Systematic Risk Factors Research Articles

Ruin probability of a continuous-time model with dependence between insurance and financial risks caused by systematic factors

Ruin problems of continuous-time models with various dependence structures under risky investment are extensively studied in the literature. Those studies focus on dependence structures arising from insurance businesses themselves and pay few attentions to dependence between insurance risk and investment risk. This study considers a continuous-time Poisson risk model with insurance claims and investment return jumps shocked by common systematic risk factors. Systematic risk factors cause immediate jumps of investment returns but there are often random delays for insurers to settle incurred claims. The study further assumes that the arrival times of claims are delayed by a common random time to the ones of their corresponding investment return jumps. When claim sizes are heavy-tailed distributed, a uniform asymptotic estimate for ruin probabilities of the model is established and a numerical study is given to show the accuracy of the result. The result captures the effect of the dependence structures caused by systematic risk factors on the asymptotic behaviors of ruin probabilities and allows arbitrary dependence structures between claim sizes and their corresponding investment return jumps.

Comparison of Statistical Underlying Systematic Risk Factors and Betas Driving Returns on Equities

The objective of this paper is to compare four dimension reduction techniques used for extracting the underlying systematic risk factors driving returns on equities of the Mexican Market. The methodology used compares the results of estimation produced by Principal Component Analysis (PCA), Factor Analysis (FA), Independent Component Analysis (ICA), and Neural Networks Principal Component Analysis (NNPCA) under three different perspectives. The results showed that in general: PCA, FA, and ICA produced similar systematic risk factors and betas; NNPCA and ICA produced the greatest number of fully accepted models in the econometric contrast; and, the interpretation of systematic risk factors across the four techniques was not constant. Additional research testing alternative extraction techniques, econometric contrast, and interpretation methodologies are recommended, considering the limitations derived from the scope of this work. The originality and main contribution of this paper lie in the comparison of these four techniques in both the financial and Mexican contexts. The main conclusion is that depending on the purpose of the analysis, one technique will be more suitable than another.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative in the Mexican stock exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

Statistical and computational techniques for extraction of underlying systematic risk factors: a comparative study in the Mexican Stock Exchange

This paper compares the dimension reduction or feature extraction techniques, e.g., Principal Component Analysis, Factor Analysis, Independent Component Analysis and Neural Networks Principal Component Analysis, which are used as techniques for extracting the underlying systematic risk factors driving the returns on equities of the Mexican Stock Exchange, under a statistical approach to the Arbitrage Pricing Theory. We carry out our research according to two different perspectives. First, we evaluate them from a theoretical and matrix scope, making a parallelism among their particular mixing and demixing processes, as well as the attributes of the factors extracted by each method. Secondly, we accomplish an empirical study in order to measure the level of accuracy in the reconstruction of the original variables.

The impact of COVID-19 on formation and evaluation of portfolio performance: A case of Indonesia

This paper examines how to build a portfolio and assess the impact of the COVID-19 on portfolio performance using the Sharpe single index model. The research sample consists of ten high market capitalization stocks representing five price fractions of the population listed stocks on the Indonesia Stock Exchange during the COVID-19 outbreak from March 1 to May 31, 2020. The results show that there are four stocks that are included in the portfolio formation, namely CASA with a proportion of 50%, BNLI with a proportion of 26 %, UNVR with a proportion of 15%, and HMSP with a proportion of 9%. Based on portfolio performance testing using the Sharpe single index model, it is known that the portfolio during the COVID-19 has a negative Sharpe ratio, meaning that portfolio performance is underperforming. The findings provide evidence that COVID-19 has had a negative impact on the stock market so that many investors have suffered losses on their portfolios. The implications of findings are that investors must evaluate portfolio performance and restructure the formation of new portfolios by considering the COVID-19 pandemic outbreak as a systematic risk factor that can determine the expected returns.

Systematic risk and performance of stock market in Kenya

Stock prices in Kenya have been experiencing drastic volatility over the years. In the year 2015 alone, the value of the listed companies shrunk by about 2.5 billion USD, representing about 25% of the national government annual budget. The performance of the stock market is an important proxy of a country’s economic environment. Rational investors constantly value and revise their portfolio composition so as to maximize their wealth. Whereas effectively diversified portfolio minimizes the unsystematic risk, systematic risks cannot be managed by simple diversification. Investors, therefore, need to understand the effect of these systematic risks on the stock performance. The study sought to determine the relationship between systematic risk factors using Inflation and interest rates and the performance of the stock market in Kenya. The study adopted a positivist philosophy and employed a correlation research design. The study targeted all the stock listed in the Nairobi Securities exchange. The study was underpinned by the Efficient Market Hypothesis, Arbitrage Pricing theory, and used integration analysis to establish the relationships between the variables of the study. The study found a significant long-run positive relationship between interest rate, inflation, and performance of the stock market in Kenya. Investment firms, the financial analyst should use past data on 91 Treasury bills rate and Inflation, to predict the future performance of stock exchange for the benefit of investors.

