Crypto Volatility Bitcoin Correlation Strategy Description:
The Crypto Volatility Bitcoin Correlation Strategy is designed to leverage market volatility specifically in Bitcoin (BTC) using a combination of volatility indicators and trend-following techniques. This strategy utilizes the VIXFix (a volatility indicator adapted for crypto markets) and the BVOL7D (Bitcoin 7-Day Volatility Index from BitMEX) to identify periods of high volatility, while confirming trends with the Exponential Moving Average (EMA). These components work together to offer a comprehensive system that traders can use to enter positions when volatility and trends are aligned in their favor.
Key Features:
VIXFix (Volatility Index for Crypto Markets): This indicator measures the highest price of Bitcoin over a set period and compares it with the current low price to gauge market volatility. A rise in VIXFix indicates increasing market volatility, signaling that large price movements could occur.
BVOL7D (Bitcoin 7-Day Volatility Index): This volatility index, provided by BitMEX, measures the volatility of Bitcoin over the past 7 days. It helps traders monitor the recent volatility trend in the market, particularly useful when making short-term trading decisions.
Exponential Moving Average (EMA): The 50-period EMA acts as a trend indicator. When the price is above the EMA, it suggests the market is in an uptrend, and when the price is below the EMA, it suggests a downtrend.
How It Works:
Long Entry: A long position is triggered when both the VIXFix and BVOL7D indicators are rising, signaling increased volatility, and the price is above the 50-period EMA, confirming that the market is trending upward.
Exit: The strategy exits the position when the price crosses below the 50-period EMA, which signals a potential weakening of the uptrend and a decrease in volatility.
This strategy ensures that traders only enter positions when the volatility aligns with a clear trend, minimizing the risk of entering trades during periods of market uncertainty.
Testing and Timeframe:
This strategy has been tested on Bitcoin using the daily timeframe, which provides a longer-term perspective on market trends and volatility. However, users can adjust the timeframe according to their trading preferences. It is crucial to note that this strategy does not include comprehensive risk management, aside from the exit condition when the price crosses below the EMA. Users are strongly advised to implement their own risk management techniques, such as setting appropriate stop-loss levels, to safeguard their positions during high volatility periods.
Utility:
The Crypto Volatility Bitcoin Correlation Strategy is particularly well-suited for traders who aim to capitalize on the high volatility often seen in the Bitcoin market. By combining volatility measurements (VIXFix and BVOL7D) with a trend-following mechanism (EMA), this strategy helps identify optimal moments for entering and exiting trades. This approach ensures that traders participate in potentially profitable market moves while minimizing exposure during times of uncertainty.
Use Cases:
Volatility-Based Entries: Traders looking to take advantage of market volatility spikes will find this strategy useful for timing entry points during market swings.
Trend Confirmation: By using the EMA as a confirmation tool, traders can avoid entering trades that go against the trend, which can result in significant losses during volatile market conditions.
Risk Management: While the strategy exits when price falls below the EMA, it is important to recognize that this is not a full risk management system. Traders should use caution and integrate additional risk measures, such as stop-losses and position sizing, to better manage potential losses.
How to Use:
Step 1: Monitor the VIXFix and BVOL7D indicators. When both are rising and the Bitcoin price is above the EMA, the strategy will trigger a long entry, indicating that the market is experiencing increased volatility with a confirmed uptrend.
Step 2: Exit the position when the price drops below the 50-period EMA, signaling that the trend may be reversing or weakening, reducing the likelihood of continued upward price movement.
This strategy is open-source and is intended to help traders navigate volatile market conditions, particularly in Bitcoin, using proven indicators for volatility and trend confirmation.
Risk Disclaimer:
This strategy has been tested on the daily timeframe of Bitcoin, but users should be aware that it does not include built-in risk management except for the below-EMA exit condition. Users should be extremely cautious when using this strategy and are encouraged to implement their own risk management, such as using stop-losses, position sizing, and setting appropriate limits. Trading involves significant risk, and this strategy does not guarantee profits or prevent losses. Past performance is not indicative of future results. Always test any strategy in a demo environment before applying it to live markets.
