Strategic trading in the wrong direction by a large institutional insider

Many theoretical papers suggest that large informed traders should make misleading or random trades to disguise their trading. Alternatively, informed traders may trade purely on their estimate of stock value. This paper examines the trading behavior of a large institutional insider that periodically trades in the wrong direction, i.e., makes occasional sell (buy) trades within packages of buy (sell) trades. Using a hand-collected data set, we find that three quarters of the trade packages include wrong-direction trades. Wrong trades appear to be used mostly to disguise right-direction trades. We find that the wrong-trade stocks are larger and have less noisy returns, hence, they lack natural disguise. Wrong trades are relatively small, used to accentuate return volatility, distributed evenly during a package of trades, and are not consistently profitable.     

Foreclosure Sales: The Effects of Price Expectations, Volatility and Equity Losses

Where borrowers are personally liable for shortfalls when they default on their mortgages, lenders have to exercise a duty of good faith in securing a reasonable value for the foreclosed property. The lender is entitled to recover the outstanding loan as quickly as possible, and is not bound to sell the foreclosed property at the highest price. Such an institutional setting allows us to study lender and borrower behavior, specifically the influence of price expectations, volatility and equity losses on foreclosure transactions using non-foreclosure transactions as a comparison. Our results show that differences in seller response to market expectations and equity losses exist across foreclosure and non-foreclosure transactions. Seller behavior matters. While price expectations, volatility and equity losses are influential factors for individual households, past price movements is the most important. This study also further seeks to distinguish loss aversion from disposition effect. By controlling for properties that suffered losses in equity but did not sell, we are able to examine the disposition effect in house owners. The result shows that there is disposition effect for non-foreclosure properties, where individual homeowners are reluctant to sell if the properties suffer losses.

Are the Insider Trades of a Large Institutional Investor Informed?

We use a unique data set to consider whether a large institution's (Fidelity funds) insider trades are informed. Theoretical studies of large informed traders suggest that their information advantage could be greater for buy trades than sell trades, be short‐ or long‐lived, and be exploited by varying the pace of trade execution. Although there is evidence of each of these, Fidelity seems to be informed only for quickly executed buy trades. Other trades outperform a stock market index but not a four‐factor return model. This performance profile is consistent with Fidelity's fees, which depend on performance compared to an index.     

TRADING PATTERNS OF SMALL AND LARGE TRADERS AROUND STOCK SPLIT EX-DATES

We investigate the trading patterns of small and large traders around stock split ex-dates. Using the intraday transaction database for the Toronto Stock Exchange during 1983–89, we find that stock splits are associated with significant changes in trading patterns. Although stock splits appear to have little effect on the trading behavior of large traders (trade value of at least $100,000), they are associated with significant decreases in odd-lot trading and increases in small board-lot trading (trade value of less than $10,000). Although the liquidity premia decrease for all trade sizes, trade direction changes significantly from sell to buy after split ex-dates for all but the large trades, where the change is in the opposite direction. The significant increase in variances after split ex-dates is explained by various microstructure-related variables, and small (large) trades appear to be (de)stabilizing.     

NYSE execution quality subsequent to migration to hybrid

In October 2006, the NYSE began rolling-out phase three of a four-phase plan initiate its new Hybrid trading mechanism. The results show that this new trading platform introduced a much larger proportion of electronic transactions relative to floor auction transactions. This migration to electronic transactions is further evidenced by a mirror shift in price discovery from floor trades to trades marked for automatic electronic execution. In addition, the move to Hybrid trading introduced a significant decrease in inventory control costs, as well as a noticeable increase in trade persistence. Finally, the new trading platform has increased the speed with which orders are met, and has also decreased the proportion of executed shares which receive price improvement.

Who You Going to Call? Performance of Realtors and Non-realtors in a MLS Setting

This study attempts to shed some light on the extent of non-realtor broker listings on the MLS and their resulting price and time-on-the markets effects. Using duration, probit and selling price models, this study empirically examines whether the REALTOR designation provides a signal of quality that is reflected in the price and time on the market for sellers. Results indicate that properties listed by non-realtors on the MLS setting sell at lower prices, take slightly longer to sell, and are less likely to sell than properties listed by REALTORs in a MLS setting. Working with a REALTOR in a MLS setting appears to be advantageous to the seller.

