Sail

We will be employing a mixture of classic investing techniques (Including traditional fundamental analysis of financial statements as well as physical 'detective' work like speaking to suppliers and management) along side of the tools that new technology has brought to markets. This includes quantitative analysis of extremely large datasets, automated aggregation and presentation of new information, machine learning algorithms and more. We use the programming language Python heavliy for our analytics in combination with robust data science libraries as well as third party and custom mining and machine learning tools. In addition to the backend stuff, we also employ proprietary front end solutions with either a web development stack (HTML/CSS/PHP/SQL/Flask) and/or Excel VBa to present results and incoming information to us in an easy to interpret and rapidly actionable manner.

We believe that tools of this nature in combination with classic value investing techniques will give us the edge needed to outperform in the next market cycle. In a minimal example below, we've added a Net Asset Value Per Share calculator to this page. If you are familiar with the writings of Benjamin Graham you will remember his fondness for this analytical approach. We add up the value of a companies' assets and calculate how much of the companies' share price is backed by assets (in practice we of course take this a step further and mark down inventories and long term assets based on industry). The thinking goes that any time a company is trading at or below it's NAVPS (Net Asset Value Per Share), then the company is certainly worth looking into. Feel free to try it out below

Assets
Cash and Equivalents	$
Short Term Investments	$
Net Receivables	$
Inventory	$
Other Current Assets	$
Total Current Assets	$
Long Term Investments	$
Fixed Assets	$
Goodwill	$
Other Assets	$
Total Assets	$

Net Asset Value Per Share	Ratio