Friday, March 24, 2017

Electric cars pose little threat to oil demand

The popular claim that a surge in electric cars will hasten the arrival of peak oil demand is undermined by the data. The majority of the world’s cars will remain powered by petrol, also commonly known as gasoline, for at least the next two decades and this will drive oil demand, according to data from Facts Global Energy. With the number of passenger vehicles expected to grow to 1.8bn by 2040, the energy consultancy estimates only 10 per cent will be accounted for by electric cars and a further 20 per cent by hybrids. This might sound contentious given the hype around Tesla, the flag-bearer of electric vehicle producers, and many analysts forecasting a structural decline in oil consumption. But most research simplifies the matter, suggesting that falling battery prices are tightly correlated with electric car sales. The reality is more complex. The shift towards electric has to be supported by significant government incentives. Norway, for example, owes its success to the hundreds of millions of dollars in tax revenues diverted towards subsidies making it almost free to drive an electric car. Today it is normal for a Norwegian to buy an electric car in addition to a petrol vehicle for daily use to save money. Without such a subsidy, sales would fall, as demonstrated in Denmark last year. When the incentive was dropped in January 2016, electric car sales plunged 80 per cent from the previous year. Battery technology is improving but not as fast as necessary. Even at the $150/kWh — considered widely as the level to trigger mass production — a battery pack for an electric car with a comparable range to that of a petrol-powered car would cost tens of thousands of dollars. Cost aside, the improvement in battery effectiveness as measured by energy density is also slow. It is not possible to quickly increase the amount of distance travelled unless you add more batteries to a car, which means more weight and, in turn, a reduction in how far you can go. The love affair with the sport utility vehicles, partly driven by low oil prices, remains a problem. Last year, Ford sold six F-series light trucks in the US for every plug-in vehicle, providing solid petrol demand for the years to come. Even in China, one in every three cars sold is an SUV. With relatively low oil prices for at least the next decade, in FGE’s view, this trend will continue. Production capacity is another obstacle. Despite impressive annual growth rates, total electric car production was less than 500,000 in 2016, compared with global light vehicle production capacity of more than 70m. Tesla put just 80,000 cars on the road in 2016. Mass electrification of global road transport will not be possible without large-scale involvement from the main car manufacturers. A case in point is the Nissan Leaf, now one of the world’s bestselling and affordable electric cars. Since its launch six years ago, cumulative sales of the Leaf amounted to just 250,000. While its parent group sold almost 10m vehicles last year, less than 1 per cent were electric. Global car production grew approximately 2m units a year over the past decade. Even if battery electric vehicle production were to grow at this rate for the next two decades, their share in the total fleet would remain limited. The fate of petrol demand — and oil for that matter — will not be set in the west but in Asia, which is only at the start of mass motorisation. Asia accounts for approximately one-third of the global light vehicle fleet of 1.1bn. FGE expects growth in the region over the next 25 years of more than 500m units, more than the growth in rest of the world combined. By 2040, almost every other car in the world will be driven in Asia. Even with the most generous electrification assumptions, it is hard to see a “peak” in petrol demand followed by a subsequent drop. A more likely scenario is it continues to grow for decades to come.

