Standard Deviation Of Returns Research Articles

Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices

The Shanghai crude oil futures market exudes distinct speculative attributes, underscoring the pivotal significance of precise price forecasts. Accurate forecasting of Shanghai crude oil futures prices assumes vital importance for investors to optimize their portfolios profitably, for producers to mitigate production risks in the crude oil spot market, and for providing cogent decision-making support to government entities. This study implements a groundbreaking unbiased structural forecasting for Shanghai crude oil futures' open-high-low-close (OHLC) prices leveraging the Transformer framework coupled with the model-driven and penalty term-based loss function designs. Based on OHLC forecasts, this study devises three intraday trading strategies. Notably, our results evince that the forecasting accuracy of the Transformer outperforms the Naïve method, vector autoregression (VAR) and vector error correction model (VECM), multiple linear regression (MLR), support vector regression (SVR), and long short-term memory (LSTM) neural network when applied to different temporal granularities of Shanghai crude oil futures OHLC data. Furthermore, the three proposed intraday trading strategies exhibit higher annualized return rates and Sharpe ratios, alongside lower maximum drawdowns and standard deviations of returns in comparison to the conventional close-to-close strategy relying solely on the close price. Remarkably, the forecasting process and intraday trading strategies explicated in this study can equally apply to other futures products in the energy sector, including electricity, coal, and natural gas.

Benchmarking an allocation to the foreign Sub-portfolio from a South African perspective

This paper responds to the recent (2022) change to Regulation 28 of the South African Pension Funds Act which now permits an increased allocation (raised from 30% to 45%) in foreign investments. Our primary aim is to establish a strategic (long-term) benchmark weight for the allocation to foreign assets. Our secondary aim is to assist in building intuition on potential tactical (shorter-term) foreign allocation decisions. To ensure rigour in our study, we use a novel dataset dating back to the 1930s and we utilise methodologies in recent academic literature in the mean-variance framework. Our optimisation evidence supports a strategic foreign benchmark allocation of 39% (with 61% allocated to local asset classes). We highlight that this strategic foreign benchmark of 39% (probably for the first time) enables managers to potentially take on meaningful tactical overweight foreign positions. We establish that this strategic foreign benchmark would have reduced the risk (standard deviation of returns) of the local-only optimal portfolio significantly from 10% p.a. down to 8.7% p.a. over the 92 year period analysed, whilst increasing the return by an additional 1.1% p.a. over the local-only portfolio. Lastly, we provide guidance on tactical foreign allocation decisions based on four potential local economic regimes.

Impacts of COVID-19 Pandemic on the Price Volatility of Listed Commercial Bank Stocks in Vietnam

This article aims to estimate the relationship between COVID-19 and the price volatility of listed commercial bank stocks in Vietnam during the two most severely affected years of the pandemic (2020–2021), and measuring the impacts of macroeconomic factors on those stocks’ returns and their price volatility (measured by standard deviation of returns) with previous studies’ results before the pandemic. Using the data from 16 listed commercial banks’ stock returns on Ho Chi Minh Stock Exchange (HOSE) and Hanoi Stock Exchange (HNX) during the study period, we used OLS to find the effect, with important findings: (1) COVID-19 daily reported cases had a weak negative effect on Vietnam listed banks’ stock returns and hardly any relation with stock returns’ standard deviation. (2) GDP influenced commercial bank stock returns positively, while CPI, number of COVID-19 cases, and businesses closed had a negative effect. Also, listed commercial bank stock returns were insignificantly impacted by the interest rate. (3) Macroeconomic factors’ impact on the standard deviation of returns were weak, during the pandemic. GDPs and CPIs effect turned out to be insignificant while interest rate had a negative effect on the volatility rate, and was only significant in two out of the three models, implying potential negative impacts of COVID-19 on the macroeconomy. JELClassification: G21, F62, F65, G18, G28

Circular Economy, Stock Volatility, and Resilience to the COVID-19 Shock: Evidence from European Companies

