Options Data forecasting turning points and key levels
Options are major weapon (if properly used) in toolset of Trader. Billions of dollars each day are floating on market and speculation here is an art. Art performed by Big Guys (aka Smart Money), where funds are often significantly higher in comparison to Futures Market. With help of Machine Learning algorithms, I load Options Flow data, parse and analyse it and extract to Quandl Dataset. From there, I load it via API to Tradingview and display results in indicators. And I trade with edge instruments from Futures Market.
This data doesn't need to be always used on Intraday timeframes. We can't forget about Big Picture aka Context. From D1 timeframe alongside with properly parsed Options Data, we're able to identify real key levels (not by using Price Action but by using Balance Points, where Volume of CALL options is equal to Volume of PUT options) - marked on DAX chart with red horizontal lines. Those are close prices of candles, on which indicator identified Balance Points (blue background on indicator). Demand always is trying to reach balance with Supply - therefore that's why it's even more important to observe such levels. I personally love to play retests of those levels and breakouts - especially when they happen after at least few days since initial Balance Point.
We can't forget about Pressure. Who is dominating at the market? This is the question that traders are asking themselves each session. Based on multiple factors, like: Put/Call Ratio, Strike Prices and Expirations of Options, Volume put on Options, Type of Options (ATM, ITM or OTM) - Machine Learning is allocating weigh ratio to those factors and return result identified on indicator by green/red area. Bigger Area show stronger Imbalance on market (aka one side dominates the market).
We have so many data around us, sorry - tons of data! We are unable to parse it and get insights manually. Here Machine Learning comes handy. I encourage you to deep dive into Options Market and combine it with picture, that Market draws you via chart. Market is based on emotions, so play what you see from moves of Big Players - which in majority believe me - are present on Options market.
This data doesn't need to be always used on Intraday timeframes. We can't forget about Big Picture aka Context. From D1 timeframe alongside with properly parsed Options Data, we're able to identify real key levels (not by using Price Action but by using Balance Points, where Volume of CALL options is equal to Volume of PUT options) - marked on DAX chart with red horizontal lines. Those are close prices of candles, on which indicator identified Balance Points (blue background on indicator). Demand always is trying to reach balance with Supply - therefore that's why it's even more important to observe such levels. I personally love to play retests of those levels and breakouts - especially when they happen after at least few days since initial Balance Point.
We can't forget about Pressure. Who is dominating at the market? This is the question that traders are asking themselves each session. Based on multiple factors, like: Put/Call Ratio, Strike Prices and Expirations of Options, Volume put on Options, Type of Options (ATM, ITM or OTM) - Machine Learning is allocating weigh ratio to those factors and return result identified on indicator by green/red area. Bigger Area show stronger Imbalance on market (aka one side dominates the market).
We have so many data around us, sorry - tons of data! We are unable to parse it and get insights manually. Here Machine Learning comes handy. I encourage you to deep dive into Options Market and combine it with picture, that Market draws you via chart. Market is based on emotions, so play what you see from moves of Big Players - which in majority believe me - are present on Options market.
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