Renters Now Rule Half of U.S. Cities

Detroit was once known as a city where a working-class family could afford to own a home. Now it’s a city of renters.
Just 49 percent of Motor City households were homeowners in 2015, down from 55 percent in 2009 and the lowest percentage in more than 50 years. Detroit isn’t alone, of course: The rate of U.S. home ownership fell steadily for a decade as the foreclosure crisis turned millions of owners into renters and tight housing markets made it hard for renters to buy homes. Demographic shifts—millennials (finally) moving out of their parents basements, for instance, or a rising Hispanic population—further fed the renter pool.
Fifty-two of the 100 largest U.S. cities were majority-renter in 2015, according to U.S. Census Bureau data compiled for Bloomberg by real estate brokerage Redfin. Twenty-one of those cities have shifted to renter-domination since 2009. These include such hot housing markets as Denver and San Diego and lukewarm locales, such as Detroit and Baltimore, better known for vacant homes than residential development. 
While U.S. home ownership ticked up in the second half of 2016, there are reasons to think the trend toward renting will continue. A 2015 report from the Urban Institute predicted that rentership would keep rising through 2030, thanks to demographic trends that include aging baby boomers who downsize into rentals.
In the shorter term, housing market dynamics will also play a role. Fewer than 1 million homes were on the market in the first quarter of 2017, the lowest number since Trulia began recording inventory data in 2012. The shortage makes it harder for renters to buy. Meanwhile, rental landlords, including large Wall Street players and mom-and-pop investors, continue to plow cash into single-family homes.
Those shifts are likely to present new challenges for cities unequipped to handle high rental populations. Detroit Future City, a nonprofit that highlighted Detroit’s shift in a report earlier this month, argues that the city needs an intentional strategy for dealing with the rising population of such households. 
That could include providing new protections for renters or creating resources to help landlords keep properties in good repair. On a grander scale, the Center for Budget Policy & Priorities, a Washington-based research institute, published a proposal this month calling for a new tax credit for low-wage workers, seniors, and people for disabilities. 
Most low-income families don’t rent by choice, said Nela Richardson, chief economist at Redfin. And plenty of higher-income households rent because they can’t afford to buy. “We don’t have enough affordable supply in either rental or for-sale markets,” said Richardson, adding that cities interested in promoting renter-friendly policies can rethink their zoning policies to encourage more construction. 
At an even more basic level, city leaders should check old assumptions about the role renter households play in their communities, said Andrew Jakabovics, vice president for policy development at Enterprise Community Partners, an affordable housing nonprofit. 
Homeowners have traditionally been regarded as more engaged, with more at stake in the long-term prospects of their neighborhood, Jakabovics said. That view can unfairly shortchange renters.
“It goes a long way just to make sure you’re valuing renters and making sure voices are heard when it’s time to allocate resources to schools or parks or transit lines,” he said. 

Machine learning will transform investment management

Watch out, investment professionals — machine learning is coming to a company like yours. This subset of artificial intelligence isn't just for programming self-driving cars or sorting cat pictures. It's entering the investment management space, and its disruptive potential is only beginning to emerge.
From Siri and Alexa to Amazon and IBM's Watson, computer programs driven by artificial intelligence draw on massive amounts of data to solve previously intractable problems. Machine learning gives computers the additional ability to learn without being explicitly programmed. This type of AI enables computers to change — to learn — when exposed to new data.
The technology behind machine learning is being propelled by major algorithmic innovations that allow machines to synthesize extremely large data sets and reveal patterns, trends and associations that are relevant to prediction problems. And the increasing ubiquity of inexpensive parallel computation is making this technology accessible to even lean startups.
The technology already has transformed many industries, from the medical to the automotive. In addition, machine learning is widely seen as a leading driver of revenue at Google, Facebook and Amazon. However, its adoption in investment management so far has been limited. With the exception of a few leading hedge funds, the industry has failed to recognize machine learning's potential to drive investment decisions.

Algorithms that continuously improve

ML automates the discovery of predictive algorithms that are able to continuously improve as they get access to more data. Recently, the focus has been on automating many of the tasks traditionally performed by data scientists, including data cleaning, model selection, data clustering, automatic feature generation and dimensionality reduction.
One technique, deep learning, has been responsible for many recent breakthroughs, including learning to play the game of Go well enough to beat the world's third-ranked player. Deep learning is enabling image recognition that is on par with human abilities and is significantly improving speech recognition and language translation; it is also permitting better story and ad targeting at places like Google and Facebook. Part of what makes deep learning so powerful is that it can organize and aggregate large unlabeled data sets into abstracted forms, which are more useful for prediction. The results have been stunning, both in speed and accuracy.

What does this mean for investment management?

We believe that machine learning will transform the way investment strategies are administered by all types of managers. Even the most fundamental, non-quantitative managers will be generating ideas from data that originally was sourced and synthesized via ML. For example, deep learning's ability to create structured data could be used to extract topic and sentiment from text sources such as earnings calls, SEC filings and social media; or for the analysis of satellite imagery for parking lot or crop data; or to evaluate location data from mobile phones.
While quant managers will certainly use these new data sources, they will also be able to use machine learning to conquer the classic hazard of overfitting. The problem with overfitting lies in the temptation for investment committees, or their portfolio managers, to believe they could have discovered a data-driven relationship before they really could have or to mistake spurious correlation for causation.
Overfitting often starts when data scientists take their favorite methodology, set up a number of input features and put in place the parameters of their method and a utility function. Then they run their algorithm on a part of their data (the training set), and look at results on another part of their data (the hold-out set). When invariably, things don't work as predicted, the researchers will tweak their parameters, or the features of their data, or the algorithm being used. Over time, the results are overfitted, as the value of the hold-out set becomes contaminated with each new test.

