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Articles 1 - 11 of 11
Full-Text Articles in Business
Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Green Transition And Financial Stability: The Role Of Green Monetary And Macroprudential Policies And Vouchers, Ying Tung Chan, Maria Teresa Punzi, Hong Zhao
Sim Kee Boon Institute for Financial Economics
This paper analyzes a mix of alternative policies in supporting the green transition and the phase-out of fossil fuels, without compromising financial stability. An environmental dynamic stochastic general equilibrium (E-DSGE) model with two sectors (green and brown) and endogenous default is developed to assess potential climate-induced financial stability threats that can be mainly generated through physical and transition risks mechanism. Those risks are evaluated through a compound capital depreciation shock and a carbon tax shock. The paper offers several findings. First of all, a too stringent carbon tax would increase the medium-term default rate in both sectors, harming financial stability …
Local Institutional Investors And Corporate Monitoring: Evidence From Cross-Listed Korean Stocks In The Us Market, Changhwan Choi, Chune Young Chung, Jun Myung Song
Local Institutional Investors And Corporate Monitoring: Evidence From Cross-Listed Korean Stocks In The Us Market, Changhwan Choi, Chune Young Chung, Jun Myung Song
Sim Kee Boon Institute for Financial Economics
Using Korean firms that are cross-listed in the US market, this paper investigates whether there are standalone effects of geographic and market proximity of institutional investors on monitoring performance. We find that Korean institutional ownership is negatively associated with earnings management while the US institutional ownership has no impact on earnings management. This suggests that there is the geographic proximity advantage over the market proximity advantage in the emerging markets. Furthermore, we also show that the impact of geographic proximity is stronger for firms with high informational opacity
Hedging Cryptos With Bitcoin Futures, Francis Liu, Natalie Packham, Meng-Jou Lu, Wolfgang Karl Haerdle
Hedging Cryptos With Bitcoin Futures, Francis Liu, Natalie Packham, Meng-Jou Lu, Wolfgang Karl Haerdle
Sim Kee Boon Institute for Financial Economics
The introduction of derivatives on Bitcoin enables investors to hedge risk exposures in cryptocurrencies. Because of volatility swings and jumps in cryptocurrency prices, the traditional variance-based approach to obtain hedge ratios may not be suitable for hedgers. In this work, we consider two extensions of the traditional approach: first, different dependence structures are modelled by different copulae, such as the Gaussian, Student-t, Normal Inverse Gaussian and Archimedean copulae; second, different risk measures, such as value-at-risk, expected shortfall and spectral risk measures are employed to find the optimal hedge ratio. Extensive out-of-sample tests using the data from the time …
Assessing The Odds Of A Us Recession, Thomas Lam, David Fernandez
Assessing The Odds Of A Us Recession, Thomas Lam, David Fernandez
Sim Kee Boon Institute for Financial Economics
In this commentary, SMU Sim Kee Boon Institute for Financial Economics (SKBI) Principal Researcher Thomas Lam and SKBI Director SMU Professor of Finance (Practice) Dave Fernandez offer their perspectives on the current multifaceted and highly charged US recession debate. While America is currently not in a downturn, the near-term odds of one have edged up, according to models based on key monthly and weekly indicators.
Sandwiched Between A Rock And A Hard Place?, Thomas Lam, David Fernandez
Sandwiched Between A Rock And A Hard Place?, Thomas Lam, David Fernandez
Sim Kee Boon Institute for Financial Economics
The policy gap between US and China is likely to be widening further, potentially raising and unevenly distributing the risks of negative spillovers for Asia and the rest of the world.
