Research articles for the 2019-11-21
SSRN
Bank risk-taking behavior is of significant interest for researches and policy makers because financial failures due to excessive risk in this sector can have severe consequences for the bankâs numerous stakeholders and for the macroeconomic system overall. A growing literature investigates the main factors contributing to âwell above averageâ risk. In particular, this study explains risk strategies in firms taking into account the bounded rationality of corporate governance agents. On a panel dataset of 110 listed US banks in the period of 2011-2016 empirical evidence is provided that excessive risk-taking in banks arises from the cognitive bias of the overconfidence of CEO decision-making. The study also presents how the impact of an overconfident CEO on risk-taking is affected considering the interaction of CEO overconfidence with the board of directors. It was revealed that the CEO's positive influence on risk is moderated if the board is an effective monitoring mechanism with the presence of independent directors who are experts in the financial sphere.
SSRN
This paper studies the relationship between banks' holdings of domestic sovereign securities and credit growth to the private sector in emerging market and developing economies. Higher banks' holdings of government debt are associated with a lower credit growth to the private sector and with a higher return on assets of the banking sector. Analysis suggests that the negative relationship between banks' claims on the government and private sector credit growth mainly reflects a portfolio rebalancing of banks towards safer, more liquid public assets in stress times and provides only limited evidence of a crowding-out effect due to financial repression.
arXiv
We develop an equilibrium framework that relaxes the standard assumption that people have a correctly-specified view of their environment. Each player is characterized by a (possibly misspecified) subjective model, which describes the set of feasible beliefs over payoff-relevant consequences as a function of actions. We introduce the notion of a Berk-Nash equilibrium: Each player follows a strategy that is optimal given her belief, and her belief is restricted to be the best fit among the set of beliefs she considers possible. The notion of best fit is formalized in terms of minimizing the Kullback-Leibler divergence, which is endogenous and depends on the equilibrium strategy profile. Standard solution concepts such as Nash equilibrium and self-confirming equilibrium constitute special cases where players have correctly-specified models. We provide a learning foundation for Berk-Nash equilibrium by extending and combining results from the statistics literature on misspecified learning and the economics literature on learning in games.
arXiv
Financial exchange operators cater to the needs of their users while simultaneously ensuring compliance with the financial regulations. In this work, we focus on the operators' commitment for fair treatment of all competing participants. We first discuss unbounded temporal fairness and then investigate its implementation and infrastructure requirements for exchanges. We find that these requirements can be fully met only under ideal conditions and argue that unbounded fairness in FIFO markets is unrealistic. To further support this claim, we analyse several real-world incidents and show that subtle implementation inefficiencies and technical optimizations suffice to give unfair advantages to a minority of the participants. We finally introduce, {\epsilon}-fairness, a bounded definition of temporal fairness and discuss how it can be combined with non-continuous market designs to provide equal participant treatment with minimum divergence from the existing market operation.
SSRN
Most of the extensive literature on corporate governance during the past fifty years has approached the topic from the perspective of agency theory and it has focused on dimensions of governance that are relatively easy to measure (e.g., ownership structure, size and structure of boards, executive compensation). Although the literature has greatly enhanced our knowledge of corporate governance, this focus has likely blinded us to other dimensions of governance that are hard to measure, unrelated to agency costs, but important determinants of firm performance and survival. This paper suggests one such dimension, corporate agility, which refers to the speed with which firms adapt to changes in their environments and discusses the potential role that governance plays in promoting or impeding corporate agility.
SSRN
The real estate crowdfunding market in Germany and Austria has experienced a strong growth in recent years. By end of 2018 nearly ⬠400m have been raised through real estate crowdfunding in Germany. From the investorsâ perspective, however, things do not always look so shiny. More and more projects fall into insolvency. At the same time, German authorities warn against fraudulent investments on the internet.In this market report we analyze real estate crowdfunding projects offered in Germany and Austria. These are analyses of data from over 500 projects and over half a billion euros of brokered real estate crowdfunding capital. Our study draws on a comprehensive database dating back to the first real estate crowdfunding project in 2012. First, we provide an overview of the German and Austrian real estate crowdfunding market. For this purpose, descriptive data of the market, such as the development of volumes, number of projects, maturities and interest rates are examined, separately for bonds and loans. Secondly, we analyze the success of real estate crowdfunding and conduct a trend analysis based on historical data and preliminary data from 2019. Among other things, we found that there is a clear trend from subordinated loans towards bonds and the market has grown significantly in the first few months of 2019, while the growth rate continues to decline.
