Author Archives: Scalper1

Are Hedge Funds Really That Evil? Challenging The Common Hedge Fund Myths

Click to enlarge I will not surprise anyone by concluding that the coverage of hedge funds in the media and the general public opinion about them is negative, including some regulators and representatives of the Academia. This is counter intuitive, because, as I explained before , properly selected hedge funds demonstrate great results and have the potential to improve any investment portfolio. But what we see in the headlines most of the time is “average performance”, “high fees”, “flashy” lifestyles of hedge fund managers or fraud related “scandals”. Indeed such topics generate more buzz than news about good performance, but part of the reason is that hedge funds are slightly mysterious and not fully understood, especially by individual investors, “grey area” in the investment field thus surrounded by many rooted myths. In this article I summarize, discuss and try to bust some of the most prevalent hedge fund myths and misconceptions. MYTH NO. 1: Hedge funds are only accessible to institutional investors and (ultra) high net worth individuals – they are not available to retail investors like me and you. REALITY: Due to structural innovations, e.g. liquid alternatives, UCITS funds, etc., hedge funds are lately as accessible to retail investors as ever since their minimum investment amount may be as low as USD10k or even USD1k. Moreover, some hedge funds are traded on exchanges (e.g. London Stock Exchange Hedge fund list or Eurekahedge UCITS database), while funds of hedge funds may pool private investors’ money together and invest into hedge funds otherwise harder to access. Finally, there is a wave of fin-tech startups engaging in various ways to replicate hedge fund strategies or pool investors’ capital that are entering the scene (e.g. Sliced). On the other hand, hedge funds are complex structures requiring knowledge and experience to comprehend, thus it is naive to expect and strive to have every mom and dad be able to invest with them. Besides, hedge funds are dedicated for long term investment and create the most value over long investment horizons, thus higher minimum investment amount makes sure to filter those who can afford themselves quarterly or even annual liquidity, i.e. are less likely to experience sudden liquidity needs. MYTH NO. 2: Hedge funds are very risky. REALITY: All investment tools, vehicles and strategies bare both general and their own unique risks. Most of hedge funds’ structure and operational risks are addressed via proper due diligence process, while if we define riskiness by the standard deviation of performance, hedge funds as a group are less volatile than such traditional assets as stocks. Click to enlarge So it means that owning stocks has significantly more downside risk than owning hedge funds, because the latter are more flexible, active and have a wider toolkit of strategies at hand, including shorting. Moreover, since hedge funds exhibit low correlation to most traditional asset classes (see below), once added to an investment portfolio, they are able to reduce the volatility of the overall investment portfolio. Click to enlarge Source: Natixis MYTH NO. 3: Investing with hedge funds, investors have to give up liquidity and access to their capital. REALITY: Liquidity profiles of hedge funds can range from daily liquidity (e.g. liquid alternatives), to very common monthly liquidity, to quarterly or annual, so if liquidity is the main criteria of an investor, (s)he definitely has a range of options. However, firstly, liquidity profile determines and affects directly the opportunity set the manager is able to tackle, so it is difficult to expect a daily liquidity fund post the same results as annual liquidity vehicle, and secondly, if your main criteria is liquidity, hedge funds might not be the place for you at all. To conclude, yes you can access highly liquid options in hedge fund space, but then you might need to give up some of the less liquid (but naturally higher potential) opportunities that hedge funds are only able to tackle due to their structure in the first place. MYTH NO. 4: Hedge funds are too expensive. REALITY: It depends very much who you are comparing to. Yes, hedge fund fees are higher in absolute terms than e.g. mutual fund fees. However, this is the price not only for the access to different, complex, unique, niche tools and strategies hedge funds provide, but also the risk management infrastructure in place to handle difficult situations in the markets better than yourself or a long only mutual fund manager would. Moreover, hedge fund fee structure serves in aligning the interests of investors and managers which are both interested in better results, while you can’t really call mutual fund fees “motivating”. Finally, hedge funds’ results we see are already after-fee results and they obviously satisfy investors and justify the fees since industry assets are at all-time highs and large part of the hedge fund inflows come from very sophisticated institutional investors. MYTH NO. 5: Hedge funds don’t help in a market crash. REALITY: As demonstrated earlier, hedge funds exhibit lower correlation to traditional asset classes, providing the real diversification (and downside protection) exactly when it is needed the most – during crises and market