Wednesday, December 30, 2020

Thoughts on ICAEW Data Analytics Certificate Programme

 

Signed up and completed the ICAEW Data Analytics Certificate Programme. Side note: there is an interesting list of ICAEW's view on when Python is a more efficient and effective choice compare to Excel, see here.

As an ICAEW member, this costs GBP 594. With 20% VAT, this came up to ~SGD 1,300. I completed the course in about two weeks at a casual pace (caveat: I have prior basic Python knowledge).

Programme benefits according to ICAEW:



What I liked:

  • Practical examples with a focus on Finance (as expected given the collaboration with ICAEW). For instance journals testing, and profits/sales forecasting.
  • 1 year subscription to Datacamp. I will leverage this to build my Tableau, PowerBI and Oracle know-how

What could be improved:

  • I personally found that the sequence of videos on Python was a little unstructured. For those completely new to Python, the learning curve could be steep.

Would I recommend it? 

If you believe that the ICAEW brand name is important, and you are looking for practical examples that specifically relate to Accounting/Finance, then this should be on your shortlist. Otherwise, there are more cost-efficient alternatives to get a grasp of the concepts in Data Analytics (e.g. Coursera, or other online/offline resources).

If you need more information / advice on the course, leave a comment below and I will try and help where I can.



ICAEW




Monday, November 30, 2020

Commercial Property Price Dynamics

This is the second part to the earlier post.

In summary, the framework returns the following predictions regarding the sensitivity of house prices to different drivers: 
  • prices should be higher when households’ disposable income and population growth are higher;
  • lower when interest rates are higher; and 
  • higher when credit conditions loosen and the footprint of international investors is higher.



At the heart of the model is the observation that market forces should adjust to make households indifferent between buying and renting. There is a ”user cost relationship” linking house prices, rents and interest rates. According to this relationship, market forces should equate the cost of renting – the rent/price ratio – to the cost of home ownership – the interest income forgone upon purchasing a
property net of expected house price appreciation

A second relationship represents demand for housing, and states that rents are higher when the stock of housing is lower, but also that rents increase when households have more income to spend on accommodation services and when population increases. 

The model is completed by a third relationship capturing housing supply, which assumes that new housing is built when house prices increase relative to the marginal cost of building new dwellings. The framework implies that house prices increase when interest rates fall; when disposable income and/or the size of population increase; and when building costs rise.

Since housing purchases are typically financed through mortgage loans, and many potential homeowners are constrained in the amount of credit they can obtain, credit supply ought to impact house prices. Pressures on the housing market may also arise from abroad – for example, because foreign investors with abundant liquidity and a high willingness to pay acquire property in local residential markets

An increase in credit availability and a loosening of borrowing constraints, for example, is likely to reduce the interest rates faced by households and push prices up.

The sensitivity of house prices to drivers varies across jurisdictions depending on the structural characteristics of each economy. For example, the interest rate sensitivity of prices ought to be greater in countries where mortgages are predominantly adjustable rate rather than fixed rate. More broadly, changes in housing demand drivers should have a larger impact on house prices in countries where the price elasticity of supply is low. Price sensitivities to demand drivers could also be expected to be greater in jurisdictions with tax incentives for home ownership such as tax deductibility of mortgage interest payments.

How about Commercial Real Estate?

The framework for thinking about commercial real estate markets – the user cost model – is the same as that for residential, with the exception that the drivers are somewhat different because most commercial real estate is purchased for the purpose of generating rental income instead of for the consumption of housing services. 

The framework links commercial property prices, the supply of commercial space and commercial rents (endogenous variables) to each other, as well as to returns on alternative investments (including interest rates), GDP growth (demand drivers) and building costs (supply drivers). Concretely, in the commercial real estate case, market forces should make investors indifferent between purchasing commercial properties and acquiring other assets. In other words, commercial real estate prices should equate the returns on holding commercial property – capitalisation rates – to the risk-adjusted returns on alternative investments (eg bonds and stocks), which tend to increase with interest rates. In addition to this user cost relationship, the framework includes a “commercial space demand” relationship linking rental income to the stock of available commercial space and economic growth: as the economy expands, businesses increase demand for space and rental income increases. The model is completed by a supply relationship postulating that new commercial space is built when prices increase relative to the marginal cost of building. It implies that commercial real estate prices increase when
  • interest rates fall; 
  • when increases in economic activity push up rental income; and 
  • when building costs rise.

