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POSTS BY TOM BERRY
  • CFA Institute Officially Launches the Asia-Pacific Research Exchange

    25 Jun 2017
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    Unveiled at a global launch event held in Hong Kong on June 20, 2017, the Asia-Pacific Research Exchange or ARX (www.arx.cfa), is a user-driven community hub that gathers scholarly papers, research reports, articles and blogs, conference presentations and datasets from both practitioners and academics.

    Commenting on ARX, Nick Pollard, Managing Director, APAC, CFA Institute, explained that: "We are responding to a need. With ARX, we provide a platform that allows people to share their knowledge and wisdom." He continued: "ARX is a community that supports the development of healthy capital markets. It is specifically dedicated to the Asia-Pacific investment management industry, promoting excellence and educating market participants.”

    During its soft-launch phase, ARX quickly caught the attention of CFA Institute members and charterholders, industry practitioners, and academics. Governments have also been using the platform, as have regulators. Indeed, the period leading up to the official launch has seen ARX accumulate 36 institutional contributors and over 2,500 research reports and articles. This early adoption supports the belief that ARX will become a catalyst for robust conversations about what is important in the Asian investment management industry.

    From a practical nature, ARX is also easy to use, with Scott Lee, Director, Asia-Pacific Research Exchange, guiding attendees through the site's key features. He also underlined the fact that ARX is a free service and registered users will gain unrestricted access to all content on the platform and be the first to hear about CFA Institute events.

    Scott also highlighted the success of the online-to-offline (O2O) capabilities of ARX, with contributors able to organize events around a particular piece of research. To this end, he introduced Hong Hao, CFA, Managing Director and Chief Strategist, Bank of Communications International, who took his widely read paper, Post-Brexit: How to Trade China, and presented it to CFA members at the first-ever ARX O2O event, held in Shenzhen in late 2016.

    Further evidence of the collaborative potential of ARX came from Esmond Lee, Senior Advisor, Hong Kong Financial Services Development Council (FSDC), who pointed out the strategic partnership that exists between his organisation and CFA Institute: "In the past few months, we have shared research and subsequently co-hosted a number of events that have explored topics such as compliance, green finance and ESG for state-owned enterprises."

    Turning to CFA Institute members and how it meets their particular demands, Yin Toa Lee, CFA, ARX Society Engagement Council and Representative of the Hong Kong Society of Financial Analysts (HKSFA), explained how he has used the service to successfully share his doctorate thesis with a wider audience than would otherwise have been the case: "In a short period, I have received several hundred views from a cross section of industry participants – both here in Asia and farther afield."

    To conclude, Mary Leung, CFA, Head, Standards & Advocacy APAC, CFA Institute, explored what happens next: "We are committed to improving the platform's features, and future developments will include public profiling, private messaging and discussion forums. Also, we are pursuing new strategic partnerships and plan to deepen levels of user engagement."
     
  • Leviathan Inc. and Corporate Environmental Engagement (Video Presentation)

    20 Jun 2017
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    State-owned enterprises (SOEs) have been criticized for poor governance and questionable efficiency. In a recent paper titled ‘Leviathan Inc. and Corporate Environmental Engagement,’ Dr. Pedro Matos from the Darden School of Business, University of Virginia, and his colleagues from the University of Hong Kong and Singapore Management University conducted an international study of the impact of state ownership on a firm’s engagement in environmental, social, and governance (ESG) issues. 

    There has been significant debate on the effects of ESG issues on shareholder value. In this paper, it was found that SOEs are, in fact, more engaged in environmental issues and, more importantly, this engagement does not come at the expense of shareholder value. Furthermore, SOEs are also more engaged in social issues, but they do not reveal better corporate governance performance.

    This is a recording of the presentation hosted by CFA Institute, HKSFA, ACCA, FSDC, HKIRA, and HKU SPACE Executive Academy on June 6, 2017 at HKU SPACE Po Leung Kuk Stanley Ho Community College in Hong Kong.
  • Green Finance Forum II: Is ESG Integration a Fad, or Does It Have Alpha Potential?

    31 May 2017
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    In Asia, the subject of ESG investing has been a very trendy topic.  As we all know, for many years, many investors have tried to incorporate elements of values and social responsibility into their investment strategies.  However, the return of these strategies has in the past left a lot to be desired.  It is natural to wonder why a rational investor would be willing to compromise the chances of superior performance in return for moral gratification.
     
    Well, past performance is not always a guide to future performance, and change is in the air.  More and more investors and asset owners are now placing increasing focus on ESG.  As an example, California State Teachers Retirement System, one of the largest asset owners in the world, has asked their fund managers to evaluate and assess 21 risk factors in each of their holdings, including, among others regulation, human rights, environmental and governance.

