Oh Venture Capital, you evil mistress of every startup founder or executive. Your song is so sweet but sting can be deadly if handled without care. So the question for 2018 is where will the big boys be placing there chips in 2018? Where will the promise of being the next Unicorn be told?

Here is my take on the VC outlook in 2018 as I see it.

One thing is certain, the supply of capital is still plentiful. The record-high fundraising activity of the past 19 months has been driving the growing amount deals. One differential, and I believe it to be a good thing, is that valuation as a discipline has returned as seen in the total investments as to raised by VC’s themselves. The investment thesis has shifted from “growth at all costs” to “growth with fundamentals.” 

Investment into venture-backed companies in 2017 (couldn’t find definitive Q4 data yet) is on track to match or exceed dollars deployed in 2016, and if this pace holds, full-year 2017 venture capital (VC) dollars invested could be the highest in the past decade. Venture investors deployed $21.5 billion to more than 1,699 venture-backed companies during the third quarter, bringing 2017’s total investment to $61.4 billion deployed across 5,948 deals to date.

In the VC ecosystem, sensitivity to political and corporate governance issues is growing. The past six months have hinted at the growing impact of political climate and corporate governance on private tech companies. These issues include the ongoing immigration debate, VC activism at Uber, sexual harassment allegations at leading VC firms, and diversity discussions at tech companies.

VCs are hoarding cash for the inevitable rainy day

Given these issues and the impending rise in the cost of capital do to macro-economic factors and the Federal Reserve it is no surprise that there is a correlation. A correlation between the amount VCs have risen themselves versus investing in startups, especially seed stage and the number of exits.

These trends point to VCs not only being more selective in areas of interest to result in the “home run” for them but skeptical of those startups claiming expertise or participation in those areas. Anyone who has been around the startup world for more than a minute can recognize the first time startup founder vomiting buzzwords in their pitches only to fall far short when it comes the the actual product or service.

So where will VCs be focusing their investment attention then… here’s 6 areas.

