**TOOL USED**

R

MICROSOFT AZURE

MICROSOFT EXCEL

**SUMMARY**

The Dataset is time series data of crypto currency consisting of of 1869 observation and 21 features(each feature showing different crypto currency). Frequency of the observations is 5 min showing from date 18/01/18 to 24/01/18.

**BUSINESS UNDERSTANDING**

As the data belongs to the crypto exchange. Intraday short-term data infers to the short-term speculation objective of the prediction model.

Predicting the 5 min data for particular observations in continuous time format.

**DATA UNDERSTANDING**

Each observation (21) in the dataset is closing value of respective observation along with timestamp. Columns are numerical values.

**DATA PREPERATION**

There were lot many observations missing in the dataset. We built regression model to impute those values.

**MODELING**

Plot, examine, and prepare series for modeling

Extract the seasonality component from the time series

Test for stationarity and apply appropriate transformations

Choose the order of an ARIMA model

Forecast the series

## 2 thoughts on “CRYPTO CURRENCY PREDICTION”

Correct me if I am wrong, but there is no code or output, nor any links to any of these.

this must be a mistake – probably somebody from the jury has voted thinking that the best score is represented by the highest number