Various Models of Option Selling

When we discuss some instruments, there has to be an approach. The approach can be unrelated to each other like ideas of Tradingview having multiple theories for multiple trades.

Also, the approach can be specific and model-based, quant-based, definitive. Lets talk about some definitive approaches over BankNIFTY and NIFTY weekly option selling

In weekly options, the impact of theta is more because the expiry is near!

In weekly options, the impact of vega is lower for the same reason as well!

But, as we are discussing intraday, option buying models will also have a lower impact of theta as they are closing the trade EOD anyways. Anyways, we shall discuss about option buying models later on.

There are lots of approaches

Machine Learning Models

An example can be seen here –

Stock market forecasting using Time Series

The stock market is designed to transfer money from the active to the patient.

– Warren Buffett

It takes past data, the Machine Learner gets trained. It’s like a human reading the data and processing it. And, based on that data it throws projection. It is pretty diverse. It can make a correlation model based on the movement of other indexes like Dax.

It can make short term pattern models, statistical models. The above link shows detail way to do Time Series analysis

Statistical Models

So, Machine Learning models are statistical models.The model we will discuss in through is also a statistical one.

Technical Models

SuperTrend Strategy based models.

Moving Average Based models.

Price Action based Models

L model – It takes SnR and does a quick sentiment analysis.

OI Based Models

The strategy discussed in the banknifty max pain page. Check there

Greek based Models

A strategy discussed in the volatility spread section. Basically you start from selling a straddle or strangle and keep balancing the delta.

There is nothing called a fundamental model because that is not something that can be defined or quantified. It’s like more of a gut feel. Gut feels can not be coded; otherwise, there would be lots of Ultrons or Javrises roaming around

Sentiment Analysis

Here is one interesting example

This bot watches Donald Trump’s tweets and waits for him to mention any publicly traded companies. When he does, it uses sentiment analysis to determine whether his opinions are positive or negative toward those companies. The bot then automatically executes trades on the relevant stocks according to the expected market reaction.

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