Strategy
BTC Perpetual Futures Premium [Morty]Version 1.0, 20210409
This is an oscillator indicator that shows the premium between BTC perpetual futures and spot prices.
The prices of futures and spot are weighted average prices, weighted by the exchange's trading volume.
When the indicator is in the upper half of the region, the funding rate of perpetual contracts is relatively high, and the market trend is bullish.
When the indicator is in the upper half of the region, the funding rate of perpetual contracts is relatively high, and the market trend is bearish.
You can set the upper and lower limits of the premium. When the indicator exceeds the upper or lower limit, the trend usually reverses.
Buy the dip, Sell the high.
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Version 1.0, 20210409
这是一个振荡器指标，它显示了BTC永续期货和现货之间的溢价。
期货和现货的价格是加权平均价格，由交易所的交易量加权。
当指标在上半部区域时，永续合约的资金费率相对较高，市场趋势是牛市。
当指标在上半部区域时，永续合约的资金费率相对较高，市场趋势是熊市。
您可以设置溢价的上限和下限。当指标超过上限或者下限，通常会趋势反转。
Buy the dip, Sell the high.
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Multi Moving Average Crossing (by Coinrule)Moving Averages are among the most common trading indicators. They are straightforward to interpret and effective to use.
One of the limitations of using moving averages is they can provide buy and sell signals with a relatively high lag , making it very difficult to spot the lows and tops of the trend.
Moving averages calculated with a low number of periods like the MA9 (the average of the previous nine price periods) react very fast to price moves providing prompt signals. On the other side, more signals may end up with more false-signals and more trades in a loss.
On the contrary, moving averages calculated with a higher number of periods like the MA100 (which considers the previous one hundred price periods) give more reliable signals, but with a delay.
A system catching the crossing of the MA50 over the MA100 is a good compromise for successful long-term strategies. It provides, on average, reliable buy signals.
The Multi Moving Average Crossing Strategy tries to optimize the exit without waiting for the same opposite crossing (MA50 below MA100). It uses the MA9 crossing below the MA50, instead, to spot a better time for selling.
The setup is as follows.
BUY when the Moving Average 50 crosses above the Moving Average 100
SELL when the Moving Average 9 crosses below the Moving Average 50
The higher is the time frame to calculate the Moving Averages, the better is the overall performance of the strategy. The 4-hour (or 6-hour) time frame seems to be the best, even if it results in fewer trades. If you want to trade more still with good results, the 1-hour time is a good compromise.
Advantages of the strategy
This strategy seeks to catch those that are more likely relevant uptrends and close the trade relatively quickly. More trades mean more opportunities. This is especially effective if you run the strategy on all the available coins on the market, as you could do with Coinrule.
Generally, a Multi Moving Averages approach beats the classic crossing strategy involving only two Moving Averages. We backtested a sample of twenty trading pairs to assess the benefits empirically.
The results show that the Multi Moving Average Strategy
outperforms 13 out of 20 times
has 95% higher average return
has 67% higher median return
The strategy assumes each order to trade 30% of the available capital and opens a trade at a time. A trading fee of 0.1% is taken into account.
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Arbitrage Sniper (POC)Good Morning Traders!
Today I want to share with you the proof-of-concept of how you would be able to do arbitrage with crypto pairs.
THE INDICATOR MUST BE PLACED ON THE TRADING PAIR OF THE TWO CURRENCIES (i.e. ETH/BTC, EOS/ETH etc.)
This arbitrage method is based on the transitional decorrelation between the crypto treding pair and the price ratio of the involved currencies, of course computing commissions as well.
Whenever the non-arbitrage condition is not respected, there is an arbitrage oportunity.
This indicator won't consider the chance of shorting, so if the arbitrage oportunity occurs the indicator will suggest you just the chance of buying the relative-undervalued currency (but inside the code you will know how to do the alternative method as well, by shorting the relative-overvalued currency)
Let's take the trading pair ETH/BTC (as in the graph) → if we assume commissions for the 0.075% of the order, the non-arbitrage condition will be presented like this
This arbitrage method will need three orders, so n=3
So let's assume that P(ETH)/(P(BTC)*P(ETH/BTC))>(1-0.075)^(-3) → it means that the price of Ethereum is currently overreated enough (relatively to the trading pair) for doing arbitrage.
