Everyone knows how Amazon started as a simple book store or how Meta began in a dorm room. At some point all of today’s great companies were just a passion project, a great idea in need of capital, employees, and the first real customer. While some ideas grow to become companies organically without outside investors, most companies need help. They need capital, they need expertise, they need connections and support.

Venture capital investing is the process by which these great ideas get funded and become dynamic companies capable of scaling and growing profitable. The return profiles for successful companies can be huge, but it’s an incredibly nuanced and risky part of the investing world and not suitable for everyone. Nonetheless, it’s where the best ideas are tried, tested, and eventually brought to fruition.

Investing in Venture Markets

You can’t invest in the venture space without recognizing that failure is an essential part of the creative process. Venture companies are dreaming big – and not every moonshot works out. In fact, most small companies end up failing and shutting the doors. Investing in the space successfully hinges on one or two ventures succeeding within a much broader portfolio. The companies that make it often hit escape velocity – they can hyperscale and the the returns can be exponential. The returns on a single venture investment could be enough to justify dozens of failures.

The complexity of the market is further complicated by the lack of transparency and minimal reporting requirements. The environment is rife with fraud and exaggeration. A great idea may be nothing more than an idea and may have no substance or practical marketability. Successfully navigating the venture space consequently requires a nuanced understanding of how businesses are run and an astute approach to avoid falling prey to exploitation. Subject matter expertise is also essential to see through the sales pitch and understand the substance of the idea.

Finally, we have to take a moment to discuss how hyperscale growth can be risky even when it succeeds. Unlike mature companies who are kicking off cash to investors, most venture investments are purely growth oriented. That growth can be awesome, but can also lead to long investing time frames – venture investing is not for those who need liquidity, even if they can handle the risk.

However, for those with the risk appetite, the time, and the expertise, the venture space can be incredibly rewarding. Diversified and done properly, a venture capital fund can be a vehicle for cutting edge ideas to become wonderful portfolio investments experiencing exponential growth over time.

Timing The Economic Cycle

This already exciting space is even more intriguing because of where we are in the market cycle. Smaller companies are typically the most exposed to the broader economic cycles and the venture space is no exception. The past two years are a great example. Inflation and interest rate hikes put a damper on the economy and small companies took it on the chin. Exuberance in 2021 turned into austerity in 2022; it’s hard to overstate the monumental shift in perspective. Think about some public market companies with established user bases and real products – companies like Teladoc or Zoom or PayPal. In 2021 their valuations were extended, and in 2022 and 2023 those valuations came tumbling downwards.

The same thing happened in private markets and in venture capital markets. In many cases it was actually worse in venture markets as the underlying products were far less tried and tested. The stress on the venture space was further exacerbated as soaring interest rates and a crisis of confidence caused the collapse of the venture-oriented bank SVB. Consequently, raising funds in venture markets today has become much more difficult. Many ventures have shut their doors and those still standing are fighting to raise capital at any valuation. Rather than looking for growth and appreciation, founders are looking at flat fundraising rounds as a victory.

This is also reflected in the IPO market. Many successful venture companies have delayed their public market debuts and have opted to stay private until capital markets start to open back up. The lack of activity in the last year or two stands in stark contrast to the successful listings of companies like Snowflake or Doordash when markets were less troubled.

However, companies resilient enough to weather downturns tend to flourish when market conditions improve. Difficult market conditions make it essential to not only have a good idea, but to become a good operator. Conserving cash, focusing on profitability, finding ways to efficiently acquire customers – these are lessons that companies learn during downturns. Taking that expertise to the broader market when capital markets start to unlock can lead to rapid growth both in terms of profitability, and in terms of the valuation of the firm.

Read the full article in Forbes.

Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

Artificial intelligence (AI) has been a hot topic of discussion for many years now, and for good reason. AI has the potential to revolutionize many industries and aspects of our lives. Recently, the pace of AI innovation has accelerated sharply and easy to use AI tools have started to become readily available to the broader population. Recent breakthroughs have the potential to impact workflows across industries and may have significant impacts on investment portfolios.

AI – What Is It:

There are a lot of different kinds of AI tools being developed as our skill at building new machine learning models increases. In particular, deep learning and large language models have made rapid advancements. Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Neural networks are inspired by the human brain, and they are able to learn complex patterns from data that would be difficult or impossible for traditional machine learning algorithms to learn.

Deep learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, speech recognition, and natural language processing.

A similar process is used in the development of large language models (LLMs). These models are able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. These models have recently burst onto the scene as they are easy to work with and highly interactive. They have many uses for day to day productivity, and show promise in assisting with a broad variety of content generation ranging from helping write code to generating articles or other creative content.

AI Constraints:

There are two primary inputs that act as limitations on the development of new AI models; data and processing power. Both resources are crucial. Data without processing power won’t yield a very accurate model, and processing power with low quality data will yield an AI tool full of biases or inaccuracies.

