ProfiTrade 0.0.4

A proprietary open source fintech python package with a plethora of features for building equity and cryptocurrency trading algorithms.

# ProfiTrade-Package 0.0.4

A proprietary open-source fintech python package with a plethora of features for building equity and cryptocurrency trading algorithms.

## Features

### Data.Price

Crypto (Class):

• Historical: This function takes the interval and outputsize as parameters, using the alpha vantage API, it returns a df with historical price data.

• Current: If toAppend (parameter) is set true, the function takes in a pandas dataframe and appends the current price data. Else, when toAppend is false, using the alpha vantage API, it returns a df with the current crypto exchange rate.

Stock (Class):

• historicalIntraday: This function takes the interval and outputsize as parameters, using the alpha vantage API, it returns a df with historical intraday price data.

• historicalIntradayExtended: This function takes the interval as parameters, using the alpha vantage API, it returns a df with extended historical intraday price data.

• historicalDaily: This function takes the outputsize as parameters, using the alpha vantage API, it returns a df with historical daily price data.

### Indicators.Technical

• SMA(func.): Given a pandas dataframe, this function calculates and adds simple moving average.

• RSI(func.): Given a pandas dataframe, this function calculates and adds relative strength index.

• EMA(func.): Given a pandas dataframe, this function calculates and adds expotential moving average.

• MACD(func.): Given a pandas dataframe, this function calculates and adds Moving Average Convergence Divergence.

• BOLBANDS(func.): Given a pandas dataframe, this function calculates and adds the Boll. Bands.

### Screen.Finviz

.Quantitative:

• MostVolatile

• MostActive

• TopGainers

.Technical:

• HorizontalSupportResistance

• SidewaysHighVolume

• SidewaysChannel

## Upcomming Features

• Multiple trade logging functions (xl, csv, email, pandas etc.)

• Catalyst (Using ML to differentiate between negative and positve news, social media sentiment etc.)

• Fundemental Analysis (Based on financial ratios, financial health and future cash flow models etc.)

• Economic Analysis (Using bond yields, interest rates, fed decisions)

• Financial Data (Cash flow and other financial statements)

• Technical Analysis

• Any many more comming soon for free!