Background: By decoupling economic growth from an intensive use of resources, preventing the impairment of natural capital, and enhancing resilience to system-wide shocks, the Circular Economy (CE) is a powerful opportunity to hedge against “linear” risk factors. In fact, it helps shielding against the risk of assets becoming stranded, can generate fresh and non-speculative demand for investments, and can improve investment results at both individual and portfolio levels. Problem: Therefore, equity investors into circular undertakings could benefit from (H1) reduced stock return volatility, as well as (H2) a greater ability to withstand exogenous negative events. Approach: For testing these hypotheses, we constructed a sample of 644 listed companies across EU-15 countries, plus Switzerland, and 17 different industries. We retrieved their market data in 2019–2020, as well as their accounting fundamentals in 2018–2019. By controlling for the latter, we investigated whether equity risk—either in total terms (i.e., the standard deviation of returns) or circumscribed to the systematic component thereof (i.e., the Beta against a European or global market index)—may be explained by a company’s degree of circularity, measured by the Circularity Score (CS). This is a novel indicator originally proposed by Zara and Ramkumar (2022), based on Refinitiv ESG data, the methodology whereof we significantly amended. As a core innovation, in weighting an entity’s performance on a CE framework, we assessed the latter’s “financial materiality” (i.e., relevance to the company’s business) at sub-industry level, applying the SASB Materiality Maps. Via OLS estimation, we tested our hypotheses (i) over the whole-time horizon, in a panel model; (ii) on specific timeframes, in a standard cross-sectional model. The latter was applied to either the entire 2020 or subperiods thereof: namely, with respect to the COVID-19 outbreak, we distinguished between a pre-shock, a shock and a post-shock phase. Our quest was refined to conduct a deeper investigation into the Oil & Gas industry, which is intrinsically the most exposed to linear risks and, also, did experience the widest volatility in 2020. Findings: Both H1 and H2 received widespread confirmation. The CS was found to exert a negative, significant and robust effect on all the three risk measures, over the whole timespan as well as in subperiods (particularly the post-shock phase). Also, amplifying effects were recorded on the Oil & Gas industry. Conclusions: Our results lend remarkable support to the idea that the CE is a powerful enabler of de-risking, also in case of a severe shock, with a view to mitigating the negative consequences and building back better. They call on firms and policymakers to foster the circular transition, thereby accelerating economic recovery in the aftermath of the pandemic crisis.

Planning resource allocation for husbandry management by portfolio optimization

The husbandry management is assessed in general by comparison of current and past economical results, which are used as a universal business metric. Sustainable management in general targets minimization of risk and maximization of the return for managing business activities. The minimization of the economic risk allows for decreasing the potential losses for the husbandry management and they are leading criteria for planning future resource allocations. The new point added in this research concerns simultaneously inclusion in the portfolio problem the risk formalization both as a standard deviation of return and the probability for losses as value-at-risk. Several portfolio problems are defined, considering the probability of losses as a goal function or constraint in the portfolio problems. The inclusion of these two formalizations allows the portfolio risk to decrease additionally in comparison with the classical portfolio problems, where the risk is quantified as a standard deviation of the portfolio return. The peculiarities of these problems and the corresponding optimal solutions are analyzed, which allows quantifying the resource allocation per different business activities. Numerical experiments are made with real data on animal husbandry, available from the Bulgarian National Statistics and the results are illustrated in a graphical way. The empirical comparison with these data gives benefits in decreasing the risk when both risk formalizations are applied in the portfolio problem.

Managerial ability and corporate risk-taking in an emerging economy

PurposeThe existing literature, generally based on US data, provides little evidence that supports whether managerial ability directly links to corporate risk-taking. Hence, this study aims to expand the limited extent by investigating the impact of managerial ability on risk-taking across Saudi firms.Design/methodology/approachThis study mainly uses a panel fixed-effects model, including firm-year and firm-industry, to analyse a sample of Saudi non-financial firms from the period 2008 – 2018. In the empirical analysis, the managerial ability is lagged by one year to mitigate endogeneity concerns that may arise from reverse causality. To avoid omitted variables bias, this study includes several firm-level control variables.FindingsThe empirical results show that the relationships between managerial ability and firm risk-taking measures are negative and statistically significant with the standard deviation of return on assets (sROA) and leverage; positive and statistically significant with the Z-score. These results indicate that firms managed by high-ability executives have the propensities to take less risk. The main results remain robust to additional sensitivity analyses including an alternative measure for managerial ability, an alternative proxy for risk-taking using logistic regression analysis, using financial crises as dummy variables, and using a cross-lagged panel model with fixed effects for endogeneity concerns.Practical implicationsWhen evaluating firms, all market and society participants including researchers, regulators, supervisors, policymakers, and boards ought to pay close attention to managerial ability as one of the main factors affecting risk-taking.Originality/valuePreviously, closely related studies, focussing on the US market, mainly find that managers with high ability are receptive to risk-taking. This paper offers further international insight into the relevant literature by providing evidence that capable managers are inclined to take low risks.