A solution to overfitting

With machine learning, we can minimize overfitting by restricting the role of the human to setting the overall investment framework. This framework will include the stock universe, trading frequency, performance benchmarks, data sources for signals and risk constraints. We leave the discovery of the specific formulation of the investment strategy to the system.
The framework will also specify the types of ML techniques that the machine will have access to as it discovers new strategies and decides which ones to trade. Essentially, the role of the quant will move to a higher-level function. The more routine steps of testing, scoring and tuning different structures will be handled by the machine, which will iterate through history in much the same way as humans do in real time (i.e. without knowing about the future).
Advances in machine learning will allow further automation of tasks, including feature discovery, algorithm selection and even the optimization of trading code that implements a signal. With these newer methods, humans can spend their time creating frameworks and obtaining new data sets. Automated methods also reduce the number of quants needed to run a firm, which, given the high cost of salaries, is increasingly important as well.
The tools that enable automated strategy discoveries will also enable customized solutions. This is because the criteria for a successful strategy can be specified upfront in the framework. For instance, one approach could search for a strategy with a specified maximum deviation from a classic index, such as U.S. small-cap value, with as much additional alpha as possible. This type of customization could lead to a new class of retail investment products.
We believe machine learning will become increasingly important for asset management and that most firms will be utilizing either machine learning tools or data within five years. Human involvement will still be critical for risk management and framework selection, but increasingly the strategy innovation process will be automated.

Thursday, March 23, 2017

Return Per Unit of Time Invested: Anil Tulsiram

In some ways the title of this post could be misleading. The other way to say the same thing would be to ‘Time is precious, decide WHAT NOT TO DO’

Time allocation is as important as capital allocation

Free capital is the book which convinced me that for private investors, focus on time allocation is as important as capital allocation. Almost all the investors in the book highlight how they try to optimize their time.
Focusing on a limited number of sectors leads to “economies of scale in knowledge production” – that is, learning about one company in a sector helps you to understand others in the sector. On the other hand, if you spend all your time looking at a few sectors, you “risk getting stuck at local optima” – that is, miss other sectors with much better opportunities. – Free capital
The scarcest resource for successful investors is not money but attention: how to manage the trade-off between time and rationality to best effect. There is not time in life to find out everything about every potential investment. Investment skill consists not in knowing everything, but in judicious neglect: making wise choices about what to overlook. 
American philosopher William James, had said the same thing more precisely  

“the art of being wise is knowing what to overlook.”

Source: Free Capital
  • Warren Buffet refused Mohnish Pabrai’s offer to work free for him. Recall Buffet’s reply “ I have given a lot of thought to optimal use of MY TIME, and I simply do best by operating by myself. “
  • There is no way for an investment manager to be on top of thousands of businesses, no matter how large the team is.
  • Investment manager has to take short-cuts with or without a team

I messed up big-time with time allocation

When I started my investment journey two years back, the most important mistake I did was not thinking about Return Per Unit of Time Invested. I was clear that I will not invest in any company which I am not comfortable for holding next five years. But I was looking for out of favor stocks [at 52 week low price] at low single digit PE & PB multiple. Majority of the stocks which satisfy both the conditions turned out to be cyclical stocks.
I failed to understand that, even after following detailed investment process for stocks like ZF SteeringGM BreweriesLG Balakrishnan etc., I was not comfortable in allocating more than 2-3% each [click on the link to download mindmaps]. I failed to follow a simple rule that TIME ALLOCATED to a particular idea should be in proportion to the CAPITAL ALLOCATED to that idea.
The biggest mistake I was doing was not putting businesses in proper matrix before I begin my detailed research. Abhinav Mansinghka [who along with Niren Parekh maintains an excellent blog here, ] helped me in understanding importance of putting businesses in proper matrix. Abhinav explained me that source of permanent loss of capital is almost always the bad businesses. Unless one pays extraordinarily high price for a high quality businesses, generally one would suffer only opportunity cost and not loss of capital.  

