nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒10‒02
thirteen papers chosen by
Stan Miles, Thompson Rivers University

  1. On the implied volatility of European and Asian call options under the stochastic volatility Bachelier model By Elisa Al\`os; Eulalia Nualart; Makar Pravosud
  2. Default Clustering Risk Premium and its Cross-Market Asset Pricing Implications By Kiwoong Byun; Baeho Kim; Dong Hwan Oh
  3. Analysis of Optimal Portfolio Management Using Hierarchical Clustering By Kapil Panda
  4. An Unconventional FX Tail Risk Story By Carlos Cañon; Eddie Gerba; Alberto Pambira; Evarist Stoja
  5. ESG Shareholder Engagement and Downside Risk By Andreas G. F. Hoepner; Ioannis Oikonomou; Zacharias Sautner; Laura T. Starks; Xiaoyan Zhou
  6. Joint Calibration of Local Volatility Models with Stochastic Interest Rates using Semimartingale Optimal Transport By Benjamin Joseph; Gregoire Loeper; Jan Obloj
  7. Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency By Chinara Azizova; Bruno Feunou; James Kyeong
  8. Hedging Forecast Combinations With an Application to the Random Forest By Elliot Beck; Damian Kozbur; Michael Wolf
  9. Russia-Ukraine war and G7 debt markets: Evidence from public sentiment towards economic sanctions during the conflict By Zunaidah Sulong; Mohammad Abdullah; Emmanuel J. A. Abakah; David Adeabah; Simplice Asongu
  10. Decoding Financial Crises: Analyzing Predictors and Evolution By JEONG, Young Sik; BAEK, Yaein
  11. The evolution of consumption inequality and riskinsurance in Chile By Carlos Madeira
  12. Exchange rate volatility and the effectiveness of FX interventions: the case of Chile By Alejandro Jara; Marco Piña
  13. A Strategic Approach to Bankruptcy Problems Based on the TAL Family of Rules By Bouwhuis, Dirck; Borm, Peter; Hendrickx, Ruud

  1. By: Elisa Al\`os; Eulalia Nualart; Makar Pravosud
    Abstract: In this paper we study the short-time behavior of the at-the-money implied volatility for European and arithmetic Asian call options with fixed strike price. The asset price is assumed to follow the Bachelier model with a general stochastic volatility process. Using techniques of the Malliavin calculus such as the anticipating It\^o's formula we first compute the level of the implied volatility when the maturity converges to zero. Then, we find a short maturity asymptotic formula for the skew of the implied volatility that depends on the roughness of the volatility model. We apply our general results to the SABR and fractional Bergomi models, and provide some numerical simulations that confirm the accurateness of the asymptotic formula for the skew.
    Date: 2023–08
  2. By: Kiwoong Byun; Baeho Kim; Dong Hwan Oh
    Abstract: This study examines the market-implied premiums for bearing default clustering risk by analyzing credit derivatives contracts on the CDX North American Investment Grade (CDX.NA.IG) portfolio between September 2005 and March 2021. Our approach involves constructing a time series of reference tranche rates exclusively derived by single-name CDS spreads. The default clustering risk premium (DCRP) is captured by comparing the original and reference tranche spreads, with the former exceeding the latter when investors require greater compensation for correlated defaults at the portfolio level. The fitted DCRP level significantly increased in response to the 2007-9 global financial crisis and remained relatively stable for a period, followed by a gradual decline beginning in 2016. Notably, the COVID-19 shock caused another sharp rise in the DCRP level. Our empirical analysis finds that the estimated DCRP has significant implications for asset pricing, particularly in affecting the investment opportunities available to U.S. stock investors during times of instability in the financial system.
    Keywords: Credit Default Swap (CDS); CDS Index (CDX); Reference Tranche Rate; Default Clustering Risk Premium
    JEL: G10 C60 C40
    Date: 2023–08–18
  3. By: Kapil Panda
    Abstract: Portfolio optimization is a task that investors use to determine the best allocations for their investments, and fund managers implement computational models to help guide their decisions. While one of the most common portfolio optimization models in the industry is the Markowitz Model, practitioners recognize limitations in its framework that lead to suboptimal out-of-sample performance and unrealistic allocations. In this study, I refine the Markowitz Model by incorporating machine learning to improve portfolio performance. By using a hierarchical clustering-based approach, I am able to enhance portfolio performance on a risk-adjusted basis compared to the Markowitz Model, across various market factors.
