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https://github.com/lipskiyp/trading_dashboard

Pandas framework to analyze financial time-series and calculate various performance metrics (e.g. Sharpe Ratio and Max Drawdown Duration).
https://github.com/lipskiyp/trading_dashboard

financial-analysis numpy pandas

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Pandas framework to analyze financial time-series and calculate various performance metrics (e.g. Sharpe Ratio and Max Drawdown Duration).

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# Pandas Trading Dashbaord

Pandas framework to calculate performance metrics for financial time-series.

## Overview

The aim of the project was to design a Pandas framework to analyze financial time-series and calculate various performance metrics (such as Sharpe Ratio and Max Drawdown Duration).

## Example Output

```bash
benchmark ts_1 ts_2
Avg. Price Change 0.06783 -0.062331 -0.092221
Avg. Annual Return 0.190378 -0.144275 -0.209066
CAGR 0.20279 -0.138661 -0.19213
Var 0.009869 0.011089 0.010094
Vol 0.099343 0.105305 0.100471
DownsideVol 0.176494 0.196947 0.198266
UpsideVol 0.011422 0.0177 0.013514
CoVar 0.009869 -0.000021 0.000511
Corr 1.0 -0.001972 0.051221
Skew 0.0 0.00001 0.000009
CoSkew 0.0 -0.000003 0.000004
Kurt 0.000145 0.000228 0.000189
CoKurt 0.000145 -0.000006 0.000016
DD -0.183349 -0.009844 -0.010982
DDur 355 days 00:00:00 7 days 00:00:00 63 days 00:00:00
MaxDD -0.183349 -0.076455 -0.085263
MaxDDur 355 days 00:00:00 101 days 00:00:00 59 days 00:00:00
PainIdx 0.10961 0.018286 0.020202
```

## Requirements

Library requirements can be installed using your preferred package manager, e.g. pip:

```bash
pip3 install -r requirements.txt
```

## Launch

To display the example trading dashboard:

```python
python3 main.py
```

## Folders Overview

### /dashborad/dashboard.py

Contains trading dashboard client example implementation which acts as an interface for metrics services.

### /dashborad/metrics

Contains metrics clients used to calculate metrics for financial time-series.

### /dashborad/timeseries

Contains time-series object for all interactions with the financial time-series.

### /timeseries

Contains random time-series factory.