In simple words there is no point is doing DETAILED RESEARCH for bad businesses. Such businesses need WIDE diversification to PROTECT against PERMANENT loss of capital. Don’t get me wrong, I am not saying its wrong to invest in bad businesses at ULTRA CHEAP valuation, but then you cannot be spending months in doing research on one such company.
In the post that follows, I have tried to explain how I am trying to increase Return Per Unit of Time Invested. Of-course, it is tailored to my investment philosophy and personality. But I think you can follow the same steps to create a strategy, which suits to your requirements.

Formulate an investment strategy 

The poet E.B. White believed if your thinking is clear, then your writing will be clear. The same is true of investing, so formulate a strategy and write it down. This discipline will help you zero in on the kinds of companies you want most and avoid getting distracted by situations that are of peripheral interest. Naturally, your investment strategy should match your personality. 
Shrinking the Investing Universe
I’m a practitioner of 80/20 investing. Essentially, this means figuring out the 20% of your investing activities that are delivering 80% of your results. I like to start by asking, “what markets/businesses do I have no chance of investing in?”. Don’t be scared of missing out on a great idea by excluding entire markets/sectors. You will miss a lot of good, even great ideas. But we are on a mission to optimize our investing time.  
“Art of Value Investing” is one of the best book which talks about investment philosophy of various successful investors. These philosophies vary from deep value stocks [diversified portfolio] to buying only high quality stocks [concentrated portfolio]. This book enable us to appreciate that there is NO ONE BEST INVESTMENT STRATEGY. I reproduce below few extracts from the book which highlight the importance of time allocation and is inline with my investment philosophy.
We consider ourselves first and foremost value investors, but we don’t start by looking for cheap stocks. We spend our time following outstanding businesses that we would want to own should they ever become cheap. They’re rarely inexpensive when we start trying to understand them, but we follow them closely so that on the rare occasion they become discounted, we can act right away. Coming at it this way also means we’re not wasting our time chasing statistically cheap companies that we will have no interest in owning. Time is precious in this business. —C.T. Fitzpatrick, Vulcan Value Partners
With the market as volatile as it has been, we’ve been more diligent about maintaining watch lists to catch companies whose stocks trade off sharply for reasons that may be more overall-market related. We’re not looking for short-term trades but, as we learned in late 2008 and early 2009, stocks of even the high-quality companies we want to own can get remarkably cheap quite fastWe want to be prepared for that. —David Nierenberg, D3 Family Funds
It’s very important to define where you’re going to look for opportunities. Time is a precious resource and if you make it your task not to miss anything, you set yourself up for failure. There are too many opportunities out there and, by definition, you will miss many of them. That’s why we narrow where we want to look first by the themes we consider most compelling . We’re not necessarily seeing things others don’t see, but we will likely have a very different view on the magnitude of the trend or the speed at which it happens. —Oliver Kratz, Deutsche Asset Management
We’re deliberately concentrated on 10 to 14 investments, for two reasons related to time. First, it takes considerable time to learn enough about a company, its people, and its industry to develop and maintain a proprietary level of insight information, or knowing more than the Street. My view is that whatever edge I have comes more from knowing where to shop than knowing specifically which of the items I buy will be the best. So I maintain roughly equal stakes to reflect that. —Ralph Shive, Wasatch Advisors
The reality is that we can’t do the level of due diligence we want on each idea and also turn the portfolio over quickly by constantly trading out good ideas for better ones. So we typically hold companies an average of five years. —Steven Romick, First Pacific Advisors
It’s the bias of the information age that people feel isolated when they’re not in touch with what’s going on. To me it’s a good discipline to often say, “I don’t really care what goes on in the market today.” When you do that you can actually get something useful done. Even something simple like saying you’ll only answer e-mails in the morning, at lunch, and at the end of the day sometimes can go a long way toward avoiding unhelpful distractions that tend to arise. —James Montier, GMO
We are typically not attracted to most technology businesses because of cut-throat competition, potential technology obsolescence, short product cycles, and the excessive use of stock options. The return on time is also a problem – you spend so many hours analysing new products and technology trends that 50 percent of your time gets spend on 5 to 10 percent of your portfolio.