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We find that common ownership leads venture capital (VC) firms to stifle competition among startups, but only in limited circumstances. Our evidence is from pharmaceutical startups, where common ownership is widespread: 39% of startups share a VC with a close competitor. After a startup sees a close competitor make progress on a new drug project, the startup is less likely to advance its own project, and less likely to obtain VC funding, if the two startups share a common VC. These anticompetitive effects, however, are concentrated in markets with few competitors, VCs with larger equity stakes, and projects with similar technologies.
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We examine the impact of hedge fund activism on investment efficiency in target firms. Investment expenditures are more responsive to opportunities aftermath of the hedge fund activism. Activism reduces the propensity of overinvestment in target firms. Consistent with Boyson & Pichler (2018), hostile resistance to activism also increases the likelihood of underinvestment. Our findings are congruent with Smith and Watts (1992) and Bebchuk and Stole (1993) in the sense that it is difficult for shareholders to observe the managerial response to different growth opportunities. However, it is relatively easier for activist hedge funds to monitor assets in place and observe any overinvestment done by firm managers.
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We propose a novel dynamic approach to forecast the weights of the global minimum variance portfolio (GMVP). We exploit that the GMVP weights can be obtained as the population coefficients of a linear regression of one benchmark return on a vector of return differences. This enables us to derive a consistent loss function from which we can infer the optimal GMVP weights without imposing any distributional assumptions on the returns. In order to capture time variation in the assets' conditional covariance structure, we model the portfolio weights through a recursive least squares (RLS) scheme as well as by generalized autoregressive score (GAS) type dynamics. Sparse parameterizations ensure scalability with respect to the number of assets. An empirical analysis of daily and monthly financial returns shows that the model performs well in- and out-of-sample in comparison to existing approaches.
SSRN
The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called âanomaly zooâ has caused many to question whether researchers are using the right tests of statistical significance. But, hereâs the thing: even if researchers use the right tests, they will still draw the wrong conclusions from their econometric analyses if they start out with the wrong priors â" i.e., if they start out with incorrect beliefs about the ex ante probability of encountering a tradable anomaly.So, what are the right priors? What is the correct anomaly base rate?We develop a first way to estimate the anomaly base rate by combining two key insights: #1) Empirical-Bayes methods capture the implicit process by which researchers form priors based on their past experience with other variables in the anomaly zoo. #2) Under certain conditions, there is a one-to-one mapping between these prior beliefs and the best-fit tuning parameter in a penalized regression. We study trading-strategy performance to verify our estimation results. If you trade on two variables with similar one-month-ahead return forecasts in different anomaly-base-rate regimes (low vs. high), the variable in the low base-rate regime consistently underperforms the otherwise identical variable in the high base-rate regime.
SSRN
I document that subjective bond risk premia implied by survey forecasts of future Treasury yields are acyclical at the one-year horizon. This is in stark contrast to large countercyclical variation in objective risk premia fitted from in-sample predictive regressions of future bond excess returns. This difference in risk premia implies a wedge between subjective and objective expectations of future short rates, which I show is predictable by trend and cycle components of macroeconomic forecasts. I show that these empirical findings can be explained with a learning model in which the agent filters latent trend and cycle components of fundamentals in real time, while an econometrician analyzing the data ex-post has full knowledge of the data-generating processes. The model also yields predictions, consistent with the data, on the joint behavior of the unconditional yield curve slope, the cyclicality of short-rate and macroeconomic expectation wedges, and the cyclicality of objective risk premia. My results suggest that equilibrium models of bond risk premia should target acyclical subjective risk premia and expectation formation, rather than ex-post in-sample fitted risk premia from predictive regressions.