    Date: 2023–08
  4. By: Carlos Cañon; Eddie Gerba; Alberto Pambira; Evarist Stoja
    Abstract: We examine how the tail risk of currency returns over the past 20 years were impacted by central bank (monetary and liquidity) measures across the globe with an original and unique dataset that we make publicly available. Using a standard factor model, we derive theoretical measures of tail risks of currency returns which we then relate to the various policy instruments employed by central banks. We find empirical evidence for the existence of a cross-border transmission channel of central bank policy through the FX market. The tail impact is particularly sizeable for asset purchases and swap lines. The effects last for up to 1 month, and are proportionally higher for joint QE actions. This cross-border source of tail risk is largely undiversifiable, even after controlling for the U.S. dollar dominance and the effects of its own monetary policy stance.
    Keywords: unconventional and conventional monetary policy, liquidity measures, currency tail risk, systematic and idiosyncratic components of tail risk
    JEL: E44 G12 G15 E52
    Date: 2023
  5. By: Andreas G. F. Hoepner (University College Dublin); Ioannis Oikonomou (University of Reading); Zacharias Sautner (University of Zurich; Swiss Finance Institute; ECGI); Laura T. Starks (University of Texas at Austin); Xiaoyan Zhou (University of Oxford)
    Abstract: We show that engagement on environmental, social, and governance issues can benefit shareholders by reducing firms’ downside risks. We find that the risk reductions (measured using value at risk and lower partial moments) vary across engagement types and success rates. Engagement is most effective in lowering downside risk when addressing environmental topics (primarily climate change). Further, targets with large downside risk reductions exhibit a decrease in environmental incidents after the engagement. We estimate that the value at risk of engagement targets decreases by 9% of the standard deviation after successful engagements, relative to control firms.
    Keywords: ESG, Shareholder Activism, Downside Risk, Corporate Governance, Climate Change
    JEL: G32 M14
    Date: 2023–09
  6. By: Benjamin Joseph; Gregoire Loeper; Jan Obloj
    Abstract: We develop and implement a non-parametric method for joint exact calibration of a local volatility model and a correlated stochastic short rate model using semimartingale optimal transport. The method relies on the duality results established in Joseph, Loeper, and Obloj, 2023 and jointly calibrates the whole equity-rate dynamics. It uses an iterative approach which starts with a parametric model and tries to stay close to it, until a perfect calibration is obtained. We demonstrate the performance of our approach on market data using European SPX options and European cap interest rate options. Finally, we compare the joint calibration approach with the sequential calibration, in which the short rate model is calibrated first and frozen.
    Date: 2023–08
  7. By: Chinara Azizova; Bruno Feunou; James Kyeong
    Abstract: In this paper, we estimate the distribution of future inflation and growth in real gross domestic product (GDP) for the Canadian economy at a daily frequency. To do this, we model the conditional moments (mean, variance, skewness and kurtosis) of inflation and GDP growth as moving averages of economic and financial conditions. Then, we translate the conditional moments into conditional distributions using a flexible parametric distribution known as the skewed generalized error distribution. We show that the probabilities of inflation and GDP growth derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022. Our methodology offers daily-frequency forecasts with flexible forecasting horizons. This is highly useful in an environment of elevated uncertainty surrounding the inflation and growth outlook.
    Keywords: Econometric and statistical methods; Business fluctuations and cycles
    JEL: C32 C58 E44 G17
    Date: 2023–09
  8. By: Elliot Beck; Damian Kozbur; Michael Wolf
    Abstract: This papers proposes a generic, high-level methodology for generating forecast combinations that would deliver the optimal linearly combined forecast in terms of the mean-squared forecast error if one had access to two population quantities: the mean vector and the covariance matrix of the vector of individual forecast errors. We point out that this problem is identical to a mean-variance portfolio construction problem, in which portfolio weights correspond to forecast combination weights. We allow negative forecast weights and interpret such weights as hedging over and under estimation risks across estimators. This interpretation follows directly as an implication of the portfolio analogy. We demonstrate our method's improved out-of-sample performance relative to standard methods in combining tree forecasts to form weighted random forests in 14 data sets.
