Because the financial markets are very complex no single indicator, even a combination of indicators can capture all the different driving factors and events which affect future market behaviour. Therefore the iQ-FOXX Index Methodology aims to categorise forecast indicators that are intuitive and aid the common understanding of causal relationships between the future market movements and their driving factors. By combining information from different sources, such as macroeconomic, fundamental and technical variables the iQ-FOXX Index Methodology gives non-correlated perspectives to future market movements and generates very powerful iQ-FOXX Indicators Models. In addition to the use of non-correlated variables it is the diversification among the forecast algorithms which makes an iQ-FOXX Indicators Model to generate consistent and superior above-average returns over medium to long term.
Depending on the underlying market an iQ-FOXX Indicators Model is based on five to seven forecast indicators, which in conjunction give a good indication for future market movements. The forecast indicators are aggregated according to rules-based framework to give a composite signal for future market movements. Each of the forecast indicators adds a different angle to the overall view on the market. None of the forecast indicators is superior to their combination. Within one forecast indicator two or more variables which have a low correlation with each other and add incremental value to the overall indicator’s signal are grouped together.
An iQ-FOXX Indicator Model is based on causal and stable relationships between an underlying market and its influencing factors. Only influencing factors based on real experience which aid the understanding of the underlying market and give a reason for a forecast signal to work, rather than relying solely on the empirical results are taken into consideration. Every forecast indicator which is used in an iQ-FOXX Indicators Model offers behavioural reason for why it should work and support future model performance. All indicators are selected based on rigorous out-of-sample analyses and live track-record which provide reassurance that every indicator should be robust in the future.
iQ-FOXX Indicators Models
Selection of the influencing factors for an underlying market.
Quantifying the quality of the influencing factors and calculation of the iQ-FOXX forecast indicators.
Rules-based aggregation of the iQ-FOXX forecast indicators to a composite forecast signal which determines the exposure to the underlying market.
Selection of influencing factors for an underlying market
Only very liquid markets across equity, bond, commodity and FX are considered as eligible underlying markets for an iQ-FOXX index. Definition and selection of the driving factors responsible for the future price movements of a specific underlying market is very important. Over a decade we have built expertise and Know-How in selecting influencing factors from macroeconomic, fundamental and technical variables. Influencing variables which do not depend on the price movement of the underlying market are known as exogenous or explicit variables. Hence, all macroeconomic and fundamental variables are exogenous variables. Many technical variables are well known as implicit or endogenous because by definition they depend on the price of the underlying market.
give important information about the future behaviour of the overall economy rather than of a particular industry sector. The main purpose for using macroeconomic variables is to characterise the current state of the economy in the economic circle and to measure the corresponding behaviour of the underlying market. This is very helpful for the creation of iQ-FOXX forecast indicators which formulate expectations about the future behaviour of the underlying market according to the expected state of the economy. Therefore, the influencing factors extracted from macroeconomic variables provide mid-term to long-term insight about future price movements of the underlying market. Important macroeconomic variables include inflation, unemployment, industrial production, purchasing manager indices, leading indices, business and consumer expectations, consumer confidence, retail sales, GDP and current account balance.
show an empirical evidence for a causal fundamental relationship to the underlying market. The basic premise is that all financial markets are related in some way. We strongly believe that any important market move should be caused by underlying fundamental factors. For example, the future market is fundamentally linked to the cash market by short term interest rates, the dividend yield and the number of days until expiry of the corresponding future contract. The equity market is influenced by the direction of interest rates. During recessions bonds rise while equities fall. The opposite is true in an inflationary environment, bonds fall while equities rise. Bonds move in the opposite direction of the interest rates and are usually influenced by commodities. Hence, the driving fundamental factor is the expected inflation. A strong USD usually has a negative impact on most of the commodities. Therefore currencies tend to be leading fundamental drivers of commodities. Commodities tend to be the fundamental driver for bonds. Bonds and market sentiment influence equities. These fundamental relationships may vary on occasion, but they are always present. Extracting information about such fundamental relationships helps to understand what is going on in one market and what is likely to be the reaction in other market(s). The main purpose for using fundamental variables is to characterise the features of the underlying market and to extract the fundamental influencing factors for future market movements. This is very helpful in order to measure sentiment and to quantify important fundamental relationships between the underlying market and various asset classes and industry sectors. The iQ-FOXX forecast indicators based on fundamental variables give a very good inside about the mid-term future behaviour of the underlying market. Important fundamental variables include traders’ net positions, put/call and price/earnings ratios, open interest, interest rates, exchange rates, commodities, equities, sectors, credit default swaps, and net inflows.
are derived from observing the characteristics of market movements along certain dimensions such as trend, physiology, volume and volatility. Technical variables aim to identify trends and reversals in early stages of their development. Therefore they are very helpful to identify trending-up, trending-down, turning points, or sideways-trading markets. Because many markets have built-in economic and fundamental relationships and react to similar economic and fundamental factors, technical variables may give additional non-correlated and very valuable information to the future direction of the underlying market.
