Measuring non-conventional monetary policy surprises

March 18, 2017

A new paper proposes a measure for monetary policy surprises that arise from asset purchases and forward guidance. The idea is to estimate the change in the first principal component of government bond yields at different maturities to the extent that it is independent of changes in the policy reference rate and on days of significant policy statements. Such identified non-conventional policy shocks have had a persistent impact on yield curves and exchange rates since 2000. Their monitoring is important for so-called “long-long” risk parity trades.

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Cash hoarding and market dynamics

March 11, 2017

Institutional asset managers can aggravate market swings due to the pro-cyclicality of redemptions, internal leverage and cash positions. A new empirical analysis shows that cash hoarding, a rise in funds’ cash positions in times of redemptions, is the norm. Cash hoarding seems to be particularly pronounced in less liquid markets and is a rational response if fire sale haircuts are prone to escalate with growing flows, i.e. if liquidating late is disproportionately costly. Investment opportunities arise initially from timely positioning and subsequently from the detection of flow-driven price distortions.

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Fake alpha

March 4, 2017

Statistical alpha can be divided into fake alpha, which is a premium for non-directional systematic risk, and true alpha, which reflects the quality of the investment process. Fake alpha arises from exposure to conventional factors that are not correlated with the market portfolio. Failing to distinguish fake and true alpha can be costly for investors and strategy developers. Fake alpha is easy and cheap to produce and after periods of high risk premia on conventional factors it can post impressive performance statistics (or backtests). Subsequently, investors overload on managers or strategies that use these factors and related performance inevitably deteriorates. This goes some way in explaining the negative historic alpha on actively managed funds.

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Equity alpha through volatility targeting

February 25, 2017

Volatility targeting has historically enhanced the statistical alpha of standard equity strategies. That is because volatility is more predictable in the short-term than returns. Thus, Sharpe ratios tend to decline, when volatility rises. Expected returns increase after turmoil but only overtime, when volatility might already be subsiding. On its own volatility is not a pure measure of risk premia and does not indicate if actual risk is overstated or underappreciated. A flipside of mechanical volatility targeting is that it contributes to herding and escalatory price dynamics.

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Volatility risk premia and FX returns

February 18, 2017

Volatility risk premia – differences between implied and realized volatility – are plausible and empirically validated predictors of directional foreign exchange returns, particularly for EM currencies. The intuition is that excess implied volatility typically results from elevated risk aversion, which should be indicative of undershooting. When calculating the volatility risk premium it is important to compare short-term implied volatility with realized volatility of that same period. One would expect positive returns on currencies whose very recent volatility has been less than feared.

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Lessons from long-term global equity performance

February 11, 2017

A truly global and long-term (116 years) data set for both successful and failed financial markets shows that equity has delivered positive long-term performance in each and every country that did not expropriate capital owners, even those that were ravaged by wars. Also, equity significantly outperformed government bonds in every country, with a world average annual return of 5% versus 1.8%. The long-term Sharpe ratio on world equity has been 0.24 versus 0.09 for bonds. Valuation-based strategies for market timing have historically struggled to improve equity portfolio performance. Active management strategies that rely on both valuation and momentum would have been more useful.

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Statistical remedies against macro information overload

February 4, 2017

“Dimension reduction” condenses the information content of a multitude of data series into small manageable set of factors or functions. This reduction is important for forecasting with macro variables because many data series have only limited and highly correlated information content. There are three types of statistical methods.The first type selects a subset of “best” explanatory variables (view post here). The second type selects a small set of latent background factors of all explanatory variables and then uses these background factors for prediction (Dynamic Factor Models). The third type generates a small set of functions of the original explanatory variables that historically would have retained their explanatory power and then deploys these for forecasting (Sufficient Dimension Reduction).

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Debt-weighted exchange rates

January 28, 2017

Trade-weighted exchange rates help assessing the impact of past currency depreciation on economic growth through the external trade channel. Debt-weighted exchange rates help assessing the impact of past currency depreciation on economic growth through the financial channel. Since these effects are usually opposite looking at both simultaneously is crucial for using exchange rate changes as a predictor of economic and local market performance. For example, as a consequence of the financial channel many EM economies fail to benefit from currency depreciation in the way that small developed economies do.

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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 power and origin of uncertainty shocks

January 14, 2017

Uncertainty shocks are changes in beliefs about probabilities. They are perhaps the most powerful driver of financial markets. Uncertainty comes in various forms, such as macro uncertainty, firm-specific uncertainty and uncertainty about others’ beliefs. However, empirical and theoretical research suggests that different types of relevant uncertainty shocks have one common dominant origin: updated beliefs about disaster risk. Hence, when markets give greater probability of downside tail risks, all sorts of uncertainty would rise, with a profound impact on macro trading strategies, whether they are directional or based on relative value.

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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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