SSRN Author: Craig W. HoldenCraig W. Holden SSRN Content
http://www.ssrn.com/author=32969
http://www.ssrn.com/rss/en-usTue, 19 Sep 2017 04:50:36 GMTeditor@ssrn.com (Editor)Tue, 19 Sep 2017 04:50:36 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: The Empirical Analysis of LiquidityWe provide a synthesis of the empirical evidence on market liquidity. The liquidity measurement literature has established standard measures of liquidity that apply to broad categories of market microstructure data. Specialized measures of liquidity have been developed to deal with data limitations in specific markets, to provide proxies from daily data, and to assess institutional trading programs. The general liquidity literature has established local cross-sectional patterns, global cross-sectional patterns, and time-series patterns. Commonality in liquidity is prevalent. Certain exchange designs enhance market liquidity: a limit order book for high volume markets, a hybrid exchange for low volume markets, and multiple competing exchanges. Automatic execution increases speed, but increases spreads. A tick size reduction yields a large improvement in liquidity. Providing ex-post transparency to an otherwise opaque market dramatically improves liquidity. Opening up the limit order ...
http://www.ssrn.com/abstract=2402215
http://www.ssrn.com/1626079.htmlMon, 18 Sep 2017 08:23:10 GMTREVISION: Costly Trading, Managerial Myopia, and Long-Term InvestmentThe costly trade theory predicts that it is much more difficult to exploit long-term private information than short-term. Thus, there is less long-term information impounded in prices. The managerial myopia theory predicts that a variety of short-term pressures, including inadequate information on long-term projects, cause asymetrically-informed corporate managers to underinvest in long-term projects. The introduction of long-term options called LEAPS provides a natural experiment to jointly test both theories, which are otherwise difficult to test. We conduct an event study around the introduction of LEAPS for a given stock and test whether corporate investment in long-term R&D/Sales increases in the years following the introduction. We find that over a two year period of time LEAPS firms increase their R&D/Sales between 23% and 28% ($125-$152 million annually) compared to matching non-LEAPS firms. The difference depends on the matching technique used. Two other proxies for ...
http://www.ssrn.com/abstract=809507
http://www.ssrn.com/1622311.htmlSat, 02 Sep 2017 08:37:50 GMTREVISION: Performance Share Plans: Valuation and Empirical TestsPerformance share plans are an increasingly important component of executive compensation. They are equity-based, long-term incentive plans where the number of shares to be awarded is a quasi-linear function of a performance result over a fixed time period. We derive closed-form formulas for the value of a performance share plan when the performance measure is: (1) a non-traded measure following an Arithmetic Brownian Motion (e.g., earnings per share), (2) a non-traded measure following a Geometric Brownian Motion (e.g., revenue), or (3) a rank-order tournament of traded asset returns that are following Arithmetic Brownian Motions (e.g., percentile of ranked stock returns). Then we empirically test our valuation formulas. We find that our valuation formulas are more accurate for performance share plans based on earnings per share when forecasting using analyst consensus prior to the grant date. We also find that the efficiency of our valuation model greatly depends on the method used ...
http://www.ssrn.com/abstract=2177363
http://www.ssrn.com/1622310.htmlSat, 02 Sep 2017 08:36:45 GMTREVISION: New Low-Frequency Spread MeasuresI develop new spread proxies that pick up on three attributes of the low-frequency (daily) data: (1) price clustering, (2) serial price covariance accounting for midpoint prices on no-trade days, and (3) the quoted spread which is available on no-trade days. I develop and empirically test two different approaches: an integrated model and combined models. I test both new and existing low-frequency spread measures relative to two high-frequency benchmarks (percent effective spread and percent quoted spread) on three performance dimensions: (1) higher individual firm correlation with the benchmarks, (2) higher portfolio correlation with the benchmarks, or (3) lower distance relative to the benchmarks. I find that on all three performance dimensions the new integrated model and the new combined model do significantly better than existing low-frequency spread proxies.
http://www.ssrn.com/abstract=1410758
http://www.ssrn.com/1622309.htmlSat, 02 Sep 2017 08:35:20 GMTREVISION: Do Liquidity Measures Measure Liquidity?Liquidity plays an increasingly important role in empirical asset pricing, market efficiency, and corporate finance. Identifying high quality proxies for liquidity based on daily data only (not intraday data) would permit liquidity to be studied over relatively long timeframes and across many countries. We introduce new liquidity measures. We run horseraces of both monthly and annual liquidity measures. Our benchmarks are effective spread, realized spread, and price impact based on both TAQ and Rule 605 data, including the decimals era. We identify the best proxies in each case and find that the new liquidity measures win the majority of horseraces.
