Target said that it was ending its diversity, equity and inclusion goals as it tries to align itself with an “evolving external landscape.”
BUSINESS
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5 Ways To Rate Your Portfolio Manager
Reviewed by JeFreda R. Brown
The overall performance of your portfolio is the ultimate measure of how well your portfolio manager does their job. The five performance ratios presented below provide investors with various measurement options.
Measuring total return isn’t the best way to determine whether or not your investments are being managed effectively. For a clearer picture, you must measure your portfolio’s risk-adjusted return.
Accounting for risk fine-tunes the concept of return. For example, a 2% annual total return may initially seem small. However, if the market only increased by 1% during the same time interval, then the portfolio performed well compared to the universe of available securities.
On the other hand, if this portfolio was exclusively focused on extremely risky micro-cap stocks, the 1% additional return over the market does not properly compensate the investor for risk exposure.
With that information, an investor could have a meaningful discussion of performance quality with their portfolio manager.
Key Takeaways
- Understanding the performance of your portfolio can help you size up the performance of your portfolio manager.
- For an effective measurement of your portfolio’s investment performance, determine your portfolio’s risk-adjusted return.
- The total return doesn’t provide the full picture of performance because risk isn’t accounted for.
- When comparing the performance of different investments, be sure to use the same ratio for each so that you compare apples to apples.
1. Sharpe Ratio
Portfolio Standard Deviation(Expected Return − Risk Free Rate)
The Sharpe ratio, also known as the reward-to-variability ratio, is perhaps the most common portfolio management metric.
The excess return of the portfolio over the risk-free rate is standardized by the standard deviation of the excess of the portfolio return.
How It Works
Hypothetically, investors should always be able to invest in government bonds and obtain the risk-free rate of return. The Sharpe ratio determines the expected realized return over that minimum.
Within the risk-reward framework of portfolio theory, higher-risk investments should produce high returns. As a result, a high Sharpe ratio indicates superior risk-adjusted-performance.
Some of the ratios that follow are similar to the Sharpe in that a measure of return over a benchmark is standardized for the inherent risk of the portfolio. But each has a slightly different approach that investors may find useful, depending on their situation.
2. Roy’s Safety-First Ratio
Portfolio Standard Deviation(Expected Return − Target Return)
Roy’s safety-first ratio is similar to the Sharpe but introduces one subtle modification. Rather than comparing portfolio returns to the risk-free rate, the portfolio’s performance is compared to a target return.
How It Works
Roy’s safety-first ratio is based on the safety-first rule, which states that a minimum portfolio return is required and that the portfolio manager must do everything they can in order to ensure this requirement is met.
An investor will often specify that their target return should be based on a certain benchmark, such as a particular financial amount that allows them to maintain a certain standard of living.
In such a case, an investor may need $50,000 per year for spending purposes; the target return on a $1 million portfolio would then be 5%.
If the benchmark is a specific index, the target return might be tied to the S&P 500. Or the investor might use the annual performance of gold as a target. The investor would have to identify their target in the investment policy statement.
3. Sortino Ratio
Downside Standard Deviation(Expected Return − Target Return)
The Sortino ratio looks similar to the Roy’s safety-first ratio. The difference is that, rather than standardizing the excess return over the standard deviation, only the downside volatility is used for the calculation.
The previous two ratios penalize upward and downward variation. For example, a portfolio that produced annual returns of +15%, +80%, and +10%, would be perceived as fairly risky, so the Sharpe and Roy’s safety-first ratio would be adjusted downward.
How It Works
The Sortino ratio, on the other hand, only includes the downside deviation. This means that only the volatility that produces fluctuating returns below a specified benchmark is taken into consideration.
Basically, only the left side of a normal distribution curve is considered as a risk indicator, so the volatility of excess positive returns is not penalized. That is, the portfolio manager’s score isn’t hurt by returning more than was expected.
Note
A risk-adjusted return for a portfolio is a higher quality metric than total return because it incorporates the risks inherent in an investment. It provides a clearer view of your reward relative to the investment’s risks.
4. Treynor Ratio
Portfolio Beta(Expected Return − Risk Free Rate)
The Treynor ratio also calculates the additional portfolio return over the risk-free rate.
How It Works
In this case, beta is used as the risk measure to standardize performance instead of standard deviation. Thus, the Treynor ratio produces a result that reflects the number of excess returns attained by a strategy per unit of systematic risk.