The framework can be adapted to characterise the sensitivity of commercial property prices to changes in global factors. Suppose that capital inflows into commercial property markets were large enough to make the “marginal” buyer of property a foreign rather than a domestic investor. Assume also that the returns on alternative investments were relatively lower for foreign investors. Then the relevant “user cost” underpinning price adjustments would fall, and commercial property prices would have to rise for foreign investors to still be indifferent between domestic commercial real estate property and other assets.

To sum up, the framework returns the following predictions about the sensitivity of commercial real estate prices to different drivers: prices should be higher when GDP growth is higher; lower when interest rates and returns on alternative investments are higher; and higher when the footprint of international investors is larger.

The sensitivity of commercial real estate prices to drivers is thought to vary across jurisdictions depending on the structural characteristics of each economy. In particular, changes in demand drivers should have a larger impact on commercial real estate prices in countries where strict zoning regulations dampen the elasticity of supply.

For more details please refer to the paper here. What are your views on the drivers, and how will your view influence your property investment decisions?

Tuesday, October 27, 2020

Upgrading Fiscal Checklist (Sep 2020)

Came across this "habitat+" pullout from the Straits Times (source). It lists the fiscal considerations for upgrading from a HDB flat to a condominium apartment.

The source states that the information is correct at the time of print (Sept 2020). 

Based on this source, it looks like the key parameters are:

  • Remaining lease on property
  • Borrower's age
  • Whether loan on existing property is paid off
  • Whether the existing property has been sold

Other than serving as a mental model to guide your upgrading decision, what I found interesting was the visual design of this flowchart. Did you find it easy to navigate? Have colours and font sizes been used in a meaningful manner? Let me know your thoughts in the comments below!

UOB upgrading HDB Condo



Sunday, September 27, 2020

Sennheiser IE 80 S Review: A Sound Investment or an Outdated Classic?

Take a moment and open your desk drawer. Alongside spare pens and forgotten chargers, you’ll likely find a graveyard of cheap, broken earbuds. This is the value trap: a recurring, frustrating expense on products that deliver mediocre sound and are seemingly designed to fail. It’s a cycle of spending that offers diminishing returns.

We advocate for a different path. The "buy it for life" philosophy isn't just for watches or leather goods; it's a savvy financial move that can be applied to your daily technology. It's about making a single, intelligent investment in a high-quality asset that delivers superior experiences and lasting value.

Enter the Sennheiser IE 80 S, a legendary benchmark in this category. Acknowledged for its precision German engineering and famously customisable sound, it has long been a go-to for those seeking premium audio without entering the world of exorbitant pricing.

But time waits for no gadget. So, we'll dissect the Sennheiser IE 80 S from a pure value perspective. In a market flooded with new, battery-dependent technology in late 2025, does this wired classic still represent a wise placement for your capital, or has its time passed?


Sunday, August 23, 2020

Coursera: Automating Real-World Tasks with Python

Recently completed the Capstone of the Google IT Automation with Python Coursera Specialisation. Being a beginner user of Python, the week 4 assessment took me almost the full allocated 120mins.

Hope to provide some guidance by sharing the final scripts I used, for reference purposes. Remember to replace the user name with your qwiklabs user name. 

The real learning comes from trying and troubleshooting your scripts! (tracebacks, tracebacks, tracebacks.....)

Coursera


Assessment Overview 

You work for an online fruits store, and you need to develop a system that will update the catalog information with data provided by your suppliers. The suppliers send the data as large images with an associated description of the products in two files (.TIF for the image and .txt for the description). The images need to be converted to smaller jpeg images and the text needs to be turned into an HTML file that shows the image and the product description. The contents of the HTML file need to be uploaded to a web service that is already running using Django. You also need to gather the name and weight of all fruits from the .txt files and use a Python request to upload it to your Django server.

You will create a Python script that will process the images and descriptions and then update your company's online website to add the new products.

Once the task is complete, the supplier should be notified with an email that indicates the total weight of fruit (in lbs) that were uploaded. The email should have a PDF attached with the name of the fruit and its total weight (in lbs).

Finally, in parallel to the automation running, we want to check the health of the system and send an email if something goes wrong.