    On April 27, 2017, CFA Institute hosted a Green Finance Forum in Hong Kong to explore this issue. Full report on that event is attached.
  • Practitioner's Brief (video): ​The Power of Private Information

    25 May 2017
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    Despite a recent crackdown on insider trading in China an assumption persists regarding the relative information inefficiency and asymmetry of less developed markets. Researcher Chi asks: How much is private information exploited in a less developed financial market like China?
    As it turns out, quite a lot.
  • Practitioner's Brief (Video):  Behind Closed Doors - How Private Meetings Move Public Markets

    25 May 2017
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    The authors of a recent study on insider trading have taken a new, financial spin on the classic thought experiment that asks whether a falling tree makes any sound in an empty forest. Looking at how corporate insiders might use confidential information to make trades, they ask ‘If executives of publicly traded companies meet with investors, and no one from the public is around, does the information exchanged still influence the stock market?’ The results are striking.
  • Practitioner's Brief (Video):  Demystifying Seasonal Chinese Stock Return Synchronicity

    17 May 2017
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    How much of a stock’s movement can be attributed to the movements in the index in which it resides? And if a stock moves in line with an index (or, in academic language, has a “high R squared”) what, exactly, accounts for that? Industry members and academics have numerous theories. The authors of a new paper tackle the question of synchronicity using earnings season in China, when the information on companies is more robust.
  • Practitioner’s Brief: Expect the Unexpected - Why Tightened Trading Rules Created a More Efficient Index Futures Market

    06 Apr 2017
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    WHAT’S THE INVESTMENT ISSUE?
    In the summer of 2015, Chinese regulators aggressively tightened fairly lax trading rules in the country’s stock index futures market in the midst of a chaotic crash. The move, an effort to tamp down rampant speculation and manipulation, was widely criticized as an overreach. With margin barriers thrown up higher and position sizes significantly capped for nonhedgers, speculators all but vanished (a desired outcome); however, so too did volume, which decreased nearly 100%—not exactly a best-case scenario. “China has killed the world’s biggest stock index futures market,” Bloomberg wrote in September 2015. Illiquidity in the market for futures tied to the China Security Index 300 “was causing problems,” the Financial Times said. In hindsight, it’s worth asking: Were these regulations, while apparently necessary, nevertheless ill-advised? No, assert the authors, who do not gloss over the fact that liquidity was severely impacted. What they do emphasize is a rather counterintuitive finding: A market in which liquidity has ground to a halt does have an upside.

    HOW DO THE AUTHORS TACKLE THIS ISSUE?
    Eugene Fama’s efficient market hypothesis (EMH) holds that stock prices immediately and inherently reflect all available information such that there’s no predictive power to be gleaned, i.e., it’s all randomness at play. EMH has been endlessly tested and re-tested since it first emerged in the 1970s at a time when low-cost passive management was coming on the scene as a disruptor to active management. Several testing methods were used to batter/gut-check EMH. Prominent among them was the variance ratio (VR) test, put to use, alongside other tests, by authors Lin and Wang. They set out to measure the efficiency levels of the Chinese stock index futures between July 2015 and September 2015. During this period, a slew of rule changes were implemented, making it harder to trade index futures, a prevalent means of speculating, hedging, arbitraging, and as it turned out, carrying out manipulative schemes, e.g., pump-and-dumps or coordinated bear attacks. The futures market plays a major role in price discovery in the broader spot Chinese stock market. Prior to the change, rules for stock index futures trading were indeed loose and transaction costs were low. Leverage was plentiful and dangerously easy to access. When all of these conditions were curbed via tighter rules, something interesting happened. Yes, volume collapsed. But what happened to the market’s efficiency?

    WHAT ARE THE FINDINGS?
    The results of VR tests (and Granger causality tests) were puzzling. Although the authors thought they would find that regulatory tightening had a detrimental impact on market efficiency and price discovery, just as it had on volume and liquidity, it did not prove to be the case. To the contrary, the VR testing found that absolute VR levels of Chinese index futures’ five-minute returns went from roughly 2.70 before the rule change to around 1.0 after—a decrease of more than 50%. In other words, markets became more efficient in the post-tightening study period. With volume and liquidity in such a freefall, why would that happen? It is possible, explained the authors, that in low liquidity environments trading mainly occurs among the most knowledgeable institutional investors. Speculators and manipulators fall away. So we’re talking about very light trading—but among very well-informed participants free from the distractive din of the less informed. This hypothesis requires testing. If additional data was available, it would be an interesting topic for further research, according to the authors.

