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1 |
The systematic risk estimation models: A different perspective
مدلهای برآورد سیستماتیک سیستماتیک: دیدگاه متفاوت-2020 In practice, the capital asset pricing model (CAPM) using the parametric estimator is almost certainly being used to estimate a firms systematic risk (beta) and cost of equity as in Eq. (1). However, the parametric estimators, even when data is normal, may not yield better performance compared with the non-parametric estimators when outliers existed. This research argued for the non-parametric Bayes estimator to be employed in the CAPM by applying both advance and basic evaluation criteria such as hypotheses/confidence intervals of the AIC/DIC, model variance, fit, and error, alpha, and beta and its standard deviation. Using all the S&P 500 stocks having monthly data from 07/2007–05/2019 (450 stocks) and the Bayesian inference, we showed the non-parametric Bayes estimator yielded less number of zeroed betas and smaller alpha compared with the parametric Bayes estimator. More importantly, this non-parametric Bayes yielded the statistically significantly smaller AIC/DIC, model variance, and beta standard deviation and higher model fit compared with the parametric Bayes estimator. These findings indicate the CAPM using the non-parametric Bayes estimator is superior compared with the parametric Bayes estimator, a contrast of common practice. Hence, the non-parametric estimator is recommended to be employed in asset pricing work. Keywords: Asset pricing | CAPM | Systematic risk | Cost of equity | Bayes estimators | Statistics | Corporate finance | Financial market | International finance | Pricing | Risk management | Business | Economics |
مقاله انگلیسی |
2 |
Smart frost measurement for anti-disaster intelligent control in greenhouses via embedding IoT and hybrid AI methods
اندازه گیری یخ زدگی هوشمند برای کنترل هوشمند ضد فاجعه در گلخانه ها از طریق تعبیه روش های اینترنت اشیا و هوش مصنوعی ترکیبی-2020 A novel Agro-industrial IoT (AIIoT) technology and architecture for intelligent frost forecasting in greenhouses
via hybrid Artificial Intelligence (AI), is reported. The Internet of Things (IoT) allows the objects
interconnection on the physical world using sensors and actuators via the Internet. The smart system
was designed and implemented through a climatological station equipped with Artificial Neural
Networks (ANN) and a fuzzy associative memory (FAM) for ecological control of the anti-frost disaster
irrigation. The ANN forecasts the inside temperature of the greenhouses and the fuzzy control predicts
the cropland temperatures for the activation of five output levels of the water pump. The results were
compared to a Fourier-statistical analysis of hourly data, showing that the ANN models provide a temperature
prediction with effectiveness higher than 90%, as compared to monthly data model. Moreover,
results of this process were validated through the determination of the coefficient of variance analysis
method (R2). Keywords: Smart frost measurement in greenhouses | Anti-frost irrigation | Artificial Neural Network | Fuzzy expert system | Internet-of-things | Hybrid AI methods |
مقاله انگلیسی |
3 |
Is estimating the Capital Asset Pricing Model using monthly and short-horizon data a good choice?
آیا تخمین مدل قیمت گذاری دارایی سرمایه با استفاده از داده های ماهانه و افق کوتاه انتخاب خوبی است؟-2020 This research argued for estimating the Capital Asset Pricing Model (CAPM) using daily and medium-horizon data over monthly and short horizon-data. Using a Gibbs sample, the Bayesian framework via both parametric and non-parametric Bayes estimators, confidence interval approach, and six data sets (two daily, two weekly, and two monthly data) from a sample of 150 randomly selected S&P 500 stocks from 2007 – 2019, the empirical results showed that the CAPM using daily data yielded a statistically significant higher model fit and smaller Beta standard deviation, model error, and Alpha compared with monthly data. The CAPM using medium-horizon data yielded a statistically significant higher model fit, smaller Beta standard deviation and Alpha, and much less zeroed Betas compared with short-horizon data. These findings show 1) daily data is more reliable and efficient, has higher forecasting power, and fits better with the assumption of market efficiency compared with monthly data. 2) Medium-horizon data is more reliable and efficient, has more explanatory power, and fits better with the assumption of market efficiency compared with monthly data. Therefore, these findings challenge the common practices of using monthly (quarterly/annually) and short-horizon data among the practitioners and researchers in asset pricing work. Keywords: Asset pricing | Bayes estimators | CAPM | Monthly data | Short-horizon data | Statistics | Economics | Finance | Accounting | Pricing | Macroeconomics | Econometrics | Business | Risk management |
مقاله انگلیسی |
4 |
The relationship between commodity markets and commodity mutual funds: A wavelet-based analysis
رابطه بین بازارهای کالا و سرمایه های متقابل کالا: یک تحلیل مبتنی بر موج کوچک-2018 This paper examines the causal relationship between commodities funds and returns using monthly data for the period May 1997–August 2015. Given the strong evidence of nonlinearity and structural breaks, we use wavelets to analyse causality between the two variables at both time and frequency domains. Wavelet coherency reveals that these two variables are primarily positively related in the short-run and over the period of 2008–2015. When we investigate the phase differences over this period, we observe that returns have predicted flows over the period of 2008–2012, with causality running in the other direction thereafter.
