Closing Stock Market Summary
The S&P 500 increased 0.1% on Monday, as gains in Apple (AAPL 284.00, +4.56, +1.6%) and energy stocks helped the benchmark index close at another record high. The Dow Jones Industrial Average (+0.3%) and Nasdaq Composite (+0.2%) also closed at new records. The Russell 2000 increased 0.1%.
Price action was muted to start the holiday-shortened trading week, as the market traded with modest gains throughout the session. Leadership from Apple, which had its price target raised to $350 from $325 at Wedbush, was an influential force in the broader market.
From a sector standpoint, the S&P 500 energy sector (+1.1%) outperformed amid strength in Apache (APA 26.53, +3.91, +17.3%), and the industrials sector (+0.6%) followed suit amid gains in Boeing (BA 337.55, +9.55, +2.9%) and 3M (MMM 178.47, +3.10, +1.8%). Conversely, the utilities (-1.0%) and real estate (-0.5%) sectors declined the most.
Boeing shareholders reacted positively to Dennis Muilenburg resigning from his positions as CEO and Board director. 3M benefited from JP Morgan upgrading the stock to Neutral from Underweight. Apache pleased investors with a 50-50 oilfield venture with France's Total (TOT 55.04, +0.67, +1.2%).
Although not market-moving, China's decision to lower import tariff rates on approximately 850 commodity products, effective Jan. 1, helped support the positive sentiment. On a related note, President Trump said the Phase One deal should be signed "very shortly." The market expects the deal to be signed in early January.
In M&A activity, Cincinnati Bell (CBB 10.45, +2.73, +35.4%) agreed to be acquired by Brookfield Infrastructure (BIP 49.14, +0.78, +1.6%) for $2.6 billion in cash. Sports betting company DraftKings will become a public company through its combination agreement with Diamond Eagle Acquisition Corp (DEAC 10.84, +0.67, +6.6%).
U.S. Treasuries finished on a lower note, pushing yields higher across the curve. The 2-yr yield increased two basis points to 1.65%, and the 10-yr yield increased two basis points to 1.94%. The U.S. Dollar Index finished flat at 97.67. WTI crude increased 0.3%, or $0.15, to $60.53/bbl.
Reviewing Monday's economic data, which included New Home Sales and Durable Goods Orders for November:
- New home sales in November increased 1.3% m/m to a seasonally adjusted annual rate of 719,000 units (consensus 735,000) from a downwardly revised 710,000 (from 733,000) in October. On a yr/yr basis, new home sales were up 16.9%.
- The key takeaway from the report is that it appears as if new home sales, like existing home sales, were crimped in November by a lack of available supply at more affordable price points.
- Total durable goods orders declined 2.0% m/m (consensus +1.4%) following a downwardly revised 0.2% increase (from 0.6%) in October. Excluding transportation, durable goods orders were unchanged, as expected, following a downwardly revised 0.3% increase (from 0.6%) in October.
- The key takeaway from the report is that orders for nondefense capital goods, excluding aircraft -- a proxy for business spending -- were up just 0.1%, which left them up 0.7% yr/yr. Shipments of those goods, which factor into GDP computations, were down 0.3% from October.
Investors will not receive any economic on Tuesday, which will be a half-day of trading (stock market will close at 1:00 p.m. ET).
- Nasdaq Composite +34.8% YTD
- S&P 500 +28.6% YTD
- Russell 2000 +24.1% YTD
- Dow Jones Industrial Average +22.4% YTD
Tesla Shares Race Past $420 Buyout Figure
Electric car maker’s stock now worth more than what Elon Musk promised to pay in last year’s failed take-private bid
A Tesla Inc. TSLA 3.36% rally has taken the stock above a symbolic threshold Monday, the $420 a share at which Chief Executive Elon Musk last year said he wanted to take the electric-vehicle maker private.
The new height of $422.00, up more than 4% in midday trading, also represents a U-turn in investor confidence after sentiment was shaken in the Silicon Valley auto maker, with shares closing as low $178.97 in the past year. A surprising third-quarter profit, the unveiling of a new pickup truck and progress toward building Model 3 compact cars in China have fueled the stock’s rise. Tesla shares are up about 74% from $241.23 on Sept. 23.
