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Unhedged is building a managed fund product for retail investors. The product solves similar problem that Spaceship, Raiz and Commsec Pocket is trying to solve, which is to automate investing by providing a managed fund solution for retail investors. However, the key differentiation that Unhedged is providing here is that it provides trading algorithms for users to develop their own investment portfolio. The UI / UX of the app is designed to gamify the process of investing, increasing user interaction with the product by giving users more control over how they want to invest through various algorithms.
The serviceable addressable market for the product is about 6.6M investors in Australia and the market is growing by 13% a year.1 The product created may not perform better from an investment return perspective, but it may provide a better user experience for those keen to have greater control on how their portfolio is constructed yet do not want the hassle of researching and picking stocks or other assets. The business model is scalable and profitable. Interest in the product is also high with more than 2000 customers in the waitlist for its beta launch. However, there hasn’t been much evidence of user testing yet with the product and the lack of customer feedback when developing the MVP might pose a risk of building a product that customers might not really want.
The business defensibility is questionable as customer’s switching cost is low and the cost to build a similar / more superior product is relatively low. There is also no obvious network effect as it scales. The one thing that might increase the stickiness of the product is the potential “hook” effect of the product. The gamification of investing in the app might intrigue users and keep them coming back to the platform.
The founding team seems credible and consists of a variety of skillsets. However, one obvious experience/skillset that is missing is the experience of working in quant trading and building algorithm trading systems in large institutional funds. The founder had a successful exit 10 years ago in London, but the rest of the founding team has not work in a startup prior to this.
According to a quant trader from a reputable bank in Australia, the algorithms that Unhedged has published in their offer document seems legit and the performance benchmark is realistic. However, compared to established algorithms in the institutional space, the algorithms currently provided by Unhedged in its beta launch significantly underperform i.e. the algorithms that some of the hedge funds are using can have a Sharpe Ratio 3-4 times better. Unhedged has emphasized their plan to develop more and better algorithms after the raise, so this might be something to keep an eye on.
Unhedged is providing a more customized and automated investing tool to the growing number of self-directed investors. There are other products such as automated managed funds already available in this space, but Unhedged is the first that is trying to package algorithm trading into a retail investing product.
There are existing products such as low fee managed ETFs that provide a similar service but does not offer the same level of customization to investment strategy or use algorithm trading strategies.
Costly Does it require capital to solve?
3
Development of the algorithm and app requires significant capital but its not extremely expensive to develop.
Mandatory Can the problem be enforced?
1
Selection of investment vehicle is always going to be an individual’s choice, hence an investment product probably won’t be able to be enforced.
Frequency of Occurrence Is the problem encountered often?
4
Good Problem Scorecard
2. Characteristics of Ideal Solution
Questions
Score
Comments
Is the solution innovative and 10x better than existing competition?
3
Depending on the algorithm used, the risk-return profile of the algorithm used typically outperform benchmark. However, compared to the algorithms that professional hedge funds with an established algorithm trading system, the algorithms that Unhedged presented seems to significantly underperform1.
Is the solution scalable? Increase in revenue does not require proportional increase in cost.
4
Increase in asset under management (aum) won’t proportionally increase the marginal cost of managing the additional assets. The key variable costs are cloud cost, AML/KYC cost (one time per customer) and forex cost.
Is there a product-market fit? Are customers willing to pay for the product?
4
Currently, customers are charged 0.49% management fees + 20% over-performance fee (against selected benchmark). The company aims to remove the fixed management fees and only charge performance fee when it scales. There are currently a waitlist of users waiting to access the beta app set to be released in August 2021 with 3 algorithms.
Is there a clear value-proposition for the customers? Does the solution improve the unit economics of solving the problem?
3
Is there a clear target customers for the solution both immediate and in the future?
4
Is the business model clear and profitable?
3
The revenue model is very clear. The business model is also very clear as shown by the Business Stack in the offer document. See revenue forecast tab for further analysis on profitability.
Good Solution Scorecard
1 Based on interview with a professional quant trader from the investment unit of an established bank in Australia
3. Traction to Date
Questions
Score
Comments
Does the company have a functional MVP? Are early customers willing to pay for the MVP? Are there any industry recognition or benchmark that shows the MVP is superior?
