Time Series Analysis and Calibration to Option Data: A Study of Various Asset Pricing Models

2015 ◽  
pp. 121-126
Author(s):  
Giuseppe Campolieti ◽  
Roman N. Makarov ◽  
Arash Soleimani Dahaj
Keyword(s):  
Time Series ◽  
Asset Pricing ◽  
Time Series Analysis ◽  
Pricing Models ◽  
Series Analysis ◽  
Asset Pricing Models

scholarly journals THE SEARCH FOR TIME-SERIES PREDICTABILITY-BASED ANOMALIES

2021 ◽  
Vol 0 (0) ◽  
pp. 1-19
Author(s):  
Javier Humberto Ospina-Holguín ◽  
Ana Milena Padilla-Ospina
Keyword(s):  
Time Series ◽  
Asset Pricing ◽  
Market Timing ◽  
The United States ◽  
Trading Rule ◽  
Optimal Parameters ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Asset Pricing Models ◽  
Out Of Sample

This paper introduces a new algorithm for exploiting time-series predictability-based patterns to obtain an abnormal return, or alpha, with respect to a given benchmark asset pricing model. The algorithm proposes a deterministic daily market timing strategy that decides between being fully invested in a risky asset or in a risk-free asset, with the trading rule represented by a parametric perceptron. The optimal parameters are sought in-sample via differential evolution to directly maximize the alpha. Successively using two modern asset pricing models and two different portfolio weighting schemes, the algorithm was able to discover an undocumented anomaly in the United States stock market cross-section, both out-of-sample and using small transaction costs. The new algorithm represents a simple and flexible alternative to technical analysis and forecast-based trading rules, neither of which necessarily maximizes the alpha. This new algorithm was inspired by recent insights into representing reinforcement learning as evolutionary computation.

scholarly journals The Gap between the Returns that Calculated by Capital Asset Pricing Model and the Actual Returns in Abu Dhabi Securities Exchange (ADX): Evidence from the United Arab Emirates

2017 ◽  
Vol 13 (3) ◽  
pp. 126
Author(s):  
Anas Ali Al-Qudah
Keyword(s):  
Time Series ◽  
Asset Pricing ◽  
Time Series Analysis ◽  
Capital Asset Pricing Model ◽  
Abu Dhabi ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Series Analysis

This study aimed to compare the Historical Returns (Rit) in companies listed in Abu Dhabi Securities Exchange (ADX) with the return which calculated by Capital Asset Pricing Model (E(Rit)) for the same companies and periods, and trying to figure out the level of dispersion, distortions and differences between them, and trying to figure out the strengths and weaknesses for the CAPM to explain the variances which happened in the Annual Return.The researcher used the time series analysis to achieve the target of this study, using Microsoft Office Excel software to introduce some figure and graphs which considered as output from Scatter charts, which are often used to find out if there's a relationship between variable X and Y to make judgment on the gap between the variables mentioned before.The researcher found that in the most of the study sample firms the capital asset pricing model could not to predict the returns were generated by companies in Abu Dhabi Securities Exchange (ADX), except in the banking sector, the result was amazing because the graphs which output from the time series analysis show the ability of CAPM to predict the Historical Returns, they were very closed and they Walking in the same direction without volatility.After the results appear in the time-series analysis researcher can says that there are weaknesses in the ability of CAPM to predict the returns in the financial markets which consistent with the (Fama & French, 1992) and with most studies conducted in this regard, but the model shows high ability to predict the returns in the banking sector. Therefore, the researchers can generalization this result on the financial markets in the United Arab Emirates. uage:EN-US;mso-fareast-language:ZH-CN;mso-bidi-language:AR-SA'>A critical demand for more nurses 30%-40% in certain units due to high work load. Most of the nurses were not satisfied about monitory compensation, participation in decision making and inadequate supplies.

Dynamical Peculiarities of Concatenational Changes in Functional Cardiovascular Parameters

2018 ◽  
Vol 3 (82) ◽  
Author(s):  
Eurelija Venskaitytė ◽  
Jonas Poderys ◽  
Tadas Česnaitis
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Functional State ◽  
The Body ◽  
Functional Changes ◽  
High Intensity Training ◽  
Series Analysis ◽  
Greco Roman ◽  
St Segment ◽  
Standard Lead

Research  background  and  hypothesis.  Traditional  time  series  analysis  techniques,  which  are  also  used  for the analysis of cardiovascular signals, do not reveal the relationship between the  changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research  results.  Significant  differences  were  found  between  inter-parametric  connections  of  ST  segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the  functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

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