Pengaruh Ekuitas Merek Dan Kinerja Perusahaan Terhadap Risiko Perusahaan Yang Terdaftar Di Indeks LQ45

This study aims to examine the effect of brand equity and company performance on company risk. This study uses two models of corporate risk measurement, namely by using the standard deviation of Return on Assets and the standard deviation of Return on Equity. This study uses panel data regression with random effects model and data processing using Stata 14 software. The findings from this study indicate that brand equity has a positive and significant effect on company risk as measured by using the standard deviation of return on equity. While the company's performance proved to have a negative and significant effect on the company's risk.

Comparison of Performance and Risk of Tourism Companies, Restaurants and Hotels Before and During the Covid-19 Pandemic

This study aims to determine the performance and risks of tourism, restaurant and hotel companies during and before the covid 19 pandemic. This study uses four proxies to measure the company's performance, namely Return on Assets (ROA), Return on Equity (ROE), Tobins Q and Net Profit. Margin (NPM) and use two proxies to measure company risk, namely the standard deviation of Return on Assets (SDROA) and the standard deviation of Return on Equity (SDROE). The population in this study are tourism, restaurant and hotel companies for the period 2019-2020. The sampling technique used is purposive sampling technique based on certain criteria. The number of samples in this study were 15 companies with 120 observations. The data analysis technique used is to perform different tests before the pandemic and during the COVID-19 pandemic. The results showed that there were significant differences in the performance and risk of tourism, restaurant and hotel companies before the pandemic and during the pandemic.

Expected mean return—standard deviation efficient frontier approximation with low‐cardinality portfolios in the presence of the risk‐free asset

AbstractIn the expected mean return, standard deviation portfolio selection problem, the first step is usually to derive the set of efficient portfolios, which in the space of objective function values is represented by the efficient frontier. With modern methods and software, it is an easy task even for thousands of assets provided that the problem is continuous. However, investors often introduce the requirement to limit the number of assets in portfolios (portfolio cardinality). The resulting mixed‐integer quadratic formulations are computationally much more complex. In this work, we assume that besides risky assets, the risk‐free asset is available to the investor, and short selling is not allowed. Since in this case the efficient frontier cannot be directly derived by a quadratic solver, we propose a naive but intuitive heuristic to approximate the efficient frontier in the presence of the risk‐free asset. In contrast to the general‐purpose evolutionary heuristics, we exploit the underlying mechanism of portfolio composition. We show by numerical experiments that in large‐scale instances it works well, even compared to a state‐of‐the‐art evolutionary multiobjective optimization algorithm. Moreover, the heuristic produces portfolios of remarkably limited cardinalities.

Risk Performance on Financial Assessment of Insurance Firms in Egypt

The subject matter of this study is the analysis of the relationship between risk assessment and firm size on financial performance. The population encompasses thirty-nine listed insurance firms in Egypt during the period 1999 – 2019, whereas a sample of nineteen insurance companies was selected. The financial assessment is a dependent variable, while the independent variable is risk assessment. This study used general linear multivariate analysis and descriptive statistics. The article is an attempt to investigate the relationship between risk assessment and firm size on financial assessment of insurance sector in Egypt. The results indicate that there is significant positive linear relationship between standard deviation of return on equity, standard deviation of return on asset, and natural logarithm of total assets with return on equity. Moreover, there is significant positive linear relationship between standard deviation of return on equity, standard deviation of return on asset and natural logarithm of total assets where on return on asset. Therefore, there is significant positive linear relationship between standard deviation of return on equity and standard deviation of return on asset on liquidity. Nevertheless, there is a negative relationship between natural logarithm of total assets.