4
The company will be launching the beta version of the app in Android and IOS with 3 algorithms in August 2021. Beta users have also been selected. There have been many users signing up to the waiting list as well. There are no industry recognition for the product but based on back-testing results, the algorithms seems to outperform the market.
Is the company quick at iterating on their MVP? Does the company have a good feedback channel?
3
The company has not demonstrated clear feedback from the customers. They are currently on alpha testing stage and will progress to beta testing in August 2021. The team plans to set up a feedback channel where they can get customer feedback and continuously improve the product. Would much prefer they started getting customer feedback while developing the MVP.
Is the company securing sales for their products at a good rate? Is the products getting exposure and demand from potential customers? Is the company securing strategic partnerships to gain exposure or expand market share?
3
The company is at pre-sales stage, but has already gather interest through a waitlist of users trying to get their hands on the product. The company has not secure any strategic partnership aside from securing an investment management firm that will be responsible for executing and maintaining trades. Plans to get asset managers and financial advisors onboard as part of the white-labelling solution will be executed further down the road.
Does the company have a solid plan / deliverable to progress to the next stage i.e. commercialise the product, expand to other markets etc.? Is the planned use of fund inline with accomplishing the capital raise deliverable? Does the company know what their biggest challenges are for the next stage and has a plan to address them?
4
Yes. The company has a clear plan on how they will attract and onboard the new users in stages. The LTV and CAC economics considered showed that in worse case scenario, new customers acquired will still be profitable.
Does the customer actually want the product and is willing to stick to this platform? Customers are presented with more choices of how they want to invest their “savings” and with savings rate set to increase, Unhedged might or might not get a share of the market.
Traction Scorecard
4. Business Defensibility
Questions
Score
Comments
Is it easy for competitors to re-create similar / more superior solution? Is the technology developed by the company protected?
2
There is no patent that protects these algorithms. The inner workings of the algorithms are trade secrets. However, a competitor can create a more superior algorithm with more R&D. Performance of algorithms is not static. The algorithms have to be reviewed from time to time to make sure they still work, which is the role of ML.
Is it easy for existing customers to switch to a competitor?
2
Yes. There is limited switching cost for the customer. The only stickiness is to do with the UI/UX and “hook” element of the product which is done by gamifying retail investment (similar to the Robinhood effect), but in a much lower risk environment.
Is there a favorable network effect as the customer base scale?
2
Is there an element of “hook” in the solution?
4
There is potentially a “hook” element in the product as users are given the power to experiment with their portfolio using various algorithms and track “their” performances. The process of investing is gamified to make users feel more involved in the investing process compared to just an automated managed fund.
Defensibility Scorecard
5. Characteristics of Founding Team
Questions
Score
Comments
Does the founding team has a unique experience with the problem? Is the reward structure of the company focused on motivating outcomes?
4
The founder is personally interested in the problem, having worked on the base algorithms for years before deciding to build it into a retail product. The founder does not get paid cash salary, only accrued minimum pay to be paid in a later date. All team members are subscribed to the ESOP with a standard vesting structure of a 12 month cliff and 1/36 vesting schedule.
Does the team have deep experience in the industry / business segment?
3
The founder’s main experience seems to be in marketing but he has a personal interest in trading and has been a full time trader for the past 5 years. The COO has a degree in quant but has worked as a management consultant most of her life. The CTO also has deep management consulting experience with a background in astro-physics. The CRO has deep experience in risk management. There is no academic quant expert in the team yet.
The only concern here is the lack of professional algorithm trading experience in institutional funds among members of the founding team. A member can be recruited or hired in a later date but this skillset / experience is too important to be omitted from the development of the MVP.
Does the team work well together? Has the team previously worked together?
3
A majority of the team will only start working together from June 2021. However, they seemed motivated to work together on this project as most of them has resigned from their existing corporate jobs.
Does the team have the ideal number of founders with varying skillsets? Does the team have a good balance of commercial and tech skillsets depending on the stage the company is at?
4
Does the team has an impressive list of advisers who are leaders in the industry?