    Date: 2023–08
  9. By: Zunaidah Sulong (Universiti Sultan Zainal Abidin, Malaysia); Mohammad Abdullah (Universiti Sultan Zainal Abidin, Malaysia); Emmanuel J. A. Abakah (University of Ghana Business School, Accra Ghana); David Adeabah (University of Ghana Business School, Accra Ghana); Simplice Asongu (Yaoundé, Cameroon)
    Abstract: War-related expectations cause changes to investors’ risks and returns preferences. In this study, we examine the implications of war and sanctions sentiment for the G7 countries’ debt markets during the Russia-Ukraine war. We use behavioral indicators across social media, news media, and internet attention to reflect the public sentiment from 1st January 2022 to 20th April 2023. We apply the quantile-on-quantile regression (QQR) and rolling window wavelet correlation (RWWC) methods. The quantile-on-quantile regression results show heterogenous impact on fixed income securities. Specifically, extreme public sentiment has a negative impact on G7 fixed income securities return. The wavelets correlation result shows dynamic correlation pattern among public sentiment and fixed income securities. There is a negative relationship between public sentiment and G7 fixed income securities. The correlation is time-varying and highly event dependent. Our additional analysis using corporate bond data indicates the robustness of our findings. Furthermore, the contagion analysis shows public sentiment significantly influence G7 fixed income securities spillover. Our findings can be of great significance while framing strategies for asset allocation, portfolio performance and risk hedging.
    Keywords: Russia-Ukraine war, economic sanctions, G7 debt, fixed income securities, quantile approaches
    Date: 2023–01
    Abstract: We examine factors that predict financial crises and the evolution of financial crises using non-traditional methodologies, such as machine learning and system dynamics. Firstly, in our random forest model, the top six most important predictors among 12 indicators for the entire period (1870-2017) are the slope of the yield curve, the CPI, consumption, the debt service ratio, equity return, and public debt. Secondly, even though the manifestations of financial crises differ in each case, five common characteristics have been identified by examining various past financial crisis cases using a system dynamics approach (causal loop diagram). The first characteristic is a feedback loop that reinforces credit expansion. Next, the feedback loop leads to the buildup of financial crisis risk. Third, there is the shock that triggers the financial crisis. Fourth, there are risk-spreading factors. Lastly, individual financial crises do not end in themselves but have the common characteristic of becoming the seeds of new crises. In conclusion, two key findings emerge. First, the financial crisis is a systemic problem rather than an individual risk factor. Second, in diagnosing the recent situation, the results point to the risk of the financial crisis spreading.
    Keywords: Financial Crisis; Economic Crisis; Machine Learning; System Dynamics
    Date: 2023–08–04
  11. By: Carlos Madeira
    Abstract: Using micro survey data, I show that income and consumption inequality fell substantially in Chile since 1987. Consumption inequality between and withingroups fell substantially over the last 35 years, especially for within groups. During this period, households use of financial services increased substantially.Estimating a standardconsumption model, the results reject both the autarky and the full risk sharing frameworks. It is found that for services and non-durable goods, consumption is almost half-way between autarky and full risk-sharing. However, purchases of Semi-Durables, Durables, Medical, Insurance, and other financial products are strongly affected by income fluctuations.
    Date: 2023–04
  12. By: Alejandro Jara; Marco Piña
    Abstract: In this paper, we study the effectiveness of FX interventions in Chile since adopting a fully flexible exchange rate regime in the late 1990s. In particular, we ask whether these interventions have dumped excess exchange rate volatility and reduced its probability of being in a high volatility state. To do so, we rely on a high-frequency GARCH(1, 1) volatility model with Markov-Switching regimes (Haas et al., 2004) and evaluate the effectiveness of FX interventions within a Local Projection setting (Jordà, 2005). We show that FX interventions in Chile tend to occur during high exchange rate volatility periods, which correlate with domestic and foreign financial factors. Moreover, we show that the FX intervention that started by the end of 2019–the latest intervention included in our study–effectively reduced the exchange rate volatility and the probability of being at a high volatility state.
    Date: 2022–09
  13. By: Bouwhuis, Dirck (Tilburg University, School of Economics and Management); Borm, Peter (Tilburg University, School of Economics and Management); Hendrickx, Ruud (Tilburg University, School of Economics and Management)
    Date: 2023

This nep-rmg issue is ©2023 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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