Processing power is the more straightforward of the two constraints. Bigger data sets or more complex AI set ups require more processing power, which means more chips and more electricity. Not all chips are made equal though – AI computing is substantially more efficient when done on graphics cards like those made by Nvidia, rather than on standard computational processors like those that currently dominate most servers across the world. Nvidia’s recent sharp stock price rise is almost entirely due to their raising guidance around expected graphics card revenues for use in AI computing. While Nvidia is currently the top player in the space, Microsoft has committed billions of dollars to help AMD design better chips for AI, and several other companies like Apple, Meta, and Alphabet all have internal chip design programs that will likely focus on AI chips as demand in that sector grows.

Data is the trickier constraint that AI models face. While processing power is primarily a question of cost versus quality, data set availability is more nuanced. The internet as a whole is a great database, but it’s very generalized and the quality is often questionable. More specialized data sets may be harder to access or may face privacy concerns. Furthermore, there are broad concerns around how data is presented when training an AI tool – will the data or the training parameters end up with the AI having a bias or tilt or blind spot. For instance, think about the difference in political perspective if the AI was sampling news from Fox News verses MSNBC. Similarly, what if it’s an automated driving AI and it’s trained without sufficient data for severe weather – the output will only be as good as the data input.

Read the full article in Forbes.

Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

While the latest electric vehicle tax credits help auto manufacturers, it will take much more to save the industry from recent challenges. The automotive industry is at a tipping point, with a growing focus on sustainability and the need to reduce carbon emissions. Electric vehicles (EVs) have emerged as a preferred solution to combat climate change, and governments worldwide are taking steps to incentivize their production and adoption. Companies are responding by pivoting their production lines to focus on EVs – Tesla has become one of the largest companies in the world producing electric cars and domestic stalwarts like GM have announced a total conversion to EVs in their business plans. Government subsidies and tax credits are a significant driver of this strong company pivot.

Subsidies, or financial incentives provided by governments, are a key driving force behind EV production. Subsidies can take various forms, such as direct payments, grants, or discounts on purchase prices; they are designed to make EVs more affordable and competitive compared to traditional gas powered vehicles. In particular, the new tax credits that took effect on April 18th, 2023, are focused on reducing the cost for the end consumer to drive EV demand.

The new electric vehicle tax credits offer up to $7,500 to consumers who purchase a new eligible EVs. Unfortunately for consumers, the range of EVs meeting the regulatory criteria for the credit is narrow. Only a handful of models currently comply with the regulations around where the batteries and parts are sourced. Furthermore, a majority of the vehicles receiving credits are both expensive and in limited supply. The irony is that the funding for these tax credits comes from the Inflation Reduction Act. Rather than helping the inflation-impacted consumer, these subsidies for EVs are more likely to stimulate spending, making it harder for the Fed to reign in the economy. Furthermore, given the prices of the EVs right now, the subsidies will mostly be utilized by individuals with above average incomes – the population least impacted by inflation.

Read the full article in Forbes.

Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!

Recently, you may have seen the headlines regarding Silicon Valley Bank collapse, creating implications for the financial system as a whole. If you looked at the performance of the financial sector over the past week or two you’d be excused for feeling a bit of panic. The deterioration in share prices slowly accelerated into a crushing run on two banks in two days. Given the way markets have been fluctuating over the past 18 months and the pressure the Fed has been putting on the market, we can understand how some people might jump to conclusions and think the financial system is finally cracking under the pressure of rate hikes and inflation.

We’re going to dive into this deeper, but lets start this reaction piece off by pressing pause on any panic you might be feeling.

Why Is The Financial Sector Under Pressure with Silicon Valley Bank Collapse

The financial sector has been under pressure as rate hike expectations have come back into focus. While we’ve had plenty of speculation around rate hikes over the past 18 months, the past week or two has seen the 2s – 10s spread expand rapidly. The 2s-10s spread is the gap between 2 year treasury yields and 10 year treasury yields. In normal markets conditions, longer maturity yields are typically higher than short maturity yields – governments or companies who issue debt have to pay more for investors to feel comfortable locking their money up for longer periods of time. However, in the current environment where rapid rate hikes are expected to be temporary, the yield of treasury bonds with shorter maturities is higher than the yield on treasuries with longer maturities.

This spread is important because the spread between long term and short term maturities can have a significant impact on bank profitability. Banks fundamentally operate in the business of borrowing short term money and lending it out to people for longer term projects. The most extreme example taking a customer deposit for say, $500,000, and then turning around and giving another customer a loan for $500,000. The bank has borrowed short term money from the depositor, and lent it out for much longer – for the sake of this example, lets say 10 years. The interest they make on the 10 year loan is used to pay for the bank’s operational costs, drive value for bank shareholders, and of course, pay the customer some interest on their savings account.

Read the full article in Forbes.

Want to reevaluate your wealth management strategy in 2o23? Contact the nationwide advising team at IHT Wealth Management today!