92 research outputs found
Droplet evaporation dynamics on surfaces
No full textDroplet evaporation governs many man-made and natural processes. Hence, it has been widely studied by many scientists over the past century. With the recent advancements in nanotechnology, many surfaces for two phase heat transfer have been developed including hydrophobic, biphilic and lubricantinfused surfaces. However, evaporation of droplets on these surfaces have not been explored in depth. Traditionally, evaporation on surfaces was characterized by observing the temporal size changes of a droplet. Yet, the transient nature coupled with the significant mass transfer governed gas dynamics occurring at the droplet three-phase contact line make the classical method crude. To accurately investigate evaporation dynamics on surfaces, we present a novel steady measurement technique. By utilizing a piezoelectric dispenser to feed microscale droplets (20 ≤ ≤ 400 μm) to a larger evaporating droplet at a prescribed frequency, we can create variable-sized droplets on any surface and study their evaporation rates by modulating the droplet addition frequency. Using our steady method, we studied evaporation of water and low surface tension fluids on surfaces including functional, biphilic, biconductive and lubricant-infused surfaces. We elucidated the physics governing the droplet evaporation process for each studied surface and working fluid. Furthermore, we developed an original high-speed focal-shift imaging technique to study droplet mobility on the interface. Our results not only shed light into the evaporation physics of droplets on different surfaces but also provides new avenues and strong experimental platforms for the study of phase change heat transfer processes that enable the decoupling of the intricate and length-scale dependent balance played by internal and external flows and binary-mixture dynamics, and the visualization of the interfacial dynamics.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Ahmet Gunay, accepted the attached license on 2019-04-12 at 18:06.The student, Ahmet Gunay, submitted this Dissertation for approval on 2019-04-12 at 18:10.This Dissertation was approved for publication on 2019-04-15 at 13:19.DSpace SAF Submission Ingestion Package generated from Vireo submission #13602 on 2019-08-22 at 16:21:14Made available in DSpace on 2019-08-23T20:47:22Z (GMT). No. of bitstreams: 2
GUNAY-DISSERTATION-2019.pdf: 3903161 bytes, checksum: 5e94946b0677fcee41a04e7f4c7dad43 (MD5)
LICENSE.txt: 4210 bytes, checksum: a2ad7010a8cd62193bcb82cebbde9fc1 (MD5)
Previous issue date: 2019-04-15Embargo set by: Seth Robbins for item 112310
Lift date: 2021-08-23T20:47:38Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112310
Lift date: 2021-08-23T20:48:32Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 112310 on 2021-08-24T09:15:20Z
Fractal Structure of the Stock Markets of Leading Asian Countries
No full textIn this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious long memory features, besides the Detrended Fluctuations Analysis (DFA), we also used Smith’s (2005) modified GPH method. As for fractal dimension calculations, they were conducted via Box-Counting and Variation tests. According to the results, while there is no long memory property in log returns of any index, we found evidence for long memory properties in the volatility of the HangSeng, the Shanghai Stock Exchange and the Straits Times Index. However, we could not find any sign of long memory in the volatility of Nikkei225 index using either the DFA or modified GPH test. Fractal dimension analysis also demonstrated that all raw index prices have fractal structure properties except for the Nikkei225 index. These findings showed that the Nikkei225 index has the most efficient market properties among these markets
DO WE LIVE IN A SIMULATION? A BEAUTIFUL FALLACY AND THE ART OF THE CODER
No full textHuman curiosity about existence often deepens at certain stages of awareness. Religion and philosophy have long sought to provide explanations, yet neither seems to fully disclose the information needed to grasp what is truly unfolding. In contemporary discourse, simulation hypothesis emerges as an alternative—or complementary—framework for interpreting creation, meaning, and illusion. This study explores questions about the purpose of life, the intention behind its design, and the role of illusion within it. Although my academic background lies in finance—a field seemingly distant from metaphysical inquiry—I draw on its reasoning style and its habit of modeling complex processes to build analogies that illuminate existential questions. In particular, I employ analogies from both finance and physics: financial reasoning provides a comparative framework, while concepts such as holography, fractals, and quantum entanglement are used not as literal explanations but as conceptual bridges for rethinking creation, perception, and the role of the Coder. Within this framework, spacetime is framed not as ultimate reality but as the Demonstration Layer—a projection in which the Coder’s research question is tested. This work does not claim to provide a definitive answer; rather, it offers a reflective attempt to revisit enduring inquiries through a modern, interdisciplinary len
Source Of The Multifractality In Exchange Markets: Multifractal Detrended Fluctuations Analysis