http://www.ssrn.com/abstract=1108553
http://www.ssrn.com/1622307.htmlSat, 02 Sep 2017 08:30:11 GMTREVISION: Penny Wise, Dollar Foolish: Buy-Sell Imbalances On and Around Round NumbersThis paper provides evidence that stock traders focus on round numbers as cognitive reference points for value. Using a random sample of more than 100 million stock transactions, we find excess buying (selling) by liquidity demanders at all price points one penny below (above) round numbers. Further, the size of the buy-sell imbalance is monotonic in the roundness of the adjacent round number (i.e., largest adjacent to integers, second-largest adjacent to half-dollars, etc.). Conditioning on the price path, we find much stronger excess buying (selling) by liquidity demanders when the ask falls (bid rises) to reach the integer than when it crosses the integer. We discuss and test three explanations for these results. Finally, 24-hour returns also vary by price point and buy-sell imbalances are a major determinant of that variation across price points. Buying (selling) by liquidity demanders below (above) round numbers yield losses approaching $1 billion per year.
http://www.ssrn.com/abstract=1569922
http://www.ssrn.com/1622306.htmlSat, 02 Sep 2017 08:28:53 GMTREVISION: Liquidity Measurement Problems in Fast, Competitive Markets: Expensive and Cheap SolutionsDo fast, competitive markets yield liquidity measurement problems when using the popular Monthly Trade and Quote (MTAQ) database? Yes. MTAQ yields distorted measures of spreads, trade location, and price impact compared with the expensive Daily Trade and Quote (DTAQ) database. These problems are driven by (1) withdrawn quotes, (2) second (versus millisecond) timestamps, and (3) other causes, including cancelled quotes. The expensive solution, using DTAQ, is first-best. For financially constrained researchers, the cheap solution – using MTAQ with our new Interpolated Time technique, adjusting for withdrawn quotes, and deleting economically nonsensical states – is second-best. These solutions change research inferences.
http://www.ssrn.com/abstract=2154000
http://www.ssrn.com/1622305.htmlSat, 02 Sep 2017 08:27:55 GMTREVISION: Order Dynamics: Recent Evidence from the NYSEAbstract: We examine investor order choices using evidence from a recent period when the NYSE trades in decimals and allows automatic executions. We analyze the decision to submit or cancel an order or to take no action. For submitted orders, we distinguish order type (market vs. limit), order side (buy vs. sell), execution method (auction vs. automatic), and pricing aggressiveness. We find that the NYSE exhibits positive serial correlation in order type on an order-by-order basis, which suggests that follow-on order strategies dominate adverse selection or liquidity considerations at a moment in time. Aggregated levels of order flow also exhibit positive serial correlation in order type, but appear to be non-stationary processes. Overall, changes in aggregated order flow have an order-type serial correlation that is close to zero at short aggregation intervals, but becomes increasingly negative at longer intervals. This implies a liquidity exhaustion-replenishment cycle. We find ...
http://www.ssrn.com/abstract=424985
http://www.ssrn.com/1622304.htmlSat, 02 Sep 2017 08:25:49 GMTREVISION: What Are the Best Liquidity Proxies for Global Research?Liquidity plays an important role in global research. We identify high quality liquidity proxies based on low-frequency (daily) data, which provide 1,000X to 10,000X computational savings compared to computing high-frequency (intraday) liquidity measures. We find that: (1) Closing Percent Quoted Spread is the best monthly percent-cost proxy when available, (2) Amihud, Closing Percent Quoted Spread Impact, LOT Mixed Impact, High-Low Impact, and FHT Impact are tied as the best monthly cost-per-dollar-volume proxy, (3) the daily version of Closing Percent Quoted Spread is the best daily percent-cost proxy, and (4) the daily version of Amihud is the best daily cost-per-dollar-volume proxy.
http://www.ssrn.com/abstract=1558447
http://www.ssrn.com/1622293.htmlSat, 02 Sep 2017 08:16:42 GMTREVISION: Do Acceptance and Publication Times Differ Across Finance Journals?I examine the acceptance time (i.e., the time that eventually-published articles take from first-round submission to final-round acceptance) and the online/print publication times (i.e., the time that eventually-published articles take from first-round submission to online/print publication) of finance journals. I collect the publication history of articles published during 2012-2015 in the top-20 academic finance journals and in top-tier academic business journals from their websites and from the American Finance Association, European Finance Association, Financial Management Association, Society for Financial Studies, and University of Washington. I post all public data on my website and plan to continue updating it. I test the journal competition hypothesis that mean and median acceptance and publication times are the same across peer journals versus the editorial differences hypothesis that they differ across peer journals. I find that the median acceptance times of the top-five ...