What you’ll do

  • Write a script that summarizes and processes sales data into different categories
  • Generate a PDF using Python
  • Automatically send a PDF by email
  • Write a script to check the health status of the system

My Submitted Script


Script 1 changeImage.py

#!/usr/bin/env python3

import os, sys
from PIL import Image

user = os.getenv('USER')
image_directory = '/home/{}/supplier-data/images/'.format(user)
for image_name in os.listdir(image_directory):
  if not image_name.startswith('.') and 'tiff' in image_name:
    image_path = image_directory + image_name
    path = os.path.splitext(image_path)[0]
    im = Image.open(image_path)
    new_path = '{}.jpeg'.format(path)
    im.convert('RGB').resize((600,400)).save(new_path, "JPEG")

Script 2 supplier_image_upload.py

#!/usr/bin/env python3
import requests, os
url = "http://localhost/upload/"
USER = os.getenv('USER')
image_directory = '/home/{}/supplier-data/images/'.format(USER)
files = os.listdir(image_directory)
for image_name in files:
  if not image_name.startswith('.') and 'jpeg' in image_name:
    image_path = image_directory + image_name
    with open(image_path, 'rb') as opened:
      r = requests.post(url, files={'file': opened})

Script 3 run.py

#! /usr/bin/env python3
import os
import requests
import json

def catalog_data(url,description_dir):
  fruit={}
  for item in os.listdir(description_dir):
    fruit.clear()
    filename=os.path.join(description_dir,item)
    with open(filename) as f:
      line=f.readlines()
      description=""
      for i in range(2,len(line)):
        description=description+line[i].strip('\n').replace(u'\xa0',u'')
        fruit["description"]=description
        fruit["weight"]=int(line[1].strip('\n').strip('lbs'))
        fruit["name"]=line[0].strip('\n')
        fruit["image_name"]=(item.strip('.txt'))+'.jpeg'
        print(fruit)
        if url!="":
          response=requests.post(url, json=fruit)
          print(response.request.url)
          print(response.status_code)
  return 0

if __name__=='__main__':
  url='http://localhost/fruits/'
  user=os.getenv('USER')
  description_directory='/home/{}/supplier-data/descriptions/'.format(user)
  catalog_data(url,description_directory)

Script 4 reports.py

#!/usr/bin/env python3

from reportlab.platypus import Paragraph, Spacer, Image, SimpleDocTemplate
from reportlab.lib.styles import getSampleStyleSheet

def generate_report(file, title, add_info):
  styles = getSampleStyleSheet()
  report = SimpleDocTemplate(file)
  report_title = Paragraph(title, styles['h1'])
  report_info = Paragraph(add_info, styles['BodyText'])
  empty_line =  Spacer(1,20)

  report.build([report_title, empty_line, report_info, empty_line])


Script 5 report_email.py

#!/usr/bin/env python3

import datetime
import os

from run import catalog_data
from reports import generate_report
from emails import generate_email, send_email

def pdf_body(input_for,desc_dir):
  res = []
  wt = []
  for item in os.listdir(desc_dir):
    filename=os.path.join(desc_dir,item)
    with open(filename) as f:
      line=f.readlines()
      weight=line[1].strip('\n')
      name=line[0].strip('\n')
      print(name,weight)
      res.append('name: ' +name)
      wt.append('weight: ' +weight)
      print(res)
      print(wt)
  new_obj = ""
  for i in range(len(res)):
    if res[i] and input_for == 'pdf':
      new_obj += res[i] + '<br />' + wt[i] + '<br />' + '<br />'
  return new_obj

if __name__ == "__main__":
  user = os.getenv('USER')
  description_directory = '/home/{}/supplier-data/descriptions/'.format(user)
  current_date = datetime.date.today().strftime("%B %d, %Y")
  title = 'Processed Update on ' + str(current_date)
  generate_report('/tmp/processed.pdf', title, pdf_body('pdf',description_directory))
  email_subject = 'Upload Completed - Online Fruit Store'
  email_body = 'All fruits are uploaded to our website successfully. A detailed list is attached to this email'
  msg = generate_email("automation@example.com", "yourstudentusername@example.com".format(user), email_subject, email_body, "/tmp/processed.pdf")
  send_email(msg)


