Decomposing the Bid-Ask Spread of Stock Options: A Trade and Risk Indicator Model

2007 ◽  
Author(s):  
Laurie Prather ◽  
David Michayluk ◽  
Li-Anne Elizabeth Woo ◽  
Henry Yip
Keyword(s):  
Stock Options ◽  
Risk Indicator ◽  
Bid Ask Spread ◽  
Indicator Model

Decomposing the Bid-Ask Spread of Stock Options: A Trade and Risk Indicator Model

2009 ◽  
Author(s):  
David Michayluk ◽  
Laurie Prather ◽  
Li-Anne Elizabeth Woo ◽  
Henry Yip
Keyword(s):  
Stock Options ◽  
Risk Indicator ◽  
Bid Ask Spread ◽  
Indicator Model

scholarly journals Leading internal and external sources of credit risk in the top South African banks

2014 ◽  
Vol 4 (3) ◽  
pp. 51-65
Author(s):  
Tankiso Moloi
Keyword(s):  
Credit Risk ◽  
South African ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Principal Component ◽  
Risk Indicators ◽  
Risk Indicator ◽  
The South ◽  
Equation Modelling ◽  
Indicator Model

This paper aimed at identifying the leading credit risk indicators in the South African banking context as well as the development of an integrated leading credit risk indicator model. A content analysis was used as a data extraction methodology and structural equation modelling was used as a data analysis methodology. The results obtained indicated that utilising the structural equation modelling, gross savings, and prime overdraft rates, number of judgements, business insolvencies and unemployment rates were formulated as leading economic and market (external) indicators of credit risk in the South African banking context. Similarly, utilising the principal component analysis, bank asset quality, bank asset concentration as well as bank trading and hedging activities were formulated as leading bank specific (internal) indicators of credit risk in the South African banking context. The Integrated Leading Credit Risk Indicator Model (ICRIM) was formulated utilising the accepted leading credit risk indicators. The ICRIM parameters were benchmarked against the generally accepted fit indices such as the RMSEA, comparative fit (baseline comparison) as well as the Hoelter and its results output were found to be consistent with these generally accepted fit indice

Stock Options als ein Instrument erfolgsorientierter Vergütung bei im NEMAX 50 notierten Unternehmen

Controlling ◽  
2002 ◽  
Vol 14 (12) ◽  
pp. 707-714
Author(s):  
Christian Krensel ◽  
Andreas Siemes ◽  
Sina Afra
Keyword(s):  
Stock Options

Firm Valuation and Accounting for Employee Stock Options

CFA Digest ◽  
1997 ◽  
Vol 27 (3) ◽  
pp. 9-11
Author(s):  
Frank T. Magiera
Keyword(s):  
Stock Options ◽  
Firm Valuation ◽  
Employee Stock Options

The Subjective and Objective Evaluation of Incentive Stock Options

CFA Digest ◽  
2006 ◽  
Vol 36 (3) ◽  
pp. 86-87
Author(s):  
William H. Sackley
Keyword(s):  
Stock Options ◽  
Objective Evaluation

“Stock Options and the Lying Liars Who Don't Want to Expense Them”: Author's Response

2004 ◽  
Vol 60 (6) ◽  
pp. 14-14 ◽  
Author(s):  
Clifford S. Asness
Keyword(s):  
Stock Options

Uji Komparasi Abnormal Return, Trading Volume, Trading Frequency, Dan Bid-Ask Spread Sebelum Dan Sesudah Share Split

2016 ◽  
Vol 8 (2) ◽  
pp. 24-45
Author(s):  
Tania Hayu Safira ◽  
Febryanti Simon
Keyword(s):  
Abnormal Return ◽  
Trading Volume ◽  
Stock Exchange ◽  
Distributed Data ◽  
Trading Frequency ◽  
Bid Ask Spread ◽  
Analysis Technique ◽  
Before And After ◽  
Test Of Hypothesis ◽  
Kolmogorov Smirnov

This study is event study that was conduct to examine the differences of abnormal return, trading volume, trading frequency and bid-ask spread before and after the events of share split. The object of this research is the companies that did share split and listed in Indonesia Stock Exchange in 2008 - 2015. The samples are 30 companies chosen by purposive sampling method. The criteria are the company did not do corporate action right issue, pre-emptive rights, a share dividend and bonus shares in the same year with share split. Event window used in this study was 30 days consisting of 15 days before and 15 days after the share split. Data analysis technique begins with a test of normality using Kolmogorov – Smirnov and transform for unnormally distributed data. Then, test of hypothesis using Paired t – test to compare the differences before and after share split. The results of this study showed that volume trading activity and trading frequency had significant differences before and after the share split. While, variable abnormal return and bid-ask spread had not significant differences before and after the share split. Keywords: Abnormal return, bid-ask spread, share split, trading frequency, trading volume.

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