 At the same time, technology is an important driver of economic growth and grows at above GDP rates, so we want to have exposure to it. We like to attack difficult industries through the side door. –  Pat English, Fiduciary Management, Inc.

How much research is enough?

He [Vernon] also made the point that it is not worth knowing everything about a company: every investigation has a time opportunity cost. Your aim is not to check all possible hygiene factors, but to check enough to reduce your error rate to a time-efficient acceptable level: a low, but probably not zero, rate of error.
A final skill which Vernon highlighted as important for the self-directed investor was effective time allocation. “Time is a limited resource with strongly diminishing returns. The first hour you spend researching a company is much more important than the tenth hour. Some private investors are management groupies – they spend too much time on their favourite companies, posting on bulletin boards and going to AGMs and all the rest of it. They are squandering time which would be better spent looking for new ideas.” To limit the time resource applied to any one company, he reminds himself of psychological research which suggests that in many contexts decisions are best made with no more than five to seven points of information. Any more information beyond that does not significantly improve decisions, and may even degrade them.
Some investors insist on trying to obtain perfect knowledge about their impending investments, researching companies until they think they know everything there is to know about them. They study the industry and the competition, contact former employees, industry consultants, and analysts, and become personally acquainted with top management. They analyze financial statements for the past decade and stock price trends for even longer. This diligence is admirable, but it has two shortcomings. First, no matter how much research is performed, some information always remains elusive; investors have to learn to live with less than complete information. Second, even if an investor could know all the facts about an investment, he or she would not necessarily profit. This is not to say that fundamental analysis is not useful. It certainly is. But information generally follows the well-known 80/20 rule: the first 80% of the available information is gathered in the first 20% of the time spent. The value of in-depth fundamental analysis is subject to diminishing marginal returns. – Seth Klarman

News is costly

News wastes time. It exacts exorbitant costs. News taxes productivity three ways.  First, count the consumption-time that news demands. That’s the time you actually waste reading, listening to or watching the news. Second, tally up the refocusing time – or switching cost. That’s the time you waste trying to get back to what  you were doing before the news interrupted you. You have to collect  your thoughts. What were you about to do? Every time you disrupt your work to check the news, reorienting yourself wastes more time. Third, news distracts us even hours after we’ve digested today’s hot items. News stories and images may pop into your mind hours, sometimes days later, constantly interrupting your train of thought. Why would you want to do that to yourself?

E-mail, participating on public forums etc

Much of the time you spend in your email inbox produces no return on time invested. You can spend countless hours each day in email, especially if you check your email first thing in the morning.  
One needs to be judicious in participating in various public forums. I have already discussed this in my earlier post on Free Capital, so will avoid repetition.


Selection by elimination process 
Choosing the right investment is really a process of elimination. A minority of the thousands of publicly traded companies in which you could conceivably invest have authentic earnings power and even in this select group fewer still will qualify as an Earnings Power Staircase company. If you are a long-term cautiously greedy investor looking for that single wonderful business, most companies are not worth touching; your focus must be on identifying firms that have the potential to be great growth stocks for the next several years without exposing you and your portfolio to excessive risk.
Aim for specialized expertise and helpful shortcuts.
Many investors think they’re smart enough to master anything, or at least they act that way. Further, they believe the world is constantly changing, and you have to be eclectic and change your approach to adapt, racing to stay up with the latest wonder. The trouble with this is that no one really can know everything, it’s hard to constantly retool and learn new tricks, and this mindset prevents the development of specialized expertise and helpful shortcuts. Warren, on the other hand, knows what he doesn’t know, sticks to what he does know, and leaves the rest for others.
 Howard Mark, Foreward to Warren Buffet Way, third edition