Script 6 emails.py

#!/usr/bin/env python 3

import email
import mimetypes
import smtplib
import os

def generate_email(sender, recipient, subject, body, attachment_path):
  message = email.message.EmailMessage()
  message["From"] = sender
  message["To"] = recipient
  message["Subject"] = subject
  message.set_content(body)

  if not attachment_path == "":
    attachment_filename = os.path.basename(attachment_path)
    mime_type, _ = mimetypes.guess_type(attachment_path)
    mime_type, mime_subtype = mime_type.split('/', 1)

    with open(attachment_path, 'rb') as ap:
      message.add_attachment(ap.read(), maintype=mime_type, subtype=mime_subtype, filename=attachment_filename)

  return message

def send_email(message):
  mail_server = smtplib.SMTP('localhost')
  mail_server.send_message(message)
  mail_server.quit()


Script 7 health_check.py

#!/usr/bin/env python3

import socket
import shutil
import psutil
import emails

def check_localhost():
  localhost = socket.gethostbyname('localhost')
  return localhost== "127.0.0.1"

def check_disk_usage(disk):
  du = shutil.disk_usage(disk)
  free = du.free / du.total * 100
  return free > 20

def check_memory_usage():
  mu = psutil.virtual_memory().available
  total = mu / (1024.0 ** 2)
  return total > 500

def check_cpu_usage():
  usage = psutil.cpu_percent(1)
  return usage < 80

def send_email(subject):
  email = emails.generate_email("automation@example.com", "yourstudentusername@example.com", subject, "Please check your system and resolve the issue as soon as practicable", "")
  emails.send_email(email)

if not check_cpu_usage() :
  subject="Error - CPU usage is over 80%"
  print(subject)
  send_email(subject)

if not check_memory_usage():
  subject = "Error - Available memory is less than 500MB"
  print(subject)

if not check_disk_usage('/') :
  subject = "Error - Available disk space is less than 20%"
  print(subject)
  send_email(subject)

if not check_localhost():
  subject = "Error - localhost cannot be resolved to 127.0.0.1"
  print(subject)
  send_email(subject)


Hope this was useful for your self-improvement quest!

Thursday, July 9, 2020

Commentary: BT Article Is there opportunity in a crisis in the residential market? 9 July 2020




Sharing my views on this interesting article here
Credits to the original author.

Decision making considerations

The author lists several factors which I generally concur with. Most are mentioned in my post regarding resale checklist here

  • Understand the reason for the purchase: As with most things in life, begin with the end in mind. Is it for owner occupation or investment? This will affect how the buyer/investor weighs the various considerations. e.g. proximity to schools and parents' homes vs tenants' perspective

  • Understand your risk profile: As with most of investing, returns are typically associated with risk. The author cited relevant risks such as incurring Additional Buyer's Stamp Duty (ABSD) due to inability to sell the existing property on time, the inability to find tenants, fall in rents, or increase in borrowing costs. 

  • There is no "perfect" property: linked to point 1, it would be easier to weigh the priorities and make compromises once we are clear on the objective of the transaction. 

  • Giving up the good in exchange for the better. e.g. I own Asset A yielding 1%. I can sell Asset A and use the sales proceeds to buy Asset B yielding in excess of 1%. While I have no fundamental disagreement on the logic, this depends on the transaction size relative to the investor's net assets. This is because for properties, the investment yield is typically no guarantee, hence there is no certainty that the exchange will be "for the better"

  • Location. Reproducing the author's views as I have nothing to add (other than the emphasis in bold) "The tenet for buying property has not changed - location - but with a new perspective. Where location was previously confined to the prime districts, the concept of location has evolved. Although a prime location remains desirable, lifestyle amenities - for example, proximity to the riverside or F&B amenities have also come to the fore as convenience becomes the new currency. Following the pandemic, the pace of decentralisation of business activities, supported by a wider variety of amenities, will gain momentum as more companies adopt a hub-and-spoke model with headquarters in the CBD and branch offices in decentralised locations."

  • Accessibility & connectivity. Reproducing the author's views as I have nothing to add, this is linked to the previous point. "Jobs will also be closer to homes as business activities continue to decentralise. This will make living away from the city centre increasingly attractive. As MRT stations become more prevalent, properties near interchange stations will command a premium as accessibility and connectivity in terms of time (instead of physical distance) become the criteria for decision-making."

