Category Financial Econometrics and Empirical Market Microstructure

Construction and Backtesting of a Multi-Factor Stress-Scenario for the Stock Market

Kirill Boldyrev, Dmitry Andrianov, and Sergey Ivliev

Abstract Nowadays stress-testing is a popular framework for the analysis of the financial stability of different markets’ institutes and objects. This work proposes a new approach to trading book stress-testing by building price paths based on generalized autoregressive conditional the heteroskedasticity (GARCH) model with Pareto distribution for the random fluctuation of prices and t-copula for describing the dependency structure between factors.

Keywords Copula theory • Extreme value theory • GARCH • Pareto distribution • Stress-testing • Stylized facts

JEL Classification C49, G17

1 Introduction

Stress-testing is a set of various techniques which allows the gauging of an institute’s vulnerability to “severe, but plausible” ...

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Unknown Real Asset Value and Informed Traders’ Errors During the Trading Process

Our GM model extension is divided into two stages. During the first stage, the market-maker loses its knowledge about possible real asset value, while conditions for informed and uninformed traders remain the same. During the second stage, in addition to uncertainty for the market-maker about possible real asset value, we introduce errors of informed participants.

The disruption of the modification sequence is motivated by conservation of research chronology, when in the beginning our task was to search for a market- maker’s strategy, since it was the hardest stage of GM model modification.

The first stage of modification is a relaxation of the assumption about the market- maker’s knowledge of possible real asset value (V and V). This is the same as in the work of Das (2005)...

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Adaptive Stress Testing Visualizations

Visualization is a crucial component to Adaptive Stress Testing. Visualization draws attention on emerging risks, and can help build intuition on how different risks are interconnected.

We can use heatmaps to prioritize attention to escalating high probability scenarios (red) and then escalating lower probability scenarios (Fig. 19).

Risk managers will focus first on the imminent threats, or escalating high PStress scenarios. Escalating low PStress scenarios are emerging scenarios, and still offer the potential for exerting control through proactive risk management. Black Swans could be lurking underneath stable low PStress scenarios, which calls for harnessing social intelligence to probe deeper into hidden fault lines.

We can also use network graphs to visualize emerging risk themes...

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The Mechanism of Causal Relationships

Risk interactions play the most important role, because of the existence of close economic, organizational and technological ties between risk owners. The occur­rence of some risks (operational, credit, market ones) for some parties implies the emergence of risks for their counterparties. The subsequent chain reaction of credit and market risks propagate through exchange within the economy. In recent decades, these relations have been developing more intensively than ever before, because of market globalization and technological progress.

This causal relationship can be illustrated by a typical example of the domino effect in business environment: discontent of the local population (i. e...

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Statistical Models for Large Tick Assets

In this section we present briefly the statistical models recently introduced by Curato and Lillo (2013) describing the high frequency dynamics of price changes for a large tick size asset in trade time. We want to show that these models are able to reproduce the phenomenon of clustering for log-returns and the scaling of hypercumulants Aq (n) in trade time.

The building blocks of these models are simple: the distribution of price changes caused by 1 transaction, i. e. Ap(i, и = 1), and the statistical properties of the dynamics of the bid-ask spread s (i). In our model we impose a coupling between the process of the price changes and of the spread in order to reproduce the price – change clustering.

We consider first a benchmark model, hereafter called i. i.d...

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Amplification Mechanisms Dr ive Systemic Risk

A stress event is a systemic breakdown, which is a form of phase transition. We observe phase transitions in all complex systems. Phase transitions are triggered after a critical point is crossed at which point self-amplification causes a transfor­mation into a state with radically different properties (e. g., solid, liquid, and gas).

The continual tension between amplifying and dampening mechanisms pow­ers complex systems. Financial cycles are driven by the inter-linkage of asset prices, leverage, and risk aversion. Furthermore, the social process of imitation is a major amplifier. Imitation is an efficient form of social learning and adaptation, and is prevalent especially during times of uncertainty (Keynes 1930).

Stability increases asset prices and leverage, and lowers risk aversion...

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