Market Risk Of Portfolio Research Articles

Influence of the Epidemic on the Three-Factor Model's Applicability in the Chinese Stock Market

The Fama-French three-factor model is regressed in this study, which examines all A-share equities for 60 consecutive months between 2017 and 2022. The portfolio is built using the average investment in the Shanghai Exchange and Shenzhen Exchange. The data for the article was downloaded from the RESSET database and contains the the market capitalization, book-to-market values, and the portfolio's return less the risk-free rate of return, weighted by market capitalization for all A-share portfolios. According to the empirical findings, there was little overall change in the coefficients of the three factors-MKT, SMB, and HML. Each portfolio's market risk indicators point to a comparable degree of market risk. The stock market can be explained and predicted well using the three-factor model. Based on the regression results, the epidemic did not have a significant impact on the overall structure of the three-factor model. This indicates that the Chinese stock market is relatively stable in the short term and more resilient to unexpected events. It also shows that A-share market can be predicted by the three-factor model.

Price spillovers between foreign exchange rate markets in Asean countries: Evidence from Covid-19 crisis and Russia-Ukraine war

This study aims to evaluate the spillover effects between the foreign exchange rate markets of ASEAN-5 countries (Indonesia, Malaysia, Singapore, Thailand, and Vietnam) using the spillover index proposed by Diebold and Yilmaz (2014). The results indicate that price spillovers between exchange rate markets are relatively low and tend to increase during recent crises, including COVID-19 and the Russia-Ukraine war. This implies that crises have caused price contagion effects. Due to their reliance on the markets in Vietnam, Singapore, and Malaysia, the forex markets in Indonesia and Thailand will not be viewed as safe havens to hedge. These spillover effects reveal that price shocks significantly impact the ASEAN-5 markets, which means that there is a contagion risk in the currency markets. These findings have crucial implications for investors and policymakers dealing with currency markets, such as predicting portfolio market risk and identifying the existence of the diversification benefits of exchange rate markets.

Treynor Ratio guided risk-return model for TSO-DSO mutualism considering energy and price volatility

Treynor Ratio (TR), a reward to volatility measure in finance, is used to quantify excess return per unit risk taken by the investor, where risk implies volatility in returns relative to market portfolio return. In this paper, TR is modified (TREP) to suggest the hourly weight of each risky energy asset at which it is worth using in the transmission and distribution levels to sustain the volatility of the market and to yield reasonable returns to both TSO and DSO. Uncertainties in the wind and solar energy sources pose energy-risk and fluctuations in grid power price poses financial risk, and both impact the TSO-DSO profit trade-off. Here, beta is used as the risk measure that evaluates the effect of uncertainty in each energy source on operators’ profit relative to the collective effect of all the energy sources available in the system. When risk is modelled using absolute measures like standard deviation or variance which are independent of market portfolio returns, it discourages risky assets more, to keep a risk-averse profile. By co-optimizing TREP values of TSO and DSO, more realistic portfolios are built by maximizing their expected profits per unit risk in relative terms. The resultant portfolio utilizes higher share of distributed energy resources (DERs) and renewable energy, thereby improving the role of DSOs in the market. The operators’ returns are found to be closer to the market portfolio returns at risks well within the market portfolio risk level.

Sensitivities-Based Method and Expected Shortfall for Market Risk Under FRTB and Its Impact on Options Risk Capital

The changes in the Basel FRTB regulation come into effect in 2023 and will expose banking institutions to new challenges in terms of implementation, risk quantification and impacts on capital requirements. This paper first suggests an algorithm for implementing the FRTB standardised approach via the sensitivities-based method to estimate a portfolio's market risk capital and presents an illustration applied to an option position. Second, it proposes a methodology to estimate the expected shortfall in options portfolios from the FRTB internal models approach. In this regard, an application is developed to measure ES and VaR's impacts under FRTB vs conventional VaR in a currency option position by considering stress scenarios from the 2007-9 and 2020-1 crises and back-testing procedures. The proposals developed weave a communication bridge between the FRTB standardised and internal approaches that can be scaled up institutionally.

PREDICTING SYSTEMATIC RISK WITH MACROECONOMIC AND FINANCIAL VARIABLES

AbstractWe analyze the predictive power of several macroeconomic and financial indicators in forecasting quarterly realized betas of 30 industry and 25 size and book‐to‐market portfolios. We model realized betas as autoregressive processes of order 1 and include lagged values of macroeconomic and financial indicators as exogenous predictor variables. In out‐of‐sample forecasting exercises, forecasts using bond market variables as exogenous predictors statistically outperform forecasts from a benchmark model without any exogenous predictors. These forecasts based on bond market variables also economically outperform benchmark forecasts by providing better performance in hedging the market risk of portfolios.

