Ziggma Stock Scores.

We apply big data analytics to fundamental analysis to rank stocks against their industry peers on a scale of 0-100.

This lets Ziggma users identify “best-of-breed” stocks in a matter of seconds, eliminating hours of research and screening.

Benefits of the Ziggma Stock Scores

Move the odds in your favour

Picking the highest ranked stocks in each industry has proven to generate substantial outperformance.

Save time

Our Ziggma Stock Scores will help you pick the winners in each industry quickly while staying away from the losers.

Take bias out of the picture

Our quantitative approach to fundamental analysis removes human bias in stock research.

Monitor your holdings

You can track the quality of your portfolio holdings over time by keeping an eye on your holdings’ Ziggma Score.

Developed by finance professionals

Our team has decades of experience working for leading global asset managers.

Proven track record

Average annualised return of 18% vs. 10.3% for the S&P 500 (2011 – Nov 2020).

The Stock Scorecard

We rank stocks against industry peers to show you who comes out on top.

Ziggma’s overarching goal is to empower you to build and maintain a diversified portfolio of high-quality holdings.

The Ziggma Stock Scorecard is instrumental to helping you achieve this. It shows you how the stock you are looking at ranks versus its industry peers, including through sub-scores for valuation, growth, profitability and financial situation.

Even more importantly, the scorecard shows you the top stocks in the industry – we call them “best-of-breed” stocks.

Finding underlying momentum

Ziggma users can draw a number of great insights from the evolution of stock sub-scores over time.

Finding trends in the evolution of sub-scores is particularly powerful. It can serve as an early indicator, for example indicating relative growth momentum or a deterioration in financial strength.

Our Approach

We apply big data analytics to fundamental analysis.

In light of the rapid progress in data processing technology we came to realize that machines were much better at doing the quantitative part of our jobs as financial analysts.

So we decided to leverage technology for fundamental analysis – as many hedge funds already do – and level the playing field for individual investors.

Our methodology captures dozens of KPIs over a multi-year observation span across the categories growth, profitability, valuation and financial position.

There are additional layers in our analysis, which as part our proprietary methodology, we prefer not to disclose on our website. We will, however, respond to individual enquiries from interested parties.

Performance

Strong outperformance.

The chart on the right-hand side illustrates the performance of a hypothetical portfolio comprising the top-rated 10% of stocks in each industry over the time period 2011 through November 2020.

It demonstrates that stocks with Ziggma Scores in the top 10% of an industry would have generated a substantial outperformance over this time period.

By deduction, top ranking stocks by Ziggma Score may produce higher long-term returns as a whole than stocks outside the top 10%.

Questions and answers.

Why is backtesting important and how we implement it?

Backtesting is the method for testing how well a strategy or a model would have done using historical data. To implement backtest, we create a hypothetical portfolio of the top 10% scored stocks in each industry using historical scores and stock returns from 01-01-2011 to 11-06-2020. The hypothetical portfolio is re-balanced once a month. In order to capture the income return, the returns are exclusive of paid dividends and are solely based on daily adjusted closing prices. The backtest results show that the strategy of Ziggma portfolio outperforms the relevant benchmark over the examined period.

Which companies do we cover?

We cover stocks trading in the US. In order to get the most robust data set, we apply a marketcap filter so that we select onlw companies whose market capitalization was greater or equal to $100 million at least once during the last 3 months. The reason for this is that below this threshold there are too many “special” cases, such as zombie companies, startups, special acquisition vehicles, etc. with aberrant ratios, income statements or balance sheets.

Why do some industries have more than one stock with the same score?

In mathematics, the pigeonhole principle refers to the situation when n pigeons are put into m containers, with n>m, then at least one container must contain more than one pigeon. Similarly, some industries incorporate more than 100 peers, so unavoidably some stocks in particular industries will have the same score/ranking (0 – 100). Although the raw score is usually a unique decimal number for each stock, using the empirical cumulative distribution we end up having two or three companies having the same score within large industries.

Why do some companies have two scores?

When more than one class of stock is offered by a company, they are usually designated as Class A shares and Class B shares. We have decided to score them both. Normally, the two have similar scores.