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Research Review | 8 October 2021 | Dynamic Portfolio Strategies

Time-Varying Factor Allocation Stefan Vincenz and Tom Oskar Karl Zeissler (Vienna U. of Economics and Business) September 15, 2021 In this empirical study,…

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This article was originally published by The Capital Spectator

Time-Varying Factor Allocation
Stefan Vincenz and Tom Oskar Karl Zeissler (Vienna U. of Economics and Business)
September 15, 2021
In this empirical study, we provide evidence on how predictive information can be utilized to profitably allocate a cross-asset factor portfolio, covering various well-known factors over the asset classes equity, commodity, fixed income, and foreign exchange. We investigate the performance of a meaningful set of predictors, which we broadly divide into macro and market indicators. Our analysis shows that tilting a global factor portfolio according to signals derived from business cycle indicators, inflation, and short-term interest rates, among other predictors, significantly outperforms a static factor benchmark. The established results are based on practical considerations, survive conservative transaction cost assumptions, and are validated over an extensive out-of-sample period. In sum, we highlight the potential benefits of an asset-allocation framework conditioned on predictive variables, but caution to time factors on a standalone basis.

Equity premium predictability over the business cycle
Emanuel Moench and Tobias Stein (Bundesbank)
12 September 2021
The US equity market follows a V-shaped pattern around recessions, with sharply negative returns heading into recessions and a strong recovery as the recession unfolds. In addition, recessions are usually preceded by an inverted yield curve. This column shows that the term spread is a robust predictor of recessions, and that model-implied recession probability forecasts do a good job of predicting the equity premium out-of-sample. An investment strategy based on the recession probability model could be used to time the equity market and lead to higher and less volatile profits over time.

The Quant Cycle
David Blitz (Robeco Quantitative Investments)
September 24, 2021
Traditional business cycle indicators do not capture much of the large cyclical variation in factor returns. Major turning points of factors seem to be caused by abrupt changes in investor sentiment instead. We infer a Quant Cycle directly from factor returns, which consists of a normal stage that is interrupted by occasional drawdowns of the value factor and subsequent reversals. Value factor drawdowns can occur in bullish environments due to growth rallies and in bearish environments due to crashes of value stocks. For the reversals we also distinguish between bullish and bearish subvariants. Empirically we show that our simple 3-stage model captures a considerable amount of time variation in factor returns. We conclude that investors should focus on better understanding the quant cycle as implied by factors themselves, rather than adhering to traditional frameworks which, at best, have a weak relation with actual factor returns.

Allocating to Thematic Investments
Koye Somefun (BNP Paribas Asset Management), et al.
September 07, 2021
In this paper we introduce the notion of themes as an additional investment dimension beyond asset classes, regions, sectors and styles, and we propose a framework to allocate to thematic investments at a strategic asset allocation level. The goal of thematic investments is to provide the means to invest in assets that have their returns significantly impacted by the structural changes underlying the theme. Such changes come about through megatrends that shape societies: Demographic shifts, social or attitudinal changes, environmental impact, resource scarcity, economic imbalances, transfer of power, technological advances and regulatory or political changes. Allocating to themes requires discipline because thematic investments are not only exposed to the theme but also to the traditional risk factors. Our approach to allocating to thematic investments uses a framework based on robust portfolio optimisation, which takes into account the expected excess return derived from the exposure to the theme as well as exposures to traditional risk factors. As an illustration, we provide an example where thematic investments in energy transition, environmental sustainability, healthcare innovation, consumer innovation and disruptive tech are added to a traditional multi-asset portfolio.

The Gain-Pain Index: Asset Allocation for Individual (And Other?) Investors
Javier Estrada (IESE Business School)
August 12, 2021
Individual investors typically determine their asset allocation using investor questionnaires, which can be viewed as black boxes that generate a result without highlighting the benefits and costs of the portfolios considered. This article introduces an asset allocation tool, the gain-pain index (GPI), that overcomes this shortcoming. The tool proposed incorporates two critical variables found in investor questionnaires, the portfolio holding period and the investor’s risk tolerance, and broadens the definition of risk beyond volatility by also considering the probability of suffering a loss and the magnitude of the loss. The model is used to determine optimal asset allocations for 21 countries and the world market, for different holding periods and levels of risk aversion.