A Sino-US comparative analysis of the hi-tech entrepreneurial model

This paper adds a government subsidy variable to expand the WWY (Wang, C., Wang, N., Yang, J., 2012) model, which is a three-stage entrepreneurial dynamic partial equilibrium model and a useful theoretical tool to analyze entrepreneurial realities after government intervention factors are considered. We analyze the productivity shock and market portfolio risk, endogenous entry and exit, investment, consumption, enterprise value and so on, using 15 parameters and 21 variables. The paper explains the present hi-tech entrepreneurial competitive advantage of US, even Chinese government provides lump sum financial subsidy. Although subsidies lower the initial entrepreneurial condition, significantly increase the number of startups, but would not improve entrepreneurial quality such as the investment and the growth of the hi-tech entrepreneurial wealth. The ongoing market deepening reforms such as IPO reform and venture capital cooperation will finally improve model parameters of China and weaken US’s advantage. Another conclusion is that debt-based entrepreneurship should not be encouraged. The conclusions will have some important policy significance.

Forecasting market risk of portfolios: copula-Markov switching multifractal approach

ABSTRACTThis paper proposes a new methodology for modeling and forecasting market risks of portfolios. It is based on a combination of copula functions and Markov switching multifractal (MSM) processes. We assess the performance of the copula-MSM model by computing the value at risk of a portfolio composed of the NASDAQ composite index and the S&P 500. Using the likelihood ratio (LR) test by Christoffersen [1998. “Evaluating Interval Forecasts.” International Economic Review 39: 841–862], the GMM duration-based test by Candelon et al. [2011. “Backtesting Value at Risk: A GMM Duration-based Test.” Journal of Financial Econometrics 9: 314–343] and the superior predictive ability (SPA) test by Hansen [2005. “A Test for Superior Predictive Ability.” Journal of Business and Economic Statistics 23, 365–380] we evaluate the predictive ability of the copula-MSM model and compare it to other common approaches such as historical simulation, variance–covariance, RiskMetrics, copula-GARCH and constant conditional correlation GARCH (CCC-GARCH) models. We find that the copula-MSM model is more robust, provides the best fit and outperforms the other models in terms of forecasting accuracy and VaR prediction.

Efficient randomized quasi-Monte Carlo methods for portfolio market risk

We consider the problem of simulating loss probabilities and conditional excesses for linear asset portfolios under the t-copula model. Although in the literature on market risk management there are papers proposing efficient variance reduction methods for Monte Carlo simulation of portfolio market risk, there is no paper discussing combining the randomized quasi-Monte Carlo method with variance reduction techniques. In this paper, we combine the randomized quasi-Monte Carlo method with importance sampling and stratified importance sampling. Numerical results for realistic portfolio examples suggest that replacing pseudorandom numbers (Monte Carlo) with quasi-random sequences (quasi-Monte Carlo) in the simulations increases the robustness of the estimates once we reduce the effective dimension and the impact of the non-smoothness of the integrands.

Are Country and Size Risks Priced in the Brazilian Stock Market?

Abstract When estimating a firm's cost of equity for valuation and other purposes in emerging markets without (or with only partial) capital market integration, many practitioners include a premium for country risk. In principle, the inclusion of such a risk factor would be justified if the particular country of interest was not sufficiently integrated into the global capital market. Initially, the paper measures and tests the degree of integration for the Brazilian market and does not reject the hypothesis of integration. The paper then tests directly the relevance of country risk premium in individual stocks' expected returns in the Brazilian market. Monthly data for the stocks of 57 of the most actively traded, non-financial firms, over the 2004 to 2014 period are used, using EMBI (Emerging Markets Bond Index) as a proxy for country risk, and this is found not to be significant. Finally, a premium for the size factor, also commonly used by practitioners, is also tested. Although it is found to be significant, the premium is negative, in contrast with current practice, which entails the addition of a positive premium to the required returns on small stocks. The inclusion of both a country risk and a size premium, in addition to the market portfolio risk premium, corresponds to the use of the Goldman Sachs model, as proposed by Mariscal and Lee (1993).

PERBANDINGAN VOLATILITAS EWMA, GARCH DAN MONTE CARLO TERHADAP NILAI TUKAR MATA UANG ASING BANK Bjb

This research addresses the comparison of accuracy volatility models especially Exponentiall Weighted Moving Average (EWMA), Generalized Autoregressive Conditional Heteroscedastic (GARCH) with its classification and Monte Carlo Simulation (MCS) for measuring market risk in order to calculate VaR of portofolio to exchange rate of AUD/IDR, EUR/IDR and USD/IDR of Bank Bjb. Testing in the validity of the model using Kupiec mixed backtest shows that GARCH volatility model and its classification with confidence level of 95% proved that three foreign currency exchange rate AUD, EUR and USD has valid and accurate model, while EWMA valid for AUD and EUR currencies and MCS valid for USD currency. Results of the portfolio market risk VaR estimation using filtered historical simulation method as amount of Rp797.083.763, gives information reserve capital or minimum capital charge to be provided by Bank BJB, in addition must also take into account the credit risk and operational risk.