Alpha enhancement in global equity markets with ESG overlay on factor-based investment strategies

Studies show that companies with a strong Environment, Social and Governance (ESG) profile are more competitive than their peers, as they use resources, human capital and innovation more efficiently. High ESG-rated companies have lower exposure to systematic risk factors and low expected cost of capital, leading to higher valuations in a DCF model framework. They are typically more transparent, particularly with respect to their risk exposures, risk management and governance standards and have better long-term vision. The paper finds that higher Alpha can be harvested by restricting investment exposure to the ESG theme combined with various style characteristics, as they display low systematic and idiosyncratic tail risks. It shows that an ESG overlay on such factor-based strategies, particularly on ‘multi-factor’, ‘value’ and ‘low volatility’ in that order, reduces both systematic and idiosyncratic risks further. ESG overlay on ‘quality’ factor provides the highest return among ESG target indices, however, the underlying ‘quality’ factor provides even higher excess return. These findings can provide some insight on return enhancement to investors investing in the global equity markets.

Factors and risk premia in individual international stock returns

We propose an estimation methodology tailored for large unbalanced panels of individual stock returns to study the factor structure and expected returns in international stock markets. We show that the local market is necessary to capture the factor structure in both developed and emerging markets. Neither the presence of multiple world or regional risk factors, systematic currency risk factors, nor a country-specific currency subsumes the importance of the local market factor. All factors, including the local market, carry significant risk premia across a large proportion of countries. The contribution of pricing errors to total expected returns is large and time-varying.

Municipal Bond Mutual Fund Performance and Active Share

This article evaluates the performance of actively managed US open-end municipal bond mutual funds between 1999 and 2020. Fund classifications span national short, intermediate, and long-term, as well as high-yield and single-state portfolios. An initial investigation reveals that municipal securities manifest characteristics of a distinct asset class. Performance measures include benchmark-adjusted returns and single- and multifactor pricing models. During the sample period, only 8% of funds generated returns that beat their benchmark indexes, and 29% produced positive excess returns (alpha) based on a four-factor pricing model. Longer-maturity funds generally performed better than short-maturity funds. Based on portfolio performance, managers specializing in single-state issues do not manifest unique knowledge or insight. Active share for the aggregate sample was 25%, implying an active expense ratio exceeding 3% and annualized active alpha below −3%. The evidence overall suggests that active management of municipal bond portfolios is not a value-enhancing activity. <b>TOPICS:</b>Mutual funds/passive investing/indexing, fixed income and structured finance, factor-based models, performance measurement <b>Key Findings</b> ▪ Municipal bonds possess several characteristics that satisfy traditional criteria qualifying them as a distinct asset class. In this first evaluation of the performance of actively managed open-end municipal security mutual funds, the authors find that the vast majority of funds underperform their benchmark indexes. They also document significant underperformance when accounting for four fixed-income market systematic risk factors. ▪ The performance results vary by fund type, with short-term funds underperforming more acutely than intermediate- or long-term funds. Single-state funds are among the worst performers, suggesting that managers do not possess unique insight about the issuer domicile and its securities. ▪ Portfolio active share for muni bond funds is about 25% (similar to what extant work finds for equity funds), which implies an annualized active expense ratio of about 3% (similar to fees charged by some hedge funds).

The feasibility and outcome of a community-based primary prevention program for cardiovascular disease in the 21st century

Objective There is no evidence that systematic screening and risk factor modification in an unselected, asymptomatic population will reduce cardiovascular disease (CVD) mortality. This study aimed to evaluate the effectiveness of a primary care CVD prevention program on mortality during a 13-year follow-up. Design A risk factor survey was sent, followed by a nurse-led lifestyle counselling to respondents with at least one CVD risk factor, and a general practitioner’s (GP) appointment for high-risk persons. Screening and interventions were performed during 2005–2006. Setting A public health care centre in the town of Harjavalta, Finland. Subjects All home-dwelling 45–70-year old inhabitants without manifested CVD or diabetes. Main outcome measures All-cause and CVD mortality. Results Altogether 74% (2121/2856) inhabitants responded to the invitation. The intervention was received by 1465 individuals (52% of the invited population): 398 risk persons had an appointment with a nurse, followed by an appointment with a GP for 1067 high-risk persons. During the follow-up, 370 persons died. Mortality among the non-respondents was twofold compared to the participants’. In subjects who received the intervention, the age- and gender-adjusted hazard ratio for all-cause mortality was 0.44 (95% CI: 0.36 to 0.54) compared to the subjects who did not receive the intervention. Conclusions Reducing mortality is possible in a primary care setting by raising health awareness in the community with screening, by targeted lifestyle counselling and evidence-based preventive medication for persons at high risk for CVD. Subjects not willing to participate in health surveys have the worst prognosis. Key Points Previously, there is no evidence that systematic screening and risk factor modification in an unselected, asymptomatic population will reduce cardiovascular disease (CVD) mortality. With a stepwise screening program it is possible to scale the magnitude of CVD prevention in the community. Reducing mortality in a community is possible by screening, targeted lifestyle counselling, and by evidence-based preventive medication for high-risk persons. Subjects not willing to participate in health surveys have the worst prognosis.

