The objective of this blog post is to analyze the fundamentals and value the 3 lines of businesses of Virinchi separately and estimate a consolidated Fair Value Per Share.
Any opinion expressed in this blog post is solely my own and does not represent views of my employer. Moreover, this stock valuation should not be misconstrued as a buy / sell recommendation
Ride sharing companies have revolutionized the way we commute. While Uber has gone global and continues to expand to other businesses, Lyft has shown a much smaller narrative and is present only in US and Canada. Lyft just filed for a much awaited IPO and should get listed by the end of this month.
I had earlier valued lyft at around $5 bn in November last year. The data and assumptions were based on the limited statistics that were available on the internet. Although, I did expect annual revenue of ~$2 bn and loss of ~$900 mn and had baked these numbers in my valuation, but I was too far off in the number of active users / riders (my source of info led me take 32 mn and 23 mn users in 2018 and 2017 respectively). This statistic is key to valuing companies such as Lyft and Uber, which are making shared economy mainstream. Now since Lyft’s financials are public, we know the active number of users is 18.6 mn (as of Q4 2018 up from 12.6 mn in Q4 2017). I plugged the actual user based statistics in my model and the valuation that I get is $17 billion.
As earlier, the valuation framework that I have used has been pioneered by the renowned NYU Stern Prof. Aswath Damodaran. In his paper, Prof. Damodaran has explained how to incorporate user economics in a DCF Valuation. The fundamental equation to value such companies that Prof. Damodaran gives is simple and intuitive:
Value of a user based company = Value of existing users + Value added by new users โ Value eroded by corporate expenses
Value of existing users (or customer lifetime value)
Each valuation needs to have a fact based story, which is essentially what we think of the company, its growth potential and the risk associated with its users/riders (i.e. would users stick or ditch).
Revenue per active user
Fact: Lyft reported a revenue of ~$130 per active user in 2018, up from ~$100 and ~$67 in 2017 and 2016 respectively. This translates to 30% revenue per user growth in 2018 and 50% growth in 2017. Moroever, Lyft’s share of revenue from gross billings is 26.7% ($2.15 bn revenue/$8.1 bn worth bookings).
Story: I believe Lyft’s wallet share would continue to grow, but the growth rate would continue to decrease from 50% (2017), 30% (2018) to 25% (2019) and 3% (Risk Free Rate in 2028).
Cost of Revenue & Operating Profit
Fact: After removing cost of revenue (which includes insurance, payment processing charges, technology costs and amortization), operating profit per active user is ~$55 in 2018, up from ~$38 and ~$13 in 2017 and 2016 respectively. This translates to a cost of revenue of 57.7% in 2018
Story: I believe the cost of revenue would be more or less the same in the near term, but would decrease in the long term as the company optimizes its operations
User Stickiness
Fact and Story: Considering that ride sharing businesses have disrupted the market with many users preferring it over their own cars (I certainly do!), I reckon that a major chunk of the existing ride sharing users would stick, although their loyalty to one company is uncertain. A subscription business model would have more user stickiness as opposed to a transaction based. With Lyft using loyalty programs and with its focused narrative on ride sharing, I go on to assume that 90% of riders would stick every year.
Using the assumptions, I go onto project after tax profit (i.e. by projecting revenue and cost) per user into the future. I take the present value of these future cash flows using a 10% cost of capital (75th percentile of global companies) and then adjust this present value for user stickiness. I get a customer lifetime value or value per existing user/rider of $450. With 18.6 million active riders, the total value for all existing customers is $8.4 billion
Value added by new users
Number of new users/riders added every year
Fact: Lyft reported a 18.6 mn active riders at the end of 2018, up from 12.6 mn and 6.6 mn in 2017 and 2016 respectively. This translates to 48% user growth in 2018 and 91% growth in 2017.