S-XRP
QQE Student's T-Distribution Bollinger Bands ScreenerThis script scans 20 custom symbols and displays the QQE Students T-Distribution Bollinger Bandwidth as a percentage, the quarter segment percentage, a score that tells you what segment of the band the price is in, and what direction the market is going in. This is useful because it can tell you how volatile a market is and how much reward is in the market. It also tells you what direction the market is going in so you can pick a symbol that has the best looking reward. I really hope that this script complements the group of indicators I have made so far. Here is a list of the other two indicators related to this script.
Please enjoy!
Moving Grid Trader - With AlertsThis script used a grid system that is set when a "buy" signal is sent to generate profits inside of a range. This script used macd to weed out bad buys and then sells once the price either reaches the grid - or hits the stoploss. This works best in bullish and ranging markets.
EMA and MACD with Trailing Stop Loss (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA.
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the security when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bearish
EMA7 is greater than EMA14
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include XRPUSDT on the 1-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly
In order to further improve the strategy, the EMA can be changed from 7 and 14 to, say, EMA20 and EMA50. Furthermore, the trailing stop loss can also be changed to ideally suit the user to match their needs.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Dap's Oscillator- Short Term Momentum and Trend. BINANCE:BTCUSDT BYBIT:BTCUSDT BYBIT:ETHUSDT BINANCE:ETHUSDT
DAP's OSCILLATOR:
WHAT IS IT?
This Oscillator was created to inspire confidence in the short-term trend of traders. This will work very well with a volatility metric (I recommend BBWP by @The_Caretaker)
WHAT IS IT MADE OF?
1. Consists of a series of equations (mainly the difference between simple to exponential moving averages) and Standard deviations of these moving average differences (length equivalent to the length of sampled ma's)
2. These equations are then boiled down through an averaging process array, after averaging the covariants are equated against the variants of the positive side of the array. This is what is presented as the aqua line.
3. The RC average (yellow) is the sma following the DAP'S Oscillator at a specified length
4. The most important part of this indicator is simply the momentum oscillator represented as a green or red line based on the value relative to the Oscillators.
HOW DO I USE THIS?
As I mentioned before mixed with a volatility metric, it should set you up for a good decision based on short-term trends. I would say to be careful for periods of consolidation, with the consolidation the momentum often meets hands with DAP's Oscillator and can cause fake-outs. You want to spot divergences from the price to the momentum difference, as well as room to work down or upward to secure a good entry on a position.
CHEAT CODE'S NOTES:
I appreciate everyone who has boosted my previous scripts, it means a lot. If you want to translate words to pine script onto a chart, feel free to PM me. I would be happy to help bring an indicator to life. I may take a quick break but will be back shortly to help create more cheat codes for yall. Thanks!
-Cheat Code
Optimised RSI strategy for Reversals (by Coinrule)The most common way to use the RSI to spot a good buy opportunity is to check for values lower than 30. Unfortunately, the RSI can remain in oversold territory for long periods, and that could leave you trapped in a trade in loss. It would be appropriate to wait for a confirmation of the trend reversal.
In the example above I use a short-term Moving Average (in this case, the MA9) coupled with an RSI lower than 40. This combination of events is relatively rare as reversal confirmations usually come when RSI values are already higher. As unusual as this setup is, it provides buy-opportunities with much higher chances of success.
The parameters of this strategy would be:
ENTRY: RSI lower than 40 and MA9 lower than the price
TAKE PROFIT and STOP-LOSS with a ratio of at least 2. That means that if you set up a take profit of 3%, your stop-loss shouldn’t be larger than 1.5%.
The advantage of this approach is that it has a high rate of success and allows you the flexibility of setting up the percentages of the take profit and stop-loss according to your preferences and risk appetite.
ICHIMOKU Crypto Swing AlertThis is a crypto swing alert for the strategy with the same name designed for timeframes bigger than 1h.
The main components are
ICHOMOKU
KDJ
Average High
Average Low
Rules for entry
For long: we have the ichimoku crosses between tenkan and baselines, we have a rising kdj line and at the same time we have a increase in the average high
For short: we have the ichimoku crosses between tenkan and baselines, we have a falling kdj line and at the same time we have an increase in the average low
Rules for exit
We exit when we have inverse conditions than the initial ones used for entry.
Caution
This strategy does not use a risk management, so be careful with it !
If you have any questions let me know !
Ripple (XRP) Model PriceAn article titled Bitcoin Stock-to-Flow Model was published in March 2019 by "PlanB" with mathematical model used to calculate Bitcoin model price during the time. We know that Ripple has a strong correlation with Bitcoin. But does this correlation have a definite rule?
