should be for a particular option you can calculate a fair value for the price. Most option pricing platforms do this for you. None of this is telling you whether a particular option is cheap or expensive, since you still need a 'fair value' for the implied vol. To do this you need to compare the implied vol of the option to other options, or make a forecast of what you think will happen to volatility (note we always do these comparisions in implied vol space, not price space). A simple way to compare an option to other options is to construct a 'volatility surface'* (confusingly this approach is sometimes called 'model free' since it makes no assumptions about the process driving prices). When you do this you may find options that are above or below the surface and therefore cheap or expensive. * 3-d for most instruments, and 4-d for interest rate products where the maturity of the interest rate is a factor For example, for a given duration of option maturity and given instrument, the surface is just a 2-d graph with strike on the x-axis and implied vol on the y-axis. If you plot all the implied volatility points on this graph, you can try and draw a line through them using something like a quartic spline (basically a curvy line- don't panic, Excel can do this). Don't use a straight line, as this won't account for the 'smile' or 'skew' of option prices, and you'll always be selling out of the money options. * Note: Make sure you use a spline with fewer 'degrees of freedom' than you have points. Otherwise the line will go through all the points and be useless. For example if you have 5 strikes, then don't use anything more complex than a cubic polynomial. If you find some points above this line then these are expensive options you should sell, and vice versa. Often these points will be out of the money vols where the wide bid-ask spread means you can't actually exploit this apparent mispricing (to check this, translate both the bid and the ask prices into implied volatility terms). Alternatively, you can compare the volatility surface to the historic shape of the surface. Again for the simple 2-d example you would compare the current implied vols to an estimate of the curvy 'fair value' line based on historic data (typically you would shift the historic line up or down so that it went exactly through the at the money strike, or it would look like all strikes were undervalued or overvalued). Intuitively then, if the 'smile' or 'skew' of options is way out of line with historic levels you would end up buying or selling away from the at the money. You can also try and forecast what volatility will do in the future ("realised volatility"). If the implied vol is higher than the expected realised vol then we'd sell options and vice versa (ideally we'd be selling straddles or strangles and delta hedging, but you can still use this approach to give you an idea of whether options are currently overvalued or undervalued). A simple way of doing this is to assume that future realised vol will be roughly what it averaged in the past few years ("mean reversion"), and if implied vol is higher than that you sell vol, and vice versa. Because mean reversion doesn't happen that quickly this works best on longer dated options (at least 3 to 6 months). There are various more complex ways of doing this, such as GARCH (mentioned by @TheBigShort). These are all models where you estimate the model parameters based on past data, and then extrapolate from the most recent levels of vol to forecast what it will be in the near future (again as @TheBigShort says you can make these models more accurate by using higher frequency data to estimate recent levels of volatility). More sophisticated models will take into account things like economic announcements and fed meetings that will briefly bump up volatility. Hope this helps. GAT
Jeez! I just quickly glanced at ET and saw a few replies and glad! Going to read over @TheBigShort and @globalarbtrader posts now! cheers
you cant code what you don't know. traders buy low and sell high...….it has got nothing to do with models. prices always move in a band...…..the band itself is a little flexible so it is not rigid. this is what traps people into thinking trading is easy...….and it is easy. sell at 14 buy 12; sell at 16 buy at 13. simple stuff. but what confuses everyone is when you sell at 16 and it continues to 30. and they wait for it to come back to 16;it goes to 45 then 65. what do they miss? it took me 30 years to understand why this happens and it has got nothing to do with models. hint: prices move in a band
thanks for the reply, but I’m asking how can I estimate the value of volatility using software other than thinkorswim? or is thinkorswim sufficient enough? The reason I bring this up is because I’ve constantly read traders talking about all these models they use for vol, and I’ve heard others say don’t trust thinkorswim numbers. So I’m not too sure how to approach this concept.
by “band” are you speaking of magnitude of price (vol)? I’m not asking how price moves. Im asking how can a reTail trader trade vol with data other than major broker platforms? the reason I’m asking is because I’ve seen traders claim thinkorswim vol numbers aren’t accurate?
check the exchanges they may declare volume what on earth is think or swim may be one idea I do not look at volume because I believe everything is in the price.