  • Growth areas. Reproducing the author's views since these are typically cited growth areas, although I would caution that the certainty of each project differs e.g. Jurong might depend on the High Speed Rail Project. "As Singapore continues to decentralise, there will be new employment areas - for example, Jurong Lake District, Jurong Innovation District, Woodlands Regional Centre and Punggol Digital District, with ready accessibility to/from other activity nodes and residential areas, facilitated by the Jurong Regional Line, Thomson-East Coast Line and North East Line extension. Neighbourhoods near learning institutes such as universities often command a premium as they anchor a cluster of knowledge-driven businesses that will in turn catalyse other activities. The presence of an institute of higher learning will also have a positive impact on the profile of the residents and amenities."

  • Park connectors, parks and nature reserves. The author argues that Covid-19 has raised the awareness of health and wellness to a new level. As such, the demand for properties located near park connectors, parks and nature reserves will increase. While I do not disagree, I believe this should be evaluated in the context of point 1 above i.e. what is the reason for buying

  • Health & wellness. This is a point which I have not previously considered. Reproducing the author's view here and I will take a closer look at this factor in a future blog post. "This pandemic has made us rethink real estate including how space is to be used. Our homes have become our workplace, classroom, entertainment venue, exercise studio and playground. Going forward, we could find more households spending time at home.The global trend towards a gig economy as well as more seniors working part-time is leading to a paradigm shift in the design of homes. For example, attention is now turned towards providing more light, cross ventilation, improving fresh air intake, views and creating dedicated or flexible space incorporating touchless design and technology to promote the well-being of those using the home for different activities. Indeed, the healthy building movement is gaining pace, as its role in public health becomes more apparent with practical designs that help communities lead healthy and active lifestyles both within and outside of our homes."

  • New versus old properties. The author asserts that while older developments tend to have larger floor areas, their designs are somewhat obsolete. In contrast space may be compact in new developments, the focus is on delivering Space as a Service and not the traditional brick-and-mortar concept of physical space. As a result, many buyers have gravitated to new sales as they are perceived to deliver value, featuring contemporary living designs supported by technology that appeal to their lifestyle needs. While I do not disagree, I believe this should be evaluated in the context of point 1 above i.e. does the buyer/tenant value Space as a Service vs having space in one's property, especially when we are compelled to work from home

Are the factors driving resilience valid?

The author cites several factors explaining the resilience of the residential market despite the COVID dampener on the real economy.
  • Memories of past cycles:  residential prices under the Sars public health crisis, and the 2008 global financial crisis rebounded after each event. However, past performance is certainly not indicative of future performance, particularly when we examine the longer-term potential of Singapore as a country from a socio-political perspective.  For instance, is it certain that Singapore will be an attractive regional hub and gateway for businesses to be in? While the scarcity of land could be relevant in weighing the equation, it would be prudent to consider the sustainability of expected future cash flows i.e. the rental inflows may not continue at current levels. My post here on the drivers of residential property prices is of relevance

  • High liquidity with limited investment options: while this is a valid point, there is no shortage of investment options in today's open economy. Overseas securities can easily be purchased via the online brokers, and alternative investments such as bitcoin and P2P lending (e.g. Funding Societies ) implies that residential properties will need to compete with other investment classes and demonstrate a better return/risk ratio.

  • Low cost of borrowing: another valid point but the leverage obtained can be deployed into alternative investment options. Perhaps properties serve as better collateral compared to alternative asset classes, allowing greater leverage. 

  • Stable asset class. past performance is not indicative of future performance

  • Emotional attachment: while emotions could interfere with rational decision making, anecdotally most of the property owners did not live in the properties they own (e.g. due to inheritance) and hence the emotional attachment may be weak or non-existent 

  • Serious investors with longer term perspective: I am not aware of any data to support the validity of this argument

  • Established developers: I am not certain whether the strength of the developers result in a resilient residential market, or whether the resilient market improves the balance sheets of developers. 
Overall, I am not convinced that the above factors would support the resilience of the residential property market, however that is based on my personal risk profile and outlook on the future.

Useful Takeaways

I found the final section to be filled with practical insights which I will share here 
  • For buyers: low interest rate environment might not last forever since mortgage rates do fluctuate. For investors, there are recurring expenses such as maintenance fees and property tax in addition to loan repayment, regardless of whether the property is tenanted or not.