No full textIn this study, we analyzed the multifractality and the source of multifractality of the returns of GBP/USD, EUR/USD, USD/JPY and USD/CHF currencies. In the examination of multifractality we performed the Multifractal Detrended Fluctuation Analysis (MF-DFA). Also, we used shuffled and surrogated data that was derived from the Statically Transformed Autoregressive Process (STAP) method to determine the source of multifractality. According to the results, GBP/USD returns have monofractal features, whereas EUR/USD, USD/JPY and USD/CHF returns have multifractal behaviours. The tests concerning the source of multifractality indicated that the reason of multifractality for EUR/USD and USD/JPY returns is fat-tails of the probability density function of returns, whereas the reason of multifractality of USD/CHF returns are both long memory and fat tails. Also we have seen that there is an ambiguous relationship between the liquidity of the currency market and multifractality
Kredi Temerrrt Swapp, Varllk Swapp ve SSffr Volatilite Spreadleri zerinden Bir Analiz: Darbe Teeebbbss ve BBST 100 Volatilitesi (An Analysis Through Credit Default Swap, Asset Swap and Zero-Volatility Spreads: Coup Attempt and BIST 100 Volatility)
No full textImpact of Public Information Arrivals on Cryptocurrency Market: A Case of Twitter Posts on Ripple
No full textPublic information arrivals and their immediate incorporation in asset price is a key component of semi-strong form of the Efficient Market Hypothesis. In this study, we explore the impact of public information arrivals on cryptocurrency market via Twitter posts. The empirical analysis was conducted through various methods including Kapetanios unit root test, Maki cointegration analysis and Markov regime switching regression analysis. Results indicate that while in bull market positive public information arrivals have a positive influence on Ripple's value; in bear market, however, even if the company releases good news, it does not divert out the Ripple from downward trend
Markov Regime Switching GARCH Model and Volatility Modeling for Oil Returns
No full textIn conjunction with the recent alternative models, a wide literature has been established for volatility modeling in finance theory. In this study, we examine return volatility of Brent oil returns through GARCH, EGARCH, GJR-GARCH and MRS-GARCH models. As a preliminary test concerning the potential regimes, first, we use modified ICSS test in order to examine the existence of breaks in the variance of return series. All volatility models are formed under normal, GED and student-t distributions. According to the AIC and BIC values, MRS-GARCH model outperforms all other alternative models. Another interesting result is the failure of the models that formed under normal distribution.
Keywords: Markov Regime Switching GARCH; Oil Volatility; Variance Breaks
JEL Classifications: C14; C22; C58; G1
Do major health shocks affect the interconnectedness of E-commerce and electronic payment markets? a regional analysis
No full textIn view of the recent pandemic and its associated impact, this study examines the relationship between e-commerce and mobile/electronic payment markets by utilizing two indices as proxies of these market developments. The study employed DCC-GARCH modeling, Hacker–Hatemi bootstrap causality test, Diebold–Yilmaz volatility spillover analysis and a volatility modeling incorporating COVID19 related death statistics of three regions: America, Europe and Asia. The results show that while the two markets display very high time-varying correlations across years, a significant causal relationship is only found during the pandemic. Causality runs from the mobile/electronic payment index to the e-commerce index. Volatility spillover analysis further supports this finding. Interestingly, the mobile/electronic payment index tends to become a net volatility transmitter in the pandemic period. When we incorporate regional COVID19 statistics on cases and deaths in the volatility modeling of the e-commerce index, we find that only COVID19 deaths in Europe have a significant effect on e-commerce returns. This result may be rationalized by the relative tightness of the e-commerce market in Europe compared to America and Asia. Likewise, demographic characteristics might be another potential driver for our findings.Full Tex
Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models
No full textPrecise modeling and forecasting of the volatility of energy futures is vital to structuring trading strategies in spot markets for risk managers. Capturing conditional distribution, fat tails and price spikes properly is crucial to the correct measurement of risk. This paper is an attempt to model volatility of energy futures under different distributions. In empirical analysis, we estimate the volatility of Natural Gas Futures, Brent Oil Futures and Heating Oil Futures through GARCH and APARCH models under gev, gat and alpha-stable distributions. We also applied various VaR analyses, Gaussian, Historical and Modified (Cornish-Fisher) VaR, for each variable. Results suggest that the APARCH model largely outperforms the GARCH model, and gat distribution performs better in modeling fat tails in returns. Our results also indicate that the correct volatility level, in gat distribution, is higher than those suggested under normal distribution with rates of 56%, 45% and 67% for Natural Gas Futures, Brent Oil Futures and Heating Oil Futures, respectively. Implemented VaR analyses also support this conclusion. Additionally, VaR test results demonstrate that energy futures display riskier behavior than S&P 500 returns. Our findings suggest that for optimum risk management and trading strategies, risk managers should consider alternative distributions in their models. According to our results, prices in energy markets are wilder than the perception of normal distribution. In this regard, regulators and policy makers should enhance transparency and competitiveness in the energy markets to protect consumers.</jats:p
- …
