Trading strategies that effectively balance trading costs with risk can make a valuable contribution to portfolio returns. By helping traders better allocate and time their trades, Axioma’s solutions empower successful investment strategies.
For firms that manage multiple strategies or accounts or utilize other managers, weighing trading costs as part of the portfolio rebalancing process can identify trades that may be pooled for cost-savings. Axioma’s flexible tools allow asset managers to consider many factors, including trading costs and market impact, when rebalancing portfolios. Trade-related constraints regarding timing, pricing, liquidity, and quantities can also be implemented on a customized basis.
- Rebalance portfolios on demand or at a specified time
- Perform historical simulations to research potential trading strategies
- Control market impact, ticket charges, commissions, and other trading-related costs
- Fairly allocate scarce liquidity across accounts and control shared market impact using multi-portfolio optimization
Multi-Portfolio Optimization and Fairness in Allocation of Trades
When trades from separately managed accounts are pooled for execution, the realized market-impact cost can be far greater than the sum of the predicted cost over all accounts. Axioma’s multi-portfolio optimization technique rebalances multiple portfolios at the same time, considering joint effects while adhering to account-specific constraints.
Multi-Period Portfolio Optimization with Alpha Decay
The traditional Markowitz MVO approach is based on a single-period model. For long-term investors, Axioma’s multi-period optimization methodology offers the opportunity to make wait-and-see policy decisions by including forecasts and long-term policy decisions beyond the rebalancing time horizon. Axioma researchers compare this model with the traditional single-period MVO model on a simulated example and show that the multi-period model tends to generate portfolios that are likely to have a better realized performance.
Tradability versus Performance: The Role of Liquidity in Minimum Variance Smart Beta Products
Low volatility-themed strategies have been among the most popular "smart beta" index products introduced in recent years, and minimum variance in particular has become a widely adopted approach to implementing low-volatility exposure. Axioma researchers consider to what extent the "theoretical" low risk of these strategies is driven by illiquidity masquerading as low volatility. Do returns of minimum variance strategies encapsulate some form of liquidity premium in addition to the outperformance of low risk stocks? And, if there is a tendency to tilt towards smaller and less liquid stocks, what can be done to ensure tradability of minimum variance portfolios?
Axioma Portfolio Optimizer: The Most Flexible Portfolio-Construction Tool on the Market
With virtually limitless objectives and an equally unlimited range of constraints, Axioma Portfolio Optimizer delivers maximum flexibility to model even the most complex strategies for a wide range of investment management approaches, from quantitative to fundamental.
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