  • For sellers: establish realistic price expectations if they wish to transact.
    • Engaging a knowledgeable broker who appreciates the strengths and potential of the property makes a huge difference. There is an even greater need to market the property to its fullest potential since buyers have many options.
    • As prices for older properties are unlikely to increase in the near term, it may be worthwhile to moderate price expectations to realise the sale earlier.
    • However, if the property enjoys unique attributes, it may be worthwhile to hold onto the property until the desired price is achieved.
  • For landlords/tenants: Landlords should be realistic in their expectations bearing in mind the realities facing prospective tenants in the job market. Some tenants may move to smaller or less prime located apartments, creating demand for these apartments
As the author wisely concludes, caveat emptor!

What were your thoughts on the original article? Let me know in the comments below!

Sunday, July 5, 2020

Introduction to SREITS

Credits to Sing T.F. "The Rise of Singapore's Real Estate Investment Trust (SREIT) Market"


What are REITS


An REIT is a securitised vehicle that converts typically illiquid real estate assets into liquid tradable securities. This is since REITs are a collective investment scheme, allowing investment in a small denomination of REIT units, without having to fork up large equity upfront. REITs serve as a conduit to funds flow from regions with surplus funds to regions with abundant supply of real estate opportunities.Typical characteristics of a REIT:
  • perceived as a defensive stock distributing >90% of earnings on a regular interval to investors as dividends
  • Tax exemptions to dividend payouts by REITs to individuals and qualified non-individual investors
In summary, REITS are viewed as a hybrid instrument combining features of stocks, bonds and real estate.

Some SREIT history


CapitaLand Limited launched the first REIT IPO in Nov 2011 - SingaMall Property Trust ("SPT") which owned three shopping malls: Junction 8, Tampines Mall, Funan the IT Mall. However the low book order resulted in the IPO being scrapped. One reasons floated for the poor acceptance was a lack of investor education, particularly since it was a relatively new product in Singapore.The SPT was restructured and relaunched as CapitaMall Trust (rebranded as CapitaLand Mall Trust in 2015) , and was oversubscribed by five times.
Source: CMT IPO Prospectus, 2002

Subsequently, Ascendas Land (Singapore) Pte. Ltd launched the second SREIT, Ascendas REIT which owned a portfolio of eight business parks, light industrial and built-to-suit properties.

SREIT Commercial Rationale

1. Developers use the REIT vehicle as an exit strategy to unlock the values of their commercial real estate assets. By converting relatively illiquid real estate assets into liquid REIT securities, developers could operate a more efficient "asset light" model with reduced assets on their balance sheet. You may read more about developers here
2. By retaining controlling stakes in REITs, developers continue to enjoy a steady income stream from real estate, while substantially reducing the liabilities on their balance sheet
3. Generate recurring fees by providing real estate fund management services to REITS. The service providers includes both traditional "brick and mortar" developers and third-party asset managers such as ARA Asset Management Limited.
4. Real estate assets are usually priced at a discount to their Net Asset Values (NAVs) when held in developers' books. A "fairer" price by the market can be achieved by separating the stable property income streams from the volatile development business.

SREIT Growth Strategies

As with most things in life, we examine the incentives for the parties involved. Since asset management fees are pegged to NAVs, SREIT managers would pursue one of two growth strategies to create value for SREIT unit holders. These are funded by 
  • using new debt
  • issuing new equity units via secondary public offers to existing unit holders and new investors

a) Dynamic Growth i.e. acquire yield-accretive assets


Market timing is key to acquiring new properties. This includes whether real estate owners are willing to sell, and also the cost of raising new capital in equity markets.
Source: CMT 2015Q3 financial results


b) Organic Growth i.e. asset enhancement initiatives (AEI)

This is traditionally achieved via sprucing up physical structure and adding new features to existing buildings. Other ways include tearing down and redeveloping an existing structure into a new building. To minimise disruption to income streams, a more popular strategy is to carry out AEIs in phases. One example would be the redevelopment of Funan undertaken by the pioneer SREIT, see more information in the press release here

Source: CMT 2015Q3 financial results

Tax Treatment 

Please see the latest IRAS e-Tax guide here
At the time of writing, the latest was the Seventh Edition published 24 Jun 2020.