    WHAT ARE THE IMPLICATIONS FOR INVESTORS AND INVESTMENT PROFESSIONALS? “Regulators can be helpful in a bad market state,” the authors said, noting that at the time the rules were imposed the stock futures market had been overrun by unchecked manipulators who were abetted by low barriers to leverage and the ability to upsize. The regulatory goal of squeezing nonhedgers out of the market was met. Authorities drastically reduced excessive manipulation—without unintentionally creating a less efficient market. Co-author Hai Lin explained in an email: “While extreme regulations do not happen often, that doesn’t mean that their potential can be ignored.” Regulations can tighten in stressful environments—or in other words, right when investors might be most inclined to employ hedging strategies. In developing risk management strategies, investors need to view regulatory conditions as a factor that can vary over time. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    Summarized by Rich Blake. Rich is a veteran financial journalist who has written for numerous media outlets, including Reuters, ABC News and Institutional Investor. The views expressed herein reflect those of the authors and do not represent the official views of CFA Institute or the authors’ employers.
  • Practitioner’s Brief: Paying Attention to Stock Ranking

    03 Apr 2017
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    WHAT’S THE INVESTMENT ISSUE?
    Investors have a limited amount of attention to give to their investment decisions. Many believe that paying attention to rankings of stocks provides them with a less attention demanding decision making shortcut. In reality, however, does paying attention to stocks ranked in a more salient place help improve financial decisions and market efficiency? Existing research on ranking and attention typically encounters the difficulty of separating out the pure effect of attention from that of fundamental news, which is especially true when rankings correlate with fundamentals. Thus, findings based on fundamental based rankings are subject to the confounding effects of both attention and fundamentals. The author tackles this challenge by exploring the price limit rule in China’s stock markets. Under that rule, stocks that hit the 10% upper price limit on a day are ranked by their daily returns, whose differentials are produced by mechanical rounding of maximum price changes as opposed to differential fundamental news. Investment practitioners in markets with the price limit rule in place may wish to exploit the impact of stock rankings for those stocks hitting the upper price limit. Thus, relevant questions to practitioners would pertain to (1) whether hitting the 10% upper price limit is truly an attention-grabbing event; (2) whether differential attention is allocated across the stocks hitting the price limit based on their rankings; and (3) whether stocks hitting the price limit that are ranked differently exhibit different subsequent returns, trading volume, volatility, and liquidity.

    HOW DOES THE AUTHOR TACKLE THIS ISSUE?
    The author conducted a series of tests to address the empirical questions posed above, studying a sample of China’s A-shares (shares that are quoted and traded in Chinese RMB) on China’s Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE). The time period is from 16 December 1996, when SSE and SZSE initially established the current price limit rule, to 31 March 2015, when the research project was initiated. The author selects 2,505 out of 4,910 trading days; during these days the markets had at least 5 upper price-limit events. We hereafter call stocks that hit the upper price limit on a day the “event” stocks. For most stocks, the daily absolute price movement is regulated to be 10% of the previous trading day’s closing price. When the 10% price change is not an integer number of cents, the daily price limit is rounded to the nearest cent. This creates different maximum returns allowed across stocks with different previous closing prices. For example, stocks with the previous closing price of RMB 9.99, RMB 10.00, and RMB 10.01 would all have a daily maximum price change of RMB 1.00; this results in a maximum return limit of 10.01%, 10.00%, and 9.99%, respectively. The differential maximum return limit is, therefore, caused by mechanical rounding and not by differential fundamental news. As a result, the author identifies the pure effect of ranking by exploring the differential attention paid to the more saliently ranked stock, which returns 10.01% in a day in the previous example, versus those with less salient rankings, which return 10% or 9.99%, and the implications of rankings for the financial market. To carry out the tests, the author hand collected the website viewer data from hexun.com, one of the largest financial websites in China. The number of viewers from different IP addresses measures the attention paid by investors to a particular stock on a day. The author tested the impact of investor ranking by comparing two groups of event stocks, based on whether their event-day return was above median (usually 10%) or not, across dimensions of contemporaneous and subsequent returns, volume, volatility, and liquidity. Event stocks with the above median return were assigned to the high-rank group (with an average of above 12 stocks per day); the remainder were assigned to the low-rank group (with an average of near 10 stocks per day).

    WHAT ARE THE FINDINGS?
    The author finds that investors do pay significantly more attention to stocks hitting the price limit for several days on and after they hit the upper limit, measuring attention by the number of viewers on the hexun.com webpage. The abnormally high attention persists for two weeks after the event day. Furthermore, the high-rank group receives even more attention than the low-rank group on the event day and the subsequent three days. Relative to the low-rank group, the high-rank group of event stocks experiences a greater price increase for two days as well as a greater price reversal that follows within one to two weeks. As for trading volume, liquidity, and return volatility, the results suggest that during the post-event period, the high-attention group of event stocks exhibits higher trading volume, better liquidity, and higher volatility. Smaller investors are more affected by the rank effect. Moreover, the effect of trading volume and volatility is larger and persists longer, but the effect of liquidity is smaller and lasts only for a few days. These effects are noticeably stronger when a larger number of stocks are hitting the upper price limit on a particular day—thus, investors are more attention constrained and top rankings are more salient. The author conducts similar analyses on stocks with a 5% price limit and stocks that hit the 10% lower price limit. The evidence is overall weak, suggesting that it is the rankings of stocks that hit the upper price limit that matter most for attention allocation. When the maximum return is not extreme enough to make the top ranking, or the ranking is for losers and mainly attracts sellers, neither strong investor attention nor the effect of attention is found.

