Endogenous Market Risk Archives | Page 2 of 3

Endogenous market risk

August 11, 2018

Understanding endogenous market risk (“setback risk”) is critical for timing and risk management of strategic macro trades. Endogenous market risk here means a gap between downside and upside risk to the mark-to-market value that is unrelated to a trade’s fundamental value proposition. Rather this specific “downside skew” arises from the market’s internal dynamics and indicates the need to return to “cleaner” positioning. Endogenous market risk consists of two components: positioning and exit probability. Positioning refers to the “crowdedness” of a trade and indicates the potential size of a setback. Exit probability refers to the likelihood of a setback and can be assessed based on complacency measures and shock effect indicators.

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The dangerous disregard for fat tails in quantitative finance

July 28, 2018

The statistical term ‘fat tails’ refers to probability distributions with relatively high probability of extreme outcomes. Fat tails also imply strong influence of extreme observations on expected future risk. Alas, they are a plausible and common feature of financial markets. A summary article by Nassim Taleb reminds practitioners that fat tails typically invalidate methods and conventions applied in quantitative finance. Standard in-sample estimates of means, variance and typical outliers of financial returns are erroneous, as are estimates of relations based on linear regression. The inconsistency between the evidence of fat tails and the ongoing dominant usage of conventional statistics in markets is plausibly a major source of inefficiency and trading opportunities.

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Identifying asset price bubbles

March 10, 2018

A new paper proposes a practical method for identifying asset price bubbles. First, one estimates deviations of prices from fundamentals based on three different approaches: a structural model, an econometric data-rich regression, and a purely statistical trend filter. Then one computes the first principal component of the three deviation series as an estimate for the common component behind them. As a general approach the method holds promise for detecting price distortions in financial markets and setback risk for ongoing trends.

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Basic theory of momentum strategies

January 27, 2018

Systematic momentum trading is a major alternative risk premium strategy across asset classes. Time series momentum motivates trend following; cross section momentum gives rise to ‘winners-minus-losers strategies’. Trend following is a market directional strategy that promises ‘convex beta’ and ‘good diversification’ for outright long and carry portfolios as it normally performs well in protracted good and bad times alike. It works best if the underlying assets earn high absolute (positive or negative) Sharpe ratios and display low correlation. By contrast, cross section momentum strategies benefit from high absolute correlation of underlying contracts and are more suitable for trading assets of a homogeneous class. The main pitfalls of both momentum strategies are jump events and high costs of ‘gamma trading’ conjoined with high leverage.

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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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The downside variance risk premium

December 9, 2017

The variance risk premium of an asset is the difference between options-implied and actual expected return variation. It can be viewed as a price for hedging against variation in volatility. However, attitudes towards volatility are asymmetric: large upside moves are fine while large downside moves are scary. A measure of aversion to negative volatility is the downside variance risk premium, the difference between options-implied and actual expected downside variation of returns. It is this downside volatility risk that investors want to protect against and whose hedging price is a valid and apparently robust indicator of future returns. Similarly, the skewness risk premium, the difference between upside and downside variance risk premia, is also a powerful predictor of markets.

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How to use financial conditions indices

October 14, 2017

There are two ways to use financial conditions indicators for macro trading. First, the tightening of aggregate financial conditions helps forecasting macroeconomic dynamics and policy responses. Second, financial vulnerability indicators, such as leverage and credit aggregates, help predicting the impact of an initial adverse shock to growth or financial markets on the subsequent macroeconomic and market dynamics. The latest IMF Global Financial Report has provided some clues as to how to combine these effects with existing economic-financial data.

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FX returns and external balances

March 29, 2017

A new paper supports the view that currency excess returns can to some extent be viewed as compensation for risk to net capital flows in imperfect markets. An increase in current account uncertainty can be approximated by economists’ forecast dispersion. Historically, a rise in current account uncertainty has reduced returns on carry currencies and investment currencies, i.e. those of countries with net capital inflows. There is also evidence that markets have been sluggish in adapting to higher uncertainty.

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FX carry trade crashes

March 25, 2017

A global historical analysis of FX carry trades shows positive long-term performance but a negative skew of returns. Large drawdowns have been associated with global financial stress. This supports the view that FX carry returns are to some extent a premium for undiversifiable risk. FX carry trade crashes have been diverse in duration and size, exceeding 2 years and 30% in extreme episodes. Historically, high carry and positive valuation metrics have shortened the duration of sell-offs in FX carry portfolios. Financial stress in the developed world has prolonged the duration of drawdowns of developed market FX carry trades.

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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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