Quantifying the quality of the selected influencing variables and calculation of iQ-FOXX forecast indicators
The iQ-FOXX Index Methodology applies three different methods to quantify the importance of the selected influencing variables in accurately predicting the future market movements. Every method has its strengths based on its nature and its different assumptions about the properties of the influencing factors and their relationship to the underlying market.
Multivariate Regression Forecasting
The first method for quantifying the quality of the influencing factors is Multivariate Regression Forecasting. This method is well-known and commonly used in finance, but also in statistics and econometrics. It has its origin in the Arbitrage Pricing Theory (APT) developed by Ross in 1976 as an alternative to the Capital Asset Pricing Model (CAPM). Ross proposed a set of macroeconomic factors, which explain stock returns. This explicit macro-factor model was extended by an implicit factor model based on Principal Component Analysis presented by Roll/Ross (1980) and Factor Analysis presented by Chen (1983), and by several explicit micro-factor models such as the Fama-French three-factor model (1993). The mathematical framework of multivariate econometric models is extremely well described in the literature with emphases on statistics, econometrics and mathematics. As the name suggests this method quantifies the importance of the multiple exogenous variables which can consists of macroeconomic, fundamental as well as endogenous technical variables in relation to the underlying market. iQ-FOXX uses Auto Regressive Moving Average Models with Exogenous variables (ARMAX) with 5-8 influencing factors which separately and in conjunction with each other show significant predictability of the future movements of the underlying market.
Univariate Rules-based Forecasting
The second method has its origin in the Capital Asset Pricing Model (CAPM) developed by Jack Treynor, William F. Sharpe, John Lintner and Jan Mossin in the early 1960s which also is commonly used in finance. The CAPM is well-known as a single factor model which implies that future movements of a security are driven by just one factor – the market risk. The iQ-FOXX univariate rules-based forecasting extends the number of factors to maximum eight – yield, inflation, currency, sentiment, expectations, economy, industry and risk. This method is based on a univariate regression and bivariate correlation framework which analyses the inter-market relationships between the underlying market and the influencing exogenous and endogenous variables. It provides valuable information about the future mid- to long-term market movements. It does not tell anything about the right level of the underlying market at any point of time, but it helps to understand how the underlying market will probably behave as a function of its causal relationships to other markets. As the name suggests the forecast signals are generated by rules, which are derived from financial theories and applied empirical research.
The third method uses a technical forecast technics for quantifying the predicting power of technical variables. It is the oldest and the most widely used method for analysing and trading securities. At the beginning of 20th century the “Dow Theory” which is a classic form of technical analysis was published by Charles H. Dow. The concept of technical analysis became very popular during the late 1920’s. Since 1970’s hundreds of books and research papers have been published introducing a huge variety of technical indicators and charting tools. Technical forecasting assumes that prices of risky assets have already discounted all available fundamental and macroeconomic information. Therefore it uses historical open, high, low and close prices, volume, open interest and volatility of the underlying market and aims to:
- detect reversals and trends in an early stage,
- identify market phases, cycles for bear and bull markets, trading patterns, and overbought vs. oversold market conditions,
- determine target-, support- and resistance-levels and trading ranges,
- measure relative strength, convergence and divergence as well as buying or selling power.
Compared to the Multivariate Regression Forecasting and to the Univariate Rules-based Forecasting, Technical Forecasting gives a very valuable and non-correlated view of the future market movements. iQ-FOXX has developed a range of innovative forecast indicators for identification of market phases, detection of market reversals or market continuations and measurement of market uncertainty.
Rules - based aggregation of the iQ-FOXX Forecast Indicators to a forecast signal which determines the exposure to the underlying market
The major difficulty of any rules-based methodology is to recognise when the underlying market is not trending and when it has reached a support or resistance level. Hence the major problem is its failure to anticipate market reversals. Therefore one of the greatest challenge is to preserve capital during non-trending periods. Because majority of rules-based methodologies are trend-following and backward looking they ride with the trend until it turns. The design of a rules-based methodology is very crucial for the achievement of superior above-average index performance in the future. In other words, turning trading ideas into a set of objective rules is much more difficult than one would expect. iQ-FOXX Index Methodology goes through the following six steps in order to determine the dynamic exposure to the underlying market:
- identification of the market environment,
- identification of a market reversal or a market pull-back,
- measurement of the market uncertainty,
- selection of the forecast signal,
- determination of the leverage factor,
- determination of the exposure to the underlying market.
Identification of the market environment – iQ-FOXX Market Phase Forecast Indicator
The first objective of the iQ-FOXX Index Methodology is to identify the market environment of the underlying market. The iQ-FOXX Market Phase Forecast Indicator aims to identify whether the market is in a trending-up, a trending-down or a sideways-trading phase. This indicator plays a very important role in the overall iQ-FOXX rules-based framework. It acts like a switch between three possible paths of a virtual decision tree and determines which of the Market Directional Forecast Indicators should be used in this market environment. The first categorisation of the market phase aims to identify which influencing factors are likely to drive future market movements. Usually, markets tend to be influenced by fundamental and macroeconomic variables in trending-up markets. In trending-down and sideways markets technical factors tend to drive future market movements.