    WHAT ARE THE IMPLICATIONS FOR INVESTORS AND INVESTMENT PROFESSIONALS?
    The findings send a clear message that even pure rankings that are uncorrelated with fundamentals dictate investor attention and lead to large and predictable effects on asset prices. Understanding how ranking affects asset prices will help to improve portfolio performance for institutional and individual investors who trade in securities markets where financial assets are presented in various ranking formats. Investors may consider exploring the temporary price momentum and subsequent price reversal of highly ranked stocks, and more importantly, exploring the return differential between high- and low-rank groups of stocks using a long-short portfolio. The conventional wisdom is that having investors who pay attention is a good thing; it means that important fundamental news is received and consumed, leading to more efficient asset prices. Advances in behavioural finance in recent years, however, suggest that attention may have a detrimental effect when it interplays with behavioural biases, such as the pure order effect. The findings of this article demonstrate such evidence as well as opportunities for smart investors who are paying attention in the right places. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Summarized by Danling Jiang and Jingyu Cui. Danling Jiang is an Associate Professor of Finance at Stony Brook University—SUNY and the Chang Jiang Scholar Visiting Professor at Southwest Jiaotong University. Jingyu Cui is a Master of Science in Finance student at Stony Brook University—SUNY.
  • Practitioner's Brief: Short-Sale Restrictions Imply Higher Returns

    02 Apr 2017
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    WHAT’S THE INVESTMENT ISSUE?
    Short-sale restriction is an important form of limits to arbitrage. In markets with partial shortsale restrictions, some stocks can be sold short (shortable stocks) whereas others cannot (no-short stocks). The latter are more subject to mispricing because of greater limits to arbitrage. Mispricing can be a source of risk, because investors may lose money if mispricing persists in the near term while they are betting against mispricing. Accordingly, finance theories predict that stocks more subject to mispricing—in this case, the no-short stocks—should on average earn a return premium as compensation for mispricing risk. Despite extensive research on short-sale constraints, few studies have directly tested the no-short return premium. Investment practitioners in markets with partial short-sale restrictions may want to exploit the no-short return premium induced by such regulations. To do so, they would ask two questions: Do the real-world data support the claim that no-short stocks on average earn higher returns? If so, how can they determine investment strategies based on the no-short return premium? The authors thus set out to reveal the superior expected excess and abnormal returns on no-short stocks over those on shortable stocks, as well as to demonstrate the strong return predictive power of the loadings on various long–short portfolios constructed using shortable and noshort stocks.

    HOW DO THE AUTHORS TACKLE THIS ISSUE?
    The authors test their prediction about the no-short return premium using the Hong Kong stock market’s unique regulatory setting. In the Stock Exchange of Hong Kong (SEHK), stocks are periodically added to or deleted from the list of shortable stocks. This list is selected from the pool of stocks satisfying criteria based on market capitalization, liquidity, and so on. Stocks on the list are “shortable,” and stocks excluded from the list are “no-short”. The authors form a portfolio consisting only of no-short stocks (denoted as N) and a portfolio of only shortable stocks (denoted as S). They then create a long–short portfolio (denoted as NMS, for “no-short minus shortable”) as the return spread between N and S. They consider four different NMS portfolios, using the SEHK size and liquidity criteria to decide which stocks should be added to, can remain on, or should be removed from the official short-sale list. Further, the authors use Fama–MacBeth two-pass regressions to investigate how well the loadings of the test assets (portfolios and stocks) on each of the four NMS portfolios can predict the cross-section of future asset returns.

    WHAT ARE THE FINDINGS?
    The authors find that from 1997 through 2014, the NMS portfolio earns a monthly return of 2% to 3%, or an abnormal monthly return of about 1.3%, after accounting for its correlations with a set of standard common factors (market, size, value, liquidity, etc.). Thus, on average, no-short stocks indeed earn a return premium over shortable stocks. Moreover, the authors discover that no-short and shortable stocks tend to co-move negatively: When no-short stocks do better, shortable stocks tend to do worse. Mostly importantly, the factor loadings on the four NMS portfolios are strong positive predictors of future portfolio and stock returns in the cross-section. For example, the regression estimates imply that moving from the lowest 20% to the highest 20% NMS loading stocks increases the expected return next month by 1.5% to 2.0%. Moving from the lowest five shortable to the highest five no-short size and book-to-market portfolios increases the future average return by more than 4% per month. The loadings on the other three NMS portfolios, formed by considering the size and liquidity criteria for the official shorting list, exhibit similar or somewhat stronger forecast power.