  1. Self-driving cars – There has been an escalating “share of wallet” for self-driving cars and related initiatives. Over the past few months C-level executives from numerous self-driving car companies including Cruise, Zoox, nuTonomy, Drive.ai, Argo AI and Mighty AI have all indicated increased courtship from the VC community. At the Code Conference, Marc Andreessen argued that we shouldn’t be concerned that self-driving vehicles will lead to job losses – in fact, just the opposite could occur. Not only could self-driving tech lead to fewer traffic deaths and a boost in productivity, it could also cause a boom in exurbs, communities that exist beyond suburbs. At a recent Silicon Valley event featuring over 15 startups focused on some aspect of autonomous vehicles, there were almost twice as many investors as entrepreneurs in attendance. Clearly, we are rapidly approaching the peak of the hype cycle regarding self-driving cars.
  2. Artificial intelligence (AI) – Machine-learning initiatives continue to occupy a substantial “share of mind” among tech leaders. For startups, riding a trend such as artificial intelligence can be the difference between a hot round of funding and no investor interest. Founders have spent the last year throwing terms like AI, neural network, and machine learning into their pitch decks in hopes of attracting investment. Those trends show no signs of slowing in 2018. Artificial-intelligence experts are so in demand that tech giants like Google, Facebook, Amazon, and Apple are paying nosebleed rates to hire them. As a result, PhD’s in the field can raise venture money without so much as an idea, let alone a real business. As the trend matures, venture investors will be looking for tangible business ideas such as startups that will use AI to help large organizations make decisions previously made by humans. That includes hiring, sales planning, preparing manufacturing instructions for machines or use AI to identify the content of videos. The collective efforts of the research community continue to impress, especially as we see low-hanging breakthroughs in areas outside of vanilla deep learning, such as reinforcement learning, adversarial networks, one-shot learning and unsupervised methods. The discussion on how AI will impact employment will shift from solely focusing on the elimination of jobs to how best to help workers accommodate the inevitable change: in their responsibilities, the skills they need or requirement to find a new role. Different countries will take different approaches. Those which combine an investment in social goods (like education and a safety net) and maintain a healthy approach to entrepreneurship and innovation will do best. We will also make more progress in understanding the commons questions of trust, fairness and justice in algorithmic systems. Sensible boards, prompted by legislators, regulators and activists, will make ethical AI a top-table issue.
  3. Cryptocurrency  Most firms can’t—or won’t—buy digital currency like bitcoin directly. But they’re high on the potential value of the underlying blockchain technology and finding creative ways to pour money into the sector. Look for investments in apps that will run on nascent crypto networks, services around the cryptocurrency ecosystem including institutional custody for cryptocurrencies, security, app distribution, and blockchain-based distributed file storage. The activity in decentralised applications and protocols based on tangle and tokenization will increase and coins like IOTA, FileCoin, Orchid and Ocean will come live. Below the speculative froth, sober-minded teams are coming together to tackle real problems using the unique attributes of blockchain technologies (solving the incentivisation problem across a market network of random participants, allowing the emergence of trust in such a system). We’ll see AI developers increasingly experiment with the fruitful combination of AI and blockchain. These areas include how to build a data commons to incentivise the sharing of data, allow the sharing of models, using blockchains and smart contracts for individual AIs to mediate their machine-to-machine interactions.
  4. Voice-centric devices – Amazon Echo and Google Home has sent tech companies scrambling to develop services for them. Investors are following with their checkbooks. Now that the “hard tech problems” like accuracy are mostly solved, startups are finding new opportunities to use voice, including advertising. So far, Amazon’s Alexa hasn’t proved terribly friendly to advertising-based businesses, causing companies like VoiceLabs to retreat. But startups with creative solutions are likely to thrive in 2018, as WIRED noted earlier this month.
  5. Mixed Reality – Clearly, there’s interest in this area, as expressed by the $1.9 billion invested in Magic Leap. But instead of the idea of augmenting our existing world –like digital recipes we can see when we’re at the stove – think wearable devices that can see and interpret what’s going on around us. If such a computer could identify people in front of you, when you last met, and how they fit into your life that would be exciting. So would it being able to tell you instantly if a product you’re holding at a store is available cheaper online.
  6. Targeted Social Networks – I think we’re seeing the natural movement toward people doing smaller, niche-focused networks again. Who isn’t less satisfied by Facebook’s increasingly information overload that has less appeal to our interested today? Artificial intelligence will be the technology investment priority for large firms.

Apple (AAPL) got hammered today after the Japanese newspaper Nikkei reported that iPhone X production has been cut in half due to disappointing sales.

Apple supply chain news tends to be high on excitement but low on accuracy, but it’s hard to argue with the market action: at one point, the stock fell as much as 2.6% to $167.07. It firmed a bit into the close, but traders appear on edge ahead of earnings on Thursday.


Elsewhere in tech, AMD (AMD) rose over 2% after MKM Partners said crypto market demand will fuel a strong quarterly earnings report. AMD’s main rival Nvidia (NVDA) also put in a solid day.

Apple’s shakedown gave the market a minor scare.

We didn’t see much turmoil in the major indices. At their intraday lows, the S&P and Nasdaq were down -0.7%, which isn’t exactly disaster territory.

However, we did see a big spike in the VIX, which rose as much as 23% today.

Earnings season still looks strong.

According to our friends at FactSet, 76% of companies have beaten earnings estimates and 81% beat sales expectations. Both are well above historical estimates.

In fact, if that 81% sales beat rate holds, this will be the single best quarter on this metric since Q2 2011, when it was 72%.

Earnings growth thus far is +12%, with every single sector in positive territory. As of December 31, growth was estimated at +11%.

JP Morgan strategist Stephen Parker told CNBC that this strong earnings season could mean more good things for the market:

“What we’re hearing is unambiguously positive,” Parker told CNBC’s “Futures Now” last week. “Not only is this quarter strong on an absolute basis, but unlike past quarters, we didn’t see the sort of analyst revisions downward that you traditionally would always see leading into fourth-quarter earnings.”

A lack of downward revisions to earnings estimates makes this quarter “even more impressive” than in the past, added Parker.

Sentiment remains remarkably positive.

The CBOE Equity-Put Call ratio’s latest reading is 0.54. This is well below the 0.654 long-term average.

The 10-day moving average is a shockingly low 0.525.