SSRN
The cashless transaction system is achieving its growth day by day, as soon as the market becomes globalized and the development of the banking sector more and more the people moves from cash to a cashless system. The cashless system is not just a necessity but also a need of todayâs order. Over the past few years, efforts to drive financial inclusion in India have delivered mixed results. Access to bank accounts has increased dramatically, driven by a strong policy and regulatory push. However, the usage of these accounts and the uptake of formal financial services beyond savings accounts has remained exceptionally difficult. The recent initiatives by the Government around demonetization and the move to cashless transactions will further drive innovation and new entrants into the Industry. The amendments to the banking act clearly demonstrate the Government, RBI and Banking institutions intent to ensure stable growth of the economy by ensuring a healthy BFSI. Building Trust within the industry will be paramount to Indiaâs further growth. Newer technologies pose different challenges to the banks and regulators, with security being a key concern. With cyber-frauds on the rise, the regulators and the bankers would have to come together to ensure control mechanisms are in place. A strong push from the Government of India has given the non-banking population easy access to financial products. Payment organizations have demonstrated the advantages of mobile-led solutions and the traditional banking organizations are now trying to make inroads into rural India by launching innovative mobile-based banking solutions. With support from the government, large technology companies are using new ways of reaching out to the rural masses and educate them about the various financial products, thus ensuring that their hard-earned income is rightly invested.
SSRN
We show that the post earnings announcement drift (PEAD) is stronger for conglomerates than single-segment firms. Conglomerates, on average, are larger than single segment firms, so it is unlikely that limits-to-arbitrage drive the difference in PEAD. Rather, we hypothesize that market participants find it more costly and difficult to understand firm-specific earnings information regarding conglomerates as they have more complicated business models than single-segment firms. This in turn slows information processing about them. In support of our hypothesis, we find that, compared to single-segment firms with similar firm characteristics, conglomerates have relatively low institutional ownership and short interest, are covered by fewer analysts, these analysts have less industry expertise and also make larger forecast errors. Finally, we find that an increase in organizational complexity leads to larger PEAD and document that more complicated conglomerates have even greater PEAD. Our results are robust to a long list of alternative explanations of PEAD as well as alternative measures of firm complexity.
SSRN
Previous literature documents that mutual funds' flows increase more than linearly with past performance. I show that this convex flow-performance relationship is consistent with a dynamic contracting model in which investors learn about the manager's skill. Learning links past performance to the manager's expected performance, whereas the optimal contract links expected performance to the slope of the flow-performance relationship. The link between past performance and the flow-performance slope becomes weaker over time because the optimal contract prescribes ex post inefficient actions in order to ensure ex ante efficiency. As a result, the model predicts that flows become more sensitive to current performance after a history of good performance, but less so for more senior managers. I test these statistical predictions in mutual fund data and find empirical support for the theory. By incorporating an explicit incentive contract for the manager, my model explains common compensation practices in the money management industry, such as convex pay-for-performance schemes and deferred compensation. My findings hold robustly across multiple contracting environments.
SSRN
We identify queue-jumping as a key mechanism that causes markets to fragment. We use the introduction (and partial removal) of the Order Protection Rule, which enforces strict inter-venue price (not time) priority, to observe its impacts on fragmentation. We document that brokers increasingly fragment their liquidity provision activities amongst alternative venues, and liquidity providers attempt to jump long queues on larger venues by increasing submissions to venues with short (or empty) queues, which reduces their adverse selection costs. Our findings help explain the acceleration of fragmentation in markets with trade-through prohibitions as compared to best executions, providing clear policy implications.
SSRN
We construct a new, comprehensive instrument-level database of sovereign debt for 18 advanced and emerging countries over the period 1913-46. The database contains data on amounts outstanding for some 3,800 individual debt instruments as well as associated qualitative information, including instrument type, coupon rate, maturity, and currency of issue. This information can provide unique insights into various policies implemented in the interwar period, which was characterized by notoriously high debt levels. We document how interwar governments rolled over debts that were largely unsustainable and how the external public debt network contributed to the collapse of the international financial system in the early 1930s.