Story: With more and more people ditching their cars (and lease rentals) and opting for on demand ride sharing, I believe Lyft would be able to tap new users every year, but the growth rate would continue to decrease from 91% (2017), 48% (2018) to 25% (2019) and 3% (Risk Free Rate in 2028). The total users added each year is adjusted for user stickiness
User/rider acquisition cost
Of the entire amount Lyft spent (Revenue + Loss), it spent $1.24 bn of it in servicing existing users (reported as Cost of Revenue in the P&L) and ~$0.45 bn in general & admin expenses. The rest of the spend (~$1.14 bn), which includes sales, marketing and operations can be attributed to acquiring new customers (18.6 – 12.6 = 6 mn). The cost of acquiring a customer that I get is ~$190
Total value added by new users
Netting off user acquisition cost ($190) from the user lifetime value ($450), I get the value added by each new user to be ~$260.
I go on to project the value added by new acquired users/riders each year by multiplying the calculated new users each year with the value added by a new user each year compounded with the inflation rate. I then take the present value using a cost of capital to arrive at the total value added by new users to be $11.5 bn (Cost of capital is taken as 12%, which is higher than the cost of capital used for existing users. A cost of capital of 12% occurs at the 90th percentile for US companies )
Value eroded by corporate expenses (G&A)
Quoting from the S-1 prospectus – “General and administrative expenses primarily consist of certain insurance costs that are generally not required under TNC or city regulations, personnel-related compensation costs, professional services fees, certain loss contingency expenses including legal accruals and settlements, claims administrative fees and other corporate costs. Following the completion of this offering, it is expected to incur additional general and administrative expenses as a result of operating as a public company.” Corporate expenses are assumed to grow at 4% every year. Discounting the future cash outflows, I get the present value of corporate expenses of close to $5 bn
Putting it all together
Value of Lyft $14.9 bn = Value of existing users $8.4 bn + Value added by new users $11.5 bn โ Value eroded by corporate expenses $5 bn
We also need to account for employee stock options ($609 mn), cash ($517.7 mn) and IPO proceeds ($2000 mn)
Removing employee stock options, and adding cash and IPO proceeds, I get the value of equity to be $16.8 billion
Since, the number of shares outstanding is 279 mn, I get a share price of $60.25 per share
Valuation is very sensitive to my assumptions on growth and user stickiness, which in turn depend upon Lyft’s ability to acquire and retain customers. The assumptions I have taken, although reasonable in my view, might be high or low. I do not claim any certitude to these numbers. As Prof. Damodaran says your story should drive numbers. Your story can very well be different from mine. Any higher values of these metrics would result in a higher valuation.
Please do let me know what you think in the comment section.
Edit (9th March 2019) – Using the user based statistics and financial information made public in Lyft’s S-1 prospectus, I have revalued Lyft at ~$17 billion. My valuation is presented in the link alongside https://investandrise.com/lyft-ipo-2019-valuation/
Ride sharing companies have revolutionized the way we commute. Both Uber and Lyft would be going public next year. While Uber has gone global and continues to expand to other businesses, Lyft has shown a much smaller narrative and is present only in US and Canada.
The most important parameter for companies born in the gig economy is the number of users/subscribers. VCs typically value (read price) such companies by “pricing” users/subscribers. The intrinsic value of an asset or business is the present value of its future cash flows (DCF – Discounted Cash Flow Valuation). So, an ideal way to value such companies would be to value users
In this blog post, I have attempted to value Lyft by valuing users using a framework taught by the renowned NYU Stern Prof. Aswath Damodaran. In his paper, Prof. Damodaran has explained how to incorporate user economics in a DCF Valuation or rather how would you use DCF to value user based companies born in the gig economy
The fundamental equation to value such companies that Prof. Damodaran gives is simple and intuitive:
Value of a user based company = Value of existing users + Value added by new users – Value eroded by corporate drag