crashes. As seen in the picture below, hedge funds proved to fare better than stocks during each of the recent market downturns. Click to enlarge Hedge funds: HFRI Fund Weighted Composite Index. World stocks: MSCI World Net Total Return hedged to USD Source: Bloomberg, MSCI, Man Group MYTH NO. 6: The most important thing in hedge fund selection is a large house and a respected name. REALITY: While many investors see these attributes as an assurance of quality and investor trust, they are no way a substitute for proper due diligence on a fund. The same way as large and well-known banks appear to engage in rate fixing scandals, there are plenty examples of “large houses” and “respected names” among hedge funds that have conducted fraud, abused investor rights and/or blew up, the classic ones being the Galleon Group, SAC Capital, Madoff Investment Securities. It is true that large investment houses provide an exceptionally high level operational infrastructure, but these days even a 100-million fund is able to access most of those solutions. Moreover, due to being nimble, innovative and diligent, smaller and newer funds reportedly outperform many of the large renowned peers. To conclude, large house and a respected name should not be a hedge fund selection criteria: neither it protects from fraud, nor guarantees superior performance. However, hedge fund due diligence and selection requires specific expertise and experience-based judgment so it is advisable to consult specialists anyway. MYTH NO. 7: Hedge fund managers are dishonest, unscrupulous fraudsters. REALITY: This is exactly the public opinion formed by the media which tends to catch and escalate the juicy stories of exuberant lifestyles and securities fraud. However, those stories are relatively few compared to almost 15 thousand hedge funds existing out there so there are as many cheaters in the hedge fund industry as there are in oil and gas, pharmaceuticals, politics and anywhere else. The majority of the hedge fund managers are very talented investment professionals with a unique idea or skillset trying to exploit it and make a living by earning investors return and their capital. It is investors’ concern to ascertain who are they trusting their money with. MYTH NO. 8: Hedge funds are unregulated “blackboxes”. REALITY: In the aftermath of the recent financial crisis, hedge funds became as regulated as ever with such impactful regulations as AIFMD, UCITS, MIFID, Dodd-Frank etc. introduced in order to maintain the perceived stability of financial sector. It depends on certain jurisdictions, but generally the times of two dudes with a laptop at a garage are gone – it takes time, money and expertise to get and maintain all the operational, compliance, reputation checks from the regulators while investor expectations and standards, especially if you target institutional investors, has also brought operational and governance practices to a new level. When it comes to transparency, the industry standard has gone further away from opaque reporting and the current best practice is monthly distribution including, depending on a strategy, a certain level of portfolio transparency allowing for a picture of strategy implementation. On the other hand, a complete or regulated transparency would take away hedge funds’ competitive advantage that allows them to generate returns in the first place. MYTH NO. 9: Hedge funds are evil and does bad to the society REALITY: Besides helping people and institutions achieve their financial goals, hedge funds serve to the financial industry and society in general. They are sometimes the last resort buyers of assets no one else wants to buy providing liquidity to the markets. They often provide capital to innovative projects as well as small and medium size businesses that face difficulties raising capital from more traditional sources. Hedge funds employ very talented and professional people for highly paid roles, who in turn pay large amount of taxes. Hedge funds not only donate significant amounts to non-profits and charities, but also when included in investment portfolios of foundations and endowments help earn money to support communities, improve education, health, economic areas, foster cultural development. Included in investment portfolios of endowments, hedge funds help them fund scholarships while included in investment portfolios of pension plans hedge funds allow them provide retirement security to millions of people. In fact, most of the money recently flowing into the hedge fund industry is exactly the institutional money. Due to some or all of the mentioned myths rooted around hedge funds, some investors miss the opportunity to access unique ideas, niche strategies and innovative tools and achieve the portfolio enhancement hedge funds provide. While the negative views on hedge funds and the whole financial industry may continue attracting the media attention, what is important for an investor is to evaluate critically, realistically and objectively the information, avoid generalization and trust their own or their advisors’ competence in finding the best solutions. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it. I have no business relationship with any company whose stock is mentioned in this article. Additional disclosure: MC Investments is a hedge fund due diligence and manager selection advisory.

