Developing stable, accurate and performant algorithms brings some extra challenges, extending the classical “Software Engineering”. For this special purpose, we have built the process of developing and tailoring the algorithms called “Algorithm Development Process” (ADP), which ensures flexibility, high pace and reliable deliverables. This process results in quantitative models to be more stable and documented.
A SECTION OF OUR ALGO INVENTORY
Cash Account Aggregation
Get an aggregated view on all cash accounts.
Define rules for savings based on account transactions and volumes.
Define target savings as objects of desire.
Suggestion of savings rate based on forecast of net income.
Categorization based on product type, region, sector, liquidity etc.
Get one integrated view on all your security deposits.
Asset Allocation (BL)
Allocation based on the (extended) Models of Black/Littermann/Markovitz.
Allocation based on the (extended) Model of French/Fama.
Risk Bearing Capacity
Calculation of the level of acceptable risk for the customer.
Set of 40 dialogues identifying desired volatility, drawdown and durations.
Simulation of various market events and their effects on the portfolio.
Comparison of risk and performance for existing and planned investments.
Rebalancing (Risk Profile)
Continuous monitoring and adoption of the portfolio based on the risk profile.
Rebalancing based on investment duration.
Library with over 50 indicators (e.g. drawdown, v@r, greeks).
Filtering of ETFs & Funds based on 50 criteria (see FinStata Lib).
Cash Account KPI
Performance Indicators calculated based upon a client’s cash accounts.
Integrate a diversified portfolio with targeted special investments.
Peer Group Cash Account
Cash account based benchmarking (e.g. based on income, outcome).
Comparison against relevant indices.
Scans for extraordinary income or outcome and triggers a dialogue.
Scans for products matching predefined trends (like Robotics, Bio, etc.).
Suggestion of changes for transforming a current portfolio into a desired one.
Approximation of product costs (TER) within the current portfolio.
DATA DRIVEN ANALYSIS
To improve our software and provide additional benefits to our clients, we analyze financial and non-financial market data as well as cash accounts & security deposits data and develop processes in order to comply with future regulation. In concrete terms our Labs do the following:
- Market Data: We derive market indicators and trends from financial markets. The trends are also bundled in our tool called “Trendvest”.
- Account Data: We analyze cash accounts & deposits to find patterns in customer actions by applying suitable algorithms. Insights are transported as rules into our software.
- Future Regulation: Together with our Venture Lexcube we test upcoming regulations early on within our software workflows.
TRENDS FROM TRENDVEST
Instead of only looking at the mere facts and figures, customers also consider their emotions when deciding on financial investments. We are constantly researching trends and therefore developed Fincite Trendvest to give more emotionally driven investors a new access to financial products.
Internet of Things Trendindex
Demographic Change Trendindex
Shopping Revolution Trendindex
DATA DRIVEN RESEARCH FOR TRENDS
To provide our clients an emotion-based alternative to stocks and bonds, we derive trends such as e.g. ageing society, business software, robotics or electromobility from research & financial market data.
150 automated searches
for patterns in market data.
and the characteristics.
identification of trends.
Building a long list
of potential products.
Manual trend hypothesis
on trends by the client.
20+ criteria for selecting
the right products.
Thorough validation of the
10+ weighting strategies
for different risk profiles.
Fincite Research Analyst
with access to Trend Libs.
Setup of the weighted
Thorough validation of the
Historic and scenario-based