Analysis of performance and risk during a period of political instability: do political connections matter

This paper examines how the political connection affects corporate risk (measured by the standard deviation of return on assets and by the standard deviation of the stock return) and performance (measured by the return on equity and the stock return) during periods of adverse macroeconomic conditions in Tunisia. This study uses a sample of 55 Tunisian listed firms during the post-revolution period (2011-2018) and a generalised least square (GLS) approach is applied to test our hypotheses. First, findings show that political connection increases risk-taking behaviour and reduces corporate performance. Secondly, findings confirm that only the relation between the political connection and market risk varies negatively with political instability. Hence, Tunisian investors are reluctant to invest in political connected firms, which lead to market undervaluation.

The Future Value of Mutual Fund Investments: Average Return Standard Deviation = Annualized Return Forecasts

The Future Value of Mutual Fund Investments: Average Return Standard Deviation = Annualized Return Forecasts

The Impact of the Covid-19 Pandemic on Boursa Kuwait Return Volatility

The main objective of this research is to detect the impact of COVID-19 on return volatility of Boursa Kuwait main indexes using EGARCH and TGARCH models on the daily data from the All Share, Premier and Main indexes. The mean return during COVID-19 from February 24 to August 31, 2020, for the three indexes was negative with a high volatility value in the standard deviation compared to a positive return and low standard deviation for the period January 2, 2019, to February 23, 2020. Both periods’ returns for the market indexes exhibited negative skewness, large kurtosis values and abnormal distributions. There were significant EGARCH negative values during the COVID-19 period in the All Share and Premier indexes indicating leverage effects. The Main index reflected positive significant values due to the positive effects of government procedures that were implemented to counter the pandemic. The TGARCH model indicated significant negative values for the All Share and Main indexes during COVID-19 with decreased volatility when positive news on COVID-19 was announced. Using the threshold generalized autoregressive conditional heteroscedasticity (TGARCH) the Premier index value is positive and significant indicating an asymmetric effect showing that volatility increased when negative news on COVID-19 was broadcast. This is an important inference for market participants and policy makers particularly when there is a difference in the magnitude of an asymmetry.

Linear beta pricing with efficient/inefficient benchmarks and short-selling restrictions

We provide two security pricing models that can be used when short sales of risky securities are not permitted. The first model uses a benchmark located on the expected return-standard deviation efficient frontier without short sales and presents security expected returns as a weighted linear function of two betas, one induced by the benchmark and the other adjusting for the short-sale constraints. The second model uses a benchmark that is inefficient relative to the efficient frontier, does not allow short sales, and expresses security returns as a weighted linear function of three betas:one induced by the inefficient benchmark, and the other two adjusting simultaneously for the short-sales restrictions and the benchmark's inefficiency.These results complement the linear pricing models that link expected returns and betas by allowing, for efficient or inefficient expected return-standard deviation, benchmarks with restricted short sales.

RESPONSE OF STOCK MARKET DURING COVID-19 AND 2008 FINANCIAL CRISIS: A COMPARATIVE EVIDENCE FROM BRICS NATIONS

This study attempts to examine the response of stock markets amid the COVID-19 pandemic on prominent stock markets of the BRICS nation and compare it with the 2008 financial crisis by employing the GARCH and EGARCH model. First, average and variance of stock returns are tested for differences before and after the pandemic, t-test and F-test were applied. Further, OLS regression was applied to study the impact of COVID-19 on the standard deviation of returns using daily data of total cases, total deaths, and returns of the indices from the date on which the first case was reported till June 2020. Second, GARCH and EGARCH models are employed to compare the impact of COVID-19 and the 2008 financial crisis on the stock market volatility by using the data of respective stock indices for the period 2005–2020. The results suggest that the increasing number of COVID-19 cases and reported death cases hurt stock markets of the five countries except for South Africa in the latter case. The findings of the GARCH and EGARCH model indicate that for India and Russia, the financial crisis of 2008 has caused more stock volatility whereas stock markets of China, Brazil, and South Africa have been more volatile during the COVID-19 pandemic. The study has practical implications for investors, portfolio managers, institutional investors, regulatory institutions, and policymakers as it provides an understanding of stock market behavior in response to a major global crisis and helps them in taking decisions considering the risk of these events.