Lyft’s being priced at $15.1 bn (as of this writing). Using a user based valuation, I have valued Lyft at just under $5 bn by taking certain base case assumptions. The assumption values could be high or low. I do not claim any certitude to these numbers. To accommodate for different cases (or different values of assumption variables), I go on to use monte carlo to get a distribution of Lyft’s valuation across simulation trials. I find that ~80% of the distribution falls below Lyft’s current pricing of ~15 bn
In Lyft’s valuation below, I estimate values for Lyft’s existing users, new users and the value eroded by corporate drag
Since Lyft is yet to go public, so financials are hard to come by. I have used the 2018 Q1, Q2 & Q3 financials reported in the information to make estimates for Q4 and then used the base estimates for 2018 to forecast cashflows into the future
Exhibit 1: Estimates based on 2018 Q1, Q2 & Q3 as reported by The Information
Simply put, the value of existing users is arrived at by estimating after tax operating profit per existing user for the base year and then forecasting it into the future, followed by taking the present value (PV) of the future cash flows. The PV per user is scaled by the number of existing users to arrive at the PV of after tax operating profit of all existing users. This PV is then slashed using the assumed probability of user lifetime
Base Year 2018 Estimates: (Data from Exhibit 1)
Assumption Variables for making Forecasts :
*This is a crude method to estimate users and I would want to replace this estimate with the actual number of users as when that statistic becomes public*
Operating Profit (for each year in the future) = Net Revenue forecast – Cost of Servicing Existing Users forecast
The future operating profit is discounted using cost of capital and then slashed using the probability of user full life
Exhibit 2: Value of Existing Lyft Users $6.1 bn (base case)
New users in the base year is the increase in users in base year 2018 over 2017. Base year value added by each new user is the amount by which value per existing user exceeds cost of adding a new user
Base Year 2018 Estimates:
Assumption Variables for making Forecasts :
New Users are estimated to increase at an assumed growth rate and decrease with the assumed annual renewal probability each year. Value per New User is forecast to increase each year with the inflation rate
Exhibit 3: Value added by New User $3.1 bn (base case)
Corporate Drag of $400 mn in the base year is an assumed base case value. (It has been simulated to take different values ranging from $200 mn to $600 mn using a normal distribution)
Moreover, Corporate Drag is assumed to grow at 4% every year
Exhibit 4: Corporate Drag estimated at $4.4 bn (base case)
Exhibit 5: (base case) Value of Lyft $4.8 bn = Value of existing users $6.1 bn + Value added by new users $3.1 bn – Value eroded by corporate drag $4.4 bn
On running a monte carlo simulation, I get the following distribution for Lyft’s valuation (Exhibit 6)
Exhibit 6: Distribution of Lyft’s valuation across simulation trials
Key statistics/observations from the distribution above:
Valuation is very sensitive to the number of users. The above is just a snapshot in time valuation based on a lot of assumptions. Closer to its IPO in 2019, when Lyft makes its financials public, then I would replace the assumptions with actuals to arrive at its fair valuation
The objective of this article is to estimate the intrinsic share value for freenlancing platform Upwork, which went public on Oct 3rd. The estimate is arrived at using a DCF valuation based on the company fundamentals given in its S-1 prospectusย and my own views/forecasts on the company
I have come up with a point estimate share value of $15.1. The IPO issue price of $15 looks fairly valued. The IPO listed at $23 i.e ~53% premium. The stock now trades at $21 per share and looks overpriced as of this writing (10/5/18)
The Impact due to the above is an illusory positive impact on the Cash Flow statement and low expenses resulting in less negative Net Income
3. R&D has been expensed instead of being capitalized
4. Operating Leases have been expensed instead of being treated as a lease asset
I have fixed 3.1, 3.3 and 3.4 in my valuation. I couldn’t fix 3.2 since the extent of net losses is not mentioned in S-1
I treated Stock based compensation as an expense and added back R&D compensation to reported EBIT to arrive at adjusted EBIT
Then I went on to use Black Scholes to value the outstanding 22.93 mn options at *$285.7 mn and eventually deducted it from my estimated value of equity to arrive at equity in common stock and subsequently got a reduced value per share. This might seem like double dipping (i.e treating stock based compensation as an expense and then deducting stock options from value of equity), but its not. Dean of Valuation and renowned NYU Stern Prof. Aswath Damodaranย has brilliantly explained the treatment of stock based compensation in valuationย ย