State-dependent Asset Allocation Using Neural Networks
Reza Bradraniaa (U. of South Australia) and Davood Pirayesh Neghab (Koc U.)
April 2021
Changes in market conditions present challenges for investors as they cause performance to deviate from the ranges predicted by long-term averages of means and covariances. The aim of conditional asset allocation strategies is to overcome this issue by adjusting portfolio allocations to hedge changes in the investment opportunity set. This paper proposes a new approach to conditional asset allocation that is based on machine learning; it analyzes historical market states and asset returns and identifies the optimal portfolio choice in a new period when new observations become available. In this approach, we directly relate state variables to portfolio weights, rather than firstly modeling the return distribution and subsequently estimating the portfolio choice. The method captures nonlinearity among the state (predicting) variables and portfolio weights without assuming any particular distribution of returns and other data, without fitting a model with a fixed number of predicting variables to data and without estimating any parameters. The empirical results for a portfolio of stock and bond indices show the proposed approach generates a more efficient outcome compared to traditional methods and is robust in using different objective functions across different sample periods.

Bayesian Portfolio Selection: Application to Tactical Asset Allocation
Majeed Simaan (Rensselaer Polytechnic Institute)
July 7, 2021
This article discusses the portfolio selection problem from a Bayesian perspective. In doing so, I first provide an overview of the portfolio problem and motivate the decision-making process from an expected utility point of view. Then, I demonstrate the analytical solution to the problem and stress the intuition behind the Bayesian application. In particular, in the case of risky assets, the optimal portfolio corresponds to three funds. The first is the minimum variance portfolio, whereas the others denote two self-financing portfolios corresponding to the mean returns. The combination between the first and the second funds is consistent with the conventional mean-variance portfolio. Furthermore, with the inclusion of the third fund, the portfolio incorporates the priors/beliefs of the decision-making into the portfolio selection. Based on the analytical insights, I conduct a small empirical experiment using two ETFs. The experiment emulates a tactical asset allocation problem. All the empirical analysis is conducted using R.

Currency News and International Bond Markets
Moustafa Abuelfadl (University of New England) and Ehab Yamani (Chicago State University)
September 10, 2021
We use a sample of 27 countries and 63 currency news announcements in an event study framework to examine the impact of currency news on international government bond markets. Our findings reveal a significant spillover of currency news into bond markets. Specifically, the evidence shows significant negative abnormal bond returns, whether measured in dollar terms or local currency terms, implying that currency news plays a role in changing the performance of international government bond markets. We also show that abnormal bond returns remain significantly negative even after controlling for macroeconomic variables. Our results are robust to using alternative risk model specifications, country-level data, and corporate bond data. Our evidence of the significant impact of currency news on bond markets provides essential insights to professional traders, policymakers, and academic researchers.

Alternative Investing: The Fairy Tale And The Future
Richard Ennis (co-found of EnnisKnupp)
August 14, 2021
A fairy tale has sustained alternative investing since the Global Financial Crisis (GFC) of 2008. Here I parse the fairy tale and then set the stage for the future of institutional investing. Freed of the misperception that maintaining several asset-class silos is necessary to achieve efficient diversification, institutional investors will begin to simplify asset allocation. Implicit here is the understanding that alternative investments are purely active strategies. Their role in the portfolio is more transitory than that of stocks and bonds, which are the essential building blocks of efficient diversification. Over time, we can expect to see fewer, more comprehensive asset classes; allocators becoming more discriminating in their choice of individual alt investments; and lesser allocations to alternative investments overall. Successful allocators will use many fewer managers and incur lower costs. There really is no other way forward.

Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
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Cryptos Crash Despite Tesla Leaving Door Open To Accepting Payments

Cryptos Crash Despite Tesla Leaving Door Open To Accepting Payments

Cryptocurrency prices plunged overnight with the selling pressure climaxing…

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Cryptos Crash Despite Tesla Leaving Door Open To Accepting Payments

Cryptocurrency prices plunged overnight with the selling pressure climaxing around the opening of the European markets, closing of Asia.

This left Bitcoin back below $60,000 for the first time in 11 days…

Source: Bloomberg

And Ethereum dropped below $4,000

Source: Bloomberg

There was no obvious news-driven catalyst for the drop and many investors were actually buoyed the last few days after a filing with the SEC suggested Tesla had left the door open to accepting Bitcoin for its products in the future.

“During the nine months ended September 30, 2021, we purchased an aggregate of $1.50 billion in bitcoin. In addition, during the three months ended March 31, 2021, we accepted bitcoin as a payment for sales of certain of our products in specified regions, subject to applicable laws, and suspended this practice in May 2021,” the 10-Q document reads.

“We may in the future restart the practice of transacting in cryptocurrencies (‘digital assets’) for our products and services.”

Additionally, CoinTelegraph reports that PlanB, creator of the popular Bitcoin Stock-to-Flow (S2F) model, called Bitcoin’s price retracement from the $60,000-level the “2nd leg” of what appeared like a long-term bull market.

In doing so, the pseudonymous analyst cited S2F, which anticipates Bitcoin to continue its leg higher and reach $100,000 to $135,000 by the end of the year.

The price projection model insists that Bitcoin’s value will keep on growing until at least $288,000 per token due to the “halving,” an event that takes place every four years and reduces BTC’s issuance rate by half against its 21 million supply cap. 

Bitcoin after the 2012, 2016 and 2020 halving. Source: PlanB

Notably, Bitcoin has undergone three halvings so far: in 2012, 2016 and 2020.

Each event decreased the cryptocurrency’s new supply rate by 50%, which was followed by notable increases in BTC price. For instance, the first two halvings prompted BTC price to rise by over 10,000% and 2,960%, respectively.

The third halving caused the price to jump from $8,787 to as high as $66,999, a 667.50% increase. So far, S2F has been largely accurate in predicting Bitcoin’s price trajectory, as shown in the chart below, leaving bulls with higher hopes that Bitcoin’s post-halving rally will have its price cross the $100,000 mark.

Bitcoin S2F as of Oct. 26. Source: PlanB

PlanB noted earlier this year that Bitcoin will reach $98,000 by November and $135,000 by December, adding that the only thing that would stop the cryptocurrency from hitting a six-digit value is “a black swan event” that the market has not seen in the last decade.

Despite the high price projections, Bitcoin can still see big corrections in the future. PlanB thinks the next crash could wipe at least 80% off Bitcoin’s market capitalization, based on the same S2F model.

“Everybody hopes for the supercycle or the ‘hyperbitcoinization’ to start right now and that we do not have a big crash after next all-time highs,” the analyst told the Unchained podcast, adding.

“As much as I would hope that were true, that we don’t see that crash anymore, I think we will. […] I think we’ll be managed by greed right now and fear later on and see another minus 80% after we top out at a couple hundred thousand dollars.”

Tyler Durden
Wed, 10/27/2021 – 08:23

Author: Tyler Durden

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Tesla Won’t Be the Only Trillion-Dollar EV Stock

Two days ago, Tesla (NASDAQ:TSLA) did something unthinkable – something that only four tech stocks in the history of capitalism have ever accomplished.

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Two days ago, Tesla (NASDAQ:TSLA) did something unthinkable – something that only four tech stocks in the history of capitalism have ever accomplished.

It became a trillion-dollar company.

It joined Alphabet (NASDAQ:GOOG), Apple (NASDAQ:AAPL), Amazon (NASDAQ:AMZN), and Microsoft (NASDAQ:MSFT) as the only U.S. companies to currently hold that distinction. Not only that, but Tesla cleared the trillion-dollar mark faster than any other company.