Since the Treynor ratio bases portfolio returns on market risk, rather than on portfolio-specific risk, it is usually combined with other ratios to give a more complete measure of performance.
After Jack L. Treynor introduced this portfolio metric, it quickly lost some of its luster to the now more popular Sharpe ratio.
However, Treynor will definitely not be forgotten. He studied under Italian economist Franco Modigliani and was one of the original researchers whose work paved the way for the capital asset pricing model.
5. Information Ratio
Tracking Error(Portfolio Return − Benchmark Return)
The information ratio is slightly more complicated than the aforementioned metrics. Yet it provides a greater understanding of the portfolio manager’s stock-picking abilities.
In contrast to passive investment management, active management requires regular trading to outperform a benchmark. While the manager may only invest in S&P 500 companies, he may attempt to take advantage of temporary security mispricing opportunities.
The return above the benchmark is referred to as the active return, which serves as the numerator in the above formula.
How It Works
In contrast to the Sharpe, Sortino and Roy’s safety-first ratios, the information ratio uses the standard deviation of active returns as a measure of risk instead of the standard deviation of the portfolio.
As the portfolio manager attempts to outperform the benchmark, they will sometimes exceed that performance and at other times fall short.
The portfolio deviation from the benchmark is the risk metric used to standardize the active return.
Potential Pitfall
Problems arise when the formulas are adjusted to account for different kinds of risk and return. Beta, for example, is significantly different from tracking-error risk. So you must use the same ratio when comparing returns.
In other words, the results of the Sortino ratio relating to one portfolio manager must only be compared to the Sortino ratio for another.
What Is Risk-Adjusted Return?
It’s the return of an investment relative to its risk. It helps investors determine whether investing in a security is worth the risk involved.
What Is Total Return?
Total return is the income produced by your investment plus the growth in its value. It’s expressed as a percentage of the amount that you have invested.
What Is the Jensen Ratio?
The Jensen ratio, or Jensen’s Alpha, is another way to measure risk-adjusted return. In particular, it measures the excess return over expected return and adjusts for market risk.
The Bottom Line
The five ratios presented above can help investors to calculate excess return per unit of risk and size up portfolio performance. They all can be interpreted in the same manner: The higher the ratio, the greater the risk-adjusted-performance.
Standardized risk-adjusted returns allow investors to understand that portfolio managers who follow a risky strategy are not more talented in any fundamental sense than low-risk strategy managers. They are just following a different strategy.
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It’s Easier Than You Think to Build With AI and Web3
Remember those middle-school writing prompts: Describe your favorite cookie.
Your teacher told you to write it as if to an alien, a being who had never encountered a cookie before, which meant touching on each sense – sight, sound, smell, touch, taste. You might not have realized it then, but describing something in a way that allows people to get a clear picture is actually quite hard.
Let me try to describe Matheus Pagani, founder and CEO of Venture Miner. Matheus is a male with light caramel skin and dark brown hair. Even though his hair is cut close, you can tell it’s curly. He’s got a thick dark brown, almost black beard, which connects to a mustache. His eyes are dark brown behind thin wire glasses. His bottom lip sticks out a little further from his top lip, giving him a look of assurance, but not arrogance.
Picturing him yet? How confident are you?
Oh yeah, and he’s Brazilian.
Got it?
Let’s see what Matheus Pagani actually looks like.
Is this what you had come up with in your head from my description? Doubt it. Whenever I told you he was Brazilian, did you accessorize him in bright colors and a feathered headdress? Something like this?
If so, check your bias, but also you’re thinking like an AI. That was what ChatGPT came up with from the prompt “some Brazilians having fun.” Pagani showed this and other examples spit out by our generative AI (Italians have fun by sitting around long tables with multiple generations eating pizza) during the AI2Web3 Bootcamp in NYC in early December.
The bootcamp, run by Pagani and Build City, brought together 59 participants across all skill levels to learn how the two buzziest (and often misunderstood) technologies can be brought together to create useful products and services. Pagani used a version of the middle-school assignment to explain how and why AI made the significant leaps that have kept us all excited and on edge over the past few years. Before there was largely only text data being used to train AIs, and as the exercise highlights, that only goes so far. But mix text information with visual data, and you get a fuller picture.
And understanding this, getting hands on with both AI and blockchain technology to understand its core components is what the bootcamp was all about. For Pagani, these skills are going to be relevant for nearly all people – engineers, tech users, journalists, artists, doctors – real soon.
