As explained in the modelling documentation, the model production generates daily signals for individual assets, e.g. the WTI June and December contracts are modelled separately.
The automated index process take these signals as input and index weights are then calculated through three sequential steps.
Business Day for an asset refers to a day where the asset is trading and has a settlement Close Price.
Asset refers to one of the selected components of the Index. Assets can be in the form of a fixed contract or a rolling contract.
Price, P(t,i) refers to the close price on business day t of Asset i.
Return, r(t,i) refers to percentage returns, (P(t,i) - P(t-1,i))/ P(t-1,i).
Product refers to the AiLA Index, where its output are daily weights for each asset in the index.
Mid Cap Logic requires the execution of instructions on the close of the next Business Day. This is typically used for indices with a capacity lower than US$1 billion.
Large Cap Logic is typically used for indices with a capacity of US$1bn and above, where a different execution process is applied as described below.
Weights are calculated just after close on each business day.
Inline with the other types of AiLA indices, each Asset is assigned Daily Rebalancing Caps across the curve to prevent trading with a significant amount of slippage. These are specified under the following four Durations to the Expiry Date:
Each Asset is assigned Daily Asset Caps equal to a given multiple of their rebalancing cap value, where the multiple used is 1x (4x) for the Mid (Large) Cap logic. The multiple hence suggests the number of days necessary to trade in/out of the max allowed weight.
The AiLA Alpha Index suite of products is designed to deliver absolute returns investment Alpha to investors. The suite of products is asset agnostic. However, it is presently focused on Commodity assets and equity indices as the underlying assets. These index products are designed to be highly liquid and tradable and constructed taking into account market liquidity. In addition, as AiLA uses opportunistic allocation to generate alpha, the strategy might not be fully allocated all the time.
The Index Methodology calculation starts from using the output of AiLA’s systematic upstream process to decide if we should go Long, Short or stay flat on a given asset. As part of the index construction process, these allocation decisions are used in a first step, together with market volatility and correlation estimates, to construct index weights with the desired risk profile, representing an ideal portfolio.
In a second step, the ideal portfolio is used to find similar but realistic index weights, which respect requirements such as Asset and Sector weight caps. These Asset and Sector weight caps are risk constraints that we would like to implement for a given strategy.
We then take into account liquidity constraints as the index seeks into incorporate actual market liquidity. This is done by setting a Daily Rebalancing Cap for each asset under the Large Cap Logic, ensuring that the strategy can be executed. As the Sector constraints and Daily rebalancing constraints are mutually exclusive, we always prioritise Sector risk constraints.
If the Large Cap Logic is in place, we ensure that all positions are closed with ample time before the expiry of a contract. Therefore, we will starting closing all active positions at least seven Business Days before the expiry of a contract.
Finally, to obtain the index values, we apply simple arithmetic calculations to calculate the Units, and Daily PNL for each Index, taking into account the change of asset prices on each trading day.
[Diversification Benefit]: Perspectives, https://ailaindices.com/diversification-benefit.php
Note: further details w.r.t. this subject are discussed in [Controlling correlation]
[SciPy]: E. Jones et al., Open Source Scientific Tools for Python (2001), http://www.scipy.org
[Controlling Correlation]: Perspectives, https://ailaindices.com/controlling-correlation.php
[SciPy]: E. Jones et al., Open Source Scientific Tools for Python (2001), http://www.scipy.org.