Source: Morning Brew
Source: Morning Brew

To a lot of folks, all of this just sounds silly.

That’s because, at a $1 trillion valuation, Tesla is now worth more than Toyota, Volkswagen, Daimler, General Motors, BMW, Ford, Stellantis, Volvo, Ferrari, Honda, and Hyundai combined – and most of those companies sold way more cars and recorded way bigger revenues than Tesla did last year.

So… Tesla at a trillion bucks… that has to be a bubble, right?


Because, last I checked, companies aren’t valued on how many cars they sell or how much revenue they rake in – they’re valued on profits. After all, to shareholders, how valuable is the sale of a $40,000 car if the automaker spent $40,000 to make, advertise, and sell the car?

It’s not valuable at all.

That’s the piece that Tesla bears are missing. Profits – not sales – matter, and Tesla is structurally and significantly more profitable than legacy automakers.


Let’s zoom out here. The reality is that, at scale, making an electric vehicle (EV) will be significantly cheaper than making a gas-powered car.

I know. That’s contrary to everything you’ve ever been told. And before you go pull up statistics showing me that EVs are more expensive to make than gas-powered cars today, let me tell you that the current EV production premium is exclusively because of the battery.

The battery comprises about 25% of an EV’s production costs. Strip out the battery and it’s way cheaper to make an EV than a gas-powered car, because there are way less parts.

With EVs, there’s no oxygen sensors, no spark plugs, no motor oil, no timing belts, etc.

The fewer parts you have, the cheaper it is to make.

So, the only thing keeping EV production costs higher than gas-car production costs is the battery – and those costs are plummeting. Between 2007 and 2020, the cost of EV battery packs has registered an average decline of 16% per year.

The more time goes on, the more battery costs go down, and the cheaper and cheaper it gets to make an EV.

Soon enough, battery costs won’t be a hurdle anymore. By that point – likely within the next decade – EVs will be significantly cheaper to make than gas-powered cars.

Not to mention, consumer demand is shifting toward EVs, so today’s prospective car buyers are willing to pay a premium for an electric car. That should result in higher sales prices for EVs, and reduce marketing costs for EV makers. Notice how Tesla hasn’t had to materially discount its cars, or how the company never runs any ads yet everyone still wants one?

In financial terms, the implications here are obvious. Tesla should sell its cars at higher prices than traditional automakers, and operate at significantly higher gross margins, with lower marketing spend, resulting in significantly higher profits per car.

Let’s put some numbers to this…

The average car sells for about $40,000. Tesla’s average sales price last quarter was $50,000. Higher sales price? Check.

Automakers typically run at 15% gross margins. Tesla clocked in at 30% gross margins last quarter. Higher gross margins? Check.

Your average automaker spends about 7% of revenues on sales and marketing, and another 5% on research and development. Tesla’s marketing spend rate is currently about 7%, and rapidly falling with an opportunity to hit 5% or lower at scale, while the R&D rate is already closing in on 4%. Lower operating expense (opex) rates? Check.

Add it all up, and the average automaker is netting about $1,200 in operating profits per new car sold, while Tesla is making about $10,500 in operating profits per new car sold – a near 9X increase.

So… significantly higher profits per car? Double check.

And that, in a nutshell, is why Tesla deserves its trillion-dollar valuation.

Elon Musk & Co. make about 9X more per car than other automakers, so TSLA deserves to be valued at about 9X your biggest legacy automaker, assuming Tesla can one day sell as many cars as that automaker (which we think is doable).

The biggest legacy automaker? Toyota. Its market capitalization? $240 billion. A 9X multiple on that is a $2-plus TRILLION potential valuation for Tesla one day.

This run isn’t over…

More importantly, though, the above “back-of-the-napkin math” is why Tesla won’t be the only trillion-dollar electric vehicle company.

Because Tesla won’t be the only company in the EV universe to benefit from economies of scale, lower production costs, and lower marketing costs. In fact, almost all pure EV makers will benefit from those dynamics, which means they will make about 9X as much profit per car sold as their legacy automakers at scale.

