Case Study - Indian IT Industry Performance 2016 – Technical Analysis using Charts & Technical Indicators

The $150-billion Indian IT industry has been slowing down since the past couple of years as the clients are decreasing the budgets on traditional outsourcing work, and the Indian IT vendors failure to  balance the fall with growth in emerging areas such as social media, analytics and cloud. Furthermore automation has killed the routine maintenance work IT infrastructure & Applications management where fresh engineering graduates were typically employed. Added to this, Donald Trump election as President of United states further complicated things. Arup Roy, research director, Gartner, in an interview to Business Standard said, “Now with Donald Trump, administration will add to the industry’s woes. The Trump administration’s protectionist views would have further dampening impact on growth prospects, if the views were to crystalise into some serious policy implementations.”

The Indian IT industry’s trade body, Nasscom, in a statement said that Trump’s observations regarding outsourcing and high-skilled immigration “were based on fabrications put out by critics of the sector.” Nasscom said that it would be keen to engage with the Trump administration. “Our sector plays a key role in helping US businesses innovate and grow and make corporate America more competitive.” For many years the Indian IT industry has been subjected to an anti-outsourcing backlash in the US ranging from facing certain class action suits to visa fees hikes drastically that significantly increased cost of operations of Indian IT companies. To negate this backlash Indian IT companies have significantly invested, build and recruited local talent through the development centers set up in various states in United States.

The slowdown in the Indian Industry has affected the performance the shares of the Top 5 Indian IT Companies in the past one year (January – December 2016). As an investor one needs to understand the performance of the companies in the last one year so as to predict the performance in the next one year. Using the technical analysis, charts & technical indicators build a case to understand which companies are doing better and which companies are not doing well.

R Code for the above Charts:

getSymbols("TCS.BO")

TCS2016=TCS.BO["2016-01-01::2016-12-24"] # Subsetting Data for 2016

chartSeries(TCS2016) # Candle Stick Chart

addSMA() # Red Line on Graph

addEMA() # Blue Line on Graph

addBBands() # dotted red lines on chart

addRSI()

addMACD()

addMomentum()

addROC()

getSymbols("INFY.BO")

INFY2016=INFY.BO["2016-01-01::2016-12-24"] # Subsetting Data for 2016

chartSeries(INFY2016) # Candle Stick Chart

addSMA() # Red Line on Graph

addEMA() # Blue Line on Graph

addBBands() # dotted red lines on chart

addRSI()

addMACD()

addMomentum()

addROC()

getSymbols("WIPRO.BO")

WIPRO2016=WIPRO.BO["2016-01-01::2016-12-24"] # Subsetting Data for 2016

chartSeries(WIPRO2016)

addSMA() # Red Line on Graph

addEMA() # Blue Line on Graph

addBBands() # dotted red lines on chart

addRSI()

addMACD()

addMomentum()

addROC()

getSymbols("HCLTECH.BO")

HCLTECH2016=HCLTECH.BO["2016-01-01::2016-12-24"] # Subsetting Data for 2016

chartSeries(HCLTECH2016)

addSMA() # Red Line on Graph

addEMA() # Blue Line on Graph

addBBands() # dotted red lines on chart

addRSI()

addMACD()

addMomentum()

addROC()

getSymbols("TECHM.BO")

TECHM2016=TECHM.BO["2016-01-01::2016-12-24"] # Subsetting Data for 2016

chartSeries(TECHM2016)

addSMA() # Red Line on Graph

addEMA() # Blue Line on Graph

addBBands() # dotted red lines on chart

addRSI()

addMACD()

addMomentum()

addROC()