The $420 mark is a uniquely Tesla milestone. When Mr. Musk in August 2018 wrote on Twitter that he wanted to take-private the electric auto maker it spurred months of upheaval
The price in 2018 represented a slightly greater than 20% premium from where the stock closed in the days before he made the announcement. The effort to take the company private, though, quickly went up in smoke when it became clear that such a move was harder to pull off than first imagined.
The surprise announcement—at a time Tesla was struggling to build its mass market Model 3 model—sent Tesla shares soaring, only to crash later when investors realized Mr. Musk hadn’t completed the funding to pull off the maneuver. It spurred an investigation by the Securities and Exchange Commission that alleged Mr. Musk misled investors with his tweets.
The SEC and Mr. Musk later settled the case. The Tesla CEO paid $20 million to settle that case, stepped down as chairman and agreed to have his material statements overseen by Tesla.
The government revealed that Mr. Musk rounded up the offering price to the $420 price from $419 to amuse his girlfriend because the number is part of marijuana culture. Mr. Musk further cemented his reputation in drug culture in September of last year when he appeared during a live-video interview puffing a marijuana blunt.
In the months that followed, Mr. Musk and Tesla faced continued challenges in building and delivering the Model 3, the company’s bet that it can evolve from a niche luxury player into a car company offering electric vehicles to mainstream buyers.
Mr. Musk, a prolific tweeter, also later ran into more trouble with the SEC when he made statement the regulator felt violated their earlier settlement. The two sides settled this year.
Since going public in 2010, Tesla has been among the most shorted stocks, with some investors gambling the company is overvalued.
For Mr. Musk, reaching $420-a-share “is about the most significant milestone for his investor credibility in the last several years,” said Gene Munster, managing partner at investment and research firm Loup Ventures. “It shows that his intuition, whether you view it as comical or not, his intuition is right.”
As the stock surged Monday, Mr. Musk weighed in on Twitter, “Whoa … the stock is so high lol.”
US should work with China to get bilateral ties back on track: Wang Yi
Chinese State Councilor and Foreign Minister Wang Yi has called on the US to work together with China to get China-US ties back on a healthy track.
His comments came during a yearly interview Monday with state media.
This year marks the 40th anniversary of the establishment of China-US bilateral ties, which should be a memorable juncture, Wang noted in an interview with the People's Daily and China's Central Television.
However, the US has continuously put pressure on China's trade and technology fields, as well as smeared China concerning its sovereignty, seriously damaging mutual trust established between the two countries in the past four decades and jeopardizing global stability and development, Wang said.
He reiterated that China will firmly safeguard its core interests and right to development. "Nobody or no force can prevent the 1.4 billion Chinese people's steps toward modernization."
As for contradictions and divergences between the two sides, Wang said that China is always willing to find solutions through negotiation and dialogue on the basis of mutual respect.
The most important experience the two countries gained in the past 40 years is that "cooperation benefits both while fight damages both," Wang said, calling for the US to work with China to eliminate conflicts and build mutual respect and win-win cooperation.
"We hope the US side can re-establish a proper acknowledgement of China and return to practical policies in regard to China," he said.
DraftKings to go public with $3.3bn valuation through merger
Fantasy sports betting platform agrees three-way deal with Diamond Eagle and SBTech
DraftKings, the US fantasy sports betting group, is set to go public in a three-way merger that values the combined business at $3.3bn.
DraftKings has agreed to be sold to Nasdaq-listed Diamond Eagle Acquisition Corp, a special purpose acquisition company founded by the former chairman of Hollywood studio MGM, Harry Sloan, and film producer Jeff Sagansky, alongside gaming technology company SBTech.
The combination with Mr Sagansky’s Spac, a publicly traded vehicle through which money is raised from investors to fund acquisitions, means that DraftKings will have a market listing without launching an initial public offering.
The deal is the latest in a wave of consolidation across the gambling industry following the lifting of a federal ban on sports betting in the US in 2018. In order to cater to the demand for sports betting, US companies have been looking to partner with European betting groups with experience in regulated gambling markets.
DraftKings’ fantasy sports rival FanDuel was bought by Flutter Entertainment, the UK parent company of Paddy Power Betfair, the same month the bill banning sports was repealed. Flutter has since merged with Stars Group, the company behind Sky Betting & Gaming, in a £10bn tie-up.
MGM Resorts International has partnered with GVC, the owner of UK bookmaker Ladbrokes Coral, in a $200m joint venture.
The DraftKings deal is expected to complete in the first half of next year.