http://www.ssrn.com/abstract=2705479
http://www.ssrn.com/1622300.htmlSat, 02 Sep 2017 08:15:45 GMTREVISION: The Empirical Analysis of LiquidityWe provide a synthesis of the empirical evidence on market liquidity. The liquidity measurement literature has established standard measures of liquidity that apply to broad categories of market microstructure data. Specialized measures of liquidity have been developed to deal with data limitations in specific markets, to provide proxies from daily data, and to assess institutional trading programs. The general liquidity literature has established local cross-sectional patterns, global cross-sectional patterns, and time-series patterns. Commonality in liquidity is prevalent. Certain exchange designs enhance market liquidity: a limit order book for high volume markets, a hybrid exchange for low volume markets, and multiple competing exchanges. Automatic execution increases speed, but increases spreads. A tick size reduction yields a large improvement in liquidity. Providing ex-post transparency to an otherwise opaque market dramatically improves liquidity. Opening up the limit order ...
http://www.ssrn.com/abstract=2402215
http://www.ssrn.com/1621335.htmlTue, 29 Aug 2017 17:15:16 GMTREVISION: Are Volatility Over Volume Liquidity Proxies Useful For Global Or US Research?We examine a general class of volatility over volume liquidity proxies as computed from low frequency (daily) data. We start from the Kyle and Obizhaeva (2016) hypothesis of transaction cost invariance to identify a new volatility over volume liquidity proxy “VoV(%Spread)” for percent spread cost and a new volatility over volume liquidity proxy “VoV(λ)” for the slope of the transaction cost function “λ”. We test the monthly and daily versions of these new and existing liquidity proxies against liquidity benchmarks as estimated from high frequency (intraday) data on both a global and US basis. We find that both the monthly and daily versions of VoV(λ) dominate the equivalent versions of Amihud and other cost-per-dollar-volume proxies on both a global and US basis. We also find that both the monthly and daily versions of VoV(%Spread) dominate the equivalent versions of other percent-cost proxies for US studies that cover pre-1993 years. These results show that the Kyle and Obizhaeva ...
http://www.ssrn.com/abstract=2989367
http://www.ssrn.com/1611667.htmlTue, 25 Jul 2017 07:13:36 GMTREVISION: Are Volatility Over Volume Liquidity Proxies Useful For Global Or US Research?We examine a general class of volatility over volume liquidity proxies as computed from low frequency (daily) data. We start from the Kyle and Obizhaeva (2016) hypothesis of transaction cost invariance to identify a new volatility over volume liquidity proxy “VoV(%Spread)” for percent spread cost and a new volatility over volume liquidity proxy “VoV(λ)” for the slope of the transaction cost function “λ”. We test the monthly and daily versions of these new and existing liquidity proxies against liquidity benchmarks as estimated from high frequency (intraday) data on both a global and US basis. We find that both the monthly and daily versions of VoV(λ) dominate the equivalent versions of Amihud and other cost-per-dollar-volume proxies on both a global and US basis. We also find that both the monthly and daily versions of VoV(%Spread) dominate the equivalent versions of other percent-cost proxies for US studies that cover pre-1993 years. These results provide support for the Kyle and ...
http://www.ssrn.com/abstract=2989367
http://www.ssrn.com/1601515.htmlTue, 20 Jun 2017 07:27:00 GMTREVISION: Performance Share Plans: Valuation and Empirical TestsPerformance share plans are an increasingly important component of executive compensation. They are equity-based, long-term incentive plans where the number of shares to be awarded is a quasi-linear function of a performance result over a fixed time period. We derive closed-form formulas for the value of a performance share plan when the performance measure is: (1) a non-traded measure following an Arithmetic Brownian Motion (e.g., earnings per share), (2) a non-traded measure following a Geometric Brownian Motion (e.g., revenue), or (3) a rank-order tournament of traded asset returns that are following Arithmetic Brownian Motions (e.g., percentile of ranked stock returns). Then we empirically test our valuation formulas. We find that our valuation formulas are more accurate for performance share plans based on earnings per share when forecasting using analyst consensus prior to the grant date. We also find that the efficiency of our valuation model greatly depends on the method used ...