In this study, we examine the relationship between bitcoin's stock-to-flow ratio and the ripple(XRP) price.
The Halving and the stock-to-flow ratio
Stock-to-flow is defined as a relationship between production and current stock that is out there.
SF = stock / flow
The term "halving" as it relates to Bitcoin has to do with how many Bitcoin tokens are found in a newly created block. Back in 2009, when Bitcoin launched, each block contained 50 BTC, but this amount was set to be reduced by 50% every 210,000 blocks (about 4 years). Today, there have been three halving events, and a block now only contains 6.25 BTC. When the next halving occurs, a block will only contain 3.125 BTC. Halving events will continue until the reward for minors reaches 0 BTC.
With each halving, the stock-to-flow ratio increased and Bitcoin experienced a huge bull market that absolutely crushed its previous all-time high. But what exactly does this affect the price of Ripple?
Price Model
I have used Bitcoin's stock-to-flow ratio and Ripple's price data from April 1, 2014 to November 3, 2021 (Daily Close-Price) as the statistical population.
Then I used linear regression to determine the relationship between the natural logarithm of the Ripple price and the natural logarithm of the Bitcoin's stock-to-flow (BSF).
You can see the results in the image below:
Basic Equation : ln(Model Price) = 3.2977 * ln(BSF) - 12.13
The high R-Squared value (R2 = 0.83) indicates a large positive linear association.
Then I "winsorized" the statistical data to limit extreme values to reduce the effect of possibly spurious outliers (This process affected less than 4.5% of the total price data).
ln(Model Price) = 3.3297 * ln(BSF) - 12.214
If we raise the both sides of the equation to the power of e, we will have:
============================================
Final Equation:
■ Model Price = Exp(- 12.214) * BSF ^ 3.3297
Where BSF is Bitcoin's stock-to-flow
============================================
If we put current Bitcoin's stock-to-flow value (54.2) into this equation we get value of 2.95USD. This is the price which is indicated by the model.
There is a power law relationship between the market price and Bitcoin's stock-to-flow (BSF). Power laws are interesting because they reveal an underlying regularity in the properties of seemingly random complex systems.
I plotted XRP model price (black) over time on the chart.
Estimating the range of price movements
I also used several bands to estimate the range of price movements and used the residual standard deviation to determine the equation for those bands.
Residual STDEV = 0.82188
ln(First-Upper-Band) = 3.3297 * ln(BSF) - 12.214 + Residual STDEV =>
ln(First-Upper-Band) = 3.3297 * ln(BSF) – 11.392 =>
■ First-Upper-Band = Exp(-11.392) * BSF ^ 3.3297
In the same way:
■ First-Lower-Band = Exp(-13.036) * BSF ^ 3.3297
I also used twice the residual standard deviation to define two extra bands:
■ Second-Upper-Band = Exp(-10.570) * BSF ^ 3.3297
■ Second-Lower-Band = Exp(-13.858) * BSF ^ 3.3297
These bands can be used to determine overbought and oversold levels.
Estimating of the future price movements
Because we know that every four years the stock-to-flow ratio, or current circulation relative to new supply, doubles, this metric can be plotted into the future.
At the time of the next halving event, Bitcoins will be produced at a rate of 450 BTC / day. There will be around 19,900,000 coins in circulation by August 2025
It is estimated that during first year of Bitcoin (2009) Satoshi Nakamoto (Bitcoin creator) mined around 1 million Bitcoins and did not move them until today. It can be debated if those coins might be lost or Satoshi is just waiting still to sell them but the fact is that they are not moving at all ever since. We simply decrease stock amount for 1 million BTC so stock to flow value would be:
BSF = (19,900,000 – 1.000.000) / (450 * 365) =115.07
Thus, Bitcoin's stock-to-flow will increase to around 115 until AUG 2025. If we put this number in the equation:
Model Price = Exp(- 12.214) * 114 ^ 3.3297 = 36.06$
Ripple has a fixed supply rate. In AUG 2025, the total number of coins in circulation will be about 56,000,000,000. According to the equation, Ripple's market cap will reach $2 trillion.
Note that these studies have been conducted only to better understand price movements and are not a financial advice.