Paul Leyland, an analyst at Regulus Partners, said the merger meant DraftKings and SBTech would “gain a level of scale and control over their own destiny that changes them from relative upstarts to a credible leadership role”.
Institutional investors have committed to buy $304m common stock in the combined company, which will trade under the DraftKings name with Jason Robins, DraftKings’ co-founder and chief executive, staying on to lead it.
Diamond Eagle anticipates the combined group will have a market capitalisation of $3.3bn once the deal closes, with more than $500m of cash on its balance sheet.
Mr Robins said the merger would allow DraftKings to become “a vertically integrated powerhouse”.
“I look forward to building significantly upon our goals of continuing our state-by-state rollout and creating the most entertaining and engaging customer experiences for sports fans globally,” he said.
DraftKings abandoned a planned a merger with FanDuel in 2017 after regulators said that combined the pair would control roughly 90 per cent of the daily fantasy sports market. Thanks to the reach of daily fantasy sports — an online game in which participants choose fantasy teams across various sports but win points based on the real-life performance of the players — the two have become the market leaders in sports betting in states where the activity is legal.
According to analysts at Morgan Stanley, however, DraftKings still trails FanDuel in downloads of sports betting apps with FanDuel holding 34 per cent share of the market and DraftKings, 25 per cent.
The industry research firm Gambling Compliance estimates that the US sports betting market will be worth $5.9bn in revenue by 2024, assuming a base case scenario of 34 states legalising the activity.
Isle of Man-based SBTech provides back-end technology to gambling companies in about 20 regulated markets.
SoftBank-backed Nemaska Lithium files for bankruptcy protection
Company scrambles for financing as investors shun sector following fall in price of metal
Nemaska Lithium, a Canadian lithium producer backed by SoftBank, has filed for bankruptcy protection as it scrambles to raise emergency funding to keep its flagship project alive.
The Toronto-listed company has been struggling to finance development of Whabouchi, a lithium mine and processing facility in Quebec, amid a cost blowout and a steep fall in the price of the metal, a constituent of electric car batteries.
Nemaska on Monday said it was seeking protection from its creditors to give it sufficient time to complete a refinancing. The company also said it might ask for court approval to sell assets or enter into a joint venture.
Analysts said the problems facing Nemaksa, a symbol of the nascent lithium industry, underscored the difficulties building an integrated lithium mining and processing project.
They also mark another blow for SoftBank, the Japanese group controlled by Masayoshi Son that has had investments sour this year.
“Once they got the SoftBank investment, people thought ‘Masa Son doesn’t make stupid investments’ but as it turns out they do,” said Joe Lowry, a lithium consultant.
“It’s the poster child for what goes wrong when money and hubris meet lithium,” he added. “It’s another black eye on lithium investments. Unwinding this is going to take forever. I don’t believe they or any successor company will be producing lithium within five years.”
With battery-powered vehicles set to go mainstream, the market has been swamped with new lithium supplies following a rapid expansion of mines, particularly in Australia.
At the same time, a cut in government subsidies for buyers of electric vehicles in China has weakened demand in the world’s largest electric car market.
This has left companies such as Nemaska struggling to find finance to complete their projects as investors shun the sector.
“Nemaska has been one of the first movers in construction of a fully integrated operation,” said Jake Fraser, a consultant at Roskill, a metals research company. “Some of the headwinds faced by Nemaska in development cost blowouts highlight the complexity of building these projects.”
The company shocked investors in February when it revealed a C$375m (US$283m) cost blowout. The budget is now running at about triple the original cost forecast.
Nemaska’s problems have been exacerbated by the crash in the lithium market this year. Lithium carbonate delivered to north Asia, the industry benchmark, is trading at $7,250 a tonne, down from $18,000 in May last year, according to S&P Global Platts.
In September investors owed $350m decided to withdraw their support following construction delays.
SoftBank invested C$99.1m in the lithium miner last year as part of a C$1.1bn fundraising and has a stake of almost 10 per cent.
Pallinghurst Group, the investment group chaired by former BHP boss Brian Gilbertson, is in exclusive negotiations with Nemaska on a proposed C$600m investment that would help it to complete construction of the lithium mine.
The company last month revealed construction was temporarily shut down until financing was secured.
Analysts say that even if it secures funding from Pallinghurst and its partner Traxys, success is not guaranteed. Pallinghurst declined to comment.