http://www.ssrn.com/abstract=2177363
http://www.ssrn.com/1579192.htmlSun, 02 Apr 2017 10:27:47 GMTREVISION: What Are the Best Liquidity Proxies for Global Research?Liquidity plays an important role in global research. We identify high quality liquidity proxies based on low-frequency (daily) data, which provide 1,000X to 10,000X computational savings compared to computing high-frequency (intraday) liquidity measures. We find that: (1) Closing Percent Quoted Spread is the best monthly percent-cost proxy when available, (2) Amihud, Closing Percent Quoted Spread Impact, LOT Mixed Impact, High-Low Impact, and FHT Impact are tied as the best monthly cost-per-dollar-volume proxy, (3) the daily version of Closing Percent Quoted Spread is the best daily percent-cost proxy, and (4) the daily version of Amihud is the best daily cost-per-dollar-volume proxy.
http://www.ssrn.com/abstract=1558447
http://www.ssrn.com/1561978.htmlSun, 29 Jan 2017 17:14:35 GMTREVISION: Testing the LCAPM vs. Generalized Liquidity-Adjusted Asset Pricing: New Evidence and New PerspectivesThe Liquidity-adjusted Capital Asset Pricing Model (LCAPM) makes two specific testable predictions: (1) the coefficient on expected liquidity cost equals average turnover and (2) the coefficient on market beta equals the coefficient on net liquidity risk beta. By contrast, Generalized Liquidity-Adjusted Asset Pricing (GLAAP) allows liquidity characteristics and/or liquidity risk factors to be priced, but without requiring these parameter restrictions. We test the LCAPM vs. GLAAP. In doing so, we expand the range of LCAPM evidence in multiple ways. First, we extend forward and backwards in time to cover 80 years. Second, we analyze NASDAQ-listed stocks as well as NYSE/AMEX-listed stocks. Third, we analyze four alternative liquidity measures: (1) the Corwin and Schultz proxy, (2) closing percent quoted spread, (3) the Amihud proxy, and (4) zeros. Fourth, we analyze the impact of adding Fama and French/Carhart risk factors to the model. Our main finding is that both of these specific ...
http://www.ssrn.com/abstract=2848373
http://www.ssrn.com/1541452.htmlSat, 05 Nov 2016 06:36:26 GMTREVISION: What Are the Best Liquidity Proxies for Global Research?Liquidity plays an important role in global research. We identify high quality liquidity proxies based on low-frequency (daily) data, which provide 1,000X to 10,000X computational savings compared to computing high-frequency (intraday) liquidity measures. We find that: (1) Closing Percent Quoted Spread is the best monthly percent-cost proxy when available, (2) Amihud, Closing Percent Quoted Spread Impact, LOT Mixed Impact, High-Low Impact, and FHT Impact are tied as the best monthly cost-per-dollar-volume proxy, (3) the daily version of Closing Percent Quoted Spread is the best daily percent-cost proxy, and (4) the daily version of Amihud is the best daily cost-per-dollar-volume proxy.
http://www.ssrn.com/abstract=1558447
http://www.ssrn.com/1535492.htmlThu, 13 Oct 2016 12:54:21 GMTREVISION: Testing the LCAPM vs. Generalized Liquidity-Adjusted Asset Pricing: New Evidence and New PerspectivesThe Liquidity-adjusted Capital Asset Pricing Model (LCAPM) includes two specific testable predictions: (1) the coefficient on expected liquidity cost equals average turnover and (2) the coefficient on market beta equals the coefficient on net liquidity risk beta. By contrast, generalized liquidity-adjusted asset pricing models allow liquidity characteristics and/or liquidity risk factors without such parameter restrictions. We empirically test these alternative theories. In doing so, we expand the range of evidence in multiple ways. First, we extend forward and backwards in time to cover 80 years. Second, we analyze NASDAQ-listed stocks as well as NYSE/AMEX-listed stocks. Third, we analyze four alternative liquidity measures: (1) the Corwin and Schultz proxy, (2) closing percent quoted spread, (3) the Amihud proxy, and (4) zeros. Fourth, we analyze the impact of adding Fama and French/Carhart risk factors to the model. Our main finding is that both of these specific predictions of ...
http://www.ssrn.com/abstract=2848373
http://www.ssrn.com/1534231.htmlSat, 08 Oct 2016 19:49:40 GMT