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Kifier's MFI/STOCH Hidden Divergence/Trend Beater
MFI/STOCH Hidden Divergence/Trend Beater
General Idea:
My premise around this strategy was to make a general strategy for crypto that would help out with finding entry positions for when you’re bullish on a crypto and want to hold on for a while, and at the same time avoiding massive drops. Essentially a way to mix long term/ swing trading; I somewhat achieved my goal however it still requires a lot of logic tuning of the trend averages.
I’m a huge proponent of volume indicators and coupled with average closing price, I think this gives a really good idea of what is happening with the market. It gives an idea on the market and retail investor sentiment. This generally gives you logical entry positions (Although I don’t know how amazing that will work with all cryptos, there’s a fine line between a good strategy and one that just rides bubble market conditions, some would argue that’s still a success and others not)
How it works:
There are many components to the strategy that try to do different things:
First of all there are two types of entries, a MFI hidden divergence with a STOCH check, essentially it will only fire when a divergence is detected while STOCH is above 50%, however this might be changed in the future as due to the volatile nature of cryptos, the STOCH is not too effective. The second entry is a simple MFI/STOCH trend, if STOCH is above 50% and the trend is detected to be in a trending long, once a MFI crossover over the 50% line is detected an entry is placed, this is designed to get out profit where the divergence would otherwise be less accurate during strongly trending conditions.
-MFI is a great indicator, as a volume weighted momentum indicator I find it the most accurate of all, the STOCH however is a great indicator to get a general picture of simple market conditions and can filter out the emotional noise of retail investors.
-VWMA and an SMA (The bottom oscillator) gives an idea of the trend tacking into account of the volume, this serves as a more short term filter of the trend for filters.
-OBV checks are done between the OBV and an EMA of the OBV, to get the idea of a volume weighted long trend, which is important for crypto as there are massive rallies to go up due to retail greed, it’s great to jump onto it at the beginning, and get off before the stack of cards fall apart.
-ATR is used to detect when the market is relatively just ranging or moving sideways, which is where the hidden divergence entries are done, during predictable and profitable market conditions.
- Stop loss is based on the closest support of the entry, this is a nice medium of room to breath but also an actual stop loss.
Future plans and improvements:
Currently there’s a lot I want to improve, mostly the divergence detection and the overall sharpe ratio could be much better, but the current value of 0.5 gives me hope that the strategy is onto something. I also want to change TP from a percentage stop to something more dynamic but that might be too optimistic. The current plan is to paper trade test this either by manual or by a python bot, to see how it performs with some user input as well.
General Idea:
My premise around this strategy was to make a general strategy for crypto that would help out with finding entry positions for when you’re bullish on a crypto and want to hold on for a while, and at the same time avoiding massive drops. Essentially a way to mix long term/ swing trading; I somewhat achieved my goal however it still requires a lot of logic tuning of the trend averages.
I’m a huge proponent of volume indicators and coupled with average closing price, I think this gives a really good idea of what is happening with the market. It gives an idea on the market and retail investor sentiment. This generally gives you logical entry positions (Although I don’t know how amazing that will work with all cryptos, there’s a fine line between a good strategy and one that just rides bubble market conditions, some would argue that’s still a success and others not)
How it works:
There are many components to the strategy that try to do different things:
First of all there are two types of entries, a MFI hidden divergence with a STOCH check, essentially it will only fire when a divergence is detected while STOCH is above 50%, however this might be changed in the future as due to the volatile nature of cryptos, the STOCH is not too effective. The second entry is a simple MFI/STOCH trend, if STOCH is above 50% and the trend is detected to be in a trending long, once a MFI crossover over the 50% line is detected an entry is placed, this is designed to get out profit where the divergence would otherwise be less accurate during strongly trending conditions.
-MFI is a great indicator, as a volume weighted momentum indicator I find it the most accurate of all, the STOCH however is a great indicator to get a general picture of simple market conditions and can filter out the emotional noise of retail investors.
-VWMA and an SMA (The bottom oscillator) gives an idea of the trend tacking into account of the volume, this serves as a more short term filter of the trend for filters.
-OBV checks are done between the OBV and an EMA of the OBV, to get the idea of a volume weighted long trend, which is important for crypto as there are massive rallies to go up due to retail greed, it’s great to jump onto it at the beginning, and get off before the stack of cards fall apart.
-ATR is used to detect when the market is relatively just ranging or moving sideways, which is where the hidden divergence entries are done, during predictable and profitable market conditions.
- Stop loss is based on the closest support of the entry, this is a nice medium of room to breath but also an actual stop loss.
Future plans and improvements:
Currently there’s a lot I want to improve, mostly the divergence detection and the overall sharpe ratio could be much better, but the current value of 0.5 gives me hope that the strategy is onto something. I also want to change TP from a percentage stop to something more dynamic but that might be too optimistic. The current plan is to paper trade test this either by manual or by a python bot, to see how it performs with some user input as well.
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