COVID-19 Power BI Dashboard

Dashboards illustrating the spread of the COVID-19 virus are springing up around the internet, almost as fast as the virus itself. Hence I thought it’d be an appropriate time to exercise my dashboarding skills and create one too.

This dashboard was created purely using Power BI, with no data wrangling using Python. Credit must go to the excellent web-scrapped data feeds from John Hopkins University (JHU). See their repository here at (…

SSB – Oct 2019

Source: https://amosang.com/singapore-savings-bonds-ssb-visualizer/

This month’s tranche gives you 1.64% p.a. for the first 3 years, only 1 basis point lower than last month’s tranche. But take a look at the 10-year return rate of 1.75% p.a and you’ll be shocked. The last time the 10-year rate was at this level was in Sep 2016, which is also the all-time low! Looks like we’re heading into the bad old days of low interest rates of 2016 once more. No wonder people barely …

SSB – Aug 2019

Source: https://amosang.com/singapore-savings-bonds-ssb-visualizer/

This month’s SSB rates are indicated by the brown line, which comes in at 1.68% p.a. for the first 3 years. It’s a rather startling drop of 20 bps from last month! For comparison, see the blue line, which shows the interest rates from the Jan 2019 tranche. Looks like rates have fallen a fair bit. And if you hold this month’s tranche for 10 years, you would only make 2.08% p.a. Notice the sharp turn in the …

Cleaning dirty data – Matching similar text strings

I once had the dubious pleasure of attempting to combine datasets where the only field in common is a free-text field containing slightly different representations of the same entity (eg: Company Name). The existing solution in place was to eyeball the records, and to manually create a mapping table to link the 2 datasets. The mapping table records are created only if the system fails (ie: reactive in nature). Here are some of my findings on how to auto-magically generate …

The Calendarific API for global holiday calendars

The Calendarific API provides an intuitive, limited-use API feed, providing access to global holiday calendars, for current, past, and future years. The data may be useful for certain scenarios:

  1. For HR or factory calendars, so that the system knows which are non-working days.
  2. For vacation planning. Since you can calculate the day-of-week from the holiday date, you can spot the possibilities to create long weekends by strategically planning your leave.
  3. Those from the travel, leisure, or tourism industries might be

Trade event data from Enterprise Singapore

Knowledge of trade event data in a specific market can be very helpful.

Use cases include: 1) Demand and capacity planning. Certain industries (eg: travel, hospitality, F&B) would benefit from knowing when demand for their services would peak, and alter their capacity and pricing accordingly. 2) Comparison against same event in the past. It is troublesome to search the internet for the exact dates of an biennial-recurring event (eg: Singapore Air Show) each time we need it.

Looking up the …

SGX high dividend stocks (non-REITs)

Pursuant to the earlier post about high yielding dividend REITs (https://amosang.com/2019/06/04/sgx-high-dividend-stocks-reits-and-business-trusts), some people have requested for the dividend yields for non-REITs instead. Diversifying to other asset classes is a good idea, so with another snap of my magic programming fingers (a la Thanos), here is a list of non-REIT stocks which have a dividend yield of 5% or greater.

The dividend yield is calculated by taking the dividends given for each stock in 2018 (by exDate), divided …

SGX high dividend stocks (REITs and Business Trusts)

The SGX stock market has been falling since the start of May 2019, fueled by fears generated from the US-China trade war. Has value emerged from the falling stock prices? Here, we present a list of REIT and Business Trusts which have a dividend yield of 5% or greater, sorted in order from low to high.

The dividend yield is calculated by taking the dividends given for each stock in 2018 (by exDate), divided by the stock’s closing price …