Indextus SMART indices Methodology Overview

Transcription

1 Indextus SMART indices Methodology Overview

2 Summary Indextus SMART (Sector-based Mixed Asset Risk Target) indices are calculated using FE Analytics*, driven by allocations generated by the Indextus technology. The academic heritage behind our indices is based on three core ideas: (1) Asset allocation is a key determinant in mixed asset portfolios (2) Regression viably captures aggregate information across dynamic financial data sets (3) Aggregated data allows indices to capture equilibrium points within markets Ongoing weekly and monthly processes maintain the accuracy of our indices *FE Analytics is a leading independent financial data system supplied by Financial Express INDEXTUS OVERVIEW 2

3 Academia Asset allocation is important. We focus on asset classes. Determinants of Portfolio Performance Brinson, Hood & Beebower Financial Analysts Journal, July/Aug 1986 INDEXTUS OVERVIEW 3

4 Academia Factorisation using statistical regression is effective. Particularly when you have the underlying holdings data. Asset Allocation Sharpe Journal of Portfolio Management, Winter 1992 INDEXTUS OVERVIEW 4

5 Academia Portfolio neutrality is an equilibrium point for analysis against uncertainty. The Indextus technology captures this across the efficient frontier. Global Asset Allocation Black & Litterman Goldman Sachs, October 1991 INDEXTUS OVERVIEW 5

6 Approach Weekly asset allocations updated and aggregated Update list of active mixed asset funds (FE data) across relevant fund sectors including those residing in the unclassified sector. Verification checks made to ensure robustness of the data (for example, weights add to 100%; submission dates within last 4 months, no skewed outlier holdings, etc.). Where appropriate this also re-bases alternative assets out of all allocations. Returns data used to bring all weight submissions to the latest time point. Will be adjusted further by fund flows data across asset classes as appropriate. Non-linear regressions applied at both asset group level and total portfolio level to generate asset class profiles. INDEXTUS OVERVIEW 6

7 Approach Monthly risk analytics applied Full covariance matrix calculated using returns (FE data) across asset class returns. Asset class profiles applied to covariance matrix to generate volatility-ranked total portfolio spectrum. Statistical averaging technique used to smooth data from month to month, this reduces jumps in the data set and improves turnover rates across index constituents. Indextus system used to generate index data series from monthly updated asset allocation weights based on specific risk targets. Checked against same calculation within FE Analytics. Interquartile scores, linear v. non-linear regression comparisons and weekly absolute changes all used to ensure data robustness. INDEXTUS OVERVIEW 7

8 Approach Monthly volatility ranking of the underlying asset classes uses a standard full covariance matrix approach based on weekly periodicity from the beginning of INDEXTUS OVERVIEW 8

9 Asset Class Allocation Output Culminates in asset class allocations for each level of volatility. 40% 35% 30% 25% 20% 15% 10% 5% 0% CASH - Cash BONDS - Gilts BONDS - Sovereigns BONDS - Corporates EQUITIES - UK EQUITIES - US EQUITIES - EUxUK EQUITIES - Japan EQUITIES - Asia EQUITIES - Emerging Risk Target Source: Indextus; as at 01/01/2018 INDEXTUS OVERVIEW 9

10 Output The Indextus technology generates risk targeted asset allocations across the volatility spectrum. Time series of weights can then be produced. This example shows 9% target volatility. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% EQUITIES - Emerging EQUITIES - Asia EQUITIES - Japan EQUITIES - EUxUK EQUITIES - US EQUITIES - UK BONDS - Corporates BONDS - Sovereigns BONDS - Gilts CASH - Cash Source: Indextus, as at 01/01/2018 INDEXTUS OVERVIEW 10

11 Fund Costs Cost adjustment To increase alignment with the IA mixed asset sectors, a cost adjustment is calculated biannually and applied to the Indextus SMART series daily. This involves adding an estimated underlying fund charges figure whilst deducting the fund costs of each index s ETF constituents, to ensure no double cost counting. The Indextus SMARTx series is also available, which does not include this cost adjustment. 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% Risk Level Source: Indextus, Financial Express; as at 01/01/2018 INDEXTUS OVERVIEW 11

12 Constituents To ensure tradability, the Indextus SMART index series uses a range of Exchange Traded Funds (ETFs) listed on the London Stock Exchange. These were selected for: Longevity of their histories. Track record of replicating underlying benchmarks that broadly capture asset class characteristics. Commitment to information transparency. Depth of market liquidity. Asset Class CASH - Cash BONDS - Gilts BONDS - Sovereigns BONDS - Corporates EQUITIES - UK EQUITIES - US EQUITIES - EUxUK EQUITIES - Japan EQUITIES - Asia EQUITIES - Emerging ETF Holding DB X-trackers II Sterling Cash UCITS ETF ishares Core UK Gilts UCITS ETF ishares Global Government Bond UCITS ETF ishares Core GBP Corporate Bond UCITS ETF ishares Core FTSE 100 UCITS ETF ishares S&P 500 UCITS ETF ishares MSCI Europe ex-uk UCITS ETF ishares MSCI Japan UCITS ETF ishares MSCI AC Far East ex-japan UCITS ETF ishares MSCI Emerging Markets UCITS ETF INDEXTUS OVERVIEW 12

13 Published Indices Asset allocations are updated on the first of each month. All calculations are verified and performed using FE Analytics, from returns data supplied by Financial Express. Indices are total return (net income reinvested) in GBP terms, using midto-mid pricing data. Three core Indextus SMART indices targeting various risk target levels are generated weekly, providing open access daily data. More information can be requested from The flagship Indextus SMART indices 1,600 1,400 1,200 1, Indextus SMART 5% Indextus SMART 9% Indextus SMART 13% Source: Indextus Ltd, Financial Express. Data as at 30/11/2017 INDEXTUS OVERVIEW 13

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