3
Carolyn Colley headlines the list of advisors. She serves as board member in multiple ASX listed financial companies. She is also personally invested in Unhedged. Other advisors will contribute in the startup development phase. There is a notable lack of expertise in the quant space.
Does the team have prior startup experience and successful exits?
3
Does the team have a track record of getting things done?
3
Founding Team Scorecard
Peter Thiel 7 Questions for Product Innovation
Questions
Score
Comments
Engineering Are they creating breakthrough tech instead of incremental improvements?
3
They are not creating a breakthrough technology, but they are the first few that are structuring their product for the mass retail market. Other algorithm trading platforms are only targeting sophisticated or institutional investors. The business model itself might be the most interesting part compared to the actual workings of the product itself.
Timing Is now the right time to start the business?
4
The implosion of investing apps have primed the market to be more open to these investing tools. Covid-19 has pushed people to save more, and with more savings, the population will look into how they can make their money work for them in the easiest possible way with the highest possible return/risk ratio.
Monopoly Are they starting with a big share of a small market?
3
People Do they have the right team?
3
See evaluation on the “Characteristics of Founding Team” above.
Distribution Do they have a way to not just create but deliver the product?
4
The team has a relatively solid GTM strategy, as long as their product works!
Durability Will their market be defensible 10 years into the future?
2
The moat of the business is questionable. There are no tough barriers to entry in the business.
Secret Have they identified a unique opportunity that others don’t see?
4
They are betting on user’s interest in directing their own investments in a more automated way i.e. manual being buying individual shares / ETFs manually and tracking data / research personally in making trading decisions (active investing), and fully automated being a managed fund where users just consistently deposit money into without changing position in the short term (passive investing).
Peter Thiel 7 Questions
Berkus Method
Questions
Score
Score Description
Valuable Business Model Base value
4
The business model aligns with the company goals, is self-reinforcing and robust.
Available Prototype Reducing technology risks
3
The product is launched in the market and generates first sales. Customers are interested and first traction is gained.
Abilities of Founding Team Reducing implementation risks
3
The roles in the team are defined and clear. The CEO has previous management experience in a bigger corporate environment.
Strategic Relationships Reducing market risks
2
There are a few verbal strategic relationships with big corporates or institutions announced.
Existing Customers Reducing production risks
2
There are only a few existing customers, infrequent buy rate and low value.
Do you think algorithmic trading works? And what are the key factors in ensuring that the process works?
Yes, algorithm trading works. But you need a team of PhDs/masters degree in stem discipline to make it have some chance of succeeding. I’d look for prior work experience at successful hedge funds/prop trading firms as indicators of success.
Is algorithmic trading a truly automated investing? i.e. for an average person who is looking for a good return and not actively managing it, would it generate their expected return or more effort has to be put in to monitor the portfolio?
Algorithm trading needs manual input and effort. Always. In this case, the manual effort is being provided by the fund manager here I am assuming and not the investor. They earn the 20% performance fee to compensate themselves for the effort.
What do you think about the algorithms developed by Unhedged based on their backtesting results?
Algorithms seem legit. I wouldn’t pay 20% performance fee because I can effectively do this myself, but I’m an expert in this field. An overall Sharpe of 1-1.5 is realistic, but it’s not that attractive. My own trading generates around 4 Sharpe for example.
Would you invest in this company?
I wouldn’t invest. It’s basically just a repackaged hedge fund that’s accessible for the retail market. The promised returns are okay but not amazing.
Do you think you would create a product like the one Unhedged is offering and offer your expertise in algorithm trading to smaller retail investors in return for a fee? Or would it be too cumbersome and using institutional money would provide a better return for yourself?
If you have a good algorithm, you would be running it yourself or at a hedge fund/prop shop, where you get a performance fee. It’s much easier to run strategies at an institution – easier access to tech, support and capital.
The only reason you would offer strategies to retail investors instead is because 1) the strategies aren’t attractive enough to be run at a hedge fund, 2) you can more easily attract retail investors into investing into a sub par product with hype like AI and ML.
I don’t think Unhedged offers much competitive advantage or unique edge. A retail investor can just invest in actual hedge funds which are well regulated (min investment is 10k usually). And investment managers don’t need retail funds if they’re actually good at what they are doing – they would have been backed by institutional money instead.