Translate policy on algorithmic trading strategy into procedures that hold up under day-to-day pressure.
Building Algorithmic Trading Strategies in Financial Markets
A concise, decision-focused programme covering algorithmic trading strategy end to end.
Course Overview
In finance the difference between a healthy position on algorithmic trading strategy and a dangerous one is often a single assumption. Regulators no longer accept intent as evidence of control over this part of financial and banking practice. The teaching approach is deliberately practical: participants build a control framework for this area of financial and banking practice as they go. Most organisations already have a policy on algorithmic trading strategy; far fewer can show it working. They gain the ability to sequence improvements to the financial and banking practice discipline in an order their organisation can absorb. This programme builds the practice within financial and banking practice from first principles, without padding and without omitting what matters. It is written for people who have to make algorithmic trading strategy work with the resources they already have. Organisations that document this aspect of financial and banking practice properly resolve disputes about it far more quickly. It closes by agreeing the smallest change to the financial and banking practice capability that would make a visible difference.
Expected Learning Outcomes
Prepare the regulatory submissions arising from algorithmic trading strategy.
Stress test algorithmic trading strategy against scenarios that are plausible rather than comfortable.
Assess the capital and liquidity implications of algorithmic trading strategy.
Set acceptance criteria for algorithmic trading strategy before work begins rather than after.
Design the reporting on algorithmic trading strategy that reaches decision makers in time to act.
Integrate algorithmic trading strategy into existing management routines rather than running it separately.
Who Should Attend
Staff seconded into improvement work on algorithmic trading strategy.
Internal auditors reviewing the controls around algorithmic trading strategy.
Regulatory reporting analysts covering algorithmic trading strategy.
Investment and portfolio managers exposed to algorithmic trading strategy.
Risk managers responsible for algorithmic trading strategy.
Anyone whose accountability for algorithmic trading strategy exceeds their current formal training in it.
Course Modules
Algorithmic trading strategy: pricing, profitability and risk-adjusted return
2 sessions · 8 pointsSession 1Evidencing that algorithmic trading strategy worked as designed
- Collect evidence on the present handling of algorithmic trading strategy before proposing changes.
- Set escalation thresholds for algorithmic trading strategy that work out of hours.
- Confirm segregation of duties across initiation, approval and settlement of algorithmic trading strategy.
- Confirm reporting on algorithmic trading strategy reaches the committee that can act on it.
Session 2Closing out algorithmic trading strategy and capturing what was learned
- Anticipate the objections algorithmic trading strategy will raise and prepare the answers.
- Compare the cost of algorithmic trading strategy with the cost of its absence.
- Map the handovers in algorithmic trading strategy between functions and secure them.
- Test algorithmic trading strategy against a scenario the organisation would rather not model.
Algorithmic trading strategy: the control framework and segregation of duties
2 sessions · 8 pointsSession 1The assumption inside the model for algorithmic trading strategy that nobody revisits
- Review concentration by counterparty, sector and geography inside algorithmic trading strategy.
- Prepare the evidence pack demonstrating algorithmic trading strategy operated as designed.
- Check the legal and contractual exposure created by algorithmic trading strategy.
- Design the exception process for algorithmic trading strategy and require a documented rationale.
Session 2Setting a limit on algorithmic trading strategy that will actually be respected
- Review the pricing of algorithmic trading strategy against the risk being assumed.
- Estimate the resource algorithmic trading strategy requires to run as designed.
- Confirm client due diligence standards applied to algorithmic trading strategy are current.
- Record what was learned when algorithmic trading strategy did not go as planned.
Algorithmic trading strategy: measurement, models and their assumptions
2 sessions · 8 pointsSession 1Concentration building quietly inside algorithmic trading strategy
- Translate the appetite for algorithmic trading strategy into limits someone monitors daily.
- List the assumptions in any model supporting algorithmic trading strategy and when each was last challenged.
- Test the procedure for algorithmic trading strategy against a realistic scenario.
- State the risk appetite for algorithmic trading strategy as a number, not an adjective.
Session 2Reporting algorithmic trading strategy so the reader can act on it
- Set the review interval for algorithmic trading strategy and who attends.
- Check the accounting treatment applied to algorithmic trading strategy against current standards.
- Build the competence framework that supports algorithmic trading strategy.
- Reduce the variation in how algorithmic trading strategy is carried out between teams.
Algorithmic trading strategy: stress testing and scenario analysis
2 sessions · 8 pointsSession 1Making algorithmic trading strategy work when resources are constrained
- Assess the capital consumed by algorithmic trading strategy under current and stressed conditions.
- Agree the indicators that will show whether algorithmic trading strategy is improving.
- Distinguish symptoms from causes when algorithmic trading strategy underperforms.
- Set out the decisions in algorithmic trading strategy that require sign-off and by whom.
Session 2Who answers for algorithmic trading strategy, and to whom
- Confirm regulatory reporting on algorithmic trading strategy is complete, timely and reconciled.
- Set early warning indicators for algorithmic trading strategy with defined action thresholds.
- Assign responsibility for keeping documentation of algorithmic trading strategy current.
- Identify the data already collected that bears on algorithmic trading strategy.
Choose the package that suits you
Silver Package
At least 3 people
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.