Introduction

 

Spearian for Excel's speed, functionality and coolness will redefine the way you work with financial and economic data and will enable you to make more robust decisions based on more sophisticated insights.

 

The Right Tool for Financial Analysis

In addition to the Excel's interface, Spearian for Excel will provide interfaces to its super-fast market data retrieval and analytical engine in Python, R, and .NET.

 

Each of the interfaces is suited for a slightly different purpose:

 

Interface

Primary Use

Advantages

Disadvantages

Excel

1.Scratch pad

2.Prototyping

3.Dashboards

1.An instantaneous GUI with little effort

2.Rich functionality

3.Excellent performance

4.Excellent visualization

1.Difficult to track changes in the sheet

2.Difficult to check the correctness of the sheet and prone to bugs as the sheet gets bigger

3.Unsatisfactory built-in numerical and statistical functions

4.Not suitable for batch processing

Python

1.Batch processing of huge datasets

1.Cross-platform

2.Standard in batch processing

3.Concise code

 

R

1.Sophisticated statistical analysis

1.Cross-platform

2.Standard in statistical computing

3.Concise code

 

.NET

1.Universal platform

1.Top Performance

2.Comfortable development

 

 

 

The Right Data Source

For each market data time series of interest, the user is advised to determine the right data source as the data sources Spearian for Excel provides may return slightly different data sets.

 

General Guidelines:

1.For financial analysis of historical securities data, Yahoo!'s feed with the Adjusted Close column used is the most suitable source as that column incorporates dividends, stock splits etc.

2.For financial analysis of live securities data, Google feed is the most suitable source as the prices are live without any delay

3.For macroeconomic analysis, Fed's Fred is the most suitable source

 

The primary data sources by Asset Class are:

1.Currencies - Open Exchange Rates

2.Macro Data - Fed's Fred

3.Equities, Indices - Google, Yahoo!

4.Everything - Quandl

 

 

Copyright © 2013-2017 Jiri Pik

Document Version: Sunday, May 7, 2017