Market noise

June 1, 2019

The term “market noise” refers to transactions that are erratic and unrelated to fundamental value. Theory suggests that without market noise profitable trading would be impossible. Yet, while irrational and erratic trading may occur, most of what we call “noise” reflects rationality disguised by complexity. Illustrating that point, a new paper shows that the effect of rebalancing cascades on the net demand for individual assets is not predictable, even if we know everything about the underlying rules and if they are fully rational. Predictions become infeasible because of alternating buy and sell orders, feedback loops and threshold-based execution rules. This cautions against dismissing seemingly non-fundamental market flows as irrational and betting against them.

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U.S. Treasuries: decomposing the yield curve and predicting returns

May 25, 2019

A new paper proposes to decompose the U.S. government bond yield curve by applying a ‘bootstrapping method’ that resamples observed return differences across maturities. The advantage of this method over the classical principal components approach would be greater robustness to misspecification of the underlying factor model. Hence, the method should be suitable for bond return predictions under model uncertainty. Empirical findings based on this method suggest that equity tail risk (options skew) and economic growth surveys are significant predictors of returns of government bonds with shorter maturities.

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How central banks can take nominal rates deeply negative

May 18, 2019

The popular view that nominal interest rates have a natural zero lower bound has become obsolete in modern financial systems. It may be more appropriate to consider this boundary a convenient policy choice that can be revised. Technically, the zero lower bound arises from potential arbitrage at negative nominal rates, in the form of cash withdrawal, storage and redeposit. However, the central bank can break this arbitrage by using its power at the cash window, i.e. by altering the conditions at which commercial banks can withdraw and redeposit paper money. There are two viable options for doing so. The so-called ‘clean approach’ creates a crawling exchange rate between paper money and electronic money, effectively devaluing the former relative to the latter at a predictable continuous rate. The so-called ‘rental fee approach’ charges commercial banks for using paper money and is equivalent to imposing negative rates on cash held by the private sector.

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Systematic trading strategies: fooled by live records

May 11, 2019

Allocators to systematic strategies usually trust live records far more than backtests. Given the moral hazard issues of backtesting in the financial industry, this is understandable (view post here). Unfortunately, for many systematic strategies live records can be even more misleading. First, the survivor bias in published live records is worsening as the business has entered the age of mass production. Second, pronounced seasonality is a natural feature of many single-principle trading strategies. This means that even multi-year live records have very wide standard deviations across time depending on the conditions for the strategy principle. If one relies upon a few years’ of live PnL the probability of investing in a losing strategy or discarding a strong long-term value generator is disturbingly high. This suggests that the use of live record as allocation criterion, without sound theoretical reasoning and backtesting, can be highly inefficient.

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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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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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