    WHAT ARE THE IMPLICATIONS FOR INVESTORS AND INVESTMENT PROFESSIONALS?
    The findings will help to improve portfolio performance for institutional and individual investors who trade in securities markets with partial short-sale restrictions. Investors may consider gaining exposure to the NMS factor beyond their exposures to other standard factors. A refined strategy would require extracting stocks with the most extreme loadings on the NMS factor, as well as forming a portfolio that is long the highest NMS loading stocks and short the lowest NMS loading stocks. Furthermore, the refined trading strategy can be combined with strategies based on other style characteristics. Popular wisdom is that investors should pay more attention to the information revealed by short selling and take advantage of this information through observed short positions. The findings in this article direct investor attention to another side of the market, however: the stocks that cannot be sold short. These no-short stocks actually earn higher average returns because many investors may shy away from trading these more likely mispriced stocks. As a result, investors who are willing to invest in these stocks are paid to do so. For firms, however, regulation is bad news: Short-sale restrictions imply higher cost of equity. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    Summarized by Danling Jiang and Xiao-Ming Li. Danling Jiang is an associate professor of finance at SUNY at Stony Brook and the Chang Jiang Scholar Visiting Professor at Southwest Jiaotong University. Xiao-Ming Li is a professor of financial economics at the School of Economics and Finance (Albany), Massey University. The views expressed herein reflect those of the authors and do not represent the official views of CFA Institute or the authors’ employers.
  • Practitioner’s Brief: Behind Closed Doors - How Private In-House Meetings Move Public Markets

    Tom Berry    Robert Bowen, Shantanu Dutta, Songlian Tang, Pengcheng (Phil) Zhu
    02 Apr 2017
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    WHAT’S THE INVESTMENT ISSUE?
    In this brief, we provide an investor’s-eye view of a piece of research that shines a floodlight on an inherently opaque subject—private meetings between senior management and investors. Both camps are presumed to know better than to share or receive anything that could be considered material non public information (MNPI). Nonetheless, the authors of this study point to some dubious trends associated with these sit-downs. The question of whether a falling tree makes noise in a forest devoid of hearing-enabled life forms has long held its own as a rudimentary philosophical riddle. But as a practical matter for debate, it’s not much of one, i.e., we’re pretty sure that in all likelihood, a tree crashing to the ground does make a sound. Now ponder this: If a private meeting between senior management and a fund manager takes place—and no one else is there to hear what’s said—are there consequences in the stock market? In other words, what is the point of these cozy sit-downs? Do the parties stand to benefit? Such meetings, of course, are routine and perfectly legal, provided the executives at the publicly traded company steer clear of disclosing any MNPI. The authors set out to ascertain, among other information, to what extent corporate insiders—who control the timing and content of meetings—trade on those meetings. “Overall, our results suggest that companies disclose material non-public information during these meetings and some participants trade on the information,” the authors state.

    HOW DO THE AUTHORS TACKLE THIS ISSUE?
    The question of whether the meetings lead to some competitively advantageous information being leaked, maybe inadvertently, under the camouflage of crafty syntax, or even brazenly, might have remained one of mankind’s eternal mysteries had it not been for the Shenzhen Stock Exchange (SZSE). In 2009, the SZSE became the first exchange to require listed companies to report dates of private meetings with investors. Since August 2012, the SZSE has also required summary notes of what was said during those meetings, creating a dataset of some 17,000 meeting reports that the quartet of authors mined to startling effect. The authors found highly suspicious trading patterns among company insiders timing transactions ahead of and in the wake of private meetings. Although only 20% of private meetings can be connected with disclosed insider-trading activities, it is worth underscoring that the trades, some USD12 billion over a 28-month sample period (August 2012–December 2014), represent nearly two-thirds of the value of all insider trading among SZSE-listed companies during that time. Interestingly, nearly three-fourths of listed companies held at least one private meeting per year; the average was around five meetings per year. Most meetings were hosted in the companies’ headquarters.

    WHAT ARE THE FINDINGS?
    The research shows a clear trend of abnormally positive stock returns starting approximately 22 days prior to the private meeting dates. In fact, the average stock price run-up translates into RMB73.1 million (or about USD11 million) per average firm in the sample. Call it the “meeting anticipation effect” whereby investors/insiders trade on the not-irrational belief that in-house meetings generally reveal positive information. Some insiders appear to be selling into what they anticipate to be herd buying, using the increased volatility to mask their offloads.