Next, I capitalize R&D which has a positive effect on reported EBIT and also gives a tax benefit on resulting the amortization of the last year
Lastly, I take find the present value of future lease commitments and this value ($3.37 mn) to total debt. This is our operating lease asset. I depreciate this and deduct the depreciation ($0.67 mn) from the current year’s lease commitment ($3.6 mn) to determine the adjustment to be made operating income – i.e. I add $2.93 mn to EBIT
Fixing 3.3 and 3.4 have a positive effect on EBIT with the result that I get an overall positive value of EBIT $24.89 mn from -$15.62 mn
Free Cash Flow to Firm or FCFFย is used to estimate Free Cash available to both debt and equity holders. It is arrived at by estimating cash flow generated from operations or the Net Operating Profit After Tax EBIT(1-T), some of which is re-invested back in the firm. Any cash over and above the re-investments is available to both debt and equity holders. This is called Free Cash Flow to Firm (FCFF). Present Value of future FCFF is the Enterprise Value (EV). Additionally, removing present debt from EV and adjusting for stock options leaves us with equity in common stock
Before jumping into the valuation we need to have a story spun aroundย facts, which is essentially what we think of the company, the industry, market size, growth potential, margin, investments needed to drive and sustain growth, capital nature of business – intensive/light/efficient, period of high growth and the transition to stable growth, business risk and the interplay of competition among other things
Now, lets take a look at the above objectively and attempt to tie certain facts it to our story
A. Fact: Market Size & Growth
A. Story: Coupling the above with increased investments in R&D and Marketing & Sales in the last 2 years makes me believe that revenue could grow at 25% Y-o-Y
B. Story: Since we have only one other publicly traded freelancing platform i.e. freelancer.com, I am wary of using it as my guiding light. I reckon that the 25% growth could last 5 years (Stage 1), which is followed by another 5 year period of slightly declining growth (Stage 2) which then gives way to lower stable growth (Stage 3) equivalent to the risk free rate of 3% (yield on the US 10 year T Bond) in perpetuity
C. Fact: Operating Marginย
C. Story:ย I know it would be to broad to assume a target pre-tax operating margin of 20%. The firm is currently at 10.92% (after making adjustments) and hence it seems reasonable to make 20% as a targeted margin. I go on to make this parameter configurable towards the end to see what kind of effect it has on my valuation
D. Fact and Story: Re-investments
Bottom-up can be put to use when there is some financial history available, but for growth firms I prefer the top-down method, which essentially requires us to have a view of the capital nature (intensive/light/efficient) of the business and then use the corresponding industry benchmark sales to capital ratios depending upon the nature. Moreover, we could also use the sales to capital ratio of the current base year and extrapolate it to future years (Nothing is incorrect! it all depends on our view of the company)
Sales to Capital ratio in the current base year = Sales / (Book Value of debt + Present Value of Future Lease commitments + Equity + Value of R&D asset (current + past un-amortized) – Cash equivalents)
Sales to Capital in current year= $228 mn / ($33.88 mn + $3.37 mn + – $30.60 mn + $77.54 mn) = 4.31
This ratio translates to a close to minimal capital need business as per industry benchmark. But, I reckon extrapolating just one year’s ratio to generalize the nature of the business and take a call on future re-investment needs is a stretch!
Prof. Aswath Damodaran gives the following benchmark ratios depending upon the capital nature –
| Minimal capital needs, no acquisitions (10.00) |
| Minimal capital needs, small acquisitions (5.00) |
| Service company median (3.00) |
| Technology company median (2.50) |
| US company median (2.00) |
| Capital intensive company median (1.50) |
In my valuation, I have used Technology company median (2.50)ย for Stage 1 and then usedย US company median (2.00) for Stage 2. I have done so since I reckon the company is neither capital intensive nor capital light. I do not claim to have any certitude about these numbers. The reduced sales to capital ratio in Stage 2 implies increased re-investments as the company transitions to stable growth
For Stage 3, we do not have to forecast this ratio.