SSRN
We study the interplay between two channels of interconnectedness in the banking system. The first one is a direct interconnectedness, via a network of interbank loans, banks' loans to other corporate and retail clients, and securities holdings. The second channel is an indirect interconnectedness, via exposures to common asset classes. To this end, we analyze a unique supervisory data set collected by the European Central Bank that covers 26 large banks in the euro area. To assess the impact of contagion, we apply a structural valuation model NEVA (Barucca et al., 2016a), in which common shocks to banks' external assets are reflected in a consistent way in the market value of banks' mutual liabilities through the network of obligations. We identify a strongly non-linear relationship between diversification of exposures, shock size, and losses due to interbank contagion. Moreover, the most systemically important sectors tend to be the households and the financial sectors of larger countries because of their size and position in the financial network. Finally, we provide policy insights into the potential impact of more diversified versus more domestic portfolio allocation strategies on the propagation of contagion, which are relevant to the policy discussion on the European Capital Market Union.
SSRN
The analysis of interconnectedness and contagion is an important part of the financial stability and risk assessment of a country's financial system. This paper offers detailed and practical guidance on how to conduct a comprehensive analysis of interconnectedness and contagion for a country's financial system under various circumstances. We survey current approaches at the IMF for analyzing interconnectedness within the interbank, cross-sector and cross-border dimensions through an overview and examples of the data and methodologies used in the Financial Sector Assessment Program. Finally, this paper offers practical advice on how to interpret results and discusses potential financial stability policy recommendations that can be drawn from this type of in-depth analysis.
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In this article we derive the shareholder loss due to a capital requirement associated to a derivatives transaction. This is a result of a transfer of wealth between shareholders and creditors of the firm. The charge required to negate this loss can be regarded as a capital valuation adjustment which we refer to as KVA2. Our approach does not assume a fixed hurdle rate on equity required by shareholders. Instead we derive the economic return on capital for a marginal derivatives trade. We provide two complementary derivations of the valuation adjustment. The first is based on a Merton single-period balance sheet model and the second on continuous time no-arbitrage arguments.Our resulting KVA expression is similar in structure to those proposed in the literature. We find however that the effective rate on capital that a shareholder should demand in a derivatives transaction is a junior funding rate as opposed to the return on equity. This is a consequence of the fact that the only risk a shareholder faces once a derivatives transaction is fully hedged is the default of the firm itself.
SSRN
This paper studies a model in which a low monetary policy rate lowers the cost of capital for entrepreneurs, potentially spurring productive investment. Low interest rates, however, also induce entrepreneurs to lever up so as to increase payouts to equity. Whereas such leveraged payouts privately benefit entrepreneurs, they come at the social cost of reducing their incentives thereby lowering productivity and discouraging investment. If leverage is unregulated (for example, due to the presence of a shadow-banking system), then the optimal monetary policy seeks to contain such socially costly leveraged payouts by stimulating investment in response to adverse shocks only up to a level below the first-best. The optimal monetary policy may even consist of âleaning against the wind,â i.e., not stimulating the economy at all, in order to fully contain leveraged payouts and maintain productive efficiency.
SSRN
Prior research has identified various determinants of Equity REIT sector dynamics and investment performance. This paper focuses on Mortgage REITs (MREITs) instead. MREITs are subject to the same statutory requirements as equity REITs, but invest in mortgages and MBS, and thus resemble non-depository financial institutions more than they do listed real estate investment companies. Drawing on recent theoretical advances in the financial intermediation literature, I test the hypothesis that growth and performance of MREITs are driven by variation in the capacity of chartered banks to hold credit-risky assets, which is proxied by the bank capital ratio. Using a cross-sectional comparison across the three main categories of MREITs, I show that institution-level expansion and contraction in the MREIT sector are significantly related to variation in the bank capital ratio. These sector dynamics coincide with variation in MREIT performance; notably, dividend yields and equity market valuations. I further document how MREITs adjust asset-type holdings and financing choices in response to variation in the bank capital ratio. The results constitute novel evidence on the association between the capitalization of chartered banks and growth, performance, as well as risk-taking in non-depository financial institutions.
