Algorithmic trading vs robo-advisor: the 7 key differences

algo trading vs robo-advisor

Algorithmic trading vs robo-advisor: the 7 key differences

With a rise in popularity in robo-advisors, there has been an increase in marketing literature attempting to explain what robo-advisors do, with some confounding ones, equating robo-advisors with algorithmic trading. 

In this article, we talk about the 7 points of differences between robo-advisory and algorithmic trading.

What is algorithmic trading?

A variation of systematic trading, it is also known as algo trading, automated trading, or black-box trading. Essentially, it refers to a computerised trade process.

In this process, the user feeds specific instructions into the software (pertaining to time, price, quantity, or any other programmable attribute) and allows it to perform transactions on its own.

The transactions depend on the software speed, i.e. the machine is capable of performing vast volumes of rapid transactions as well as vast amounts of calculations to analyze multiple variables to determine optimal take profit and stop loss positions, thereby optimizing for profit generation from such an exercise.

Here, trades are placed automatically at the best prices, and the software is capable of following the strategy fixed by the hedge fund manager.

For systematic traders, it allows them more flexibility by feeding into the system the requisite rules and letting the program run its course.

One use case for algorithmic trading for example, is for enhancing trading conditions; when fund managers want to buy a large amount of shares discreetly without affecting the price.

Algorithmic software can be left to run purely automated or it can be circumvented by fund managers as and when they see fit.

How algo trading works 

Algo trading tends to fall under two categories: proprietary trading or execution. Algo trading for execution is usually done by big banks, investment banks, institutional investors and big brokerage houses. The process for investors is simple.

Investors first discuss their financial goals with their wealth advisors or fund managers in these corporations. Wealth advisors will analyse their client’s goals, investment capital and risk aversion in order to offer them the best advice.

The resulting portfolio allocation is then executed through the algorithmic trading platform. Should there be any event which may affect a client’s investment portfolio, the fund manager will advise the client on the next best course of action to mitigate risks.

The funds which use algorithmic software for execution the most are hedge funds, mutual funds and pension funds.

The asset classes traded via algorithms are just as varied. They can range from the traditional stocks and bonds to FX spots, currencies and ETFs.

Algorithms that proprietary trading desks use are what most investors associate algo trading with – employing algo trading strategies to manage risks and achieve risk-adjusted returns.

A variety of strategies can be employed through algorithms. You can read about them in What is Systematic Trading?

What is a robo-advisor?

It is a digital platform which uses automated solutions and algorithms to manage and allocate investors’ funds. Client data are collected then entered into the robo-advisor system so that the system can recommend a portfolio based on its investment methodology.

The system is programmed based on financial models and follows a set of rules and instructions, much like algorithmic platforms for execution. However, the human advisors play a very minor role. Usually, they only facilitate the client data collection as well as tweak the rules and instructions of the robo-advisor from time to time.

Thus, companies which utilise robo-advisors usually operate with a minimal number of human advisors.

How robo-advisors work in Singapore

Although each platform has its own unique ways of offering a robo-advisor financial service, the process is mostly similar for investors.

  1. Investors answer a short questionnaire posed by the robo-advisor platform about their risk tolerance, financial situation, investment goals and intended investment time horizon.
  2. The robo-advisor platform suggests a possible portfolio allocation based on the parameters collected.
  3. Investors fund their accounts on a lump sum or monthly basis.
  4. The robo-advisor platform purchases assets according to the portfolio allocation chosen by the investor.
  5. The investment team of the robo-advisor platform monitors the market, and performs rebalancing via the robo-advisor platform when necessary to manage risk and maximise potential returns.
  6. Investors can withdraw any part of their portfolio anytime without the assistance of a human financial advisor since they are able to access their accounts at any time from anywhere.

The majority of investments are in mutual funds and ETFs with exposure to a variety of asset classes such as equities, bonds and commodities

Algorithmic trading vs robo-advisor

1. Fees and taxes

Algo hedge funds entail fees charged by the institutions offering the trading service. They include management fees, performance fees and trustee fees.

Management fees and Trustee fees are charged on a percentage of the invested funds on an agreed frequency, typically once a year. Performance fees may be split into tiers, with differing percentages based on annual returns.

