Central clearing and systemic risk

The expansion of central clearing has created a greater interconnectedness of financial markets and new systemic risks. Large losses of some of clearing members might exhaust central counterparties’ liquid assets and backup lines, triggering unfunded liquidity arrangements and strains on the remaining clearing members. Moreover, collateral requirements of central counterparties could surge in crises.

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The risks in statistical risk measures

A DNB paper warns that financial market risk models (such as value-at-risk or expected shortfall) are unreliable. Small variations in assumptions cause large differences in risk forecasts. At commonly used small samples of data forecasts are close to random noise. It would take half a century of daily data for estimates to reach their theoretical asymptotic properties.

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The root of China’s financial distortions

China’s financial distortions are rooted in deposit rate controls and implicit loan guarantees. Low remuneration on bank deposits in conjunction with capital controls have long subsidized banks and borrowers. Loan guarantees have spurred excessive lending and neglect of profitability. Reform is perilous as slowing credit would itself undermine credit quality. An IMF model analysis suggests that a removal of loan guarantees would reduce the capital intensity of the economy.

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The secular decline in the global equilibrium real interest rate

A new Bank of England paper finds a 450 bps decline in global equilibrium real interest rates over the past 35 years, due to a fundamental divergence: savings preferences surged on demographics, inequality and EM reserve accumulation, while investment spending was held back by cheapening capital goods and declining government activity. More recently, fear of secular stagnation has compounded the real rate compression.

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Collateral framework: risks and policies

The rising importance of high-quality collateral for financial transactions brings new systemic risks, such as potential collateral shortages and secured funding constraints in crisis times. Vulnerabilities are augmented by collateral optimization, transformation, re-use and re-hypothecation. Collateral policy has become an important part of central banks’ toolkit.

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How growing assets-under-management can compromise investment strategies

If investment funds maximize assets-under-management and end-investors allocate to outperforming funds, the investment process is compromised. A new theoretical paper suggests that asset managers may prefer portfolios with steady payouts (or steady expected mark-to-market gains) and neglect risks of rare large drawdowns, potentially leading to complete failure of parts of the options market.

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Momentum trading and setback risk

An empirical study suggests that momentum trades yield positive returns but carry higher downside than upside market risk. This “beta asymmetry” appears to be a global phenomenon across asset classes.  It is consistent with the broader observation that popular trading strategies come at the price of setback risk related to the crowdedness of positions.

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Using volatility to predict crises

A long-term empirical study finds two fundamental links between market volatility and financial crises. First, protracted low price volatility leads to a build-up of leverage and risk, making the financial system vulnerable in the medium term (Minsky hypothesis). Second, above-trend volatility indicates (and causes) high uncertainty, impairing investment decisions and raising the near-term crisis risk.

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The role of macroprudential policy

Macroprudential measures are often seen as a counterweight to ultra-easy monetary policy in the developed world. BIS research cautions against this expectation. Macroprudential policies are largely new and untested, have worked best as a complement (not offset) to monetary policy, and focus on specific sectors, such as banking and housing.

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Tracking trends in EM economies

Two recent papers provide useful techniques for “nowcasting” EM economies. The first uses “dynamic factor models” with high frequency indicators to estimate GDP growth in countries with scant and noisy data. The second uses seasonal adjustment with modifications for time-varying holidays that can track underlying trends in China and other countries with lunar year and Islamic holidays.

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