arXiv
Financial time-series classification (FTC) is extremely valuable for investment management. In past decades, it draws a lot of attention from a wide extent of research areas, especially Artificial Intelligence (AI). Existing researches majorly focused on exploring the effects of the Multi-Scale (MS) property or the Temporal Dependency (TD) within financial time-series. Unfortunately, most previous researches fail to combine these two properties effectively and often fall short of accuracy and profitability. To effectively combine and utilize both properties of financial time-series, we propose a Multi-Scale Temporal Dependent Recurrent Convolutional Neural Network (MSTD-RCNN) for FTC. In the proposed method, the MS features are simultaneously extracted by convolutional units to precisely describe the state of the financial market. Moreover, the TD and complementary across different scales are captured through a Recurrent Neural Network. The proposed method is evaluated on three financial time-series datasets which source from the Chinese stock market. Extensive experimental results indicate that our model achieves the state-of-the-art performance in trend classification and simulated trading, compared with classical and advanced baseline models.
arXiv
Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer's strategic planning. In otherwise standard principal-agent models with moral hazard, we allow the principal to partition agents' performance data into any finite categories and to pay for the amount of information the output signal carries. Through analysis of the trade-off between giving incentives to agents and saving the monitoring cost, we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to rising monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk. We examine the implications of these results for workforce management and firms' internal organizations.
SSRN
We examine the consequences of controversies on corporate reputation and identify two reputation-building strategies that companies are adopting to restore their trust relationships with stakeholders in the aftermath of media condemnation. In particular, we find that in the post-controversy period, firms take a bolstering strategy of reducing their discretionary accruals to boost their financial reporting quality. Furthermore, they endeavour to restore their reputation by engaging more actively in philanthropic activities. Our empirical findings vividly illustrate the importance of reputation and cohere with the image repair theory propounded by (Benoit, 1995).
SSRN
This paper studies the determinants of repeated use of Fund-supported programs in a large sample covering virtually all General Resources Account (GRA) arrangements that were approved between 1952 and 2012. Generally, the revolving nature of the IMF's resources calls for the temporary sup-port of member countries to address balance of payments problems while repeated use has often been viewed as program failure. First, using probit models we show that a small number of country-specific variables such as growth, the current account balance, the international reserves position, and the institutional framework play a significant role in explaining repeated use. Second, we discuss the role of IMF-specific and program-specific variables and find evidence that a country's track record with the Fund is a good predictor of repeated use. Finally, we conduct an out-of-sample forecasting exer-cise. While our approach has predictive power for repeated use, exact forecasting remains challenging. From a policy perspective, the results could prove useful to assess the risk IMF programs pose to the revolving nature of the Fund's financial resources.
SSRN
Due the the upcoming change in price alignment interest that is anticipated for SOFR and â¬STR, a new definition of the "hybrid" risk-neutral measure is developed, which is based on continuous reinvestment at the price alignment interest rate. A corresponding T-forward measure is defined, which is consistent with the treatment of cashflow obligations including bond prices and terminal payouts. Values obtained under the "hybrid" measure remain unchanged when combined with explicit modeling of the compensation payout at the transition time, in addition to describing any MTM change for uncompensated positions. This new measure also allows continuous construction of the forward curve in a way that is convexity-free up to and beyond the discounting transition, whereas the original pricing measure will see a sudden impact on the forward curve at the transition point. Lastly the "hybrid" measure provides a framework to model the forward curve convexity for trades with collateral agreements that do not transition simultaneously across different netting sets.
arXiv
In life-cycle economics the Samuelson paradigm (Samuelson, 1969) states that the optimal investment is in constant proportions out of lifetime wealth composed of current savings and the present value of future income. It is well known that in the presence of credit constraints this paradigm no longer applies. Instead, optimal lifecycle investment gives rise to so-called stochastic lifestyling (Cairns et al., 2006), whereby for low levels of accumulated capital it is optimal to invest fully in stocks and then gradually switch to safer assets as the level of savings increases. In stochastic lifestyling not only does the ratio between risky and safe assets change but also the mix of risky assets varies over time. While the existing literature relies on complex numerical algorithms to quantify optimal lifestyling the present paper provides a simple formula that captures the main essence of the lifestyling effect with remarkable accuracy.
arXiv
We study the mean field games equations, consisting of the coupled Kolmogorov-Fokker-Planck and Hamilton-Jacobi-Bellman equations. The equations are complemented by initial and terminal conditions. It is shown that with some specific choice of data, this problem can be reduced to solving a quadratically nonlinear system of ODEs. This situation occurs naturally in economic applications. As an example, the problem of forming an investor's opinion on an asset is considered.