Big Oil Replaces Rigs With Wind Turbines

Big oil is starting to challenge the biggest utilities in the race to erect wind turbines at sea.
Royal Dutch Shell PlcStatoil ASA and Eni SpA are moving into multi-billion-dollar offshore wind farms in the North Sea and beyond. They’re starting to score victories against leading power suppliers including Dong Energy A/S and Vattenfall AB in competitive auctions for power purchase contracts, which have developed a specialty in anchoring massive turbines on the seabed.
The oil companies have many reasons to move into the industry. They’ve spent decades building oil projects offshore, and that business is winding down in some areas where older fields have drained. Returns from wind farms are predictable and underpinned by government-regulated electricity prices. And fossil fuel executives want to get a piece of the clean-energy business as forecasts emerge that renewables will eat into their market.
“It is certainly an area of interest for us because there are obvious synergies with the traditional oil and gas business,” said Luca Cosentino, the vice president of energy solution at the Italian oil producer Eni, which is working with General Electric Co. on renewables. “As the oil and gas industry we know, we cannot get stuck where we are and wait for someone else to take this leap.”
Even as oil production declined in the North Sea over the last 15 years, economic activity has been buoyed by offshore windmills. The notorious winds that menaced generations of roughnecks working on oil platforms have become a boon for a new era of workers asked to install and maintain turbines anchored deep into the seabed. About $99 billion will be invested in North Sea wind projects from 2000 to 2017, according to Bloomberg New Energy Finance. A decade ago, the industry had projects only a fraction of that size.
While crude still supplies almost a third of the world’s energy, oil executives are starting to adjust to demands for cleaner fuels. Even so, emerging fossil-fuel alternatives including wind and solar power are starting to limit growth in oil demand.
Those technologies and electric cars may displace as much as 13 million barrels of oil a day from global demand by 2040, more than is currently being produced by Saudi Arabia, according to Bloomberg New Energy Finance. 

Shell’s Interest

Shell, whose CEO Ben van Beurden has said oil demand may peak in the second half of the next decade, has set up a business unit to identify the clean technologies where it could be most profitable, according to Sinead Lynch, the company’s chair for U.K. businesses. Wind farms are especially interesting to Shell because they can power electrolysis reactions that make hydrogen, which the company says may be a major fuel for cars in the coming decades.
It’s exploring new opportunities across Europe in offshore wind after winning contracts from the Dutch government to build the Borssele III and IV wind farms in December. Shell’s bid marked the second cheapest cost for the technology worldwide, according to Lynch, who said the oil major’s big advantage in renewables may be its expertise in marketing.
“It’s also about marketing energy,” Lynch said. “Once you produce your wind, you need to market the power and we have a phenomenally strong marketing and trading business.”

Statoil’s Costs

Oil majors are also changing the offshore wind industry by driving down costs, Statoil Senior Vice President Stephen Bull wrote in an email.
The Norwegian oil major’s Dudgeon wind farm off England’s east coast will be 40 percent cheaper than a neighboring plant built six years ago, Bull said. It’s also creating floating offshore wind foundations that eliminate the costly step of anchoring windmill masts into the seabed. In addition to the U.K., the company is developing projects in Germany and Norway and won a December auction to build an offshore wind farm in New York.  
Cost cuts for offshore wind are helping the technology start to compete with traditional forms of energy, especially nuclear, according to Bloomberg New Energy Finance. Current projects entering operation are delivering power at about half the price of farms finished in 2012 thanks to larger turbines and more competition. Costs could fall another 26 percent by 2035, according to the London-based researcher.
The entry of oil majors into renewables is part of “a longer term trend,” according to Nick Gardiner, head of offshore wind at U.K. Green Investment Bank, who notes that companies with the scale of Shell and Eni have the clout to finance projects more cheaply than many of their competitors.
“I don’t think they are doing this just for investor-relation purposes,” said Gunnar Groebler, head of wind at Sweden’s Vattenfall AB, one of the top five offshore wind developers who welcomed the added competition. “Given that these projects are billion-euro investments, I just assume that they will have done their assessments very thoroughly.”

