Standard Deviations Use In The Business World

impact of these announcements on stock returns is found to be marginally positive with +0.44

Extreme movements in stock prices will be followed by subsequent price movements in the opposite direction.

a. Firstly, investors tend to invest in companies with stable earnings rather than one with volatile earnings. With stable earnings, there will be more likely an issuance of dividends and investors could easily predict the company’s future earnings compared to one with unstable earnings. With consistent earnings generated, it gives investors a secured feeling that it will again generate earnings as predicted. Confidence in the growth of rate of earnings is crucial because stable earnings growth further may increase further business prospective and are translated into higher stock and dividend returns. It is also crucial to have stable earnings as the growth in stock price is closely dependent on the growth of

Second, research on Flash Crash stated that HFT has the impact to create irregular volatility because HFTs sold the S&P 500 stocks which E-Mini was linked and reinforced the illusion of event to scared fundamental buyers out of the market. Under normal market conditions, HFT decreases a short term volatility by making it possible to buy and sell without significantly altering prices. (Prewitt, 2012). In addition, Brogaard showed HFT data from 120 US stock from the period 2008 to 2010 that high levels of HFT performance led to lower volatility, but Foucault et al. conflicted that investors provide more stock market volatility when they have faster access to news. (Manahov et al, 2014).

As shown on figure 1, the Bollinger band which indicates the deviation of the price. Since, the price is currently at the bottom line of the Bollinger band, it can be forecasted that the price will go up as Bollinger band is one of technical indicators which suggests that the price should go up when it reaches the bottom line and it should go down

23. Jawahar Babu K.V.S.N and B.Muniraja Selkhar, IOSR Journal of Business and Management (IOSRJBM) ISSN: 2278-487X Volume 2, Issue 5 (July-Aug. 2012), PP 01-05 www.iosrjournals.org

When the stock market goes up one day, and then goes down for the next five, then up again, and then down again, that’s what you call market volatility.

To determine if the low risk phenomenon exists in the selected research universe for the selected time period, we quintile the stocks (Quintile 1 = High Volatility, Quintile 5 = Low Volatility) by trailing 250 day price return annualized volatility at each month end for the entire selected time period. We then calculate the subsequent one month average return of each quintile. The one month average return of the volatility quintiles are presented in Exhibit 1.1. Quintile 5 (lowest volatility quintile) outperforms Quintile 1 (highest volatility quintile) by 63 bps per month on average. The Quintile 5 to Quintile 1 spread of 63 bps is statistically significant at the one percent level. Exhibit 1.2 shows the risk/reward payoff of the volatility quintiles.

The interaction of agents explains the market fluctuations. To support this Baker & Wurgler (2007) mention the work of DeLong, Shleifer, Summers, & Waldmann (1990) noting that investors may be rational (not impacted by sentiment) and irrational (prone to sentiment). Assuming this, Baker & Wurgler (2007) propose a "top-down" approach, that takes investor

It has been observed that correlations between asset prices through periods of market uncertainty differ markedly from those seen in quieter periods. Literature on the subject generally coincides in that such differences in correlations are a result of either

This paper examines the relationship between stock returns and volatility using symmetric and asymmetric models of the GARCH family. For testing this relationship a time series sample of FTSE100 price index starting from 1st January 1988 to 31st December 2014 was taken. For calculating the excess returns on the stock index the risk free rate used is 3 months UKGBILL corresponding to the same time span.

Earnings expectations have ramped higher as top-line growth has stabilized and begun to recover. It is notable that earnings revisions have improved in the past three months but remain benign. See Fig 3.3. Sectors like Transportation, Technology, Utilities and Financials currently hold the most aggressive forecasts. Roughly 90% of all estimates in the Transports sector are being raised; this is roughly two standard deviations above the norm! Similarly, 68% of estimates for the Technology sector are being raised; this is slightly better than one standard deviation above the norm. It is notable that one of the most significant improvements in forecasts outside of

Derivative products like futures and options on Indian stock markets have become important instruments of price discovery, portfolio diversification and risk hedging in recent times. This paper studies the impact of introduction of index futures on spot market volatility on both S&P CNX Nifty and BSE Sensex using ARCH/GARCH technique. The empirical analysis points towards a decline in spot market volatility after the introduction of index futures due to increased impact of recent news and reduced effect of uncertainty originating from the old news. However, further investigation

In this paper the author examines whether there is any probable implication of derivatives expiration for the underlying spot market volatility. The GARCH (1,1) results show that for the entire period the derivative expiration days/weeks are the significant factors that affect the volatility of the spot market.

[7] Beyer, A. (2008). Financial analysts’ forecast revisions and managers’ reporting behavior. Journal of Accounting and Economics, 46(2-3), pp.334-348.