SSRN
The prolonged crisis exposed the vulnerability of a monetary union without a banking union. The Single Supervisory Mechanism (SSM), which started operating in November 2014, is an essential step towards restoring banks to health and rebuilding trust in the banking system. The ECB is today responsible for setting a single monetary policy applicable throughout the euro area and for supervising all euro area banks in order to ensure their safety and soundness, some directly and some indirectly. Its role in the area of financial stability has also expanded through the conferral of macroprudential tasks and tools that include tightening national measures when necessary. It thus carries out these complementary functions, while its primary objective of pursuing price stability remains unchanged. What are the working arrangements of this enlarged ECB, and what are the similarities and existing synergies among these functions? In the following pages, focusing on the organisational implications of the ânewâ ECB, we show the relative degrees of centralisation and decentralisation that exist in discharging these functions, the cycles of policy preparation and the rules governing interaction between them.
SSRN
This paper studies the relationship between investment volatility, capital structure, and cash levels. Our evidence suggests: i) firms with relatively high realizations of future investment volatility hold relatively low levels of debt and high levels of cash, ii) firms fund large investment by increasing (issuing) debt and/or decreasing (using) cash, iii) immediately after funding large investments firms reduce debt levels and increase cash holdings. Overall, our results are consistent with the DeAngelo, DeAngelo, and Whited (2011) model. In particular, firms with high realizations of future investment volatility keep their debt levels low and cash levels high to finance uncertain future investments.
SSRN
We provide evidence that the ECBâs unconventional monetary policy dampens yield cycles in secondary Eurozone sovereign debt markets around new sovereign debt auctions. This eï¬ect increases in market volatility. Cycles caused by domestic auctions and the role of market volatility are largest for countries with low credit ratings. Auctions by these countries generate highly-signiï¬cant auction cycles in other countries. Auction cycles can have a non-negligible eï¬ect on debt-servicing costs, but these may be contained by concentrating debt issuance in tranquil periods, and by coordinating auction calendars among countries, so as to maximize the dispersion of auction activity in time.
SSRN
This paper examines international spillovers from unconventional monetary policy (UMP) between the US, the Euro area, the UK and Japan, exploiting the asynchronous timing of monetary policy normalization to shed light on the term structure implications of UMP divergence. Using high frequency futures data to identify monetary policy surprises and controlling for contemporaneous news, I find that spillovers increase during periods of unconventional monetary policy, and that these strengthen in the period of asynchronous policy normalization. Local projections suggest persistent spillovers from the Federal Reserve, whereas other spillovers fade quickly. Through the lens of a shadow rate term structure model (SRTSM), I find that these surprises elicit, domestically and internationally, revisions to both the expected path of short-term interest rates and required risk compensation, with the latter gaining importance at the effective lower bound of interest rates.
