Ankit Saxena | Sharekhan Education
One can claim that trading or investing is chiefly about identifying trends to profit from them. There is an undeniable truth to the claim. Trading with the trend promises the highest probability of profit. But how does one trade with the trend unless the trend is identified correctly? Or worse, if one can’t identify the trend?
Novice traders often find it confusing to understand the underlying direction of the trend by going through price action. Unsurprisingly, they end up entering the security at an expensive price. And this is where you need tools that help with trend identification. While we at Sharekhan Education teach you an array of tools to help you with trend identification, today we will stick to perhaps the most common one – Moving Averages!
A moving average is nothing but an average of the previous closing prices of a security collected after specific chart intervals. Especially useful in markets, Moving Averages can help you make sense of price fluctuations in stock prices, commodities, and foreign exchange rates. The basic premise is simple: if the current price of a commodity or stock is higher than that of previous closing averages, you are most likely in an uptrend, and vice versa.
Hang on! Don’t just apply them randomly; there are multiple types of moving averages. Here’s what type means:
1) Simple Moving Average (SMA)
Perhaps the most common of the types, SMA is sometimes also referred to as the Arithmetic Moving Average. SMA is calculated by adding a set of values (like stock prices) and dividing them by the number of observations collected in the period. Most moving averages of prices are based on the closing price.
SMA = (A1 + A2 + …… + An) /n
2) Linearly Weighted Moving Average (LWMA)
A Linearly Weighted Moving average is a moving averages system that more heavily weights recent price data. How does it work? The most recent price has the highest weightage, and each prior value has progressively less weight, wherein the weightage drops linearly and proportionately.
LWMA = (A1*W1 + A2*W2 + …… + An*Wn)
3) Exponential Moving Average (EMA)
The Exponential Moving Average, just like LWMA, gives more weighting or importance to recent price data. But unlike LWMA, its rate of decrease from one value to the preceding one is not consistent or linear. Since new data carries greater weight, the EMA responds more quickly to price changes than the SMA does.
EMA = Price(t)×k+EMA(y)×(1−k)
Another issue for traders is: what is the right period to use? Of course, a longer period includes more data observations and is thus more reliable. But it is critical to note: by including more data in the calculation of the moving average, each day’s data becomes relatively less important. That means even a large change in the value on one day will not have a large impact on the longer moving average.
But while a longer moving is slower to pick up a trend change, it is also less likely to falsely indicate a trend change due to a short blip in the data.
Your analysis should not be limited to the information provided by a single moving average. Combining various moving averages simultaneously can help you increase the accuracy of your findings. In general, support or resistance level occurs where two moving averages cross. Also, a shorter moving average crossing above the longer one is considered a Buy signal whereas a shorter moving average declining below a longer one is considered a Sell signal.
That’s not all – moving averages are also used to determine trailing stops and entry-exit points! But that’s for some other time. We at Sharekhan Education heavily emphasise the importance of using the right tools for trend identification. And for a 360-degree understanding of trading and investing, its concepts and its strategies, we highly recommend you go through our extensive courses and pick out the one that best caters to your needs!
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