“We want to join brilliant minds from all backgrounds to come and work with AI and Web3, since the junction of their multiple perspectives can uncover new use cases that we would never envision just with a specialized Web3 or AI mindset alone,” Pagani said. “Nowadays we have tools to easily enable any non-technical enthusiasts to build practically functional applications and systems just with “plain English,” so what matters is bringing passionate people interested in solving problems together with the proper education. When you have this combination, you just need to light the match and watch it burn.”
Mind-Boggling Building
What makes the intersection of these two technologies so exciting is just how much you can build in such a short amount of time without really any prior technical experience.
Not only will AI source whole codebases with the right prompt, but the crypto industry is also building tools to help make developing at the intersection of both more intuitive and accessible.
For instance, Coinbase, who sponsored the bootcamp, launched AgentKit in November. The framework allows developers to build AI agents with their own crypto wallets, enabling the agents to interact autonomously with blockchain networks. This could be used to build a squad of agents that can monitor the markets and execute trades automatically based on predefined rules and guardrails.
“One day, we’ll have AI agents own their own cars and operate their own taxi service that gets paid by customers in crypto and then uses that crypto to purchase repairs,” Lincoln Murr, associate product manager at Coinbase, told the attendees.
Coinbase currently has a grants program ongoing for building with AgentKit. “What you build doesn’t have to be useful; we have a bias towards cool stuff,” Murr told the bootcamp, hoping to inspire projects and applications that no one has yet thought of.
Ora Network also has an interesting model for developers looking to build AI-enabled Web3 applications or vice versa. The network allows developers to utilize current large language models, including Meta’s Llama3 and Stable Diffusion, but it also enables developers to build their own models and offer a so-called initial model offering (IMO) to crowdfund its continued development.
“It’s kind of winner-takes-all right now in AI, but with this model, we’re allowing the crowdfunding of AI building and training, so people can have a share of the models, which is empowering if we think these models will run society in a decade,” Alec James, partnerships and growth lead at Ora, said during the bootcamp. “If that’s the case, we’ll want that development distributed.”
Near, Fleek and Alora were also among the companies that sponsored the bootcamp and presented their various tools and programs for building at the intersection of these two innovative technologies.
Can Devs Do Something?
During the final day of the bootcamp, nine teams presented working prototypes for projects that blended Web3 and AI. These projects ranged from AI assistants meant to help you pick gifts, order delivery or diversify your financial portfolio to applications to help crypto operators pump out memecoins with big virality potential.
Jackie Joya, a participant who had flown in from San Francisco, said the bootcamp has really inspired her to keep building. With a background in animal science, Joya is still new to engineering, but was amazed how much a novice could build with the tools available.
Other participants, across all skill levels, said similar things. Choudhury Imtiaz, a market researcher from Bangladesh, who is in the U.S. on an H-1B1 Visa waiting for a placement, hasn’t heard of Web3 before the bootcamp, but was able to pitch a team project on the last day. And Isayah Culbertson, who has worked as an engineer for both crypto and AI projects separately, was able to learn skills for building with both, which he thinks has the potential to change the world for the better.
“I see the combination accelerating the research and development of so many different fields, while also allowing for a more equitable distribution of wealth generated from that R&D,” he said.
Nasdaq Files for In-Kind Redemptions for BlackRock Spot Bitcoin ETF
Nasdaq has filed a proposed rule change to allow in-kind creation and redemption for the BlackRock iShares Bitcoin Trust (IBIT), according to a Friday filing to the U.S. Securities and Exchange Commission (SEC).
The process allows large institutional investors, called authorized participants (APs), to buy and redeem shares of the fund directly to bitcoin (BTC).
It is considered to be more efficient as it allows APs closely monitor the demand for the ETF and to act fast by buying or selling shares of the fund without cash being involved in the process. Retail investors are not eligible to participate.
When the SEC first approved spot bitcoin ETFs including IBIT last January, the agency allowed to launch the funds with cash redemption, instead of bitcoin.
“It should have been approved in the first place but Gensler/Crenshaw didn’t want to allow it for a whole host of reasons they gave,” Bloomberg Intelligence ETF analyst James Seyffart wrote on X. “Mainly [they] didn’t want brokers touching actual Bitcoin.”
BlackRock’s IBIT is the largest spot BTC ETF on the market, attracting nearly $40 billion of inflows in its first year, making it the most successful ETF debut ever.
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