AI Meets ROI: Where Artificial Intelligence Is Already Smart Business

Decades of research and billions of dollars have poured into developing artificial intelligence, which has crossed over from science fiction to gameshow novelty to the cusp of widespread business applications. Artificial intelligence is an area of computer science where computers are designed to think and operate much like a human brain, supported by advanced forms of computing and software. But it’s only as smart as the amount of information fed into its memory banks. The more information, the smarter it gets. The greatest advancements have been demonstrated in the area of game playing, but AI is now showing its mettle in the business world. “People are starting to kick the tires, looking to see how it can help their business and the bottom line,” said David Schubmehl, who follows the AI field for research firm IDC. “The return on investment evidence is not yet clear, but it’s starting to happen.” Facebook ( FB ), Alphabet ( GOOGL ), IBM ( IBM ) and Nvidia ( NVDA ) are among tech leaders with big artificial intelligence ambitions. “We’re starting to see a lot of companies beginning to use different types of AI tech for various uses,” said Schubmehl. “We’re also seeing a lot of venture capital money flowing in and a lot of acquisitions taking place.” IBM, which may have the deepest AI investments and most far-reaching ability of any company, has pitched “cognitive computing” as a tool for businesses via its cloud-based Watson platform. Facebook is using AI to decipher the best ways to bring Internet service to remote areas of the world and to make its News Feed feature more relevant to users of the social network. Alphabet is using it to enhance Google search abilities, improve voice recognition and to derive more data from images and video. Nvidia has developed chip technology for AI platforms used in autonomous driving features, and to enhance how a driver and car communicate. Alphabet, Mobileye ( MBLY ) and others also are tapping AI in the race for driverless cars. It’s not enough to have Google Maps loaded up: A self-driving system must identify potholes, weather conditions, traffic congestion and other drivers’ behavior — improvising and improving on the fly. AI: Ready, Chess, Go Artificial intelligence, a term coined in 1955, was popularized when IBM’s “Big Blue” became the first computer to beat a reigning world chess champion, Gary Kasparov, in 1997. IBM won again in 2011, when its Watson computer on “Jeopardy!” outsmarted the game show’s two top players ever. Last October, an AI computer beat a three-time European champion in the ancient Asian game of “Go.” AphaGo, built by DeepMind, part of Alphabet’s Google, beat Fan Hui by 5 games to 0, the first time a computer program has ever beaten a professional Go player and a feat thought to be a decade away. On Tuesday, AlphaGo won the first game vs. Lee Sodol, who is ranked No. 5 in the world. Tuesday’s match shows that AlphaGo has made big improvements since beating the No. 633 ranked Fan Hui last year. Google paid $400 million to acquire DeepMind in 2014. But despite rapid advances, artificial intelligence is still in the early stages of business deployment. “A lot of what AI is being used for today only scratches the surface of what can be done,” said Babak Hodjat, co-founder and chief scientist at Sentient Technologies . “It will become so ubiquitous that we won’t even call it AI anymore.” AI Picks Out Your Shoes Sentient emerged from stealth mode in late 2014 with a massively distributed AI platform that companies can use to boost performance. As shoppers at Shoes.com browse through photos of shoes and click on ones they like, Sentient’s technology narrows the selection, so people don’t get overwhelmed by choices. There’s no need for text-based searches or drill-down navigation, said Hodjat. The AI technology deciphers what shoppers are looking for, letting them quickly dive deeper into a catalog to find the perfect item that might otherwise go undiscovered. “We’ve revolutionized the user experience on an e-commerce website,” said Hodjat. “It’s a huge change in the way users interact with products online and therefore drives conversion.” Sentient has received $143 million in venture capital funding, the most of any AI startup, according to research firm CB Insights. Since 2010, AI startups have received $967 million in funding. Intel ( INTC ) alone has invested in 16 AI companies, including Saffron Technology . Saffron says its platform “mimics the fundamental principles of how humans remember and learn.” In a case study on its website, Saffron helped an insurer to identify fraudulent auto insurance claims. Over 10 weeks, Saffron examined 113,000 claims from one year in one state and found three potential fraud rings. It then detected that these rings were part of a larger ring involved with 38 claims, of which the insurance company had paid out about $400,000 in claims. Saffron was able to collect data that identified relevant and unknown relationships, including different providers, demographics and injury descriptions, creating a knowledge store that had never been done before. Saffron forecasts that the insurer can avoid a payout of tens of millions of dollars a year. AI goes by terms such as machine learning and deep learning. IBM calls it cognitive computing. In October it launched Cognitive Business Solutions, with 2,000 consultants skilled in data analytics, cloud computing and other areas. More than 500 companies have deals to use Watson, as a cloud service, to develop commercial products, apps and services. Turner Broadcasting on Feb. 29 signed a deal to use Watson in its ad sales efforts. The Time Warner ( TWX ), unit owns TBS, TNT and CNN. Using IBM Watson, Turner expects to parse through all manner of data to help draw in more advertisers and provide them with greater impact. Watson Can Predict Low Blood Sugar Watson Health is a platform for physicians, researchers, insurers and other companies focused on health and wellness. Medtronic ( MDT ) is collaborating with IBM on personalized care for people with diabetes. By analyzing patient info and data from Medtronic devices, Watson can predict low blood sugar programs three hours in advance. Artificial intelligence is all about using advanced technologies to help develop brainy reasoning from disorganized information — unstructured data — to derive accurate decisions. “What we’ve done with all our research is to really understand how to add unstructured data to a decision,” said David