Therefore, while the auto industry titans of today are worth anywhere between $50 billion and $250 billion, we think the EV industry titans of tomorrow will be worth 9X that – anywhere between $450 billion and $2 trillion.

So what does that mean for you as an investor today?

Well, most EV stocks not named Tesla are worth less than $20 billion today.

That’s why – while we’re still bullish on Tesla – we’re much more bullish on other EV stocks whose best days are still ahead of them… stocks that we feel have 10X, 20X, even 30X upside potential.

The million-dollar – er, trillion-dollar – question is: What are the names of those stocks?

That’s what we aim to uncover in our most exclusive investment research service, Early Stage Investor.

For readers who are unaware, Early Stage Investor is our small-cap investment advisory where we focus on investing in the world’s most innovative companies and game-changing technologies… while they’re still in their early stages… before they soar thousands of percent like Tesla.

Very recently, we just launched a brand-new portfolio in Early Stage Investor called the 4 EV Stocks for Financial Freedom portfolio – and in that portfolio are the names of four EV stocks that we feel are best positioned to follow in Tesla’s footsteps, turn into giants of the future EV industry, and ultimately score shareholders enormous profits.

The best part? All four of those stocks are tiny and off the radar of most investors, so getting in now is like getting in on Tesla back in 2015… before Elon Musk was a household name, and before TSLA stock turned early shareholders into “Teslanaires.”

These stocks could do the same.

The only question that remains: Will you be one of them?

On the date of publication, Luke Lango did not have (either directly or indirectly) any positions in the securities mentioned in this article.

The post Tesla Won’t Be the Only Trillion-Dollar EV Stock appeared first on InvestorPlace.

Author: Luke Lango

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Energy Continues To Lead US Equity Sectors By Wide Margin In 2021

The reboot of energy stocks rolls on in the year-to-date sector horse race, based on a set of ETFs through Tuesday’s close (Oct. 26). The rebound in…

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The reboot of energy stocks rolls on in the year-to-date sector horse race, based on a set of ETFs through Tuesday’s close (Oct. 26).

The rebound in the previously faltering energy sector began a month ago. In late-September, reported that Energy Select Sector SPDR Fund (XLE) regained the lead for the major equity sectors in 2021. That lead has subsequently strengthened through October.

XLE is up an astonishing 61.3% so far this year, or roughly twice the year-to-date gain in our previous report from a month ago. Lifting the fund is a combination of surging oil and gas prices, which in turn is driving bullish earnings expectations amid mounting evidence that higher inflation may persist for longer than previously expected.

Not surprisingly, current conditions have triggered a bullish attitude adjustment for the sector’s outlook, reports Barron’s:

About 80% of all analysts’ profit forecasts for this year and next have been increased, higher than the 74% seen in September, according to Citigroup. That means more profit projections have been increased than reduced in the past month.

The strength of energy’s year-to-date rally is no less conspicuous when you consider that the second-best sector performer this year is far behind. Financial Select Sector SPDR (XLF) is up 39.5% — a strong gain in absolute terms, but nowhere near XLE’s surge.

The US stock market overall is posting an impressive rise this year via SPDR S&P 500 (SPY). But the ETF’s 23.2% increase so far this year pales next to XLE’s advance.

The weakest sector performer this year: Consumer Staples SPDR (XLP), which is higher by a relatively moderate 7.9% year to date. The sector, traditionally considered one of the more resilient, defensive corners of the market, is struggling to keep pace with equities overall (SPY), as this chart of relative performance history shows:

When the line is rising, the broad US equity market (SPY) is outperforming XLP. ON that basis, XLP’s defensive features have remained out of favor for much of the time since the market began recovering from the coronavirus crash in the spring of 2020.

Learn To Use R For Portfolio Analysis
Quantitative Investment Portfolio Analytics In R:
An Introduction To R For Modeling Portfolio Risk and Return

By James Picerno

Author: James Picerno

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