AdSense

Friday, March 2, 2018

Bibliography: Financial Turbulence and Absorption Ratio by Mark Kritzman

[1] Financial Turbulence


Skulls, Financial Turbulence, and Risk Management
Mark Kritzman, CFA, and Yuanzhen Li
https://www.cfapubs.org/doi/abs/10.2469/faj.v66.n5.3

- An original paper dealing with the concepts and equation of the Financial Turbulence
- A brief introduction, not a research paper

- "The only problem with diversification is that it's never been tried," said Mark Kritzman, (because volatility and correlation are not stable at all)

Turbulence vs. VIX
- “Turbulence is a measure of statistical unusualness that takes into account both the magnitude of returns and how they interact with one another,” said Kritzman. “A period is deemed turbulent if either the returns are different in magnitude from their norm or if the assets interact in an uncharacteristic way.”
- In other words, turbulence is a statistical measure of both volatility and correlation. It differs from
narrower metrics such as the VIX index, which measure only one asset class (the S&P 500 in the case of the VIX) and don’t take into account correlations across asset classes.
- By incorporating information about correlations, turbulence indicates—in a way that volatility cannot—whether markets are decoupling or converging. This is important because when assets act uncharacteristically, hedging and other investment strategies that rely on consistent correlations may not work.
- Measures such as VIX have additional shortcomings, according to Kritzman. They are only available for asset classes that have liquid option markets, and they are forward-looking measures, so they don’t measure what’s actually going on now.

Turbulence Suggests When to Trim Risky Assets
- Turbulence tends to be persistent. “Even if you can’t forecast when turbulence will begin, you know it will continue for a while. The other indicators are close to random, so you don’t know whether they’ll disappear,” said Kritzman.
- During turbulent periods investors flee to safety, and risk-adjusted returns are substantially lower than in non-turbulent periods. So it makes sense to scale back on risky investments in favor of safe assets like U.S. Treasury bonds when turbulence is afoot.

More Implications for Advisors
- With portfolios that rely on traditional measures of volatility and correlation, “You’re getting diversification exactly when you don’t need it, and you’re getting unification when you don’t want it,” Kritzman said.



[2] Absorption Ratio


Principal Components as a Measure of Systemic Risk
MARK KRITZMAN, YUANZHEN LI, SEBASTIEN PAGE, AND ROBERTO RIGOBON
http://www.iinews.com/site/pdfs/JPM_Summer2011_StateStreet.pdf

- An original paper dealing with the concepts and equation of the Absorption Ratio



[3] Financial Turbulence & Absorption Ratio

Risk Regime Investing

Mark Kritzman
https://www.top1000funds.com/wp-content/uploads/2012/10/4_Mark-Kritzman-Windham.pdf
- Risk Regime Investing is an investment process which is driven by proprietary measures of financial turbulence and systemic risk(absorption ratio).

Financial turbulence measures the statistical unusualness of a set of returns given their historical pattern of behavior.
- Implied systemic risk, through a statistic called the absorption ratio, measures the fraction of market variability that is explained by a subset of the most important factors.
Financial turbulence is the statistical unusualness of a set of returns given their historical pattern of behavior, including (1) extreme price moves and (2) decoupling of correlated assets and/or convergence of uncorrelated assets.
- Important empirical features of financial turbulence: (1) returns to risk are lower during turbulent periods, (2) although it may arrive unexpectedly, turbulence tends to be persistent

- Systemic risk (absorption ratio): a measure of the extent to which markets are unified or tightly coupled, which we call the absorption ratio. When markets are tightly coupled, they are more fragile in the sense that negative shocks propagate more quickly and broadly than when markets are loosely linked.
- Important empirical features of systemic risk: (1) systemic risk (absorption ratio) tends to rise prior to the most significant market drawdowns, (2) systemic risk (absorption ratio) can be a leading indicator of financial turbulence.