Identifying Systematic Risk Factors in Companies Active in Iranian Medical Tourism Industry[1

امروزه گردشگری پزشکی یک صنعت است و برای اقتصاد بسیاری از کشورها که پتانسیل پذیرش بیماران را دارند، صنعت ارزشمندی است. با این حال موضوع نوسان تقاضا تأثيرات مخربی بر صنعت گردشگری پزشکی وارد نموده و شرکت­های فعال را با خطر ورشکستگی مواجه می­نماید. ریسک­های سیستماتیک یکی از عوامل نوسان تقاضاست که آمادگی شرکت­ها برای مقاومت در برابر آن­ها یکی از نکات با اهمیت در مدیریت ریسک می­باشد. در صورت آماده نبودن شرکت­ها و بروز مشکلات مالی و ورشکستگی گسترده می­تواند آثار و تبعات اجتماعی به همراه داشته باشد. هدف تحقیق حاضر، محاسبه ریسک سیستماتیک در شرکت­های فعال در جذب گردشگران پزشکی و تخمین عوامل مؤثر بر ریسک­ سیستماتیک می­باشد. برای این کار از روش مدل قيمت­گذاري دارایي­های سرمايه­اي ((CAPM استفاده می­گردد. در این روش برای تعیین میزان تأثيرپذیری شرکت­ها از ریسک سیستماتیک، ضریب بتا را محاسبه می­کنند که یک معیار آماری است و سرنخی را به سرمایه‌گذاران در مورد نوسان‌پذیری می‌دهند. با این حال عدم تقارن اطلاعات بین محیط درونی و بیرونی شرکت­های کوچک و متوسط باعث می­شود این گونه مطالعات با پیچیدگی بیشتری مواجه شود. مطابق نتایج حاصل از مدل پنل­دیتا بزرگی شرکت­های فعال در گردشگری پزشکی و همچنین میزان تبلیغات آن­ها اثر معکوس بر ریسک سیستماتیک دارد.

Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall

This study aims to apply value at risk (VaR) and expected shortfall (ES) as time-varying systematic and idiosyncratic risk factors to address the downside risk anomaly of various asset pricing models currently existing in the Pakistan stock exchange. The study analyses the significance of high minus low VaR and ES portfolios as a systematic risk factor in one factor, three-factor, and five-factor asset pricing model. Furthermore, the study introduced the six-factor model, deploying VaR and ES as the idiosyncratic risk factor. The theoretical and empirical alteration of traditional asset pricing models is the study’s contributions. This study reported a strong positive relationship of traditional market beta, value at risk, and expected shortfall. Market beta pertains its superiority in estimating the time-varying stock returns. Furthermore, value at risk and expected shortfall strengthen the effects of traditional beta impact on stock returns, signifying the proposed six-factor asset pricing model. Investment and profitability factors are redundant in conventional asset pricing models.

The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns

To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases.This paper was accepted by David Simchi-Levi, finance.

Market Response to Macroeconomic Announcements under Optimal Attention Allocation: Theory and Evidence

I develop a model of investor behavior around prescheduled macroeconomic announcements. My model analyzes the optimal allocation of investor attention between systematic and idiosyncratic risk factors when a macroeconomic announcement is anticipated. Skilled investors, when producing information under a limited attention capacity, optimally allocate more of their attention to analyzing the idiosyncratic risk factor when they anticipate more precise public information about the systematic risk factor from the macroeconomic announcement. Consequently, my model predicts that, the more informative (precise) the macroeconomic announcement is expected to be about the underlying risk factors, ceteris paribus, the more uncertainty pre-announcement, the more resolution of uncertainty post-announcement, and the higher the trading volume around the announcement on the market index. My empirical analysis of trading by investors around both FOMC and CPI announcements support my model's predictions. In particular, my empirical findings are consistent with model predictions about the effect of the anticipated macroeconomic announcement precision on investor attention allocation, the effect of investor attention on the levels of pre-announcement and post-announcement trading volumes, and the effect of investor attention on the ratio of post-announcement trading volume over the pre-announcement trading volume.