    WHAT ARE THE IMPLICATIONS FOR INVESTORS AND INVESTMENT PROFESSIONALS?
    Many large institutional investors will undoubtedly scoff at the implication that they are gaming the system—or being gamed—by participating in face-to face conversations with the leaders of the companies in which they are investing large sums. These fund managers will also point to proprietary research processes that emphasize sophisticated models and, using the authors’ term, a “mosaic” of skillfully assembled information. Companies that hold meetings, likewise, could just as easily frame these interactions as transparent corporate citizenry, as evidenced by the high “information quality” scores enjoyed by the majority of the companies that report private meetings. The pieces are thus firmly in place for the facilitation of reinforced feedback loops: Companies that hold meetings have more analysts covering them, and these analysts represent large funds whose trades are closely watched. Insiders, who have seen this movie before, are not blind to the ripple effects of a few well-placed dollops of promising insinuations or even flat-out MNPI utterances. That there is an opportunity, thanks to the SZSE and the authors, for a sophisticated fund manager to write an algorithm scouring the mere record that meetings took place in an effort to catch some window of upside could be seen as one logical outcropping of the findings here, although we can think of another. Regulators in a developed market such as the United States might also find it useful to require some record of private meetings. Fund managers in the United States spend USD1.4 billion a year for face time with executives. The investment pays off well for those fund managers who are invited to these meetings and who make profitable trades around the meeting dates. According to the authors, the information gained from private in-house meetings provides these fund managers, and their investors, with an additional competitive edge. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    Summarized by Rich Blake. Rich is a veteran financial journalist who has written for numerous media outlets, including Reuters, ABC News and Institutional Investor. The views expressed herein reflect those of the authors and do not represent the official views of CFA Institute or the authors’ employers.
  • Practitioner’s Brief: Demystifying Seasonal Chinese Stock Return Synchronicity

    Tom Berry    Jing Wang, Steven X. Wei, Wayne Yu
    02 Apr 2017
    185
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    WHAT'S THE INVESTMENT ISSUE?
    How much of a stock’s movement can be attributed to movements in the index in which it resides? And, if a stock moves in line with an index (or, in academic parlance, has a "high R-squared") what, exactly, accounts for that co-movement? Industry members and academics have numerous theories: shared information being digested in lockstep by portfolio managers; index funds rebalancing themselves; or random noise—some inexplicable yet observable factor that for whatever reason creates an environment of stock-return synchronicity. For quant managers spotting trends, there’s no point in asking why; they just want the trend to repeat. Not so for researchers such as Wang, Wei, and Yu, who want to bring new perspective to this puzzle, one that has proved tricky for active fundamental managers seeking to differentiate themselves against the benchmark. In tackling the question of synchronicity, the authors explore the issue across a dynamic setting—earnings season in China, when more-robust information on companies becomes available—and also consider newer companies versus older ones.

    HOW DO THE AUTHORS TACKLE THIS ISSUE?
    They examine synchronicity levels during earnings season, which for 98% of Chinese companies is January through April. The authors also go a step further, overlaying a variety of variables such as changes in fundamentals, fluctuating liquidity conditions, and corporate events. These events include any activity that could increase assets by 50% or more (e.g., a merger) and thus affect a company's systematic volatility.

    WHAT ARE THE FINDINGS?
    The authors discover that in rich information environments (i.e., earnings season), the degree of synchronicity (stocks moving in tandem) actually is reduced; and in less informative environments (non-earnings periods, May through December), synchronicity is more prevalent. This finding is noteworthy, if only in light of the overriding preconceptions about emerging markets such as China, long thought to generally be more prone to synchronous behavior relative to developed markets (for a host of reasons, including property rights considerations). Here, the authors are able to observe a repeated pattern: During Chinese earnings season, the degree of systematic volatility in that market is reduced. The trend is more pronounced for older companies with longer track records of meeting (or failing to meet) their numbers. One explanation stems from a concept that the authors call "intra-industry, cross-asset learning." Drilling down into this concept rather simplistically for illustration's sake, suppose three large companies from different industries (e.g., an automaker, a coal miner, and a retailer) make earnings announcements on the same day. Investors may make inferences about other companies in these respective industries. Now, further suppose that the following happens: The automaker’s earnings come in as expected; the coal miner’s come in better than expected; and the retailer’s do much worse than expected. In this example, one might expect share prices to behave distinctly among the three industries: mostly flat for auto firms, up for coal mining firms, and down for retailers. The market as a whole, however, may change little that day, with the offsetting share price changes in the different industries dampening the market or systematic volatility. In other words, share prices move in a less synchronized fashion because of intra-industry, cross-asset learning during the earnings announcement season, which reduces market or systematic volatility in the meantime.