Kenny, general manager of IBM Watson. Unstructured data comes from a multitude of sources that is not organized. It can be the data bits from photos, medical images or video and audio transmissions. It can be the tons of data that flows in from cameras or sensors in buildings or smartphones, from Web traffic, tweets, inside emails, government filings or business documents. The more information an artificially intelligent computer can digest the smarter it gets. Today The Weather, Tomorrow… Collecting data on a massive scale is among the reasons IBM acquired several Weather Co. properties, including Weather.com, Weather Underground and mobile and cloud-based assets, for a reported $2 billion in October. IBM will be able to analyze data from more than 2 billion weather reference points, over 40 million smartphones and 50,000 airplane flights per day, letting it offer a broad range of data-driven products and services to more than 5,000 clients in the media, aviation, energy, insurance and government industries. IBM said it can provide predictive weather analytics along with real-time analysis of social media chatter, detailed understanding of transportation flows and other data that will benefit retailers and distributors. The Weather Co. assets will serve as the foundation of a new Watson unit focused on the Internet of Things (IoT). Early this year, IBM announced that it would invest $3 billion to build out IoT products and services. “The more we do this, the smarter Watson gets and the smarter AI gets,” said Kenny. As to why AI is becoming more widespread: “It works,” Kenny said. “Users of AI are saving time and money. They’re making faster decisions and getting better outcomes.” An analysis of Facebook and Alphabet’s Google by research firm Innography shows a surge in AI patent filings that began in 2010. Alphabet currently has more than 3,000 AI patents that are active or pending government approval. Facebook has about 870. AI Knows Where You Live Facebook last June opened an artificial intelligence lab in Paris with a goal of improving the way users interact on the world’s largest social network. “It’s our hope that this research will ultimately help us make services like News Feed, photos and search even better and enable an entirely new set of ways to connect and share,” Facebook said at the time. It also has AI research teams at its Menlo Park, Calif., headquarters and in New York. Facebook in February revealed its Connectivity Lab project. It used AI to analyze 8.3 million square miles of land, using roads, schools and other structures to determine where and how many people live in a given area. That can tell Facebook’s Aquila drones where to go to provide Internet access to less-developed areas, as part of the company’s Internet.org initiative. “This data will give us a greater understanding of how populations are dispersed, so governments and others can prioritize investments in infrastructure, from transportation to healthcare and education,” Facebook said.

Can You Deal With A Stock Market Downturn?

Sometimes we’re late to interesting polls, but hey, they’re still interesting. Back in November, Gallup and Wells Fargo polled people to ask them how well they could stomach a “significant” market downturn, publishing the results on January 22nd . Or note, they defined significant as 5-10%. The results were quite confident: Gallup/Wells Fargo Downturn Poll Some wacky lines there – 87% of stockholders were at least moderately confident in their portfolios, and 82% of investors overall. People in a better position to actually handle downturns with smaller returns – those who don’t hold stocks – were only 61% moderately or better confident. Should We Trust Our Peers at their Word? In a word, no. These are interesting results, for sure, but I see lots of problems here – not just the fact that a significant downturn is defined as only 5-10%. The most recent recession saw drops an order of magnitude larger – in percentage terms (!) – of over 50% in major indices. We lost major financial institutions over a hundred years old, investors panicked, and maybe 10% of people (that’s a stretch) were confidently buying at any opportune time, let alone not panic-selling everything they owned. (We played around with what a “significant” drop might actually be in the past, but found you can be more than a few years early with your calls in some circumstances and still weather a downturn.) So let’s concentrate on our peers’ answers themselves. Do you really think this poll accurately reflects how people would react in a downturn? No, neither do I. You’ve got something of a Lake Wobegon effect going on here – you know, the “fictional” town where everyone was above average. In reality, stock markets have a tendency to over-correct – markets historically oscillate somewhere between ridiculously overpriced and a bargain (of course, identifying those periods is, perhaps, impossibly hard except in retrospect). That’s because previously confident people are selling into a downturn – “locking in losses” – and buying only when the stock market has come back “buying the highs!”. In fact, identifying actual investor results backs up those statements to a degree you’d almost think impossible. Dalbar releases studies on actual investor performance in the markets versus price (or dividend reinvested price) returns, and the results are crazily disconnected: through November 2015, in the order of earning 5.5% on S&P 500 funds in the last 20 years, versus stated returns around 9.85% . (We have a calculator so you can see dividend reinvested returns for the S&P 500 and the Dow Jones Industrial Average). Okay Smart Guy, What Then? For the average investor – and, Wobegon aside, we’re all probably closer to average than we tell ourselves – the best move is to set it and forget it. Consistently, when we do have market downturns, it turns out that many investors have actually overestimated their intestinal fortitude. For a typical person, the best move is to set your portfolio during market doldrums , with a mind to setting in up in such a way that you won’t mind too much if there is a massive move to either the upside or downside. As for re-balancing, it’s best if you go in with a plan, and openly rebalance at a standard time – and, if you can, avoid doing it that often. Believing in your portfolio is one thing, but investing during mania or a crash is no formula for a successful long-time plan. So, make the case. Would you be prepared for a significant downturn without selling most of your portfolio? Why, or why not?