Using SVAR for macro trading strategies

January 21, 2017

Structural vector autoregression may be the most practical model class for empirical macroeconomics. Yet, it can also be employed for macro trading strategies, because it helps identifying specific market and macro shocks. For example, SVAR can identify short-term policy, growth or inflation expectation shocks. Once a shock is identified it can be used for trading in two ways. First, one can compare the type of shock implied by markets with the actual news flow and detect fundamental inconsistencies. Second, different types of shocks may entail different types of subsequent asset price dynamics and may, hence, be a basis for systematic strategies.

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The importance of statistical programming for investment managers

November 1, 2016

Almost every portfolio manager uses some form of quantitative analysis. Most still rely on Excel spreadsheets, but this popular tool constrains the creativity of analysis and struggles to cope with large data sets. Statistical programming in R and Python both facilitates and widens the scope of analysis. In particular, it allows using high-frequency data, alternative data sets, textual information and machine learning. And it greatly enhances the display and presentation of analytical findings.

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The impact of U.S. economic data surprises

October 29, 2016

A new paper estimated the short-term effects of U.S. economic data surprises on treasury notes and USD exchange rates over the past 20 years. All of 21 commonly followed data releases produced highly significant surprise effects at least for parts of the sample. However, only non-farm payrolls produced a consistently highly significant impact. After short-term interest rates reached the zero lower bound, the importance of surprises to CPI inflation, housing indicators and weekly jobless claims increased noticeably, possibly related to the Fed’s struggle with its dual mandate.

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The dominance of price over value

October 1, 2016

Market prices reveal information about fundamental value indirectly. Private research produces information about fundamental value directly. Neither is a perfect indicator of fundamental value: the former due to non-fundamental market factors, and the latter due to limitations of private research. However, plausible theoretical research shows that overtime the information content of prices in respect to (known) fundamentals improves faster due to aggregation and averaging. When this happens investors rationally neglect their own fundamental research. This can erode information efficiency of the market and lead to sustained misalignments if the market as a whole misses key risks and value factors.

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Selecting macro factors for trading strategies

September 17, 2016

A powerful statistical method for selecting macro factors for trading strategies is the “Elastic Net”. The method simultaneously selects factors in accordance with their past predictive power and estimates their influence conservatively in order to contain the influence of accidental correlation. Unlike other statistical selection methods, such as “LASSO”, the “Elastic Net” can make use of a large number of correlated factors, a typical feature of economic time series.

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What made FOMC members hawkish or dovish?

September 14, 2016

An empirical analysis based on transcripts of the U.S. Federal Open Market Committee from 1994 to 2008 suggests that differences in committee members’ policy differences can partly be explained by differences in regional data, particularly unemployment rates. Also, personal background may play some role: FOMC members with experience in the non-financial private and public sectors have historically been more dovish.

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The importance of differentiating types of oil price shocks

August 13, 2016

To assess the consequences of an oil price shock for markets it is important to identify its type. A new method separates oil supply shocks, oil market-specific demand shocks and global growth shocks. Supply shocks have accounted for about 50% of price volatility since the mid-1980s. Oil market-specific shocks drive a wedge between the growth of developed and emerging economies and hence matter for exchange rate trends. Global demand shocks to oil prices do not cause such a divergence.

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Sticky expectations and predictable equity returns

July 23, 2016

New research documents that company earnings expectations of analysts have historically been sticky, plausibly reflecting that it takes time and effort to update forecasts. Such stickiness can explain two important anomalies of stock returns: price momentum and outperformance of high-profitability stocks. Indeed, these two anomalies have been correlated and stronger for stocks where analyst expectations have been stickier.

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Why fund managers share trade ideas

June 25, 2016

Through sharing research and ideas fund managers can increase both the number and quality of their trading strategies. Empirical evidence suggests that managers share ideas particularly with peers that have both the ability and the intention to provide useful feedback. This implies that portfolio managers’ communication and good intentions are critical for their success in a network of idea generation.

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How to measure economic uncertainty

March 19, 2016

Measures of economic uncertainty help investors to track popular fear or complacency for the purpose of trading strategies. Academic papers propose various methods: keyword frequencies in news, equity market volatility, earnings forecast dispersion and economic forecast disagreements. Composite measures suggest that uncertainty typically rises abruptly but declines just gradually.

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Macrosynergy is a London based macroeconomic research and technology company whose founders have developed and employed macro quantamental investment strategies in liquid, tradable asset classes, across many markets and for a variety of different factors to generate competitive, uncorrelated investment returns for institutional investors for two decades. Our quantitative-fundamental (quantamental) computing system tracks a broad range of real-time macroeconomic trends in developed and emerging countries, transforming them into macro systematic quantamental investment strategies. In June 2020 Macrosynergy and J.P. Morgan started a collaboration to scale the quantamental system and to popularize tradable economics across financial markets.

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