Diversified behavioral portfolio as an alternative to Modern Portfolio Theory

The traditional mean–variance approach has been complemented by alternative theories that use risk measures different from standard deviation of returns or involve additional distributional features of returns like skewness and kurtosis. We propose a portfolio choice model that combines different distributional characteristics of the returns in the decision-making making process, considering preferences of investors which are modeled as non-statistical uncertainties of investors using fuzzy theory. We use 20 stocks of the S&P500 from January 2013 to December 2017. We assess the obtained portfolios’ performance, and the diversified behavioral portfolios outperform than the mean–variance portfolio. This methodological proposal can be seen as a strong managerial tool to make investment portfolio decisions.

Board diversity and firm risk-taking in the tourism sector: Moderating effects of board independence, CEO duality, and free cash flows

This study examines the effect of board diversity on risk-taking for tourism firms and analyzes the moderating effect of board independence, CEO duality, and free cash flows in this proposed relationship. Using a composite index of board diversity and a sample of tourism firms from the US hotel, restaurant, and airline industries, we find that greater board diversity leads to lower risk-taking, measured in standard deviation of return on assets. Moreover, we report that the risk-reduction effect of board diversity is more profound when tourism firms have less board independence and less free cash flows for investments. When board diversity is decomposed into relation-oriented and task-oriented diversity attributes, we find that only the task-oriented diversity is influential in reducing firm risk-taking for tourism firms. Akin to main analysis, the board independence and free cash flows are significant moderators of the relationship between task-oriented diversity and firm risk-taking.

Relative Performance of Real Estate Exchange-Traded Funds

This paper examines the performance of 34 real estate exchange-traded funds (REETFs) over the period of May 2003 through September 2019. We construct equally-weighted REETF portfolios every month and compare them with the overall U.S. stock market as proxied by the S&P 500 value-weighted ETF (IVV) and the S&P 500 equal-weighted ETF (RSP). Our results show that over the entire time period the REETF portfolios experienced higher monthly returns, but also had a slightly higher standard deviation of returns. We also provide results controlling for risk differentials using the Sharp, Sortino, and Omega ratios. The results show that IVV and RSP had higher risk-adjusted performance using all of the various measures compared with REETFs portfolios. REETFs also had much higher risk and losses during the 2007–2009 financial crisis.

Application of Data Science for Understanding Emotional Dimensional Behavior and Their Connection to Uncertainty and Risk Behavior

This paper explores multidisciplinary application of emotions and human psychology within market behavior to analyse how emotional dimensions, extracted from Twitter messages and related to cryptocurrency market, are connected to future uncertainty and risk exposure. Although Twitter messages are often used to derive sentiment scores that are then linked to market performance, specific values of emotional components have not been utilised in the previous academic literature to analyze risk behavior. We connect VAD (valence, arousal and dominance) dimensions with the future hourly absolute value of returns, future 24-hour return standard deviation, future 24-hour downside deviation and future 24-hour maximal drawdown (all measuring market uncertainty and risk) on the cryptocurrency market. Results show that all target variables have various predictability from VAD dimensions, where lagged dominance variable (perceived level of control) is the key driver of predictability. Additionally, VAD dimensions have been grouped into distinct clusters by using the k-Means approach. A comparison of selected clusters on in-sample and out-of-sample data showed consistent predictability of identified clusters to all target variables. Results show that emotional components of human emotions, derived from cumulative Twitter messages, actually predict future uncertainty and risk with consistent clustering profile from lagged dominance VAD dimension where lower dominance values predict higher future risk and vice versa.

Bitcoin as a New Currency

Abstract Research background: Bitcoin is the most popular financial instrument within the new cryptocurrencies class, which emerged in the wake of the financial crisis of 2007/2008. Purpose: The purpose of this paper is to provide an analysis of Bitcoin from the perspective of the Polish market investor. More specifically, the aim of the empirical research presented in this study has been twofold: (1) comparison of Bitcoin with other currencies using returns and risk captured by the standard deviation of returns and (2) assessment of the sensitivity of the BTC/PLN exchange rate to the NBP’s monetary policy announcements. Results: Bitcoin appears to be weakly related to other currency exchange rates against the Polish zloty and the monetary policy announcements of the National Bank of Poland (NBP) have, effectively, no influence on the determination of the BTC/PLN exchange rate. Novelty: We discuss extensively the Bitcoin as a new asset on the financial market and we present the investigation of the BTC/PLN reactions to the monetary policy announcements in Poland, which is a novel analysis for this instrument using the Polish market data.