We have two alternatives:
• Buy BTC, change it into ETH (by "buying" ETH in the trading pair ETH/BTC) and then sell ETH
• Sell ETH, buy BTC, change it into ETH (by "buying" ETH in the trading pair ETH/BTC)
On the other hand, if P(ETH)/(P(BTC)*P(ETH/BTC))<(1-0.075)^(-3) → it means that the price of Ethereum is currently underrared enough (relatively to the trading pair) for doing arbitrage.
We have two alternatives:
• Buy ETH, change it into BTC (by "selling" ETH in the trading pair ETH/BTC) and then sell BTC
• Sell BTC, buy ETH, change it into BTC (by "selling" ETH in the trading pair ETH/BTC)
I'm saying that is nothing more than a proof-of-concept since:
- Arbitrage Oportunities will emerge frequently just nearly zero commissions
- Data of prices are retrieved using security() function and there can be some delay (so the arbitrage oportunity will be already extinguished by the time the signal is retrieved)
- In order to have the freshest data, repiainting will occurr Indicator
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KAMA Strategy - Kaufman's Adaptive Moving AverageThis strategy combines Kaufman's Adaptive Moving Average for entry with optional KAMA, PSAR, and Trailing ATR stops for exits.
Kaufman's Adaptive Moving Average is, in my opinion, a gem among the plethora of indicators. It is underrated considering it offers a solution that intuitively makes a lot of sense. When I first read about it, it was a real 'aha!' moment. Look at the top, pink line. Notice how during trending times it follows the trend quickly and closely, but during choppy, non-trending periods, the KAMA stays absolutely flat? Interesting! To trade with it, we simply follow the direction the KAMA is pointing. Is it up? Go long. Is it down? Go short. Is it flat? Hold on.
How does it manage to quickly follow real trends like a fast EMA but ignore choppy conditions that would whipsaw a fast EMA back and forth? It analyses whether recent price moves are significant relative to recent noise and then adapts the length of the EMA window accordingly. If price movement is big compared to the recent noise, the EMA window gets smaller. If price movement is relatively small or average compared to the recent noise, the EMA window gets bigger. In practice it means:
The KAMA would be flat if a 20 point upwards move occurred during a period that has had, on average, regular 20 point moves BUT
the KAMA would point up if a 20 point move occurred during a period that has, on average, had moves of only around 5 points.
In other words, it's a slow EMA during choppy flat / quiet flat periods, and a fast EMA as soon as significant volatility occurs. Perfect!
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The Strategy
The strategy is more than just a KAMA indicator. It contains:
KAMA exit (optional)
ATR trailing stop loss exit (optional)
PSAR stop loss exit (optional)
KAMA filter for entry and exits
All features are adjustable in the strategy settings
The Technical Details:
Check out the strategy's 'Inputs' panel. The buy and sell signals are based on the 'KAMA 1' there.
KAMA 1: Length -- 14 is the default. This is the length of the window the KAMA looks back over. In this instance, it c
KAMA 1: Fast KAMA Length -- 2 is the default. This is the tightest the EMA length is allowed to get. It will tend towards this length when volatility is high.
KAMA 1: Slow KAMA Length -- 20 is the default. This is the biggest the EMA length is allowed to get. It will tend towards this length when volatility is low.
KAMA Filter
The strategy buys when the KAMA begins to point up and sells when the KAMA points down. Generally, the KAMA is very good at filtering out the noise itself - it will go flat during noisy/choppy periods. But to add another layer of safety, its author, Perry Kaufman, proposed a KAMA filter. It works by taking the standard deviation of returns over the length of the the 'KAMA 1: Length' I mentioned above and multiplying it by an 'Entry Filter' (1 by default) and 'Exit Filter' (0.5 by default). The entry condition to go long is that the KAMA is pointing up and and it moved up more than 1 x St. Dev. of Returns. The exit condition is when the KAMA is pointing down and it moved down by more than 0.5 x St. Dev. of Returns.
Thanks
Thanks to ChuckBanger, cheatcountry, millerrh, and racer8 for parts of the code. I was able to build upon their good work.
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I hope this strategy is helpful to you.
Do you have any thoughts, ideas, or questions? Let me know in the comments or send me a message! I'd be glad to help you out.
If you need an indicator or strategy to be built or customised for you, let me know! I'll be glad to help and it'll probably be cheaper than you think! Strategy