Cryptocurrency Spot RatesThis is an overlay indicator on the chart that will plot cryptocurrency spot prices of the following exchanges:
- Coinbase
- Poloniex
- OKCOIN
- Binance
- Huobi
- Bittrex
- HitBTC
- Kraken
- Bitfinex
Additionally it plots the price average of all those exchanges.
This overlay is intended to be used on charts with derivatives/futures such as BitMEX/Deribit/...
It works with all USD and Tether pairs on the main chart (for example BTCUSD, ETHUSD, BCHUSD,...)
USDT SupplyThis script shows the USDT (Tether) supply, total USDT market capitalization and USDT supply on various Cryptocurrency exchanges.
It is based on this script:
Changes:
- added HiTBTC and Huobi exchange
- updated to Pine Script v4
- improved default style and line width to highlight global USDT plots against exchange-specific plot lines
EVWMA VWAP MACD Strategy [QuantNomad]Based on comment of @coondawg71 I tried to compare VWAP and EVWMA.
Both are sort of moving averages so I decided to create a MACD based on these 2 indicators.
In parameters you can set EVWMA Length and 2 smoothing lengths for "macd" and "signal".
Strategy seems to work pretty good at 2h-8h timeframes for crypto.
What do you thing about it?
On Balance Volume Oscillator Strategy [QuantNomad]Looking for the way to use OBV Oscillator in a strategy.
Here is my first try. I just enter to position of a cross of 2 emas based on OBV.
Here is my original oscillator indicator:
Kozlod - Simple BB Strategy - XRPBTC - 1 minutePretty good performance of simple BB on XRPBTC 1minute chart.
No SL or PT used.
And remember:
Past performance does not guarantee future results.
Top 5 coins cummulated Upvol/Dnvol and Money FlowThis script reads price and volume information for the top 5 coins (on 9 exchanges, a total of 29 pairs), calculates the cummulative upvolume and downvolume according to the Money Flow (MFI) formula, and shows upvolume and downvolume separately on the chart as a green and a red line.
The coins used are BTC, ETH, LTC, XRP and EOS. They are the top 5 coins by daily volume, as of 24th of February 2019.
Because of the many security() calls needed, the script is VERY slow, so have lots of patience.
I find it useful as a broad crypto market indicator - for example to compare the current pump with the pumps in the past.
Can also calculate the aggregated Money Flow (MFI) if you check that option in the indicator's configuration. Make sure to wait for recalculation and rescale the chart afterwards - MFI has a value from 0 to 100 and you may need to zoom in.
XRPUSD LONG/SHORT RATIO BITFINEXXRP longs and shorts on finex.
Red line -> Shorts
Green line -> Longs
Area -> Longs/Shorts normalized.
Bitfinex XRP Long/Short +Ratiodefault:
ON - BitFinex longs/shorts and sub
OFF - itFinex longs/shorts ratio
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
XRPBTCSHORTS XRPBTCLONGS - Bitfinex XRP Shorts & Longs// Created by titanlyy
// This script was inspired by @autemox who created the BTC version of this.
// Hope this helps. Peace out.
// 7th September 2018
True Price XRPArbitrage is the simultaneous purchase and sale of an asset to profit from a difference in the price. It is a trade that profits by exploiting the price differences of identical or similar financial instruments on different markets or in different forms.
In cryptocurrencies, arbitrage is difficult - if not impossible to profit from due to the large transaction costs of buying and sell on the different exchanges.
Some exchanges have fees in excess of 3%. This means that the difference in price between exchanges would have to be greater than the transaction cost in order to profit.
This also does not take into account the risk of price movement in the time it would take to transfer funds between exchanges, making the ability to profit from arbitrage impossible for the retail investor.
While "arbitrage" may be intuitively associated with "sabotage" to the uninformed, the occurence is not a result of greedy price manipulation. The difference in price between exchanges can be simply justified by the separation of market depth creating an indipendantly operating order book.
Essentially, this is an individually performing market with a unique price spread.
In order to determine the most visually accurate price, I have averaged the asking price of these six exchanges:
1. KRAKEN
2. BITSTAMP
3. BITFINEX
4. BITTREX
5. POLONIEX
6. BITSO
This plotted line can be overlayed on top of any XRP/USD price from any given exchange in order to view the variance from the average in real-time, or you can hide the underlying chart to view only the average of the six exchanges as demonstrated in the chart above.
Find this in the public indicator library!
Like and follow for more great scripts.