Hedge Fund Performance Evaluation Using the Kalman Filter

In the capital asset pricing model, portfolio market risk is recognised through β while α summarises asset selection skill. Traditional parameter estimation techniques assume time-invariance and use rolling-window, ordinary least squares regression methods. The Kalman filter estimates dynamic αs and βs where measurement noise covariance and state noise covariance are known - or may be calibrated - in a state-space framework. These time-varying parameters result in superior predictive accuracy of fund return forecasts against ordinary least square (and other) estimates, particularly during the financial crisis of 2008/9 and are used to demonstrate increasing correlation between hedge funds and the market.

Will Futures Clearing Replace the Unnecessary Complexity and Systemic Risk of OTC Trading and Clearing Before the Dark Pools Do?

Over-the-counter (OTC) traders cannot pursue the two fundamental objectives of portfolio management, the identification of portfolio market risk and return and its diversification. The result of this major market shortcoming is a complex, systemically risky market disequilibrium. The tradable instruments that would address this problem – making financial markets simpler, safer, and transparent – are missing. They would permit dealers to manage OTC portfolios by conventional means, instead of the complicated, subjective valuation and systemically risky hedging methods available now. The introduction summarizes the current market disequilibrium. The second section summarizes adjustments that permit price discovery and diversification of risks by opening asset and derivative trading and market pricing in OTC markets. The third section describes FFDs, zero-market-value instruments that complete OTC derivatives markets. The fourth section describes new OTC asset trading mechanisms. The final section concludes.

Portfolio diversification during monetary loosening policy

Purpose– The purpose of the paper is to analyze the impact of quantitative easing (QE) performed in the USA on relationship between assets mainly from mining and oil industries. Based on the empirical results, the method of diversified portfolio creation has been proposed.Design/methodology/approach– Nine DCC-GARCH-type models have been estimated for each group centered around a main asset: a company from the oil or mining industry, the appropriate currency pair for its market of origin, commodities which could be used for the diversification of risk involved in investing in a portfolio containing the company, and the largest company from the same industry listed on the US market. Each series of conditional correlations was analyzed with regard to the changes that occurred during the various stages of QE.Findings– The correlations are shown to be stabilizing in the successive stages of QE. The most significant changes in the distribution of correlations can be observed after the first stage of QE. The effects of QE are evident not only in the USA but also in other countries; however, the level of its influence varies between different markets and assets. It is possible to diversify the inflation, currency and market portfolio risk by appropriately chosen asset decomposition.Research limitations/implications– The DCC model is limited, so to provide more precise results, more sophisticated models can be estimated and compared.Practical implications– The paper investigate the fact of stabilization in financial markets relations. The findings may prove the validity of continuation of QE. A portfolio creation method has been proposed – it has been stated that including commodity in portfolio is more appropriate then only-bond–equity mix.Originality/value– The new approach of analyzing financial stability has been proposed – the control for stability of conditional correlation.

Who takes Risks When and Why: Determinants of Changes in Investor Risk Taking*

Between September 08 and June 09, a period with significant market events, we surveyed UK online-brokerage customers at 3-month intervals for their willingness to take risk, 3-month expectations of returns and risks for the market and their own portfolio, and self-reported risk attitude. This unique dataset allowed us to analyze how these variables changed over time, and whether changes in risk taking were related to changes in expectations and/or risk attitudes. Risk taking changed substantially during the period, as did return and risk expectations. Numeric assessments of return and risk expectations were only weakly correlated with corresponding subjective judgments. Consistent with the risk-as-feelings hypothesis, changes in risk taking were associated with changes in subjective expectations of market portfolio risk and returns, but less with changes in numeric expectations.

Asymmetric effects and long memory in dynamic volatility relationships between stock returns and exchange rates

We use univariate and multivariate GARCH-type models to investigate the properties of conditional volatilities of stock returns and exchange rates, as well as their empirical relationships. Taking three European stock markets and two popular US dollar exchange rates as case study, our results show strong evidence of asymmetry and long memory in the conditional variances of all the series considered. In multivariate settings we find that bilateral relationships between stock and foreign exchange markets are highly significant for France and Germany. Moreover, both the univariate FIAPARCH and bivariate CCC-FIAPARCH models provide more accurate in-sample estimates and out-of-sample forecasts than the other competing GARCH-based specifications in almost all cases. Finally, there is evidence to support the suitability of the FIAPARCH model in forecasting portfolio's market risk exposure and the existence of diversification benefits between stock and foreign exchange markets.

