XRD. Equity Risk Models IDENTIFY ANALYZE QUANTIFY NORTHFIELD

Transcription

1 XRD Equity Risk Models IDENTIFY ANALYZE QUANTIFY NORTHFIELD

2 Jul The XRD Equity Risk Models Table of Contents SUMMARY... 3 USA Model Summary... 3 Europe Model Summary... 3 Japan Model Summary... 3 Asia ex Japan Model Summary... 3 Latin America Model Summary... 3 Natural Resources Model Summary... 3 Global Model Summary... 4 UNIQUE FEATURES... 4 Double Hybrid Methodology... 4 Multiple Stock Betas... 4 Weight and Exposure Differentiation... 4 Currency Factors... 4 Estimation Error Minimization... 4 Macro-Economic & Commodity Sensitivities... 4 Calendar Effect Minimization... 4 Base Currencies... 4 CONSTRUCTION DETAILS... 5 Delivery Channels... 5 Model Start Date... 5 Model Universe... 5 Time-Weighting... 5 Statistical Significance... 5 Beta Winsorisation... 5 Cross Reference Day XRD risk model... 5 Market Factors... 5 Industry Factors... 5 Statistical Factors... 5 REGIONAL CURRENCY FACTOR LIST... 6 REGIONAL STYLE FACTOR LIST... 7 REGIONAL MARKET FACTOR LIST

3 REGIONAL INDUSTRY FACTOR LIST... 8 STATISTICAL FACTOR LIST... 9 STYLE FACTOR DEFINITIONS Dividend Yield Current Value Growth Trend Growth Momentum Short-term Momentum Long-term Momentum Leverage Liquidity Quality

4 Summary The Northfield XRD Equity Risk Models are available for the USA, Europe, Japan, Asia ex Japan, Latin America and a Natural Resources region (which consists of Australia, New Zealand, Canada and South Africa), as well as a Global model. USA Model Summary Europe Model Summary Japan Model Summary Asia ex Japan Model Summary Latin America Model Summary Natural Resources Model Summary Asset coverage 13,200 Currency factors 6 Style factors 9 Market factors 2 Industry factors 20 Asset coverage 12,500 Currency factors 14 Style factors 9 Market factors 33 Industry factors 19 Asset coverage 3,800 Currency factors 3 Style factors 9 Market factors 2 Industry factors 19 Asset coverage 17,800 Currency factors 13 Style factors 9 Market factors 12 Industry factors 19 Asset coverage 1,500 Currency factors 6 Style factors 9 Market factors 6 Industry factors 17 Asset coverage 8,000 Currency factors 7 Style factors 9 Market factors 6 Industry factors

5 Global Model Summary Unique Features Double Hybrid Methodology Multiple Stock Betas Weight and Exposure Differentiation Currency Factors Estimation Error Minimization Macro-Economic & Commodity Sensitivities Calendar Effect Minimization Base Currencies Asset coverage 56,200 Currency factors 31 Style factors 54 Market factors 61 Industry factors 113 Northfield's double hybrid methodology combines the advantages of both time-series and cross-sectional regressions for different types of defined factors, and the addition of statistical factors to capture residual systematic common factor risk ensures that stock specific risk really is due to stock specific effects, and is uncorrelated with other assets. Time-series regressions using Bayesian priors are used to determine the sensitivity of all stocks to their Currency, Market and Industry factors. We then use statistical significance tests to see whether stocks have additional exposures to other Market and Industry factors. The XRD betas capture the underlying economic exposures of each individual security, so the risk model recognizes that there will be high beta and low beta stocks for all factors. The portfolio betas to these factors enable fund managers to distinguish between portfolio weights and portfolio exposures, which can, of course, be very different. The Currency factors capture the foreign currency exposure of foreign stocks. This feature is particularly helpful to investors seeking to hedge their foreign currency exposures, as the portfolio betas to the Currency factors represent the appropriate hedging ratios for these currencies. Using time series regressions to estimate the Currency, Market and Industry betas has the advantage that some of the estimation error will diversify away when portfolio betas are calculated. Our proprietary XRD technology also helps to minimize sample specific estimation errors, with the result that the Northfield XRD Risk Models give more accurate portfolio risk forecasts. Fund managers can use this risk model to estimate the exposure of their portfolios to a very wide range of Commodities and Macro-Economic variables, spanning the G20 countries and more. The overall risk model universe currently includes equities, ADRs, GDRs, ETFs and indices. The risk model is updated every Thursday morning, using four historic lookback periods of eighty 4-weekly returns (just over 6 years). This ensures that all the security returns are the same length (unlike calendar months), and also avoids the biases that may arise from concentrating the impact of endof-month, end-of-quarter and end-of-year effects. All XRD models are available in a wide range of base currencies. 4

6 Construction Details Delivery Channels Model Start Date Model Universe Time-Weighting Statistical Significance Beta Winsorisation Cross Reference Day XRD risk model Market Factors Industry Factors Statistical Factors Each of the XRD risk models are automatically updated weekly within our Portfolio Risk Management system, PRISM. The risk model is also available weekly in Flat File Format (Pipe Delimited text file) 2004 or 2005 At least the top 98% of each market by capitalization The model is based on eighty exponentially time-weighted 4-weekly returns Time-weighting exponential coefficient = Half-life = 46.9 * 4 weeks = 3.6 years Half-weight = 28.6 * 4 weeks = 2.2 years Test for inclusion 97.5% Test for exclusion 92.5% Winsorise the highest and lowest 2% of betas for each time series factor to the next nearest beta to that factor within each of the 4 SRD models. We first build 4 Single Reference Day (SRD) risk models using 4 sets of historic returns offset by 1 week each. The 4 SRD models are then averaged to produce the XRD risk model. This technique significantly reduces samplespecific estimation errors, and gives better portfolio risk forecasts. These are weighted by current market capitalization with a maximum constituent weight of 30%. The Large Market factor is built from the top 80% stocks by market capitalization, there is a (Mid Cap) gap of 8% to 10%, and the Small Market factor is built from the next 8% to 10% of stocks. These are weighted by current market capitalization with a maximum constituent weight of 30%. Industry priors are based on the Global Industry Classification Standard (GICS). These are constructed by running Principal Components Analysis on the correlation matrix formed from the residual returns of all full history stocks. 5