SSRN
Chinese Abstract: æ¬ææ¢è®¨äºå½"æèµè å ·ææéå ³æ³¨åº¦æ¶ï¼å ç§'æä»·å¼ä¿¡æ¯çå»¶è¿æ©æ£å¸¦æ¥çæèµæºä¼ã卿éå ³æ³¨åº¦å设ä¸ï¼æèµè å¾å'äºå¿½ç¥ä¼ä¸é´çç§'æå ³è"ï¼å¯¼è´ç§'æä»·å¼å¨åç±»ç§'æå ¬å¸ä¸çä¼ é'产ç"å»¶è¿ï¼ä»èå¸¦æ¥æèµæºä¼ãç¶èï¼å¨æ'å½è¡ç¥¨æ"¶ççåéçæ§å ç´ å½±å"è¿å¤ï¼ä¸éåç"¨ä½ç§'ææº¢åºæåº"ç代çåéãæ¬æé¦æ¬¡æåºï¼åæå¸ä¸è´çä½é¢æµä¿®æ£æ¯"è¡ç¥¨æ"¶ççæ´éåç"¨æ¥è¡¡éä¸å¸å ¬å¸çç§'æä»·å¼ãæ¬ææ ¹æ®ä¸å¸å ¬å¸ææçä¸"å©è®¡ç®äºä¸åå ¬å¸é´çç§'æå ³è"ï¼å¹¶ç»"ååæå¸ä¸è´çä½é¢æµä¿®æ£è®¾è®¡äºâç§'æä¿®æ£å åâãéè¿è¯¥å åæå»ºçå¥å©ç»åå¯ä»¥è·å¾1.00%çæåæ"¶çãæ¬æä¸ä» éªè¯äºç§'æå ³è"卿'å½è¡ç¥¨å¸åºçä¿¡æ¯ä¼ é'è½åï¼èä¸"æ·±å ¥æ¢è®¨äºæèµè æéå ³æ³¨åº¦å¨æ¤è¿ç¨ä¸èµ·å°çä½ç"¨ãæ¬æå'ç°ç§'æä¿®æ£å åçæèµä»·å¼ä¸æ¹é¢æ¥æºäºå ¶è½å¤é¢æµæªæ¥çåæå¸ä¸è´çä½é¢æµä¿®æ£ï¼ä¸æ¹é¢æ¥æºäºå ¶è½å¤é¢æµå ¬å¸æªæ¥ççä½ååãæ¬æé¦æ¬¡å°åæå¸è¡ä¸ºä¿¡æ¯ä¸ä¸å¸å ¬å¸é´çç§'æå ³è"ç»"åèµ·æ¥è¿ç"¨ï¼è¯¥æè·¯ä¸ä» æå©äºå¢å æèµè 对ç§'æå ³è"çåº"ç"¨ï¼èä¸"æå©äºæ´å å åå°ææåæå¸è¡ä¸ºä¿¡æ¯çä»·å¼ãEnglish Abstract: This paper investigates the investment opportunities from the delayed information diffusion through technological links among firms. Under the assumption of limited attention, investors tend to neglect the technological linkages among firms, resulting in delayed information diffusion among technological peers, thus bringing investment opportunities. However, the stock return is affected by too many irrational factors in China, which makes it unsuitable to be treated as proxy for the spillover effect of technology development. This paper proposes for the first time that analyst consensus earnings forecast revision is more suitable than stock return to measure technology value of listed companies. Using analyst consensus earnings forecast revision, this paper proposes the TechRev factor. Then the roles of technological links and limited attention in asset pricing are investigated.Firstly, this paper defined the technological correlation between firms based on the patents belonging to the focal firm. Then the TechRev for the focal firm can be calculated by averaging the analyst consensus earnings forecast revision of its technological peers, using the technological correlations as the weights. The empirical results show that: (1) the TechRev factor has significant investment value and the long-short strategy based on it yields monthly return of 100 basis points; (2) both portfolio test and the Fama-Macbeth regression verify that the investment value of TechRev is not derived from the well-known anomaly factors, but based on the specific information it contains essentially; (3) the TechRev factor is more efficient among the firms with stronger patent intensity or less analyst reports coverage, which means that the limited attention mechanism plays an important role; (4) the predictability of TechRev factor for the future stock return of the focal firm is derived from its predictability for the analyst consensus forecast revisions and the unexpected earnings of the focal firm; (5) the TechRev anomaly is more attributed to mispricing instead of risk premium.Because of the huge difference between the stock markets of China and developed countries, many effective investment strategies in mature markets lose their effects in China. However, this does not mean that the operation mode of China's stock market does not conform to the basic economic or financial laws. At least, the limited attention paradigm embodies well in the markets of both China and the US. And the securities analysts play indispensable roles in the stock market, although the independence of China's securities analysts has been suspected for a long time. As the information medium between listed companies and investors, securities analysts can not only the transmit information among the market, but also provide deeper and more effective investment information for the majority of investors based on their professional investment knowledge. At present, the market still cannot make full use of the analyst behavior information. This paper opens a new perspective by combining the analyst behavior information with the technological linkages of the listed firms, which is not only conducive to providing investors with new investment strategies, but also conducive to improving the efficiency of the whole stock market in China.