Investor Research Survey · March 2026

Help shape the future of algorithmic trading for retail investors

Algosark is building a no-code platform that generates personalised algorithmic trading strategies for everyday investors. Your responses directly inform how we design it.

~10 minutes to complete

6 sections, 22 questions

Fully anonymous

Confidentiality notice: All responses are collected anonymously and used solely for academic and product research purposes by Tomiwa Kunle Oluwadare & Samuel Vikas Gujju. No personal data will be shared with third parties. By proceeding you consent to this use.

Section 1 of 5

About you

Basic demographic information to help us understand our respondent base.

What is your age group?*

18 – 24

25 – 34

35 – 44

45 – 54

55 – 64

65 and above

Please select your age group.

What is your gender?*

Male

Female

Non-binary / gender diverse

Prefer not to say

Please select an option.

What is your approximate annual gross income?*

Under £20,000

£20,000 – £35,000

£35,000 – £60,000

£60,000 – £100,000

Over £100,000

Prefer not to say

Please select your income range.

What is your employment status?*

Employed (full/part-time)

Self-employed

Retired

Student

Unemployed / seeking work

Please select your employment status.

Section 2 of 5

Your trading profile

Tell us about your current investment activity and experience.

How many years of trading or investing experience do you have?*

Less than 1 year

1 – 2 years

2 – 5 years

5 – 10 years

10+ years

Please select your experience level.

Which asset classes do you currently trade or invest in? (Select all that apply)*

Stocks / Equities

ETFs

Forex / FX

Cryptocurrency

Options / Derivatives

Bonds / Fixed income

Commodities

None yet — I'm just starting

Please select at least one asset class.

How frequently do you trade?*

Multiple times a day

Daily

Weekly

Monthly

Rarely / buy-and-hold

Please select your trading frequency.

What is the approximate total value of your investment portfolio?*

Under £5,000

£5,000 – £25,000

£25,000 – £100,000

£100,000 – £250,000

Over £250,000

Prefer not to say

Please select your portfolio range.

Section 3 of 5

Risk tolerance

Understanding your comfort with risk helps us calibrate strategies appropriately.

How would you describe your risk appetite?*

Very Low — I prioritise capital preservation above all else

Low — Modest returns; I'm uncomfortable with significant losses

Medium — Balanced; I accept some volatility for reasonable returns

High — Growth-focused; comfortable with large swings

Very High — Speculative; I target maximum returns and accept high drawdowns

Please select your risk appetite.

Q10

If your portfolio dropped 20% in one month, you would most likely:*

Sell everything immediately to stop further losses

Reduce positions and reassess the strategy

Hold — drawdowns are part of the process

Buy more — this is a buying opportunity

Please select your most likely response.

Q11

What is the maximum monthly drawdown you would accept before pausing a strategy?*

Drag the slider to indicate your threshold

0% (no loss tolerated) 50% (very high tolerance)

15%

Q12

What is your primary investment objective?*

Capital preservation

Regular income

Long-term growth

Short-term speculation

Portfolio diversification

Please select your primary objective.

Section 4 of 5

Algorithmic trading awareness

We want to understand your current familiarity with automated trading systems.

Q13

How familiar are you with algorithmic (automated) trading?*

Not at all familiar — I've never heard of it

I've heard of it but don't understand how it works

I have a basic understanding but haven't used it

I've tried using basic algo tools

I actively use algorithmic trading tools

Please select your familiarity level.

Q14

What is the biggest barrier stopping you from using algorithmic trading? (Select your top reason)*

It's too complex / requires coding skills

I don't understand how to build strategies

I don't trust AI / automated decisions with my money

The cost of platforms is prohibitive

I don't have time to learn or manage it

There is no barrier — I already use it

Please select the main barrier.

Q15

Have you ever used any of the following trading tools or platforms? (Select all that apply)

eToro

Trading 212

IG Markets

QuantConnect

MetaTrader 4/5

Interactive Brokers

Hargreaves Lansdown

Vanguard

None of the above

Q16

How did you first learn about algorithmic trading?*

Please select a discovery channel.

Section 5 of 5

Algosark — your interest & expectations

The final section. Help us understand what would make Algosark valuable to you.

ℹ Algosark is a no-code platform that generates personalised algorithmic trading strategies from a short risk survey — no coding, no quant finance background required. Strategies are backtested and delivered via a paper-trading dashboard before you commit real capital.

Q17

How interested are you in using a platform like Algosark?*

Very Interested — I would sign up today

Interested — I'd like to learn more first

Neutral — I'm not sure yet

Unlikely — I prefer to manage trades myself

Not Interested

Please select your level of interest.

Q18

Which feature of Algosark is most important to you? (Select your top priority)*

Personalised strategy

Historical backtesting

Ease of use / no-code

Full automation

Risk management tools

Transparency / explainability

Performance analytics

Brokerage API connection

Please select your top feature priority.

Q19

How much would you be willing to pay per month for a personalised algo trading strategy platform?*

£29 / month

£59 / month

£99 / month

Custom amount

Drag to set your custom monthly amount

£0 £200+

£50/month

Please select your willingness to pay.

Q20

Would you be willing to try paper trading (virtual funds, zero real-money risk) before subscribing?*

Yes, definitely

Probably yes

I'm unsure

No — I'd prefer live trading immediately

Please select your preference.

Q21

How likely are you to adopt Algosark if it matches your risk profile?*

1 = Very unlikely 10 = Extremely likely

1 — Very unlikely 10 — Extremely likely

5 / 10

Q22

Any other comments, suggestions, or questions about Algosark?

Optional — your feedback is very welcome

✓

Response submitted

Thank you for taking part

Your responses have been recorded and will directly inform the development of Algosark. We genuinely appreciate the time you've given to help us build a better platform for UK retail investors.

— Time taken

22 Questions answered

5 Sections covered

What happens next: Your data is anonymised and analysed alongside other responses. Results will be used in the Algosark research report by Tomiwa Kunle Oluwadare & Samuel Vikas Gujju. Contact: [email protected]