SEC Investigating BMW Over Sales Practices
Auto maker says it is cooperating the investigation, declines further comment
The Securities and Exchange Commission is investigating German auto maker BMW, BMW -0.82% a company spokesman said. The probe is focusing on sales practices, according to a person familiar with the matter.
BMW said it is cooperating with the investigation and declined further comment.
Early premarket gappers
- Gapping up: ITCI +39.23%, CBB +29.53%, APA +5.17%, SLNO +3.47%, TSLA +1.64%, VLRX +1.54%, PEI +1.28%, IAG +1.23%, BDX +1.20%, MMM +0.92%, IAC +0.88%, LCI +0.66%, BA +0.44%, JNJ +0.41%, TWTR +0.31%
- Gapping down: OSMT -6.78%, CLS -2.84%, ACB -2.67%, MT -0.50%
Machine learning: the big risks and how to manage them
There is no precedent for how this type of trading, which adapts based on experience, might play out
Algorithmic trading has been prevalent in equities trading for more than two decades. It is also now well entrenched in fixed income, too.
It has created new opportunities by speeding up execution of orders, cutting costs and increasing volumes. But it has also introduced new hazards for market participants and created the occasional “flash crash”. We have also seen trading algorithms being programmed to manipulate markets.
Now we face an even bigger challenge — machine learning. This technology, centred on computer models that can learn from experience, poses serious challenges and requires a global response.
The Bank of England and the UK Financial Regulation Authority recently published a survey of banks and capital markets firms which found that about half of respondents use machine learning in a modest way today. Most expect to make much greater use of it over the next few years.
Today, machine learning is deployed mainly in back-office functions such as anti-money laundering, fraud detection and credit risk management. It is not currently used much in front-line trading functions, but we expect material change in this area over the next few years. We therefore have the responsibility to consider potential risks and to mitigate them, as far as possible.
Unlike traditional rules-based algorithms, machine-learning algorithms are not static engines, programmed to run only along the paths created by their human programmers.
Instead, they use massive data sets and enormous computational power to enable them to recognise patterns, train themselves, and to make decisions about when and how to trade without human intervention.
This is a transformative moment for those trading in financial markets. It will bring great opportunities, but it will also create new hazards that we simply have not had to think about before. Here are four to consider.
First, what we call “model drift”. Machine-learning trading engines learn for themselves how to create prices by repeated and constantly evolving experimentation. In this optimisation process it becomes hard, or even impossible, to trace how decisions are made. It is therefore very difficult to prevent undesirable outcomes in advance, or to correct them afterwards.
These concerns over transparency explain the present regulatory focus on model risk management and software validation, as well as questions about how company boards can satisfy themselves that they have an appropriate level of understanding about what is going on inside the “black box”.
Second, bias. Machine learning creates the potential for unexpected or unfair changes in pricing or liquidity for certain types of market users, or even for individual customers — as a result of factors that are impossible to uncover because they lie, effectively undiscoverable, in the heart of the optimisation engine. Unless the machine chooses to tell you its secrets, you will never know why it did something.
More worrying, perhaps, is that a machine optimising on its own will probably find that unethical, manipulative trading practices are more profitable. How do we ensure that the machine understands not just the law and regulatory rules, but also concepts of right and wrong?
Third, market concentration. The way in which machine learning models improve by accessing increasing quantities of data is likely to create network effects, where a small number of data providers effectively control access. That may, in turn, throw up high barriers to entry.
Such barriers could entrench the power of today’s large banks and financial services firms or, alternatively, allow technology-based competitors to create new oligopolies at the expense of today’s financial sector.
But the consequences of concentrated market structures need careful thought. Participants in the market could be disadvantaged, through unfair rationing of liquidity and skewed pricing.
Fourth, the skills gap. There is a massive shortfall of expert programmers, data scientists and risk managers needed to safely develop, test and implement machine learning in financial markets.
This is just as much the case in the private sector as it is among central banks and market regulators. It creates a significant knowledge gap in the boardrooms of financial services firms and within policymaking institutions about the challenges and hazards posed by machine learning.
Given the international nature of financial markets, these are all challenges that need to be properly considered and addressed at a global level.
The complexity of the issues raised also makes collaboration between public authorities and the private sector essential. A fragmented approach could lead to a trading environment where no one truly knows what the black box is going to do. That is a risk for everyone, not just wholesale markets in one location or another.