Identification of a market reversal or a pull-back – iQ-FOXX Transition Forecast Indicator
Important changes in trend usually require a period of transition. It is very difficult to identify a trend reversal during a transition period. Very often sideways market indicates a consolidation in the existing trend after which the original trend is continued. During transition periods markets face resistance after an overshooting or are looking for support after a reversal has taken place. The iQ-FOXX Transition Forecast Indicator aims to identify whether an important reversal in trend is likely to take place or after a short pull-back the existing trend is likely to resume. This indicator aims to detect turning points at an early stage and is a very important complementary indicator to the iQ-FOXX Market Phase Forecast Indicator which is not in a position to identify transition periods.
Measuring market uncertainty – iQ-FOXX Market Neutral Forecast Indicator
One of the most crucial parts of a rules-based methodology is the control of down-side risk. To avoid losses, to reduce draw-downs and to let profits running is easy to be said, but very difficult to implement. The risks related to the underlying market could be manifold. To measure market uncertainty caused by specific internal, but also external factors is very important for preserving capital. Many causal fundamental relationships and established correlations between the underlying market and the influencing factors brake down in periods with increased market uncertainty. This leads to non-normal and irrational market behaviour. In such non-normal environment markets tend to overreact to new information which increases the market volatility. As a consequence, the predicting accuracy and reliability of forecast signals is reduced, which requires many systematic models to be redesigned and adjusted. iQ-FOXX Market Neutral Forecast Indicator aims to identify risks associated with the current and future movements of the underlying market in order to set exit and entry points.
Selection of the forecast signal – iQ-FOXX Market Direction Forecast Indicators
We believe that a very important part of a rules-based methodology is its ability to anticipate future market movements. We believe that diversity among methods, influencing factors and time frames is the key for superior above-average performance results. Based on this philosophy iQ-FOXX Index Methodology applies three different and non-correlated Market Direction Forecast Indicators based on three different forecast methods. Each of these indicators aims to correctly predict future market movements based on its own specific assumptions about the characteristics of the underlying market. The iQ-FOXX Market Direction Forecast Indicator I is generated by the multivariate regression method based on information contained in exogenous macroeconomic and fundamental as well as endogenous technical variables. The accuracy of this forecast signal is above the average in trending-up markets. Its reliability usually decreases in transition periods and trending-down markets. The iQ-FOXX Market Direction Forecast Indicator II is generated by the univariate rules-based method which quantifies macroeconomic, fundamental and technical influencing factors. This forecast signal is very reliable during trending-up markets. Its forecast accuracy usually is reduced in sideways-trading and trending-down market environment. Many fundamental and economic relationships do not hold in a market environment with high uncertainty, market volatility and irrational behaviour. The iQ-FOXX Methodology aggregates the Market Direction Forecast Indicator I and the Market Direction Forecast Indicator II into a composite forecast signal in trending-up market environment. The forecast signal of the iQ-FOXX Market Direction Forecast Indicator III is generated by the technical forecasting method based on technical factors. It has an above average accuracy in trending-down markets and it is very reliable in sideways-trading markets during transition periods.
Determining the leverage – iQ-FOXX Leverage Indicator
The reliability and accuracy of any rules-based Methodology usually vary between different market phases. It is obvious that to predict reversals of an existing trend and to time sideways-trading markets is an extremely hard job. The accuracy of iQ-FOXX forecast signals is more robust and reliable in trending-up markets. The iQ-FOXX Leverage Indicator aims to systematically apply dynamic leverage only for a long exposure to the underlying market in a trending-up market environment by tacking into account the accuracy of the forecast signals.
Determining the exposure to the underlying market – iQ-FOXX Forecast Signal
The final stage of the iQ-FOXX Methodology is to generate the iQ-FOXX Forecast Signal which determines the exposure to the underlying market. The rules-based combination of the iQ-FOXX Market Phase Forecast Indicator, the iQ-FOXX Transition Forecast Indicator, the iQ-FOXX Market Neutral Forecast Indicator, the three iQ-FOXX Market Direction Forecast Indicators and the iQ-FOXX Leverage Indicator generates the iQ-FOXX Forecast Signal.
iQ-FOXX Methodology applies a diversity of influencing factors and methods aiming to characterise the properties of the underlying market. Our objectives are to better understand the market behavior, to anticipate the market reaction according to influencing factors, to predict correctly future market movements more than 60% of the time and to achieve a superior above-average return over a medium to long term horizon.
Index descriptions and index rules documentation for all iQ-FOXX Indices is available upon . If you are a current customer and require assistance, please click here. You can download an example of an index description and index rules documentation below.
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