Porsche eyes expansion with digital showrooms

As Porsche launched its sixth model in just over a year on Wednesday, the sports luxury car brand is creating its brand presence felt in the country with hundreds of organised drives for customers and by creating digital showrooms.
While 2016 didn’t fare too well for the luxury car market, Porsche did considerably well despite being in the higher end of the luxury segment.
“While the luxury car market declined by about 6 per cent last year, we were able to maintain almost flat growth through 2016, thanks to the new launches with the help of which we now have a complete portfolio,” Pavan Shetty, Director, Porsche India, told BusinessLine.
In 2015, Porsche sold 408 cars in the country, while in 2016, it sold 401, most of which were priced well over ₹1 crore.
But just launches were not enough for the German brand, which has been focusing on creating stronger connect with the customer.
“We did close to 140 customer events last year. We also started doing brunch drives for Porsche owners. It is getting people together. It is a mandate for all six dealerships to have such drives at least once in two months. All of this are showing benefits now as people want to be a part of such exclusive clubs are interested in buying a Porsche to do that,” Shetty said.
Porsche is also expanding its footprint by launching dealerships in Chennai and Hyderabad in the next two months.
To reach other parts of the country, the company is looking at building digital showrooms wherein small pop-up stores could be created with minimal investments.
“Instead of focusing on higher numbers, we want to focus on profitability while ensuring happy customers and stronger customer satisfaction, creating a structure for the future — getting digital experience solution at places where customers don’t have access to a dealership,” Shetty said.
Last year, Porsche entered into the sub-one crore segment with the launch of Porsche Macan, which is bringing more buyers into the Porsche domain. Shetty feels if there are any positive changes made in the tax structure for luxury cars, the market which is less than one per cent of the overall car market in India, will explode.
On Wednesday Porsche launched its fully redeveloped second generation Panamera Turbo in India for price starting ₹1.93 crore ex-showroom Maharashtra.
“The only three things common in the old and the new Panamera are the name, the idea of having a sports car in the luxury saloon segment and the Porsche crest-rest everything has changed,” Shetty said.
The car comes with a new display wherein touch-sensitive surfaces replace classic hard keys, and high-resolution displays merge into the interior.
The Panamera Turbo engine has been redesigned to produce more power, whilst improving fuel economy and reducing emissions. Panamera Turbo’s new 4.0-litre twin-turbo V8 develops 550 hp at 5,750 rpm, with a maximum torque of 770 Nm between 1,960 and 4,500 rpm. It has 30 hp more than its predecessor as well as a torque increase of 70 Nm. The vehicle accelerates to 100 km/h in 3.8 seconds, whilst with the Sport Chrono Package the sprint time is down to 3.6 seconds.
The new turbo model features a top speed of 306 km/h.

Monday, March 20, 2017

Vodafone, Idea Agree on Merger to Create India Mobile Leader

Vodafone Group Plc’s Indian unit agreed to merge with Idea Cellular Ltd. to create a wireless company that’s more than twice as big as AT&T Inc. by subscribers -- and a new leader in a market that’s so competitive after India’s richest man offered phone calls for free. 
Vodafone will own 45.1 percent of the combined company, after selling a 4.9 percent stake in the new entity to billionaire Kumar Mangalam Birla’s holding companies, according to a stock exchange filing Monday. Birla’s companies will take a 26 percent holding, with the remainder being held by the public. The new company is worth $23.2 billion, based on the enterprise value of $12.4 billion for Vodafone India and $10.8 billion for Idea Cellular. Shares of Idea Cellular jumped as much as 14 percent in Mumbai.
The enlarged wireless operator would have 395 million subscribers, exceeding those of market leader Bharti Airtel Ltd. Vodafone would gain a listing in the world’s second-largest wireless market, which it has been considering since at least 2011.
Vodafone and Idea will each control three seats on the board of the new company, which in addition will have six independent directors. Birla will have the right to appoint a chairman.  
For Vodafone, the deal would allow it to unload an unprofitable business that has forced the U.K. carrier to take a $5 billion writedown and pumpmore than $7 billion into the unit. Idea’s promoters will buy the 4.9 percent stake in the merged entity for 38.74 billion rupees ($592 million) in cash, on completion of the transaction.
The latest transaction is expected to be completed in 2018, according to the statement. It’s the biggest deal to emerge after billionaire Mukesh Ambani’s Reliance Jio Infocomm Ltd. stormed into the market last year by offering free calls and data, pressuring other carriers to consolidate.
Last month, Bharti agreed to acquire Telenor ASA’s Indian business. The Norwegian state-controlled carrier said at the time that prospects for the industry didn’t warrant further investments.
Birla units, including Aditya Birla Nuvo Ltd., own 42 percent of Idea, according to the company’s website. Malaysian carrier Axiata Group Bhdhas a 20 percent stake. Vodafone India Ltd. is a wholly owned unit of Vodafone.
In the quarter ended Dec. 31, Idea reported its first loss for the group in about a decade. Idea reduced its voice calling rates by 11 percent and mobile data rates by 15 percent from the previous quarter. Free calls and data offered by Reliance Jio also reduced data consumers on its network.