My quantitative finance journey over 25 years

1. Research: Investment Solutions for
FinTech Apps
Dr Drago Indjic
University of Greenwich
5 September 2019

2. Content
• Personal and research profile
• Quantitative finance (1993-)
– Asset management: ETFs via hedge funds
– Empirical ETF and Alternative Beta
• Fintech (2015-)
– Digital (household) investment agent(s)
– Suitability, risk attitudes, goals, life-events, (CX/IX)

3. Profile
• PhD (Control Engineering), Imperial College, 1995
• “data science”: start-ups funds and tech ventures
– EU Expert (1997-): H2020 fintech & Machine Learning → EIC
– buy-side quant: never a banker/trader, yet still FCA (CF30)
• Fintech: robo-advisory, D2C
• Portfolios of hedge fund strategies/funds
– Market risk and liquidity management/optimisation
– Alternative β theory (LBS) and practice (Sunningdale LLP)
• @dindjic
– SlideShare; ResearchGate; Quora; F6S …

4. Core Tools and Techniques
• Machine Learning, 1987
• R language, 1993

5. Teaching
• E416 Hedge Funds, LBS (2003-date), Prof. Naik
– https://www.slideshare.net/barcelonagse/hedge-funds-for-the-2010s
+ UPF Barcelona (block) for 7 years
• Corporate Finance (2012/13), Dr Gamlath
• https://www.uwl.ac.uk/academic-schools/business
• Quantitative Finance (2004/05), Prof. Urošević
• http://imqf.ekof.bg.ac.rs/imqf/
• Fintech (2020 - )

6. Fintech Syllabus (2018/19)
• .

7. Fintech
• “Wealthtech”: Judge (2016); Regents (2017)
– https://www.slideshare.net/dindjic/digital-wealth-product-
design
– https://vimeo.com/204023046
– https://youtu.be/BvynzSSY-A0

8. Core Teaching
• Financial markets and instruments
• Investments
• Portfolio analysis
• XLS and R
• Behaviour and risk attitudes
• Case studies: independent investment “app”
• 1st in the EU, launched 2016 (2nd to Nutmeg)
• https://youtu.be/j8YliLcJc4g (+ African, Balkans)

9. MSc/PhD Topics
• Fintech “Investment Engines”
– Principles: MVP and enhancements
– Clients: suitability and risk profiling
– Goals: Life-cycle/events re-planning
– Model: completion portfolios
• Lo, Ang, Roncalli, Scherer monographs
– Real-world practice: TER/Costs, investability
– Inclusion/Impact: frontier markets, local FX
components for African, CEE and China retail

10. Implementation
• Suitability
• Risk rated product: client profiling
– complexity = product liability
• Massive personalisation
• Implementation: bootstrap by €/£20 pm regular inflows
• Personal advice vs guidance (segmentation)
• Quality: conflicted? Delegated (= Costly)
• Financial planning goals over stream of life events
• Deliver investment experience (engagement, fun)

11. Invest for Free
• Investment business break-even AUM
– Performance/Flow ≠ Cost/Flow relationship
– Components: average asset weighted, ~20 bps
– Strategy: all inclusive “robo” fee, ~50 bps

12. Portfolio Model
• Rebalancing allocations, regular inflows
• Asset allocation “selection” (0/1) <> weighting
• %weight: top/down, bottom-up, risk control
• objective(s), constraints → periodicity, cost
• “%Strategy”
• Plain vanilla ETF
• What is missing?
• Smart (bond) Beta
• CTA, convertible bonds …

13. Personal Investment Solutions
• Demand shift: investment apps, well scaling
• “digital, customer-centricity, shift in end customer base
combine to radically alter the fund management”
• Risk profiling: on-going activity, not onboard’d
• Produce evidence of total past investment experience
• “Quality”, value for money (cost of guarantees)
• Portfolio service synthesis: reliability, p(target)
• Choice of portfolio components, inc trading costs
• Only one or many products (over time)?

14. Research Canvas
• SlideShare + ResearchGate; Quora etc

15. Pedigree: 15+ Years

16. Research (1): β via ETFs
• Fund universe analysis
• http://soft-finance.com/ for 15 years
• Risk models
– Single risk models dominate in practice – why?
– Closed risk/performance feedback loops
• ETF economics
– ETF financial audit data; product graveyards

17. Digital, but Skilled
• Investment experience
– Direct, transparent, engaging, inclusive
• Risk-controlled, glide-path portfolios
– Cost-, risk- and liquidity-adjusted performance
– ETFs remain open, don’t return capital
– Hedge funds do not produce income
– “Long only” lacks several degrees of freedom
• New investment business models
– Skill pricing: Huddlestock, SharingAlpha …

18. Expenses
• .

19. Graveyards
• .

20. Exotic ETF
• Bond: NIRP and #deep index criteria (FTSE)
• Commodities; plethora of “smart”
– Volatility
• Convertible bonds: index as well as arbitrage
– S&P vs DE:ECBD “TR Balanced Euro” ..
• Managed futures (CTA)
– Active strategy index replication or index fund
• Pro
– Re-defining and re-pricing risk premia
– Diversification and tactics on tap

21. Research II: Alternative β
• Hedge fund strategies
• Portfolios of hedge funds
• Alternative Beta risk premia

22. Exposure Format Choice
• e.g. CTA: (select) fund (Winton, Palomar), an
index fund or alternative/smart Beta?
• Capacity? Fees? Bargaining power?

23. Liquidity Management
• Contractual redemption duration
• Joint daily Beta/liquidity risk control

24. Portfolio Effect Inefficiencies
• Investors and FoHF managers are over-focused on
bottom up hedge fund selection
– Individual hedge fund risk factors (or implemented
manager’s views) can be correlated (funding risk,
short squeeze)
– Not risk managed; aggregate systematic effects are
not corrected (or managed) at the portfolio level
– May aspire to be contrarian or defensive
• FoHF as a factor portfolio: consider a single Beta
hedge fund market index factor for FoHF
– 𝑅 𝐹𝑜𝐻𝐹 = β ∗ 𝑅 𝐻𝐹 𝑚𝑎𝑟𝑘𝑒𝑡

25. Reverse Viewpoint
– Index products replicating reverse and long index

26. October 2011
•

27. Replication Regimes
– “Good” (2014Q3) vs “Bad” regime (2015Q1)

28. Insight: Market Neutral
– Post-June 2013: if replication is broken, stay away

29. Daily Walk-Forward
– Daily since Jan 2010; delta zero switchable since Jun
13; 0.5%/5% performance fees

30. Performance Attribution
– ITD: 28 Long, 25 Short and 43 Neutral trades

31. Sept 2015

32. Bibliography
– A new investment paradigm: Alpha-Beta
separation (2009) Euromoney
– Olympia Dynamic FoHF (2010)
– Hedge Fund Dynamic Beta Investing: An Overview
(2014) Beachhead
– Redefining αlpha and βeta (2014) JP Morgan
– @dindjic