VIX term structure as a trading signal

June 23, 2018

The VIX futures curve reflects expectations of future implied volatility of S&P500 index options. The slope of the curve is indicative of expected volatility and uncertainty relative to volatility and uncertainty priced in the market at present. Loosely speaking, a steeply upward sloped VIX futures curve should be indicative of present market complacency, while an inverted downward sloped curve should be indicative of present market panic and capitulation. In both cases the slope of the curve would serve as a contrarian indicator for market directional positions. An empirical analysis for 2010-2017 suggests that an inverted VIX curves has had a significant positive relation with subsequent S&P500 returns. Normal VIX curves, however, did not have significant predictive power, possibly because a market can stay complacent longer than it can panic.

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FX carry strategies (part 1)

June 9, 2018

FX forward-implied carry is a valid basis for investment strategies because it is related to policy subsidies and risk premia. However, it also contains misdirection such as rational expectations of currency depreciation. To increase the signal-noise ratio FX carry should – at the very least – be adjusted for expected inflation differentials and external deficits. Even with such plausible adjustments FX carry is a hazardous signal for directional trades because it favours positions with correlated risks and great sensitivity to global equity markets. By contrast, relative adjusted carry has been a plausible and successful basis for setting up relative normalized carry trades across similar currencies. It has historically produced respectable Sharpe ratios and low directional risk correlation. Such strategies seem to generate alpha and exploit alternative risk premia alike.

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Using yield curve information for FX trading

May 12, 2018

FX carry trading strategies only use short-term interest rates (and forward basis) as signal. Yet both theoretical and empirical research suggests that the whole relative yield curve contains important information on monetary policy and risk premia. In particular, the curvature of a yield curve indicates – to some extent – the speed of adjustment of the short rate towards a longer-term yield. Since relative curvature between two countries is therefore a measure of the relative trajectory of monetary policy it is a valid directional signal for FX trading. Indeed, recent empirical research suggests that this signal is statistically significant. A curvature-based trading rule produces higher Sharpe ratios and less negative skewness than conventional FX carry strategies.

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Fixed income carry as trading signal

April 28, 2018

Empirical evidence for 27 markets suggests that carry on interest rate swaps has been positively correlated with subsequent returns for the past two decades. Indeed, a naïve strategy following carry as signal has produced respectable risk-adjusted returns. However, this positive past performance masks the fundamental flaw of the carry signal: it disregards the expected future drift in interest rates and favours receiver position in markets with very low real rates. In the 2000s and 2010s this oversight mattered little because inflation and yields drifted broadly lower. If the inflation cycle turns or just stabilizes, however, short-term rates normalization should become very consequential. Indeed, enhancing the IRS carry signal by a plausible medium term drift in short rates has already in the past produced more stable returns and more convincing actual “alpha”.

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The correlation risk premium

April 21, 2018

The correlation risk premium is a premium for uncertainty of future correlation of securities among each other or with a benchmark. A rise in correlation reduces diversification benefits. The common adage that in a crash ‘all correlations go to one’ reflects that there is typically not much diversification in large market downturns and systemic crises, except through outright shorts. Correlation risk premia can be estimated based on option prices and their implied correlation across stocks. There is evidence that these estimates are useful predictors for long-term individual stock performance, over and above the predictive power of variance risk premia.

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The passive investment boom and its consequences

March 31, 2018

Passive investment vehicles have been expanding rapidly over the past 10 years, with assets reaching about USD8 trillion or 20% of aggregate investment funds last year. ETFs alone now account for 14% of fund assets. Beyond, the share of informal passive investing, such as ‘closet indexing’, is probably even larger. The plausible consequences of the passive investment boom include [i] less information efficiency of markets, [ii] greater incentive for low-quality issuance and corporate leverage, [iii] greater price correlation across securities, and [iv] stronger transmission of financial shocks into emerging economies.

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Interest rate swap returns: empirical lessons

March 17, 2018

Interest rate swaps trade duration risk across developed and emerging markets. Since 2000 fixed rate receivers have posted positive returns in 26 of 27 markets. Returns have been positively correlated across virtually all countries, even though low yield swaps correlated negatively with global equities and high-yield swaps positively. IRS returns have posted fat tails in all markets, i.e. a greater proclivity to outliers than would be expected from a normal distribution. Active volatility management failed to contain extreme returns. Relative IRS positions across countries can be calibrated based on estimated relative standard deviations and allow setting up more country-specific trades. However, such relative IRS positions have even fatter tails and carry more directional risk. Regression-based hedging goes a long way in reducing directionality, even if risk correlations are circumstantial rather than structural.

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Directional predictability of daily equity returns

March 3, 2018

A new empirical paper provides evidence that the direction of daily equity returns in the Dow Jones has been predictable over the past 15 years, based on conventional short-term factors and out-of-sample selection and forecasting methods. Hit ratios have been 51-52%. The predictability has been statistically significant and consistent over time. Trading returns based on forecasting have been economically meaningful. Simple forecasting methods have outperformed more complex machine learning.

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Information inefficiency in market experiments

February 3, 2018

Experimental research illustrates the mechanics of market inefficiency. If information is costly traders will only procure it to the extent that markets are seen as inefficient. In particular, when observing others’ investment in information, traders will cut their own information spending. Full information efficiency can never be reached. Moreover, business models that invest heavily in information may have higher trading profits, but still earn lower overall profits due to the costs of improving their signals. What seems crucial is high cognitive reflection so as to invest in relevant information where or when others do not.

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Clues for estimating market beta

January 6, 2018

A new empirical paper compares methods for estimating “beta”, i.e. the sensitivity of individual asset prices to changes in a broad market benchmark. It analyzes a large range of stocks and more than 50 years of history. The findings point to a useful set of initial default rules for beta estimation: [i] use a lookback window of about one year, [ii] apply an exponential moving average to the observations in the lookback window, and [iii] adjust the statistical estimates by reasonable theoretical priors, such as the similarity of betas for assets with similar characteristics.

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asset management Asset Purchase Program banks bond returns bond yields bubbles capital regulation carry China collateral commodities credit returns default ECB economic data EM equity returns euro area crisis Fed financial crisis FX FX interventions FX returns government debt government deficits herding inflation information insurances Japan leverage liquidity machine learning market turmoil price factors regulation risk management shadow banking statistical methods term structure trend following variance risk premium VIX volatility ZLB
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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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