Statistical and Financial MetricsGood morning traders!
This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market)
By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle
Here are the metrics you can have by storing data from a variable period of candles (by default 51):
✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE)
✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER)
✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close
✓ Covariance of the two datasets (in BLUE)
✓ Correlation coefficient of the two datasets (in AQUA)
✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same).
WHAT IS BETA (β)?
The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds.
We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk).
The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio.
Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset.
So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well
According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld.
In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f)
where:
r_i = expected yeld of the asset
r_f = risk free interest rate
β = beta
r_m = yeld of market portfolio
I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
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USDT PremiumThis is a simple script that aggregates the USDTUSD pairs available on PulseWire and shows the average price of (USDTUSD - 1).
Heavy buying of BTC on USD exchanges (read: Coinbase) will result in a positive USDT premium
Heavy selling of BTC on USD exchanges (read: Coinbase) will result in a negative USDT premium
Heavy buying of BTC on USDT exchanges result in a negative USDT premium
Heavy selling of BTC on USDT exchanges will result in a positive USDT premium
Here is a quote about USDT premiums from Zhao Dong, one of China's largest OTC traders, from the article "Chinese Bitcoin Billionaire Argues USDT Premium is Caused by USD Inflow, Not Tether Inflation":
"So let me tell you a little bit about where the plus or minus premium for usdt comes from. Right
The biggest exchange in America is coinbase, which trades in dollars. In addition to coinbase, most exchanges with large trading volume are usdt trading. Since BTC and usdt can flow freely between exchanges, the price difference is very small.
Assuming that the market is stable, there is no difference between the prices of usd and usdt. Btcusd = btcusdt
At some point the market starts to recover, goes up, and the otc money starts to come into the market. Coinbase is a compliance exchange, so the usd deposit is very smooth, while the usd deposit through usdt needs to be converted into usdt first and then deposited into the exchange, so the usdt will be slightly delayed in price transmission, so the usd exchange price is higher than the usdt exchange price. If there is a lot of dollars to buy, coinbase goes up first and usdt goes up later.
At this point, the coinbase price is higher than the usdt exchange price. If btcusd>btcusdt, because BTC is free flowing, that means usdt is in a positive premium to usd.
This arbitrage space will prompt the brick moving party to sell BTC from coinbase to usd, and then use usd to buy usdt, thus facilitating the issuance of usdt.
A negative usdt premium would prompt Tether to take back the usdt and destroy it."
Includes an option for repainting -- default value is true, meaning the script will repaint the current bar.
False = Not Repainting = Value for the current bar is not repainted, but all past values are offset by 1 bar.
True = Repainting = Value for the current bar is repainted, but all past values are correct and not offset by 1 bar.
In both cases, all of the historical values are correct, it is just a matter of whether you prefer the current bar to be realistically painted and the historical bars offset by 1, or the current bar to be repainted and the historical data to match their respective price bars.
As explained by PulseWire,`f_security()` is for coders who want to offer their users a repainting/no-repainting version of the HTF data. Indicator
CRYPTO HA Strategy money maker long termToday I bring you another amazing strategy.
Its made of 2 EMA in this case 50 and 100.
At the same time, internaly for candles we calculate the candles using the HA system ( while still using in live the normal candles). This way we can assure that even if we use HA candles, we avoid repainting, and its legit.
We first calculate the HA candles based on the EMA 50 values, and after that , we use that candle properties to apply to EMA 100.
Once we have that, for entries we have the next conditions :
sell = o2 > c2 and o2 < c2 and time_cond
buy = o2 < c2 and o2 > c2 and time_cond
For sell : Our open from HA 100 is bigger than Close from ha 100, and the previous open is smaller than previous close
For long : Our open from ha 100 is smaller than close from ha 100 and the previous open is bigger than previous close.
Then we have 2 options :
If we wnat to go only long , which is my prefered version ,or the original one where we go both long and short.
I found that the best results are in general around bigger timeframes, 1h+ , 3h works the best so far on my tests.
For exit we have 2 versions :
1 lets say we had a long signal, as soon as we have a short signal we close the trade. Viceversa for short.
2. Is based on price % movement. In this case I use 7.5% price movement of asset.
We have no TP in use for this system.
For the purpose of this test I use 10.000 $ account. For test I use 100% of it, without any leverage.
I use the SL based on price movement , which is a very risky tool, since it can fluctuate even at 20-30% of our capital.
For comission I used 0.1% for each deal, and a slippage of 5 points.
Be cautious with this system !
If you have any questions , message me. Strategy
Crypto MultiTrend multi timeframesHello, today I bring you another crypto strategy which can work with multiple timeframes and most of crypto currencies
Its made entirelly of multiple EMA , of different lengths : like super fast, fast, normal, slow and very slow
We also combine a little bit of price action together with the trend direction both for entry and for exits, to have a more precise control.
The rules for long close is above all EMA's, they are in ascending order and the at same time close is bigger than the previous high, and previous high > second previous high, close > 3rd previous high , close > 4th previous high, close > 5th previous high, 5th high > 6th high.
For short we have the same, but instead of high, we use lows, and instead of > we use < .
As exit we have 2 conditions for long and 2 for short
To exit long we have : super fast ema < fast ema and fast ema < normal and normal < slow ema. For short, they would be the opposite, using > sign.
The second exit for long is when our current low crosses below 4 of ours EMA during the same candle. For short, is when the high crosses above 4 of ours EMA during the same candle.
CAUTIOUS : Currently it uses not risk management system, so in this current condition is extremely risky . Be careful
If you have any questions lets me know Strategy
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