7 Regional Currency Factor List US Europe Japan Asia ex Japan Latin America Natural Resources ARS (Argentine Peso) AUD (Australian Dollar) BRL (Brazilian Real) CAD (Canadian Dollar) CHF (Swiss Franc) CLP (Chilean Peso) CNY (Chinese Yuan) COP (Colombian Peso) EUR (Euro) GBP (British Pound) HUF (Hungarian Forint) IDR (Indonesian Rupiah) ILS (Israeli Shekel) INR (Indian Rupee) JPY (Japanese Yen) KRW (South Korean Won) MXN (Mexican Peso) MYR (Malaysian Ringgitt) NOK (Norwegian Krone) NZD (New Zealand Dollar) PEN (Peruvian Nuevo Sol) PHP (Philippine Peso) PLN (Polish Zloty) RON (Romanian New Leu) RUB (Russian Ruble) SEK (Swedish Krona) SGD (Singapore Dollar) THB (Thai Baht) TRY (Turkish Lire) TWD (Taiwanese Dollar) ZAR (South African Rand) *This table shows the Currency Factors in each model (and together, the Global model) from the perspective of a US Dollar based investor. All XRD Models are available in any of the above currencies. In alternative base currency versions, the US Dollar would then become a Currency factor in the model, replacing the new base currency. 6

8 Regional Style Factor List US Europe Japan Asia ex Japan Latin America Natural Resources Dividend Yield Current Value Trend Growth Growth Momentum Short Momentum Long Momentum Leverage Liquidity Quality Regional Market Factor List US MARKET FACTORS** US Large US Small JAPAN MARKET FACTORS** Japan Large Japan Small NATURAL RESOURCE MARKET FACTORS** Australia Large Australia Small Canada Large Canada Small New Zealand South Africa EUROPE MARKET FACTORS** Austria Baltic Region (EST, LVA, LTU) Belgium Denmark Emerging Europe (UKR, CZE, SVK, SRB) Finland France Large France Small Germany Large Germany Small Greece & Cyprus Hungary Ireland Israel Italy Large 7

9 Regional Market Factor List ASIA EX JAPAN MARKET FACTORS** China Hong Kong Large Hong Kong Small India Indonesia Malaysia Philippines Singapore South Korea Large South Korea Small Taiwan Thailand LATIN AMERICA MARKET FACTORS Argentina Brazil Chile Colombia Mexico Peru Italy Small Luxembourg Netherlands Large Netherlands Small Norway Poland Portugal Romania Russia & Kazakhstan Spain Large Spain Small Sweden Large Sweden Small Switzerland Large Switzerland Small Turkey UK Large UK Small Regional Industry Factor List US Europe Japan Asia ex Japan Latin America Natural Resources Aerospace & Defense Industrials & Aerospace Industrials Banking 8

10 Regional Industry Factor List US Europe Japan Asia ex Japan Latin America Natural Resources Capital Markets Diversified Financials Insurance Building & Construction Real Estate Consumer Discretionary Consumer Staples Retailers Energy Equipment & Services Hardware & Software Hardware & Technology Hardware & Telecoms Software & IT Services Telecom Services Biotech & Pharma Health Care Health Care, Biotech & Pharma Materials Metals & Mining Other Materials Transport Utilities Statistical Factor List Statistical Factor 1 Statistical Factor 3 Statistical Factor 2 Statistical Factor 4 9

11 Style Factor Definitions Dividend Yield Current Value Growth Trend Growth Momentum Short-term Momentum Long-term Momentum Leverage Liquidity Quality Captures the return component due to each stock's exposure to Dividend Yield, defined as the Dividends per share paid over the past year as a percentage of the current stock price. Captures the return component due to each stock's exposure to Current Value, defined as the average of normalised Book to Price, Cash-flow to Price, and Earnings to Price. Captures the return component due to each stock's Growth, defined as the average of normalised Earnings Growth, Sales Growth, and Book Value Growth Captures the return component due to each stock's exposure to changes in its rate of Growth, defined as the average of Earnings Momentum, Sales Momentum, and Book Value Momentum Captures the return component due to each stock's Price Momentum over the last month, defined as the regression slope of standardized stock prices over the past 21 trading days. Captures the return component due to each stock's Price Momentum over the last year, defined as the regression slope of standardized stock prices at the beginning of each of the past 13 4-week periods Captures the return component due to each stock's exposure to financial Leverage, defined as the ratio of Total Debt to (Total Assets - Total Debt). Captures the return component due to each stock's exposure to Liquidity, defined as the ratio of Time-weighted Volume over the past 2 weeks to Average Quarterly Volume Captures the return component due to each stock's exposure to Quality, defined as the average of normalised Sustainable Growth, Cash Flow to Sales, Return on Equity and Return on Assets. 10

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