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Data Driven Value-At-Risk Forecasting Using A Svr-Garch-Kde Hybrid, Marius Lux, Wolfgang Karl Hardle, Stefan Lessmann
Sim Kee Boon Institute for Financial Economics
Appropriate risk management is crucial to ensure the competitiveness of financial institutions and the stability of the economy. One widely used financial risk measure is value-at-risk (VaR). VaR estimates based on linear and parametric models can lead to biased results or even underestimation of risk due to time varying volatility, skewness and leptokurtosis of financial return series. The paper proposes a nonlinear and nonparametric framework to forecast VaR that is motivated by overcoming the disadvantages of parametric models with a purely data driven approach. Mean and volatility are modeled via support vector regression (SVR) where the volatility model is motivated …
Frm Financial Risk Meter, Andrija Mihoci, Michael Althof, Cathy Yi-Hsuan Chen, Wolfgang Karl Hardle
Frm Financial Risk Meter, Andrija Mihoci, Michael Althof, Cathy Yi-Hsuan Chen, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
A systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilizing tail event information. Financial Risk Meter (FRM) is based on least absolute shrinkage and selection operator quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identify risk factors. In practice, FRM is applied to the return time series of selected financial institutions …
Teres: Tail Event Risk Expectile Shortfall, Andrija Mihoci, Wolfgang Karl Hardle, Cathy Yi-Hsuan Chen
Teres: Tail Event Risk Expectile Shortfall, Andrija Mihoci, Wolfgang Karl Hardle, Cathy Yi-Hsuan Chen
Sim Kee Boon Institute for Financial Economics
We propose a generalized risk measure for expectile-based expected shortfall estimation. The generalization is designed with a mixture of Gaussian and Laplace densities. Our plug-in estimator is derived from an analytic relationship between expectiles and expected shortfall. We investigate the sensitivity and robustness of the expected shortfall to the underlying mixture parameter specification and the risk level. Empirical results from the US, German and UK stock markets and for selected NASDAQ blue chip companies indicate that expected shortfall can be successfully estimated using the proposed method on a monthly, weekly, daily and intra-day basis using a 1-year or 1-day time …
Investing With Cryptocurrencies: A Liquidity Constrained Investment Approach, Simon Trimborn, Mingyang Li, Wolfgang Karl Hardle
Investing With Cryptocurrencies: A Liquidity Constrained Investment Approach, Simon Trimborn, Mingyang Li, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
Cryptocurrencies have left the dark side of the finance universe and become an object of study for asset and portfolio management. Since they have low liquidity compared to traditional assets, one needs to take into account liquidity issues when adding them to a portfolio. We propose a Liquidity Bounded Risk-return Optimization (LIBRO) approach, which is a combination of risk-return portfolio optimization under liquidity constraints. Cryptocurrencies are included in portfolios formed with stocks of the S&P 100, US Bonds, and commodities. We illustrate the importance of the liquidity constraints in an in-sample and out-of-sample study. LIBRO improves the weight optimization in …
An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop
An Ai Approach To Measuring Financial Risk, Lining Yu, Wolfgang Karl Hardle, Lukas Borke, Thijs Benschop
Sim Kee Boon Institute for Financial Economics
AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here, we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ" role="presentation" style="box-sizing: border-box; display: inline; font-style: normal; font-weight: normal; line-height: normal; font-size: 18px; text-indent: 0px; text-align: left; text-transform: none; letter-spacing: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">λλ) of a linear quantile lasso regression. The FRM is calculated by taking the average …
Forecasting In Blockchain-Based Local Energy Markets, Michael Kostmann, Wolfgang Karl Hardle
Forecasting In Blockchain-Based Local Energy Markets, Michael Kostmann, Wolfgang Karl Hardle
Sim Kee Boon Institute for Financial Economics
Increasingly volatile and distributed energy production challenges traditional mechanisms to manage grid loads and price energy. Local energy markets (LEMs) may be a response to those challenges as they can balance energy production and consumption locally and may lower energy costs for consumers. Blockchain-based LEMs provide a decentralized market to local energy consumer and prosumers. They implement a market mechanism in the form of a smart contract without the need for a central authority coordinating the market. Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of …