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Mutual Funds: Beta - Volatility Measure

It is common knowledge that mutual funds are benchmarked against particular market indices. In general, diversified funds are benchmarked against Sensex or Nifty, while sectoral funds are benchmarked against their particular sector index. It is fair to then assume that the ups and downs of any index will affect the funds that are benchmarked against it. In other words, if the Sensex falls, you can expect a diversified fund like HDFC Equity (which is benchmarked against the Sensex) to fall as well. But while some funds might be affected more by an index's volatility, others might not. So, then how does an investor get an idea of how volatile a fund is with respect to its index? Here is where Beta enters the picture. Beta is the measure of a fund's (or stock's) volatility relative to the market or benchmark. For example, if a fund is benchmarked against the Sensex, a beta of more than 1 would imply that the fund is more volatile than the index. And of course, a beta of less ...

Beta

Beta is a statistical term ; it measures the volatility of stock (or fund) relative to the market (or the benchmark). The value of beta of a stock or mutual fund is always stated against its benchmark. The beta of benchmark or market is always equal to 1. If a stock is benchmarked against Sensex and has a beta value greater than 1 (say 1.5), this indicates that the stock is 50 percent more volatile than the market as the beta of Sensex is 1. The stated stock will deliver 15 percent return if the market has delivered a 10 percent return in same time period. Its opposite is also true if Sensex delivers 10 percent negative return, then the stated stock will fall by 15 percent in the same time period. A beta of less than 1 implies lesser volatility. The desirable value of beta depends upon the individual risk bearing capacity. So while you can expect a high return from a stock that has a beta of 2, you will have to expect it to drop much more when the stock market falls.

Measure volatility of a stock by using “Beta”

How you can gauge volatility of a stock and evaluate stock value The stock market movements over the past few weeks can be best described as unpredictable. It goes a few impressive points up, only to slide back after a few days. The upward and downward fluctuations can create panic among investors. Returns on stocks become increasingly difficult to predict over the short term. It may be a reaction to global market conditions, high oil prices, world economy and soaring inflation. Volatile markets torment investors. How do you measure market stability? A measure of volatility gives ample information for an investor to base his decisions. The time to enter, buy or sell, are critical decisions that depend on market moods. Shrewd investors find volatile markets or crashes an ideal time for picking value stocks at bargain prices. Since these are purchased at discounted rates, it gives a sufficient cushion for the long-term investor. Though scouting for bargain stocks may appear a lu...

Mutual Funds: Returns Are Not All

5 points that matter while buying MF More often than not meritocracy of investments is often decided by the returns. Quite simply then a fund generating more returns than the other is considered better than the other. But this is just half the story. What most of us would appreciate is the level of risk that a fund has taken to generate this return? So what is really relevant is not just performance or returns. What matters therefore are Risk Adjusted Returns. The only caveat whilst using any risk-adjusted performance is the fact that their clairvoyance is decided by the past. Each of these measures uses past performance data and to that extent are not accurate indicators of the future. As an investor you just have to hope that the fund continues to be managed by the same set of principles in the future too. Following are the 5 Points: 1. STANDARD DEVIATION 2. BETA 3. R-SQUARED 4. ALPHA 5. SHARPE RATIO 1. STANDARD DEVIATION The most basic of all measures- Standard Deviation allows you ...
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