2021 was an exceptional year for fintech. In the year, we witnessed once-nascent businesses scaled up to become the potential next giants in the economy. For example, Coinbase and Robinhood were listed respectively in May and July. Coinbase was listed with a market capitalisation of $86 billion and Robinhood was listed at $32 billion, surpassing the market capitalisation of some decades-old reputable companies such as Nasdaq ($26B). These companies have taken about a decade to dethrone and challenge the market share of big financial services companies.
In this ECA, we seek to explore and understand the chain of events culminating to these major developments and how these developments will further accelerate the adoption of technology to deliver affordable financial services to the masses.
Select and examine four (4) factors that contribute to the meteoric rise of fintech companies.
Make good use of examples, statistics, and events to augment and conclude your discussion.
In 2018, the CEO of DBS Piyush Gupta has said that At DBS, we act less like a bank and more like a tech companyand this sufficiently reflects how banks have changed the way they view and use technology.
Appraise and explain banks have changed the way they deploy technology in their banking business.
Make good uses of examples, statistics and events to augment and conclude your discussion.
Assess and discuss how the role of financial regulators has evolved, as we now have both incumbent banks and fintech businesses providing the same financial services to the masses.
Make good use of examples, statistics and events to augment and develop your discussion.
In your GBA, we have examined how to design a 3-stocks portfolio to meet the target return of a client. In this question, we will continue to automate and simplify the inputs to the robo-advisor so that it can be used by the client directly, without a human advisor.
Figure 1: Python’s inputs
Given the financial aspirations of the client, your robo-advisor must be able to advise the client on
the required monthly return and
the portfolio that is to be created in order to achieve her financial goal
Make use of Python to report the monthly return that is required to fulfill the target_wealth of the client in invt_period years. The client will deposit monthly_invt every month with the robo-advisor to acquire the recommended portfolio.
Based on the required return, the robo-advisor will design and recommend a portfolio of 3 stocks. Report the names and allocation of stocks to an accuracy of two (2) decimal points (e.g. an allocation of [0.25, 0.49, 0.26]).
Appendix A documents the operations and settings of the robo-advisor and Appendix B documents the data structure in the data_file.
Once the portfolio has been constructed, the client can make use of the roboadvisor to query the portfolio value on the query_date. In the event of underperformance by the portfolio from pc_date up to query_date, the robo-advisor is to propose a new monthly investment amount to make up for the shortfall in portfolio performance so that the target_wealth can be achieved in the remaining investment period.
To calculate the new monthly investment amount needed to achieve the target_wealth in the remaining investment period, you can assume that the future portfolio performance will be the observed performance from pc_date to query_date.
Make use of Python to automate the calculations of the portfolio value and the revised monthly investment amount on query_date.
You can assume that query_date will always be the last calendar date of a year and fractional holdings of stocks in the portfolio is allowed.
You are reminded to practice good programming habits in your code development and your code must be driven entirely off the inputs given in Figure 1.
A stock universe refers to all the stocks that fulfill the selection criteria of the roboadvisors. Typical selection criteria include good liquidity so that it is easy to buy/sell the stocks with minimum transaction costs.
In this robo-advisor, analysts select stocks that have been trading continuously for a period of data_tenure years.
With the stock universe defined, the return of a stock x in the month k, rx,k is calculated as follows: (A.1)
where Sx,k and Sx,k-1 are the month-end prices of stock x at k and k – 1 month respectively.
These monthly returns are used to evaluate the mean return, rx and volatility, sx of stock x. The Sharpe ratio SR of stock x is calculated using
Once the stocks in the universe are characterised by their Sharpe ratio, the 3 stocks with the highest Sharpe ratio are used to construct a portfolio.
The robo-advisor will carry out all portfolio construction and transactions on the last trading day of every month.
The robo-advisor will update the stock universe on the last trading date of every month. Hence, even if the portfolio construction date, pc_date, as given in Figure 1 is 15-Jun2017, the portfolio will be constructed effectively on the last trading date of Jun-2017.
The 3 stocks will be selected from all the stocks that have been trading continuously from the first trading date of Jul-2014 to the last trading date of Jun-2017.
Many portfolios can be constructed from the selected stocks and a portfolio is optimised if
it fulfilled the target return of the client and
it has the highest Sharpe ratio, SRp which is defined as (A.3)
where rp and sp are the portfolio’s return and volatility respectively. The portfolio’s return and volatility are calculated as (A.4) and (A.5)
where w = [wA, wB, wC] is the allocation of stocks in the portfolio and ρij is the correlation of monthly returns between the stock pair i and j. To ensure sufficient diversification, the allocation of a stock in the portfolio must be above min_weight.
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