keywords: Commodity returns and flows| Granger causality| Nonlinearity| Time and frequency domains| Wavelet |
مقاله انگلیسی |
5 |
Google Trends and tourists arrivals: Emerging biases and proposed corrections
گرایشات گوگل و ورودی های گردشگران: انحراف های پدید آمده و تصحیح های پیشنهادی-2018 As search engines constitute a leading tool in planning vacations, researchers have adopted search engine query data to predict the consumption of tourism products. However, when the prevailing shares of visitors come from countries in different languages and with different dominating search engine platforms, the identification of the aggregate search intensity index to forecast overall international arrivals, becomes challenging since two critical sources of bias are involved. After defining the language bias and the platform bias, this study focuses on a destination with a multilingual set of source markets along with different dominating search engine platforms. We analyze monthly data (2004–2015) for Cyprus with two non-causality testing procedures. We find that the corrected aggregate search engine volume index, adjusted for different search languages and different search platforms, is preferable in forecasting international visitor volumes compared to the non-adjusted index.
keywords: Web search intensity |Google Trends |Tourists arrivals |
مقاله انگلیسی |
6 |
The role of active management and asset allocation policy on government and corporate bond fund returns
نقش سیاست مدیریت فعال و تخصیص دارایی در صندوق اوراق قرضه دولتی و شرکتی بازدهی می شود-2018 The role of asset allocation policy and active management on equity mutual fund returns has been a popular research topic, while there is
almost no literature on the subject covering bond funds. We check sources of performance for Israeli corporate and government bond funds,
which together account for above 70% of the Israeli mutual fund market, using a unique monthly database of approximately 10-years. Our
results reveal that active management is far more important than policy for corporate bond fund returns, which is mainly attributable to
managers security selection skills. The reverse is true for government bond funds and strategic long term policies account for a larger part of
excess market return variability. Furthermore, if we take into account management fees, government bond funds lose from active management.
The greater heterogeneity of investments open to corporate bond funds is a possible explanation for the difference in results.
Keywords: Active management; Bond funds; Corporate bonds; Policy; Security selection; Timing |
مقاله انگلیسی |
7 |
Characterizing the behavior of handheld devices and its implications
توصیف رفتار دستگاه های دستی-2017 The Bring-Your-Own-Handheld-device (BYOH) phenomenon continues to make inroads as more people
bring their own handheld devices to work or school. While convenient to device owners, this trend
presents novel management challenges to network administrators as they have no control over these
devices and no solid understanding of the behavior of these emerging devices. In order to cope with
the impact of these BYOHs on current existing network management infrastructures, we identify two
tightly-coupled questions that network administrators need to answer: (a) how do these BYOHs behave?
and (b) how can we manage them more effectively based on the understanding of their behaviors? In
response, we design and deploy Brofiler, a framework that could enable network administrators to effec
tively manage BYOHs via behavior-aware profiling. Our behavior-aware profiling captures the behaviors of
each individual BYOH and improves the visibility on managing these BYOHs. In detail, the contributions
of our work are three-fold. First, we present Brofiler, a time-aware device-centric approach for grouping
devices into intuitive behavioral groups from multiple perspectives, including data plane, temporal be
havior, and the protocol and control plane. Second, we conduct an extensive study of BYOHs using our
approach with real data collected over a year, and highlight several novel insights on the behavior of
BYOHs. For example, we find that 70% of the BYOHs generate 50% of their monthly data traffic in one
day, while remaining mostly idle the rest of the month. In addition, 68% of BYOHs do not conform to
DHCP protocol specifications. Third, we present the implications of our study based on the framework
in DHCP management, bandwidth management and access control. Overall, our approach could enable
network administrators better understand and manage these new emerging devices for their networks in
the post-PC era.
Keywords: Handheld devices | Behavior | Measurement | Management |
مقاله انگلیسی |
8 |
Importance of early snowfall for Swedish ski resorts: Evidence based on monthly data
اهمیت بارش برف زود هنگام اسکی سوئدی: شواهد بر اساس داده های ماهانه-2016 Since the early 1970s, Sweden has experienced an almost uninterrupted surge in demand for downhill skiing. However, from the 2009/2010 season, lift ticket sales have stagnated. With the use of monthly data, this study investigates the role of snow depth and economic factors in the demand for downhill skiing in Sweden. The empirical approach is based on a seemingly unrelated regression model, allowing snow conditions, but not economic factors to differ during the season. The estimates show that an early season increase in natural snow depth by 10 cm raises the growth rate of lift ticket sales by 9 percentage points in the same period. Further, the results indicate that downhill skiing is characterised by low in- come and price elasticities, implying weak impacts on demand for such changes. The price increase of lift tickets exceeds that of the inflation rate. The recent decline in demand might indicate changed leisure preferences.© 2015 Elsevier Ltd. All rights reserved.
Swedish ski resorts | Snow depth | Snow in early and late season | Winter tourism | Demand for downhill skiing | Income and price elasticities |
مقاله انگلیسی |
9 |
How strong is the linkage between tourism and economic growth in Europe
ارتباط بین گردشگری و رشد اقتصادی در اروپا چگونه قوی است-2015 In this study, we examine the dynamic relationship between tourism growth and economic growth, using a
newly introduced spillover index approach. Based on monthly data for 10 European countries over the period
1995–2012, our analysis reveals the following empirical regularities. First, the tourism-economic growth
relationship is not stable over time in terms of both magnitude and direction, indicating that the tourism-led
economic growth (TLEG) and the economic-driven tourism growth (EDTG) hypotheses are time-dependent.
Second, the aforementioned relationship is also highly economic event-dependent, as it is influenced by the
Great Recession of 2007 and the ongoing Eurozone debt crisis that began in 2010. Finally, the impact of these
economic events is more pronounced in Cyprus, Greece, Portugal and Spain, which are the European countries
that have witnessed the greatest economic downturn since 2009. Plausible explanations of these results are
provided and policy implications are drawn.
Keywords:
Tourism-led economic growth
Economic-driven tourism growth
Spillover
Time-varying relationship
Variance decomposition
Europe |
مقاله انگلیسی |