Macro Trends and Factor Timing

We find that the value of well-known systematic (characteristics-based) risk factors, like SMB and HML, is anchored to macroeconomic trends related to inflation and real economic activity. Exploiting the cointegration logic, when the price of a factor is greater than the long-term value implied by the macro trends, expected returns should be lower over the next period. We provide strong supporting evidence for this intuition: deviations of factor prices from their value implied by macroeconomic conditions predict factor returns both in- and out-of-sample, translating into significant economic gains from the perspective of a mean-variance investor. Finally, our approach leads to an estimated SDF that displays sizable variation over time when benchmarked against standard long-run risk or habit models.

Time-varying risk aversion and currency excess returns

This paper documents an economically significant risk premium associated with a currency’s sensitivity to time-varying risk aversion. Consequently, an investment strategy that takes a long (short) position in currencies with high (low) sensitivity to the aggregate market risk aversion yields significantly positive excess returns. While advanced market currencies including the Euro, Yen and Swiss Francs dominate the short end of these portfolios with low sensitivity to risk aversion, emerging market currencies including the Brazilian Real, Mexican Peso and Turkish Lira are found to be the most sensitive currencies to risk aversion. The excess returns from the proposed strategy are significant even after controlling for systematic equity market risk factors as well as liquidity risk and cannot be explained by measures of economic conditions or uncertainty. Interestingly the excess returns generated by the risk aversion based strategy are found to have significant loadings on global momentum, suggesting possible commonality in the behavioral drivers of anomalies in the global equity and currency markets. The findings highlight the role of behavioral factors as predictor of currency excess returns with significant investment implications.

Arbitrage Pricing Theory, the Stochastic Discount Factor and Estimation of Risk Premia from Portfolios

The arbitrage pricing theory (APT) attributes differences in expected returns to exposure to systematic risk factors, which are typically assumed to be strong. In this paper we consider two aspects of the APT. Firstly we relate the factors in the statistical factor model to a theoretically consistent set of factors defined by their conditional covariation with the stochastic discount factor (mt) used to price securities within inter-temporal asset pricing models. We show that risk premia arise from non-zero correlation of observed factors with mt; and the pricing errors arise from the correlation of the errors in the statistical factor model with mt: Secondly we compare estimates of factor risk premia using portfolios with the ones obtained using individual securities, and show that the identification conditions in terms of the strength of the factor are the same and that, in general, no clear cut ranking of the small sample bias of the two estimators is possible.

Factor Investing, Learning from Prices, and Endogenous Uncertainty in Asset Markets

We study learning and uncertainty under the factor investing paradigm using an endogenous information model with correlated assets. As investors shift attention from firms towards systematic risk factors, stock prices become less informative, increasing systematic uncertainty and incentivizing learning about the systematic risk. This learning complementarity leads to multiple regimes in systematic uncertainty and attention allocation. We specify and estimate a model-based, forward-looking measure of attention to systematic versus firm-level information. Consistent with the model, the measure follows a regime-switching process. The high-level regime is linked to lower stock price sensitivity to firm-specific information and a higher systematic risk concentration.

Liquidity Commonality and its Pricing: Evidence from Firms in Supply Chain Networks

This paper investigates how economic links from customer-supplier relationships affect liquidity commonality and its pricing. I show that a stock's liquidity co-moves with liquidity of its economically linked stocks and this liquidity commonality decreases with the level of information asymmetry on the stock. A long-short portfolio from the high-minus-low liquidity commonality with economically linked firms yields economically and statistically significant average returns, and these returns cannot be explained by majorly known systematic risk factors. The results imply that supply-chain networks are another important channel for liquidity risk.

Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework

This study employs a mean semi-variance asset pricing framework to examine the influence of risk factors on stock returns of oil and gas companies. This study also examines how downside risk is priced in stock performance. The time-series estimations expose that market, size, momentum, oil, gas, and exchange rate have significant impacts on oil and gas stock returns, but effects are heterogeneous depending on an individual stock. The two-stage cross-section estimations provide new insights about investors’ risk-return trade-off when facing downside risks. The results show that downside risk exposures to market, momentum, oil, and exchange rate factors are negatively priced in the Malaysian oil and gas stocks. This implies that investors are penalized for their downside exposure to these risk factors, and such inference is consistent with the risk preference explanation of prospect theory. Liquefied natural gas (LNG) is the only risk factor found to be positively priced in the returns of oil and gas stocks. Additionally, we find a negative relationship between LNG factor and total risk. This suggests that as the risk exposure to LNG increases, the total risk decreases, implying that the LNG risk factor is an idiosyncratic risk and not a systematic risk factor. Such interpretation is consistent with the correlation result, which shows no association between LNG and the market risk factor.