REITs are accorded tax transparency status subject to compliance with the investment and distribution conditions. Tax transparency generally means that the specified income will not be taxed in the hands of the trustee of the REIT, but will only be taxed in the hands of the unit holders (i.e. the beneficiary of the distributions received from the trustee), unless the unit holders are specifically exempted from tax.

What Lies Ahead

Gazing into the crystal ball, the SREIT market faces headwinds from other Asian REIT markets including China and India. It would be wise for Singapore to continue setting good corporate governance requirements, and consider new REIT models (e.g. the externally-advised model in the US REIT market) to maintain market leadership.

What do you think are the propects for SREITs in the near/long term? Let me know in the comments below!

Tuesday, June 23, 2020

Tableau Visualisation of HDB prices

Came across this interesting use of data visualisation applied to HDB prices.
Kudos to the team that came up with this great application of Tableau to derive insights from data!

While I am figuring out how to embed the interactive version in this blog (comments welcome if you could guide me on how to do this!), you can navigate to the public dashboard here

This also reminds all of us the importance of continuous re-skilling and up-skilling as described in my earlier post here.

Hope this inspires you to think of how you can leverage data as part of your quest to uncover value!



Credit to the authors of the original Tableau Dashboard

Tuesday, June 16, 2020

What determines Residential Property prices?



"Price is What You Pay; Value is What You Get" - Warren Buffet

Ever wondered about the price discrepancies among properties in different part of Singapore, or even within different parts of the same estate? What explains the huge observed variance in psf from $6xx to $2xxx?

What exactly is fair value?

FRS 13 defines fair value as the price that would be received to sell an asset or paid to transfer a liability in an orderly transaction between market participants at the measurement date. 

What valuation techniques are available?

The market approach uses prices and other relevant information generated by market
transactions involving identical or comparable (ie similar) assets, liabilities or a group of
assets and liabilities, such as a business. For example, some people might refer to recent transacted prices at the HDB resource here to determine what an appropriate price could be.

The cost approach reflects the amount that would be required currently to replace the service
capacity of an asset (often referred to as current replacement cost). In the Singapore context, this could be more relevant to landed property where in addition to the land price, the parties could also consider how much Additions and Alterations costs have been, or would be incurred.

The income approach converts future amounts (eg cash flows or income and expenses) to a single current (ie discounted) amount. When the income approach is used, the fair value measurement reflects current market expectations about those future amounts. This can be easily understood in the scenario of holding an investment property: typical inflows could be receipts of tenants' rental, and outflows would be the mortgage repayments and/or the future sale proceeds.

Application to the Residential property market

At the heart of the model is the observation that market forces should adjust to make households indifferent between buying and renting

There is a ”user cost relationship” linking house prices, rents and interest rates. According to this relationship, market forces should equate the cost of renting – the rent/price ratio – to the cost of home ownership – the interest income forgone upon purchasing a property net of expected house price appreciation

A second relationship represents demand for housing, and states that rents are higher when the stock of housing is lower, but also that rents increase when households have more income to spend on accommodation services and when population increases. 

The third leg of the model is relationship capturing housing supply, which assumes that new
housing is built when house prices increase relative to the marginal cost of building new dwellings. 

The framework implies that house prices increase when interest rates fall; when disposable income and/or the size of population increase; and when building costs rise.

Since housing purchases are typically financed through mortgage loans, and many potential
homeowners are constrained in the amount of credit they can obtain, credit supply ought to impact house prices. An increase in credit availability and a loosening of borrowing constraints, for example, is likely to reduce the interest rates faced by households and push prices up

Pressures on the housing market may also arise from abroad – for example, because foreign investors with abundant liquidity and a high willingness to pay acquire property in local residential markets

While this blog is primarily concerned about Singapore real estate, it is interesting to note that the sensitivity of house prices to drivers varies across jurisdictions depending on the structural characteristics of each economy. For example, the interest rate sensitivity of prices ought to be greater in countries where mortgages are predominantly adjustable rate rather than fixed rate. More broadly, changes in housing demand drivers should have a larger impact on house prices in countries
where the price elasticity of supply is low. Price sensitivities to demand drivers could also be expected to be greater in jurisdictions with tax incentives for home ownership such as tax deductibility of mortgage interest payments.