Who Takes Risks When and Why: Determinants of Changes in Investor Risk Taking

Between September08 and June09, a period with significant market events, we surveyed UK online-brokerage customers at three-months intervals for their willingness to take risk, three-months expectations of returns and risks for the market and their own portfolio, and self-reported risk attitude. This unique dataset allowed us to analyze how these variables changed over time, and whether changes in risk taking were related to changes in expectations and/or risk attitudes. Risk taking changed substantially during the period, as did return and risk expectations. Numeric assessments of return and risk expectations were only weakly correlated with corresponding subjective judgments. Consistent with the risk-as-feelings hypothesis, changes in risk taking were associated with changes in subjective expectations of market portfolio risk and returns, but less with changes in numeric expectations.

Reexamination of capital asset pricing model (CAPM): An application of quantile regression

Capital asset pricing model (CAPM) plays a very important role in risky asset evaluation. This paper tries to explore the important aspect in CAPM, which is perfect linear relationship assumption between return and market portfolio risk and further discusses the application of CAPM. Empirical evidence shows that the model in ordinary least squares (OLS) supports the positive relationship between systematic risk and return. However, by quantile regression (QR) analysis, not all relationships between systematic risk and return are positive. For lower quantiles, the relationship is not significantly positive although the positive relationship is concluded for higher quantiles. To sum it up, it is not always sustainable for a positive relationship between systematic risk and return. Besides, non-parametric estimations show that the linear assumption between market portfolio risk and return in CAPM is suspicious. Therefore, we find that the two important associated assumptions, which are positive and linear relationships between market portfolio risk and return, do not necessarily exist. Key words: CAPM, quantile regression, nonlinear.

Cointegration and Causality Analysis on Developed Asian Markets for Risk Management and Portfolio Selection

Both practitioners and academics demand a linkage model across financial markets, particularly among regional capital markets, for both risk management and portfolio selection purposes. Researchers frequently use cointegration and causality analysis in investigating the dependence or co-movement of three or more stock markets in different countries. However, they mostly conduct causality in mean tests but not causality in variance tests.This study assesses the cointegration and causal relations among seven developed Asian markets, i.e., Tokyo, Hong Kong, Korea, Taiwan, Shanghai, Singapore, and Kuala Lumpur stock exchanges, using more frequent time series data. It employs the recently developed techniques for investigating unit roots, cointegration, time-varying volatility, and causality in variance. For estimating portfolio market risk, this study employs Value-at-Risk with delta normal approach. The results would recommend whether fund managers are able to diversify their portfolio in these developed stock markets either in long run or in short run.

Modelling VaR for foreign-asset portfolios in continuous time

VaR is widely viewed as a measure of market risk of a portfolio. The purpose of this article is to provide a VaR model for foreign-asset portfolios in continuous time. In the VaR model, the VaRs are not only a function of volatilities of asset returns and exchange rate but also a function of correlation coefficient between foreign assets and exchange rate. Moreover, by backtesting, the empirical results show that the new VaR model can efficiently evaluate the market risk of foreign-asset portfolios.

Investment Model Uncertainty and Fair Pricing

Modern investment theory takes it for granted that a Security Market Line (SML) is as certain as its corresponding Capital Market Line. (CML). However, it can be easily demonstrated that this is not the case. Knightian non-probabilistic, information gap uncertainty exists in the security markets, as the bivariate Galton's Error and its concomitant information gap proves (Journal of Banking & Finance, 23, 1999, 1793-1829). In fact, an SML graph needs (at least) two parallel horizontal beta axes, implying that a particular mean security return corresponds with a limited Knightian uncertainty range of betas, although it does correspond with only one market portfolio risk volatility. This implies that a security' risk premium is uncertain and that a Knightian uncertainty range of SMLs and of pricing exists. This paper both updates the empirical evidence and graphically traces the financial market consequences of this model uncertainty for modern investment theory. First, any investment knowledge about the securities risk remains uncertain. Investment valuations carry with them epistemological (modeling) risk in addition to the Markowitz-Sharpe market risk. Second, since idiosyncratic, or firm-specific, risk is limited-uncertain, the real option value of a firm is also limited-uncertain This explains the simultaneous coexistence of different analyst valuations of investment projects, particular firms or industries, included a category undecided. Third, we can now distinguish between buy, sell and trading orders based on an empirically determined collection of SMLs, based this Knightian modeling risk. The coexistence of such simultaneous value signals for the same security is necessary for the existence of a market for that security! Without epistemological investment uncertainty, no ongoing markets for securities could exist. In the absence of transaction costs and other inefficiencies, Knightian uncertainty is the necessary energy for market trading, since it creates potential or perceived arbitrage (= trading) opportunities, but it is also necessary for investors to hold securities. Knightian uncertainty provides a possible reason why the SEC can't obtain consensus on what constitutes fair pricing. The paper also shows that Malkiel's recommended CML-based investments are extremely conservative and non-robust.