    WHAT ARE THE IMPLICATIONS FOR INVESTORS AND INVESTMENT PROFESSIONALS?
    This study challenges the prevailing wisdom that Chinese stocks tend to move in step with each other, particularly with a time consideration (i.e., earnings season, when a higher intensity of firm-specific information arrives in the market). For stock pickers trying to differentiate themselves from a benchmark, earnings season would thus provide an especially opportune moment to show their ability to make a judgment call on a stock, take a position (bullish or bearish), and not have it mooted by the whims of the overall market. Conversely, for index investors, the authors’ findings suggest that the time to rebalance toward a passive approach would be during non-earnings season when Chinese stock market return synchronicity appears to be at a higher level. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    Summarized by Rich Blake. Rich is a veteran financial journalist who has written for numerous media outlets, including Reuters, ABC News and Institutional Investor. The views expressed herein reflect those of the authors and do not represent the official views of CFA Institute or the authors’ employers.
  • Practitioner’s Brief: The Power of Private Information

    12 Mar 2017
    293
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    WHAT'S THE INVESTMENT ISSUE?
    During the last 18 months, China has witnessed a flurry of securities fraud investigations and arrests involving a wide cross-section of the industry, from high-rolling financiers to humble accounting professors, and even some regulators. The insider-trading crackdown is partly an effort to wash away perceived stains of corruption following the crash of summer 2015. Even before that, though, Chinese insider trading cases had begun to mount as the market, and mechanisms to regulate it, matured. Despite its relative inexperience, China’s stock market is the second largest on earth. Still, an assumption persists (and is studied by researchers such as Chi) regarding the relative information inefficiency and asymmetry of less developed markets such as China. In his article, Chi makes no secret of his own perceptions about the pervasiveness of non-public information used for investing. One given in the hypothesis suggesting there are greater inefficiencies to potentially exploit in China relative to the United States is the fact that most Chinese mutual funds can outperform the index—certainly not the case in the United States. For Chi, then, the driving question becomes: To what extent is private information exploited in a less developed financial market such as China? To a significant degree, as it turns out. Chi’s research suggests that at a minimum, the insider buy is a powerful predictive tool for the generally upward direction of the stocks being bought, particularly for issues from state-owned enterprises (SOEs), and even more so for highly volatile stocks.

    HOW DOES THE AUTHOR TACKLE THIS ISSUE?
    Chi sets out to study insider trading in China via a proxy that, although an obvious choice, is nevertheless not to be conflated with criminal insider trading. That is, he looks at legal, disclosed trades made by corporate insiders, which, despite being purportedly aboveboard, still carry a connotation of information advantage. By creating a basic strategy to mimic insider buys, Chi demonstrates, at least on paper, the ability to add considerable alpha. Note that mimicking insider sells is not a good idea because sellers can have multiple motivations (e.g., liquidity or diversification needs). Buyers, on the other hand, generally are motivated by positive information. Mimicking insider buys may once have worked in the United States, when its stock market was nascent. Today, however, although by no means devoid of insider trading, the US market is viewed in academic terms as "efficient in semi-strong form." More informally, the system is not "rigged." If it were, Chi asserts, more US mutual fund managers would beat the index. In China, the perception of a rigged system became increasingly rampant after the summer of 2015 crash, as traders such as Xu Xiang (the Carl Ichan of China) seemed impervious to the market collapse when most other investors were crushed. Xu would later admit to conspiring with executives to control the timing of corporate announcements. To explore how private information is wielded in China, the author tapped the Wind Information database to study trading activity of corporate insiders (top executives, board members) between April 2007 and June 2014, focusing on the A-share market on two exchanges (Shanghai and Shenzhen) comprising some 2,555 stocks with a combined market cap (in 2013) of RMB20 trillion, or USD$3.3 trillion. The insiders' trading activity amounted to RMB900 billion, or 0.3% of total trading. Chi found the following: • Insiders reap large profits trading their company stocks. • Insider buys possess predictive power to stock prices; insider buys from SOEs have even stronger predicative power. • A rudimentary “mimicking-strategy” implemented for 12-month periods added 14.4% worth of annual alpha above the benchmark. And guess what else he found? The best-performing Chinese mutual funds' returns strongly correlated to the insider-mimicking strategy. Importantly, the fact that a fund trades in the same direction as insiders does not necessarily imply trading on material inside information. The author merely claims “that more correlated trading patterns point to a higher likelihood of private information shared by stock funds and corporate insiders." Because of data limitations, he cannot make a further claim about how fund managers obtain such private information.