The fees of robo-advisor platforms are generally lower than that of an algo hedge fund, given robos mainly charged platform fee for performing the service of assisted portfolio allocation.

Other fees to look out for would be currency conversion fees, asset operating fees, custody fees, platform fees as well as a different fee rate for each portfolio invested. These can vary greatly from one platform to another, and may also be included in the underlying funds’ cost as well, thereby affecting actual performance.

Since many robo-advisors in Singapore buy ETFs listed in the U.S., your dividends are subject to a 30% dividend withholding tax. This will reduce your dividend returns and you will end up earning less compared to buying ETFs listed elsewhere. Note that not all robo-advisors take this tax into account when doing their projections.

2. Minimum investment

The minimum investment required for robo-advisors is generally lower than that of algo funds. As it can be as low as USD1, the platform provides an accessible starting point for new investors before diversifying to other options, with the vast majority of the client base made up of retail investors trying out investing for the first time. 

3. Flexibility

Some robo-advisors give investors more flexibility than algo trading. 

Algo trading operates mostly on an automated system and it is typically a discretionary trading service designed by the algo traders or fund manager to achieve optimal risk-adjusted returns. 

It does not allow investors to include or exclude assets according to their personal preferences. Only the manager in charge of the algorithm can make that decision. 

For instance, some investors may be against supporting non-halal investments. Some may prefer to support ESG (environmental, social and corporate governance) centric investments.

Clients with strong preference in the underlying investment may be more suited for robo-advisory platforms, which may provide the option for investors to choose their investment allocations across the various asset classes.

4. The human touch

A robo-advisor only creates a portfolio based on the information that the investor inputs into the software. The investor has full control of his investment and can change the entire portfolio based on a single event, or because he wants to react to a sudden change in market trends.

As there may not be any human touch after the robo-advisory service has commenced, the investor may make a decision which will impact his overall return negatively. 

Algo funds, on the other hand, have qualified fund managers and relationship managers to advise investors not to act rashly, and not to lose track of their overall investment plan.

5. Personalised portfolio

Though it is true that a robo-advisor can personalise a portfolio based on investor preferences, it is unable to do so on a completely individual level. It is incapable of going to the extent of taking into account a client’s unique life situation as there is no input factor for this aspect.

In contrast, algo funds have fund managers, relationship managers and even partners from other financial firms who can offer qualified advice in terms of adjustments to a portfolio to suit a client’s change in lifestyle of needs.

6. Financial planning

Most robo-advisors do not offer sufficient financial planning services due to economical considerations. For example, estate planning, tax planning, retirement planning, insurance needs and general budgeting. They also cannot give tax or legal advice, or update investors on the latest tax information or estate planning strategies.

7. Diversification

Robo-advisors offer more diversification than algo platforms. Here is why. 

Robo advisors allow investors to own fractional portions of ETFs, which may not be possible without a large capital. Since most robo-advisors tend to invest in a variety of overseas ETFs, this offers diversification in portfolio.

However, individual algo funds offer access to specific asset classes and niche investment strategies. In order to diversify, investors can consider including several different funds in their portfolio.

Conclusion

Robo-advisors and algorithmic trading are vastly different, and have their own strengths and weaknesses. At the end of the day, as an investor, you must choose what suits you. 

If you are just starting out and have a small amount of capital to try out investing, robo-advisors might be for you. If you are a qualified investor with a larger capital base who appreciates the need to diversify into alternative investments, algorithmic trading might be just for you.

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Raphael Ng

<b>Associate Director, FX Algorithmic Trading</b> <br /><br /> Raphael has a diverse range of skill-sets from managing infrastructure systems to auditing investment algorithms. Since 2013, Raphael has been researching and developing scalable FX Algorithmic Trading strategies that matched global FX liquidity pools. <br /><br /> Leveraging on his Technology and Finance background, Raphael seeks to present a robust set of algorithm trading offerings for Salzworth Global Currency Fund and to provide relevant connections to benefit clients and partners of Salzworth. <br /><br /> <a href="https://salzworth.com/our-team#raphael" target="_blank" rel="noopener">More information about Raphael Ng</a>