Bollinger bands better than the macd for cry.ptocurrency trading bitcoin usd

Bollinger bands better than the macd for cry.ptocurrency trading bitcoin usd
The below is an excerpt of a longer article I have written on A Technical Indicator That Works for Cryocurrencies — Python Trading. I have selected the part relevant for the qution but feel free to check out the full article in the link. Cryocurrency trading has exploded in recent years as it shows tremendous potential and opportunities. It is true that it is still in its baby form which means there are still many areas to explore and exploit. In this article, we will first understand the logic behind cryocurrencies before creating an indicator and back tting its protability as a systematic trading strategy. Quick Introduction to Cryocurrencies Cryocurrencies Cryography Currencies are a form of electronic mon. ey created with the intent to facilitate some tasks and transfers. As the name suggts, they are usually associated with the fact of hiding ones identity. As there is no middle man between the transactions, the costs tend to be cheaper than government issued fiat currencies. In order to ensure authenticity and avoid fraud, users can record and verify at the same time their transactions as well as the transactions of others. These recordings are known as ledgers and are public to everyone for transparency purposes. The first cryocurrency is the well known Bitcoin, created by the simultaneously known and unknown Satoshi Nakamoto. Bitcoin in USD terms BTCUSD. Image by Author Nowadays, there are a lot of cryocurrencies trading with the known ones such as BTCUSD and ETHUSD and the lesser known ones such as Cardano and Dogecoin. The next part will discuss the indicator we will be creating from scratch before applying it to Bitcoin, Ethereum, and Ripple. Finally, we will be able to evaluate the efficiency of the strategy we have created. Creating the Indicator Cryo trading is co.nstantly evolving and many traders are interted in diversifying their knowledge and portfolios by including cryocurrencies. This has prompted an explosion in the number of trades, thus, lowering costs and giving way to more liquidity. We will present an indicator that I have found to wor.k quite well on cryocurrencies within given risk management co.nditions. Let us first present the intuition of the indicator. Every action must have a reaction and therefore an up move should have a corrective down move. The qution is When and what is the magnitude? The answer to that qution is complicated but we can try to approach it with simple tools. Perfection is non existent in financial dictionnaries but by time we can reach satisfactory strategies if we remain focused and disciplined. This formula can also be found when calculating the Relative Vigor Index and thus I take no credit in it, also I have named it temporarily the Real Range Indicator until I find out if it exists already or not in that case, all credits go to its creator. The Real Range Indicator is calculated following this formula Image by Author. The function in Python is very simple. We have to use it on an OHLC Open, High, Low, Close array, then the function will select a column using the where variable and then apply the formula. Remember that the fourth column Datai, 3 refers to the closing price, the first column Datai, 0 refers to the opening price, the seco.nd column Datai, 1 refers to the high, and the third column Datai, 2 refers to the low. This is because Pythons indexing starts at zero. PYTHON CODE GOES HERE BUT DUE TO FORMATTING ISSUES CAN BE FOUND IN THE ORIGINAL ARTICLE LINK ON MEDIUM, SORRY BTCUSD versus the RRI. Image by Author It looks like we can form a boundary around 0.75 and 0.75 and this seems to wor.k on other pairs as well. This is to be expected co.nsidering the formula of the RRI. Hence, the trading co.nditions can be the following Go long Buy whenever the RRI reaches 0.75 with the previous value being above 0.75. Hold this position until getting another signal or getting closed out due to risk management mentioned above. Go short Se.ll whenever the oscillator reaches 0.75 with the previous value being less than 0.75. Hold this position until getting another signal or getting closed out due to risk management mentioned above. PYTHON CODE GOES HERE BUT DUE TO FORMATTING ISSUES CAN BE FOUND IN THE ORIGINAL ARTICLE LINK ON MEDIUM, SORRY Also, to make this a trading system rather than just systematic signals, I will add a risk management component using the Exponential Average True Range that we have seen together in previous articles. Back tting the Strategy The way I use systematic strategies is to give the algorithms space to breathe and therefore I violate my very own first rule of risk reward ratio. I generally target 1x eATR and risk 4x eATR as opposed to the normal target at 2x ATR and stop a 1x ATR. The entry triggers will be based on signals generated following t