Bayesian Risk Forecasting

May 4, 2019

Portfolio risk forecasting is subject to great parameter uncertainty, particularly for longer forward horizons. This simply reflects that large drawdowns are observed only rarely, making it hard to estimate their ‘structural’ properties. Bayesian forecasting addresses parameter uncertainty directly when estimating risk metrics, such as Value-at-Risk or Expected Shortfall, which depend on highly uncertain tail parameters. Also, the Bayesian risk forecasting method can use ‘importance sampling’ for generating simulations that oversample the high-loss scenarios, increasing computational efficiency. Academic work claims that Bayesian methods also produce more accurate risk forecasts for short- and long-term horizons.

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The implicit subsidies behind simple trading rules

April 27, 2019

Implicit subsidies are premia paid by large financial markets participants for reasons other than risk-return optimization (view post here). Their estimation requires skill and a strong “quantamental system”. However, implicit subsidies are behind the popularity and temporary success of many simple trading rules, including those based on variance risk premia, contract hedge value, short volatility bias, and “low-risk effects”. The closest link is between implicit subsidies and cross-asset carry. However, carry is not itself a reliable measure of a subsidy but just correlated with it and – at best – a starting point for estimation The distinction between subsidy and conventional carry is essential for actual long-term value generation of related trading strategies.

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Implicit subsidies paid in financial markets: updated primer

April 20, 2019

Implicit subsidies in financial markets are premia paid through transactions that have motives other than conventional risk-return optimization. They manifest as expected returns over and above the risk-free rate and conventional risk premia. Implicit subsidies are a bit like fees for the service of compliant positioning. They are opaque rather than openly declared, typically for political reasons. Implicit subsidies have valid motives, such as financial stabilization objectives of governments, profit hedging of commodity producers, or downside protection of institutional portfolios. Detecting and receiving implicit subsidies is challenging and information-intensive but creates stable risk-adjusted value. Implicit subsidies are receivable in all major markets, albeit often at the peril of crowded positioning and recurrent setbacks. It is critical to distinguish strategies based on implicit subsidies, which actually create investor value through information efficiency and those that simply receive non-directional risk premia, which are based on rough proxies and do not create risk-adjusted value.

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The duration extraction effect

April 13, 2019

Under non-conventional monetary policy central banks influence financial markets through the “portfolio rebalancing channel”. The purchase of assets changes the structure of prices. A particularly powerful portfolio rebalancing effect arises from duration extraction, i.e. the combined size expansion and duration extension of the assets that have been absorbed onto the central bank’s balance sheet. Duration extraction has a significant and persistent impact on the yield curve and the exchange rate. Importantly, the effect arises from hints or announcements of new parameters for the future stock of assets. Given the large size of central bank balance sheets, this explains why changes in expected asset purchases, re-investments or redemption plans have a profound impact on financial markets.

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Tiered reserve systems

April 6, 2019

Negative monetary policy rates can undermine financial transmission, because they encourage cash hoarding and reduce the profitability of traditional banking. This danger increases with depth and duration of negative interest rate policies. Therefore, some countries (Japan, Sweden, Switzerland, and Denmark) have introduced tiered reserve systems, effectively exempting a part of the banking system’s excess reserves from negative rates. Importantly, a tiered reserve system is now also considered by the European Central Bank for the second largest currency area in the world. Since tiered reserve systems are on the verge of “going mainstream” their impact on asset pricing formulas and quantitative trading strategies deserves careful consideration.

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Survival in the trading factor zoo

March 30, 2019

The algorithmic strategy business likes quoting academic research to support specific trading factors, particularly in the equity space. Unfortunately, the rules of conventional academic success provide strong incentives for data mining and presenting ‘significant’ results. This greases the wheels of a trial-and-error machinery that discover factors merely by the force of large numbers and clever fitting of the data: some 400 trading factors have so far been published in academic journals (called the “factor zoo”). The number of unpublished and rejected tested factors is probably a high multiple of that. With so many tryouts, conventional significance indicators are largely meaningless and misleading. As with the problem of overfitting (view post here), the best remedies are plausible mathematical adjustments and reliance upon solid prior theory.

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Signaling systemic risk

March 23, 2019

Systemic financial crises arise when vulnerable financial systems meet adverse shocks. A systemic risk indicator tracks the vulnerability rather than the shocks (which are the subject of ‘stress indicators’). A systemic risk indicator is by nature slow-moving and should signal elevated probability of financial system crises long before they manifest. A recent ECB paper proposed a practical approach to building domestic systemic risk indicators across countries. For each relevant categories of financial vulnerability, one representative measure is chosen on the basis of its early warning qualities. The measures are then normalized and aggregated linearly. In the past, aggregate systemic risk indicators would have shown vulnerability years ahead of crises. They would also have indicated the depth of ensuing economic downturns.

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How to estimate risk in extreme market situations

March 16, 2019

Estimating portfolio risk in extreme situations means answering two questions: First, has the market entered an extreme state? Second, how are returns likely to be distributed in such an extreme state? There are three different types of models to address these questions statistically. Conventional “extreme value theory” really only answers the second question, by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. “Extreme value mixture models” simultaneously estimate the threshold for extreme distributions and the extreme distribution itself. This method seems appropriate if uncertainty over threshold values is high. Finally, “changepoint extreme value mixture models” even go a step further and estimate the timing and nature of changes in extreme distributions. The assumption of changing extreme distributions across episodes seems realistic but should make it harder to apply the method out-of-sample.

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The dollar as barometer for credit market risk

March 9, 2019

The external value of the USD has become a key factor of U.S. and global credit conditions. This reflects the surge in global USD-denominated debt in conjunction with the growing importance of mutual funds as the ultimate source of loan financing. There is empirical evidence that USD strength has been correlated with credit tightening by U.S. banks. There is also evidence that this tightening arises from deteriorating secondary market conditions for U.S. corporate loans, which, in turn, are related to outflows of credit funds after USD appreciation. The outflows are a rational response to the negative balance sheet effect of a strong dollar on EM corporates in particular. One upshot is that the dollar exchange rate has become an important early indicator for credit market conditions.

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How salience theory explains the mispricing of risk

March 2, 2019

Salience theory suggests that decision makers exaggerate the probability of extreme events if they are aware of their possibility. This gives rise to subjective probability distributions and undermines conventional rationality. In particular, salience theory explains skewness preference, i.e. the overpricing of assets with a positive skew and the under-pricing of contracts with a negative skew. There is ample evidence of skewness preference, most obviously the overpayment for insurance contracts and lottery tickets. In financial markets, growth stocks with positively-skewed expected returns have historically been overpriced relative to value stocks. This is important for macro trading. For example, a specific publicly discussed disaster risk should pay an excessive premium, and short-volatility strategies in times of fear of large drawdowns for the underlying should have positive expected value.

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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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