Revision of Interest Rates for BOC SmartSaver

From August onwards, BOC SmartSaver will be revising the prevailing interest rate which is tiered based on the amount of account balance.

Across the tranches, the reduction in base interest rate ranges from 0.175 to 0.275 percentage point. Account holders will be earning 0.1% for balance up to $20,000 and 0.15% for balance up to $100,000. 

On top of that, the bonus interest section will undergo major reduction as follows:

There will be a decline of at least 0.5 percentage point for the bonus interest related to salary crediting and credit card spending. The bill payment category is the least impacted with just a decrease of 0.05 percentage point.The Extra Savings bonus interest will apply to account balance above $80,000 instead of $60,000 from August. 

A new category that awards bonus interest for the purchase of eligible BOC wealth product has been added but there seems to be limited information surrounding this category. Given that the BOC website has listed RMB funds, insurance and unit trust as part of the wealth products, I would assume that it is one of these 3 options. 

For an account holder who credits his salary, spends on his BOC credit card and pays 3 bills, he will be earning 0.9% bonus interest, down from the current 1.95%. 

Overall, the revised interest rate chart, inclusive of the prevailing interest rate will be as follows:

The bonus and prevailing interest rate remains largely within the range of 1% to 1.04%. Subsequently, it climbs to 1.12% from $80,000 onwards due to the boost from extra savings category. However, it should be noted that this would require a significant capital of $100,000.

Revision of Interest Rates for UOB One Account

Overview of the Interest Rates for the 3 Local Banks

Comparison with other Active Savings Accounts

Comparison with other Savings Instruments

• Singapore Savings Bonds: Using the data of the Aug 20 issue, the interest rate for first year is a pittance of 0.27%. The minimum investment amount is $500 for each issue. 
• Fixed Deposits: If you do not mind forgoing liquidity, DBS currently provides the highest interest rate of 1.15% on a 12-months fixed deposit with a minimum placement of $1,000. 
• Citi MaxiGain Account: Taking 1-month SIBOR to be at 0.25, the base interest is calculated to be 0.125%. The bonus interest can reach a maximum of 0.6% after 12 months of stepping up. Hence, the total interest rate sums up to be 0.73%. 
• CIMB FastSaver Account: A fuss-free savings account that offers competitive interest rate of 0.825% on the first $100,000 balance which can be an attractive alternative to active savings accounts. 
• RHB High-Yield Savings Account: Another fuss-free savings account that is similar to CIMB FastSaver Account. Account holders can earn 0.08% on the first $10,000 and 1% on the next $90,000. The effective interest rate is calculated to be 0.908%. 
• Singlife Account: Instead of a savings account, the Singlife Account is basically an insurance savings plan that delivers 2.5% p.a. returns on the first $10,000 and 1% on the next $90,000 with no lock-in period. The returns are calculated daily and credited on a monthly basis. It should be noted that the capital in the Singlife Account is protected under the Policy Owners' Protection Scheme (PPF Scheme) by Singapore Deposit Insurance Corporation (SDIC) but the interest rates of 2.5% and 1% are not guaranteed. 
• Stashaway Simple: This cash management portfolio invests equally in the LionGlobal SGD Money Market Fund and LionGlobal SGD Enhanced Liquidity Fund, both are funds that invest in short-term debt instruments. While the net returns is projected to be 1.9% with no minimum balance, investors should be informed that the returns is not guaranteed and may fluctuate in volatile economic conditions. As with other investment products, it is not totally risk free and there is possibility, albeit remote, of losses. Furthermore, the invested capital is not insured by SDIC. 
• ABF Singapore Bond Index Fund: The ETF invests in the constituents of the iBoxx ABF Singapore Bond Index which tracks a basket of high-quality bonds issued primarily by the Singapore government and quasi-Singapore government entities. Based on its declared 2020 dividend of $0.0249 and the recent price of $1.264 (as of 30 July), the dividend yield is approximately 2%. Kindly note that this is excluding any capital gain/loss due to price movement on the bourse.

from pandas_datareader import data as pdr
import pandas as pd
import yfinance as yf

yf.pdr_override()

# Indicate start and end date
start = '1987-01-01'
end   = '2016-01-01'

# Generate STI price data
sti = pdr.get_data_yahoo('^STI', start, end)['Adj Close']

# Extract STI year-end price data
yearly_sti = sti.groupby(pd.Grouper(freq='Y')).tail(1)

# Generate STI annual returns
yearly_rtn = round(yearly_sti.pct_change()*100,2)

# List the election years
election_year = [1988, 1991, 1997, 2001, 2006, 2011, 2015]

# Filter STI returns on election years
election_year_rtn = []
for year in election_year:
    election_year_rtn.append(float(yearly_rtn.values[yearly_rtn.index.year == year]))

# List the election dates
election_dates = pd.to_datetime(['1988-09-03','1991-08-31','1997-01-02',
                                 '2001-11-3','2006-5-6','2011-5-7','2015-9-11'])

# Obtain the dates one month before and after the Polling Day
election_1m_before = []
election_1m_after = []

for date in election_dates:
    election_1m_before.append(date - pd.DateOffset(months=1))
    election_1m_after.append(date + pd.DateOffset(months=1))

# Adjustment if the dates coincide with the weekends    
election_1m_before_adj= []
election_1m_after_adj = []
counter1 = 0
counter2 = 0

for item1 in election_1m_before:
    if not (sti.index == item1).any():
        election_1m_before_adj.append(election_dates[counter1] 
                                      - pd.DateOffset(months=1,days=1))
    else:
        election_1m_before_adj.append(item1)
    counter1+=1
    
for item2 in election_1m_after:
    if not (sti.index == item2).any():
        election_1m_after_adj.append(election_dates[counter2] 
                                     + pd.DateOffset(months=1,days=1))
    else:
        election_1m_after_adj.append(item2)
    counter2+=1

# Compute STI returns one month before and after the Polling Day
diff = sti.loc[election_1m_after_adj].values - sti.loc[election_1m_before_adj].values
returns = diff/sti.loc[election_1m_before_adj].values * 100

from scipy.stats import pearsonr 

returns = list(returns)

# List the vote percentage won by PAP for the past elections
vote = [63.2, 61, 65, 75.3, 66.6, 60.14, 69.86]

# Calculate the correlation coefficient between the vote count and STI returns
corr, _ = pearsonr(vote, returns) 
print('Pearson correlation: %.3f' % corr)

# Drop the element for 2015 General Election
returns.pop()
vote.pop()

# Calculate the correlation coefficient between the vote count and STI returns
corr, _ = pearsonr(vote, returns) 
print('Pearson correlation: %.3f' % corr)