During stable growth, Re-investment Rate = Growth Rate / ROIC
ROIC again is tricky. The adjusted base year ROIC is calculated in Exhibit – 4.ย Adjusted ROIC base year = 32.96%
During stable growth, I have taken a 75th percentile ROIC benchmark, which is 20%. Transitioning from the current adjusted ROIC of 32.96% to 20% in stable growth seems reasonable (againย I do not claim to have any certitude about these numbers)
E. Cost of Capital
I have used the cost of capital from the S-1 prospectus directly which is 7.2 %
The above **Facts->Stories->Numbers (well, from A through to D)ย helped me forecast the followingย main parameters we need for this valuation –
On plugging these parameters into the valuation, I get a per fair share value which is very close to the IPO share issue price of $15. On reducing the Sales to Capital ratio to 2 for both Stage 1 & 2 and also toning down my ROIC expectations to 12.5% (which is the US industry median), I get a share value of $13.1 (which again is not too far off from the IPO share issue price). However, post the public issue the stock has become overpriced.ย ย
We have been talking a lot about renewable sources of energy and how the energy mix is slowly but steadily changing. Under the National Solar Mission, the government aims to install 100 GW of solar capacity by 2022. Currently, 5 GW of solar installed capacity has been achieved and it is poised to cross 20 GW in the next 18 months. ย This is applaudable, but there is yet another renewable source of energy which does not get much mention and which is often ignored – municipal waste!
Per estimates, 62 million tonnes of Municipal Solid Waste (MSW) is generated in India every year. ย The yearly increase is slated at around 5%. If MSW is dumped without treatment then it will need 3,40,000 cubic meter of landfill space everyday. The Waste To Energy (WTE) plant seems to end the woes of landfill. It takes in MSW and generates energy with negligible levels of pollutants. Various MSW to energy technologies have come to the fore such as incineration, biomethanation, gasification and pyrolysis. Of these, incineration and biomethanation have gained prominence.
The WTE plants require segregation of wastes upfront. The moisture reduces the calorific value of the wastes. The biomethanation WTE plant in Lucknow was a flop show due to inefficient segregation of wastes. Blame it on the collection at the source , inappropriate transport facilities for waste or constrained marred urban local bodies in India.
The waste to energy plant at Okhla, New Delhi which treated 1950 MT of MSW and generated 16 MW of power has been shut down due to alleged non-compliance to the right incineration technology. A quick back of the envelope calculation suggests that if all MSW is treated then it has the potential to generate around 1400 MW of power everyday. Ministry of New & Renewal Energy (MNRE) estimates the current potential at 1700 MW and has been bullish in saying that this potential could increase to 5200 MW by 2017.ย Of the current potential, only about 24 MW has been exploited in India, which is less than 1.5% of the total potential.
A quick peek at how MSW fares in the US. Until last year,ย there were 84 WTE plants in the US that generated electricity or produced steam. These plants combusted 30 million tons of MSW yearly, and sold more than 14.5 million mwh to the grid, about the same amount used by 1.3 million US households.ย In addition, many plants sold steam directly to end users offsetting the use of fossil fuels to make that energy. Despite all this,ย MSW is ย considered to be an abundant, valuable yet under utilised source of domestic and renewable energy since only 7.63% of the total waste in the US is processed in these facilities. The main reason why WTE has been a success in the US is because of the appropriate segregation of wastes upfront and proper waste collection and transporation facilities.
Last year, the government of India gave nod to 6 WTE facilities across India. More and more private players wish to foray into the untapped WTE potential but are deterred by lack of a proper waste management infrastructure and regulatory environment. Interestingly, challenges present opportunities. A lot of firms are attempting to leverage opportunities present in the entire MSW value chain be it collection, segregation, transportation or disposal under the regulatory and operational control of municipal bodies. Such firms are direct collaborators to potential WTE facilities.
The most interesting part is that the government can leverage WTE to showcase some quick wins as part of its Smart Cities initiative since it not only catches the waste and landfill problem by its tail, but also acts as a renewable energy source. The government can put its weight behind such installations, have single window of clearances for the entire value chain and get a (say) 2000 MT facility constructed and operational within 1-1.5 years. This is by no means very ambitious since such facilities do not have high installation time. Couple that with the Swachch Bharat (Clean India) program (not ignoring the tax receipts that would now come through it) to transform the bottlenecks (required extended infrastructure) into facilitators and you are on your way to achieve an energy oxymoron ย โ swachch and eco-friendly waste!