Most of the world’s financial services have been affected by the recent global instability. This forced many players to rethink their business model and to reconfigure their pricing, modelling and market risk management.
Trading Integral Solutions has worked with many clients in the banking, insurance and capital management industries, simplifying and strengthening their market risk management, and implementing simple yet robust quantitative models, used in their front and middle offices.
We do not claim to solve World issues, but we do help simplify complex business situations through:
- Simple yet robust modelling of extreme events (tail risk)
- Building custom pricing and performance measurement engines
- Risk convergence: Systematic harmonization of governance, risk management and control functions
- Integration of external pricing and hedging libraries into front office systems
- Simplification and streamlining of pricing sheets into a unified platform
- Modelling, implementation and back-testing of statistical arbitrage strategies
- Key performance measures for different strategies and aggregation into overall portfolio measures
- Smart dashboard and management reports for different portfolios
Through different engagements in banking, insurance and fund management, we have strived to add real value using a pragmatic, flexible and real-world approach founded on robust financial theory and quantitative modelling.
Click below to learn more about some delivered featured projects.
Simulating trading strategies for a hedge fund
This scenario-based simulation of trading strategies’ P&L and key performance ratios, incorporates the effect of capital re-investment ratio depending on past levels of draw-down.
Simulating Trading StrategiesSimulating market prices for a re-insurance company
This is a methodology and framework used in the front and middle offices to carry out:
- a real-world vs. risk-neutral simulation of market prices using both binomial and mean-reverting jump diffusion models.
- a simulation of one path, or a thousand paths with distributions across paths or time
Simulating Market PricesPairs trading for an investment bank
This is a design and an implementation of a winning cross-commodity statistical arbitrage strategy which identifies pairs sharing long-term dependency measured by the speed of mean-reversion and exhibiting enough volatility to take advantage of the spread swings around the identified trend.
Pairs trading using cointegrationPortfolio flower structure for a large capital management firm
This is a playful representation of a large hedge fund portfolio with a preserved structural hierarchy and position sizes.
Portfolio flowerAnimated dynamic portfolio allocation for a hedge fund
This is another playful representation of risk, return and size of investments through history. In a risk-return quadrant, historical dynamic asset allocation is represented, where each ball diameter represents the size of the portfolio allocated to an index, and the balls’ movements in the quadrant depend on their rolling annual average risk and return profiles.
Dynamic portfolio allocation
We selected a sample of software applications implemented for different clients and reproduced demo versions that, whilst offering minimal functionality, indicated the implemented solution using interactive real-time computations in the cloud.
Click below to learn more about these solutions.
Simulating Trading Strategies
This interactive online application allows you to configure ratios of capital re-investment, depending on past draw-down levels, and then simulate market prices using two different models. The distribution of your portfolio P&L, key performance indicators and a complete daily report of portfolio P&L are shown.
Trading SimulatorSimulating Market Prices
This interactive online application allows you to choose parameters to simulate a mean-reverting jump diffusion model or a simpler binomial model for visualizing different kinds of distributions.
Price SimulatorFitting Volatility Curve
This interactive online application uses your data, such as historical forward curves and seasonality partitions. The application renders a 3-dimensional representation of historical forward curves and then calibrates model-implied volatilities to historical ones.
Volatility calibrator