For more details, including empirical observations (i.e. with real data), please refer to the paper here

What can I do with this model?

In summary, the framework returns the following predictions regarding the sensitivity of house prices to different drivers: prices should be higher when
  • households’ disposable income are higher;
  • population growth are higher; 
  • interest rates are lower; 
  • credit conditions loosen; and 
  • footprint of international investors is higher.
Anecdotally, in the current Jun 2020 environment:
  • Household income should be lower due to lower consumer confidence
  • Population growth should be lower due to possible reduction in foreign workforce
  • Interest rates are lower directly/indirectly due to monetary policy
  • Credit should be simpler to obtain for example the MAS SGD facility for esg loans
  • There could be more international investors particularly from Hong Kong
Depending on your views on each of those drivers, and the relative weightage accorded to each driver, how do you think residential property prices will behave? How can you benefit from the price trends? Let me know in the comments below.

Tuesday, June 9, 2020

Covid-19 aka "Crisis of a Generation": Should I buy or sell now?

How is the Market Situation?

The Straits Times reported on 9 June 2020 that resale transactions for non-landed private homes saw a plunge in sales volumes with 171 transactions in May 2020. This is 80% lower than May 2019 and a 43% decrease compared to the 300 transactions in April 2020.

Prices increased 0.1 per cent compared to April.

The Straits Times reported on 4 June 2020 that Housing Board resale flat volumes dropped in May 2020 to levels not seen in the last thirty years. 364 flats changed hands. This compares to 2019 total resale volume of 23,714 (monthly average 1,976).


Similar to the non-landed private home sector, prices increased 0.1 per cent compared to April.

The reduction in transactions could possibly be due to Circuit Breaker measures preventing physical viewings, or general reduction in consumer confidence resulting in deferral of big-ticket spend.


Recap of 2008 Property Boom

Singapore experienced a property boom in the middle of the recession triggered by the financial crisis. This was widely attributed to a change in investors' perception: an increasing number of people viewed real estate as a safe haven after reports of failures in financial products.

Transact or wait?

Given the possibility for borrowers to defer payments for both home and personal loans, it is unlikely that we will witness a significant fire sale in the near future. Barring exceptional changes in personal circumstances, sellers will likely have the holding power to wait out any temporary price weaknesses.

For buyers, in the short term, the pre-pandemic factors continue to apply: reassess your available budget depending on how your earning power will be affected - affordability is key.

In the long term, I would recommend all participants in the real estate market to scrutinize PM Lee Hsien Loong's 7 June National Broadcast  here. As we face the "crisis of a generation", should real estate continue to be the asset class of choice for wealth preservation/growth? This question would require examination of the drivers of property prices which I will share in a subsequent post here.

Thank you for reading.

Friday, May 15, 2020

Post COVID Virtual Communication Guide



In the current lockdown/quarantine environment, work has taken on a slightly new dimension. Other than the challenges of your physical working environment (is there a proper home office available), family arrangements (young and elderly in your household), one significant challenge is to adapt to the main mode of communication: virtual communication.

While this is not new for most millennials, what is different is that virtual communication used to be one (out of many) means of communication, whereas now almost all communication will be virtual.

How then can we thrive in this environment?

Over-communicate

Go back to basics: Be clear and frequent in your communications.

Allow peers and your superiors an opportunity to understand your thoughts, plans, work, and emotions. Try practising the habits below:
  1. Make your work more visible:  Agree with your team where and how to give updates. Ie. project updates on gsheet, status updates chat (slack/workplace/teams) group, begin each week with a standup meeting. 
  2. Create communication channel norms:   Align with your team/manager on the best ways to stay in touch and when. Try using the channel map below! 
  3.  Use emojis to convey tone:  Tone can be mistaken when communicating virtually. Try using emojis to help you communicate more effectively.
  4.  Ask for clarity & feedback:  Most people will not communicate with perfect accuracy all the time. Do not be afraid to seek clarity if you did not understand something. Equally important, ask for feedback from others.

Create a communications channel map 

This should be co-developed with your team to align communication norms (when, where, what to communicate). An example is as follows:




Where do you start?

Ask at least one person today for feedback on how you can improve your communication!

And as always, leave comments below for more ideas that you would like to share.