Backtesting
A comprehensive evaluation of value-at-risk models and a comparison of their performance in emerging markets
This paper aims to evaluate the performance of different value-at-risk (VaR) calculation methods, allowing the authors to identify models that are valid for use in emerging markets.
Risk Markets Technology Awards 2019: Vendors enter the pick-and-mix era
Modular tech and micro-services – plus new risk and regulatory needs – are creating openings for insurgents and incumbents
The disputed terrain of model risk scoring
There is no concord on how banks should police their model risk. But two Fed economists have an idea
Obstacles and opportunities in adopting cloud computing
Sponsored Q&A
Back to backtesting: integrated backtesting for value-at-risk and expected shortfall in practice
This paper aims to reflect the current state of the discussion on the validation of market risk forecasts by means of backtesting.
Systematic testing of systematic trading strategies
This study reviews the various statistical methodologies that are in place to test multiple systematic trading strategies and implements these methodologies under simulation with known artificial trading rules in order to critically compare and evaluate…
Quants tout improved expected shortfall backtest
Measure aims to provide better gauge of VAR violations
New backtests for unconditional coverage of expected shortfall
In this paper, the authors present a new backtest for the unconditional coverage property of expected shortfall.
Estimation window strategies for value-at-risk and expected shortfall forecasting
This paper analyzes the impact of different estimation window strategies, including structural breaks and forecast combinations, on forecasting common risk measures such as VaR and ES.
Shrunk volatility value-at-risk: an application on US balanced portfolios
In this paper, the authors adopt a new method of predicting VaR, to estimate balanced portfolios’ VaR.
On the offensive – Seeking a new edge, buy-side invests in portfolio and risk analytics
A fast-moving, headstrong hedge fund – hit by rare losses after a black swan event touched on an overweight country exposure – ponders adding fresh quantitative expertise. Much to traders’ chagrin, the chief investment officer and chief operating officer…
UBS shrugs off VAR exceptions
The Swiss bank has crunched down its market RWAs to Sfr12.3 billion
The validation of filtered historical value-at-risk models
In this paper, the authors examine the problem of validating and calibrating FHS VaR models, focussing in particular on the Hull and White (1998) approach with EWMA volatility estimates, given its extended use in the industry.
Study finds holes in quality factor indexes
Metrics commonly used to build indexes bring zero alpha, says Research Affiliates
Optimising VAR and terminating Arnie-VAR
Albanese, Caenazzo and Syrkin show how full-revaluation VAR is more accurate and robust than sensitivity-based VAR measures
FRTB: proxy risk factors may trigger model failures
Swapping non-modellable risk factors for proxies may make it harder to pass P&L attribution test
Performance testing of margin models using time series similarity
This paper proposes a performance test based on empirical similarity that would account for margin shortfall, procyclicality and efficiency in a single score.
CCP margin backtests can hide flaws, research finds
In richer test, ‘filtered’ VAR beats five other measures
Mnuchin makes life harder for quants
Proposed CCAR changes make KVA calculations even more complex
Academic shines light on data mining in alternative beta
Sharpe ratios on complex products fall 73% compared with backtests
Statistical testing of DeMark technical indicators on commodity futures
This paper examines the performance of three DeMark indicators over twenty-one commodity futures markets and ten years of daily data.
Correctness of backtest engines
In this paper, the authors provide tools to test the correctness of backtest engines for setups with at most one entry and one exit.
A sound modelling and backtesting framework for forecasting initial margin requirements
Anfuso, Aziz, Loukopoulos and Giltinan propose a method to develop and backtest forecasting models for IM