REGIMES, TURBULENCE AND BRITTLENESS – A NEW WAY OF LOOKING AT RISK
Andrew Harma
http://www.cfsgam.com.au/uploadedFiles/Content/Funds_-_Investment_strategies/Asset_Class_overview/Multi_asset_solutions/Multi_asset_research_papers/MAS%20Research%20Paper%20Issue%208_%20Regimes%20Turbulence%20and%20Brittleness%20-%20A%20new%20way%20of%20looking%20at%20risk.pdf

- A brief introduction, not a research paper, which covers both Financial Turbulence and Absorption Ratio

- Over time financial market relationships evolve and change. These changes, or shifts, can have significant impact on the expected risk and returns of various investments. Traditional risk measures, such as volatility, correlation and betas, have fallen short in timely identification of these shifts.
Allocating capital in a changing financial world
- The investment challenge is to monitor and understand the changing financial landscape and allocate capital accordingly. Shifts in market behavior where relationships change or no long hold, which we would describe as a regime shift, provide significant challenges to asset allocation.
- As asset allocators we constantly monitor a large range of risk measures and indicators with turbulence and absorption ratio (Although the author used brittleness instead of the original word "absorption ratio," the original word is used here.) being two measures of capital market structure.
Do you have the time?
- While there is clearly no silver bullet, a "set-and-forget" asset allocation approach often falls short due to the timing of harmful capital market events relative to a particular investor's time horizon.

Risk is evolutionary, not stationary
- The traditional measures of risk, such as betas, volatilities, correlations, and Value-at-Risk, provide forward-looking or historical point estimates of portfolio characteristics.
- Large changes in the input assumptions can have a meaningful impact on the results and resulting interpretations, or indeed if the future is unlike the past.
- Correlations are not stationary and exhibit asymmetry.
- There is a large body of evidence showing that downside correlations for equity markets are much higher than upside correlations.
- Extreme movements, which focus on the tails of the return distribution, large negative movements result in a much higher correlation than large positive movements.
- The rationale for dynamic reallocation of capital is reinforced by Longin and Solnik's (2001) findings that correlations asymmetries are exacerbated amongst small, value and negative momentum stocks.
Which 'normal'? Old nomal, new normal or abnormal?
- A significant challenge to portfolio construction and risk management is the concept of regime shifts. For example, a shift could be caused by unanticipated changes in growth, inflation, monetary policy, regulation, brittleness of the financial system or other secular shifts. The challenge for investors is to be able to identify regime shifts and determine the appropriate action, which could be a conscious decision of no-action.
- Regime shifts result in different asset returns, volatilities and asset correlations (not to mention autocorrelations). To help us monitor regime shifts, we first need to determine an appropriate measure of abnormality in data or process for the identification of outliners. Mahalanobis (1927, 1936) defines a distance measure that was prompted by requirement to compare the similarilities, or lack therefof, of human skulls. We use this measure to calculate the degree of uncharacteristic behavior within financial markets, capturing extreme price movements and changing relationships. Kritzman and Li (2010) coined the application of this measure to financial markets 'Turbulence'.
- Although historical identification of crises is informative, it would be more useful to identify when a regime shift occurs. This allows for a timely review of any assumptions, such as volatilities and correlations, and the resulting allocations. A portfolio built on average market assumptions will become inappropriate when market behavior changes.
Contagion: are my exposures unified or diversified?
- The holy grail of asset allocation is the identification of uncorrelated compounding assets. So being able to find uncorrelated return and risk drivers would be significantly meaningful. Or in a risk context, the reverse would be informative: how unified are my exposures?
- We use principal components analysis (PCA) to decompose the variation in returns into uncorrelated factors that explain as much of the variation in returns as possible. This quantifies the degree to which performance is explained by the first n factors. Kritzman et al. (2011) used the moniker of ‘Absorption’ to describe the application of PCA to financial market returns. We prefer ‘Brittleness’ as a more intuitive description. The quantum these n factors can explain is called the brittleness ratio. As the brittleness (absorption) ratio increases capital markets become more fragile, increasing the likelihood of shocks propagating through markets as fewer factors drive returns.
- Taking the brittleness ratio we again use regime shifts to provide us with a quantitative measure of the unification of financial markets.
- When capital markets become coupled, broad portfolio protection strategies and tail risk strategies are likely to become meaningful.

Why do we care?
- Although there may be strong fundamental reasons underlying an investment thesis. At times the macro environment is going to dominate: momentum can grow; cheap assets can get cheaper; and expensive assets can continue to rise in value. It is very difficult to design a portfolio based on irrational behaviour, although, it is possible to ensure that it is resilient.
- The reason why we monitor turbulence and brittleness is to capture an additional dimension of risk. As asset allocators we closely monitor valuations, carry, momentum and other meaningful inputs such as supply and demand; central bank action and the political landscape to name a few. But these are only useful if we can understand them in the current market context.


Deep Learning (Regression, Multiple Features/Explanatory Variables, Supervised Learning): Impelementation and Showing Biases and Weights

Deep Learning (Regression, Multiple Features/Explanatory Variables, Supervised Learning): Impelementation and Showing Biases and Weights ...