And we still haven’t had a single day above the long-term historical average since December 6.

So as I’ve been writing every day for weeks, traders are buying up call options like crazy.

Of course, that’s been a great strategy because the market’s been going up and up and up.

I’d give you one of the usual one-liners like “this is all gonna end badly,” but there’s already enough of that going around.

AAPL is is a vulnerable spot after forming a shooting star candle and closing below short term trend support. The RSI has a clear downward slope and the stock hasn’t tagged even the 50SMA since 2014. 

The market is ripe for a correction and although has shrugged off every news catalysts this can not go on indefinitely. This is a huge earnings week so the big names could spark major movement if estimates aren’t blown away. 

In my role as a startup advisor, I sometimes see people who are very intelligent and well-educated, but not adept at problem solving. Yet I’m convinced that this trait can be learned by discipline and practice. If you want to improve your strength in this area, or need to coach your team along these lines, I recommend the following steps:

  1. Approach every problem as a positive business opportunity. At worst, it’s a learning opportunity for you and your team, which can lead to providing a better customer solution or experience. At best, you may find a new revenue stream providing a product or service that eliminates a painful problem for both you and your customers. Look first for positives.
  2. Step back and collect the facts, without emotion. Entrepreneurs are often too passionate and impatient. It’s not effective to attack a problem you don’t understand, and jump to conclusions in the heat of a crisis. All too often, a small problem will become a big one if you let emotion get the best of you. In all cases, get clarity and plan your attack.
  3. Enlist help and advice from the right people. When you have a problem to solve, it’s not smart to just grab the least-busy person on your team for help. These individuals may not have the skills or mindset you need, and can delay the solution or instigate a bigger problem. Problems are best solved by open-minded team members who know the ropes.
  4. Identify all potential sources of the problem. It’s easy to jump to conclusions. For example, what looks like a sales revenue problem may actually be a new competitor offering, a marketing decline, or a lag in receivables. Attacking the wrong source only delays the solution, antagonizes people, and increases costs. Check all the angles.
  5. Perform a root cause analysis. Problems don’t get solved by treating the symptoms. The best approach to get to the root of a problem is to iteratively question the source of each symptom until all answers point to the same source. By eliminating that source, you won’t waste time fixing symptoms or chasing the same problem with different symptoms.
  6. Identify and prioritize alternative solutions. There are always multiple ways to fix a problem, so don’t jump too quickly on the first alternative that surfaces. Identify several, then prioritize based on cost, time, and risk. In business, an acceptable solution, done quickly, is usually superior to the perfect solution that will take more time and money.
  7. Select a solution, and initiate immediate action. Some people find it hard to make a decision, even when all the necessary information in on the table. Don’t let costs escalate, or customers escape for lack of action. An important step is to communicate the problem and solution to all constituents, along with your action plan. Initiate action.
  8. Clearly assign solution implementation and follow-up. The best entrepreneurs drive responsibility down to the relevant person, rather than trying to orchestrate all activities and tracking personally. Assignments should be documented and communicated, rather than assumed. Don’t allow confusion or multiple people to be set as responsible.
  9. Establish metrics to assure solution and prevent recurrence. Problems have the positive impact of suggesting that something needs to be measured. Define the required metrics, including a check for side effects and follow-on problems. Often, the removal of one constraint in a system leads to other problems further down in the process.

If you are not a great problem solver yourself, it pays to surround yourself with people who are. You can learn from these people, and rely on them to keep your business running smoothly. Look for problem solving examples in the resumes of every new team member, and ask some hard questions in your interviews.

Slow economic week for forex. All eyes will be on if dollar can hold its recent base of 88.50. If can, given the short bias past months, could bounce but the 91 handle is now a big resistance area. Most aren’t even expecting the FOMC policy announcement to be eventful and a;ready baked into prices. Some with jobs on Fri. I am looking for a bounce in the USD as so oversold but unless it breaks the 91 handle I’d expect it to retrace back again. So given historical inverse dollar to markets correlation, if the dollar does bounce a bit, and the big earnings aren’t blowouts, could “could” be a spark people seem to be waiting for to start a pullback in the markets. The usd bounce / retrace unless breaks big levels is the same/inverse for what I think the markets could do.