    WHAT ARE THE IMPLICATIONS FOR PORTFOLIO MANAGERS?
    Before one delves into the art and science of insider-mimicking strategies, it is important to note an additional finding by the author. Chi split his six-year study into two three-year periods. In the latter period, the predicative power of the insider buy diminished significantly compared with the first period. So, as time passed, the Chinese market appears to have become more, not less, efficient. Here’s one last bit of material information that is hardly any secret: China’s recent insider trading crackdown will serve only to accelerate this trend. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    Summarized by Rich Blake. Rich is a veteran financial journalist who has written for numerous media outlets, including Reuters, ABC News and Institutional Investor. The views expressed herein reflect those of the author(s) and do not represent the official views of CFA Institute or the authors’ employers.
  • Japan Snapshot - Discovering Phi: Motivation as the Hidden Variable of Performance

    Tom Berry    State Street Center for Applied Research (CAR), CFA Institute
    12 Mar 2017
    2482
    15

    Building upon the success of CAR’s Folklore of Finance: How beliefs and behaviors sabotage success in the investment management industry, this18-month flagship study sought an answer to the pressing question: How can motivators produce better financial outcomes in the investment management industry? - Developed in partnership with the CFA Institute, Discovering Phi: Motivation as the Hidden Variable of Performance is based on input from nearly 7,000 survey respondents across 20 countries, interviews with more than 200 global industry leaders, as well as extensive secondary research and quantitative modeling. - “Phi” is derived from the motivational forces of purpose, habits and incentives that direct our behaviors and actions. It drives behaviors and attitudes among investors to reach higher levels of engagement and progress towards long term goals. - This presentation covers the study’s Japan individual investor results specifically. Please visit www.statestreet.com/CAR, www.cfainstitute.org/motivations for more information.
  • Hong Kong Snapshot - Discovering Phi: Motivation as the Hidden Variable of Performance

    Tom Berry    State Street Center for Applied Research (CAR), CFA Institute
    12 Mar 2017
    467
    13

    Building upon the success of CAR’s Folklore of Finance: How beliefs and behaviors sabotage success in the investment management industry, this18-month flagship study sought an answer to the pressing question: How can motivators produce better financial outcomes in the investment management industry? - Developed in partnership with the CFA Institute, Discovering Phi: Motivation as the Hidden Variable of Performance is based on input from nearly 7,000 survey respondents across 20 countries, interviews with more than 200 global industry leaders, as well as extensive secondary research and quantitative modeling. - “Phi” is derived from the motivational forces of purpose, habits and incentives that direct our behaviors and actions. It drives behaviors and attitudes among investors to reach higher levels of engagement and progress towards long term goals. - This presentation covers the study’s Hong Kong individual investor results specifically. Please visit www.statestreet.com/CAR, www.cfainstitute.org/motivations for more information.
  • China Snapshot - Discovering Phi: Motivation as the Hidden Variable of Performance

    Tom Berry    State Street Center for Applied Research (CAR), CFA Institute
    12 Mar 2017
    124
    7

    Building upon the success of CAR’s Folklore of Finance: How beliefs and behaviors sabotage success in the investment management industry, this18-month flagship study sought an answer to the pressing question: How can motivators produce better financial outcomes in the investment management industry? - Developed in partnership with the CFA Institute, Discovering Phi: Motivation as the Hidden Variable of Performance is based on input from nearly 7,000 survey respondents across 20 countries, interviews with more than 200 global industry leaders, as well as extensive secondary research and quantitative modeling. - “Phi” is derived from the motivational forces of purpose, habits and incentives that direct our behaviors and actions. It drives behaviors and attitudes among investors to reach higher levels of engagement and progress towards long term goals. - This presentation covers the study’s China individual investor results specifically. Please visit www.statestreet.com/CAR, www.cfainstitute.org/motivations for more information.
  • Australia Snapshot - Discovering Phi: Motivation as the Hidden Variable of Performance

    Tom Berry    State Street Center for Applied Research (CAR), CFA Institute
    12 Mar 2017
    110
    7

    Building upon the success of CAR’s Folklore of Finance: How beliefs and behaviors sabotage success in the investment management industry, this18-month flagship study sought an answer to the pressing question: How can motivators produce better financial outcomes in the investment management industry? - Developed in partnership with the CFA Institute, Discovering Phi: Motivation as the Hidden Variable of Performance is based on input from nearly 7,000 survey respondents across 20 countries, interviews with more than 200 global industry leaders, as well as extensive secondary research and quantitative modeling. - “Phi” is derived from the motivational forces of purpose, habits and incentives that direct our behaviors and actions. It drives behaviors and attitudes among investors to reach higher levels of engagement and progress towards long term goals. - This presentation covers the study’s Australia individual investor results specifically. Please visit www.statestreet.com/CAR, www.cfainstitute.org/motivations for more information.