Strategic investment decisions under fast mean-reversion stochastic volatility

2010 ◽  
Vol 27 (1) ◽  
pp. 61-69 ◽  
Author(s):  
Max O. Souza ◽  
Jorge P. Zubelli
Keyword(s):  
Stochastic Volatility ◽  
Investment Decisions ◽  
Mean Reversion ◽  
Strategic Investment

Strategic IT Investment Decisions

2011 ◽  
pp. 3589-3593
Author(s):  
Tzu-Chuan Chou ◽  
Robert G. Dyson ◽  
Philip L. Powell
Keyword(s):  
Organizational Performance ◽  
Decision Process ◽  
Investment Decision ◽  
Investment Decisions ◽  
Decision Processes ◽  
It Investment ◽  
Strategic Investment ◽  
Integrative Framework ◽  
Concept Of Information ◽  
Information Intensity

As many as half the decisions taken in organizations result in failure (Nutt, 1999). As information technology (IT) assumes a greater prominence in firms’ strategic portfolios, managers need to pay more attention to managing the technology. However, while IT can have a significant impact on organizational performance, it can also be a major inhibitor of change and can be a resource-hungry investment that often disappoints. Organizations can best influence the success of IT projects at the decision stage by rejecting poor ones and accepting beneficial ones. This may enable better implementation, as Nutt (1999) suggests most decision failures are due to implementation failure that tends to be under managers’ control. However, little is known about IT decision processes. Research demonstrates the importance of managing strategic IT investment decisions (SITIDs) effectively. SITIDs form part of the wider range of corporate strategic investment decisions (SIDs) that cover all aspects in which the organization might wish to invest. Strategic investment decisions will have different degrees of IT intensity that may impact outcome. IT investment intensity is the degree to which IT is present in an investment decision. That is, some decisions will be wholly about IT investments while others will have little or no IT—most, though, will be blended programs of IT and non-IT elements. Here, IT investment intensity is defined as the ratio of IT spending to total investment. The higher the IT investment intensity, the more important IT is to the whole investment. For example, Chou, Dyson, and Powell (1997) find IT investment intensity to be negatively associated with SID effectiveness. The concept of IT intensity is similar to, but also somewhat different from, the concept of information intensity. Information intensity is the degree to which information is present in the product or service (Porter & Millar, 1985). Management may use different processes in order to make different types of decisions (Dean & Sharfman, 1996). The link between decision process and outcome is so intimate that “the process is itself an outcome” (Mohr, 1982, p. 34). This may imply that the link between IT investment intensity and SID effectiveness is not direct but that the impact of IT investment intensity may be through the decision process. If different IT intensity in projects leads to different decision processes, leading to different outcomes, then it is important to know what factors act in this, in evaluating and managing SITIDs. This chapter presents an integrative framework for exploring the IT investment intensity-SID effectiveness relationship.

Noise trading and stock market bubbles: what the derivatives market is telling us

2020 ◽  
Vol 46 (9) ◽  
pp. 1165-1182
Author(s):  
Scott B. Beyer ◽  
J. Christopher Hughen ◽  
Robert A. Kunkel
Keyword(s):  
Stochastic Volatility ◽  
Noise Level ◽  
Implied Volatility ◽  
Mean Reversion ◽  
Jump Diffusion ◽  
Futures Prices ◽  
Noise Traders ◽  
Content Type ◽  
Noise Trading ◽  
Technology Bubble

PurposeThe authors examine the relation between noise trading in equity markets and stochastic volatility by estimating a two-factor jump diffusion model. Their analysis shows that contemporaneous price deviations in the derivatives market are statistically significant in explaining movements in index futures prices and option-market volatility measures.Design/methodology/approachTo understand the impact noise may have in the S&P 500 derivatives market, the authors first measure and evaluate the influence noise exerts on futures prices and then investigate its influence on option volatility.FindingsIn the period from 1996 to 2003, this study finds significant changes in the volatility and mean reversion in the noise level and a significant increase in its relation to implied volatility in option prices. The results are consistent with a bubble in technology stocks that occurred with significant increases in noise trading.Research limitations/implicationsThis study provides estimates for this model during the periods preceding and during the technology bubble. The study analysis shows that the volatility and mean reversion in the noise level are much stronger during the bubble period. Furthermore, the relation between noise trading and implied volatility in the futures market was of a significantly larger magnitude during this period. The study results support the importance of noise trading in market bubbles.Practical implicationsBloomfield, O'Hara and Saar (2009) find that noise traders lower bid–ask spreads and improve liquidity through increases in trading volume and market depth. Such improved market conditions could have positive effects on market quality, and this impact could be evidenced by lower implied volatility when noise traders are more active. Indeed, the results in this study indicate that the level and characteristics of noise trading are fundamentally different during the technology bubble, and this noise trading activity has a larger impact during this period on implied volatility in the options market.Originality/valueThis paper uniquely analyzes derivatives on the S&P 500 Index in order to detect the presence and influence of noise traders. The authors derive and implement a two-factor jump diffusion noise model. In their model, noise rectifies the difference of analysts' opinions, market information and beliefs among traders. By incorporating a reduced-form temporal expression of heterogeneities among traders, the model is rich enough to capture salient time-series characteristics of equity prices (i.e. stochastic volatility and jumps). A singular feature of the authors’ model is that stochastic volatility represents the random movements in asset prices that are attributed to nonmarket fundamentals.

Managing Strategic IT Investment Decisions

2005 ◽  
pp. 1875-1879
Author(s):  
Tzu-Chuan Chou ◽  
Robert G. Dyson ◽  
Philip L. Powell
Keyword(s):  
Organizational Performance ◽  
Investment Decision ◽  
Investment Decisions ◽  
Decision Processes ◽  
It Investment ◽  
Strategic Investment ◽  
Intensity Information ◽  
Total Investment ◽  
Concept Of Information ◽  
Information Intensity

IT can have a significant impact on organizational performance, but it can also be a major inhibitor of change and can be a resource-hungry investment that often disappoints. Organizations can best influence the success of IT projects at the decision stage by rejecting poor ones and accepting beneficial ones. However, little is known about IT decision processes. Research demonstrates the importance of managing strategic IT investment decisions (SITIDs) effectively. SITIDs form part of the wider range of corporate strategic investment decisions (SIDs) that cover all aspects that the organization might wish to invest in. SIDs will then have different degrees of IT intensity that may impact on outcome. IT investment intensity is the degree to which IT is present in an investment decision. Here, IT investment intensity is defined as the ratio of IT spending to total investment. The higher IT investment intensity, the more important IT is to the whole investment. For example, Chou et al. (1997) find IT investment intensity to be negatively associated with SID effectiveness. The concept of IT intensity is similar to, but also somewhat different from, the concept of information intensity. Information intensity may be defined as the degree to which information is present in the product or service of a business (Porter & Millar, 1985).

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