Calendar Anomalies: The Case of International Property Shares

In this paper we analyze the price dynamics of international property shares for the ten most prominent markets from around the world plus South-Africa. We focus on the presence of calendar effects in daily and monthly price returns and examine these effects both over time and across countries. For the daily returns we find price anomalies for Fridays and Mondays in all markets. Friday returns tend to be the highest of the week, while Mondays are weakest. We find that these patterns were most prominent during the 1980s and early 1990s and in the smaller markets in our sample. For the monthly returns we found little evidence for price irregularities. In most cases January was superior to most other months, but these differences lacked statistical significance. More interesting was the sell in May effect that seemed to be present in ten out of 11 markets. Price returns during the winter season outperformed the summer months and in five countries these difference were both economically and statistically significant. Finally, we looked at firm level returns to isolate the drivers of these infamous calendar effects. The day-of-the-week effect appears to be most pronounced among small and young firms that have little or no institutional investors. Large and long-established listed real estate firms with a large portion of loyal block-holders experience no significant price patterns during the trading week.

Institutional investors,intangible information,and the book-to-market effect

This paper establishes a robust link between the trading behavior of institutions and the book-to-market effect. Building on work by Daniel and Titman (2006), who argue that the book-to-market effect is driven by the reversal of intangible returns, I find that institutions tend to buy (sell) shares in response to positive (negative) intangible information and that the reversal of the intangible return is most pronounced among stocks for which a large proportion of active institutions trade in the direction of intangible information. Furthermore, the book-to-market effect is large and significant in stocks with intense past institutional trading but nonexistent in stocks with moderate institutional trading. This influence of institutional trading on the book-to-market effect is distinct from that of firm size. These results are consistent with the view that the tendency of institutions to trade in the direction of intangible information exacerbates price overreaction, thereby contributing to the value premium.     

The Effect of Reputation and Competition on the Advice of Real Estate Agents

We study a two-period bargaining game where buyers and sellers employ real estate agents to help them determine the sales price of a house. We find that agents are less likely to provide aggressive bargaining advice to their client when they receive percentage commissions and when they work for the buyer. In addition, we find that agents are less likely to suggest aggressive bargaining strategies when there is little market competition, the gains to trade are large, in markets where housing values appreciate slowly, and when dual agency is permitted. More importantly, we show that an agent is more likely to bargain aggressively and capture a portion of the gains to trade for a client when the house’s sales price is closely related to the agent’s reputation and future business (referrals).

Commercial Real Estate Valuation: Fundamentals Versus Investor Sentiment

This paper investigates the role of fundamentals and investor sentiment in commercial real estate valuation. In real estate markets, heterogeneous properties trade in illiquid, highly segmented and informationally inefficient local markets. Moreover, the inability to short sell private real estate restricts the ability of sophisticated traders to enter the market and eliminate mispricing. These characteristics would seem to render private real estate markets highly susceptible to sentiment-induced mispricing. Using error correction models to carefully model potential lags in the adjustment process, this paper extends previous work on cap rate dynamics by examining the extent to which fundamentals and investor sentiment help to explain the time-series variation in national-level cap rates. We find evidence that investor sentiment impacts pricing, even after controlling for changes in expected rental growth, equity risk premiums, T-bond yields, and lagged adjustments from long run equilibrium.

Trade size clustering and the cost of trading at the London Stock Exchange

For the London Stock Exchange, this paper investigates differences in trading costs between market maker (off-book) and order book trades, in the context of clustering in trade sizes and prices. We report several substantial findings. Even after controlling for differences in trade size, the realised spread measure is lower for off-book trades. For the order book, trade size clustering is not associated with differences in transaction costs nor with differences in the information content of trades. For the off-book market, trades in clustered (popular) sizes carry significantly more information than non-clustered trades. Despite the significant differences in the price impact estimates between the order book and off-book, we show that traders placing large orders off-book are still better off than trading via the order book as they benefit from a large discount from the current midpoint price. Additionally, we highlight that price and size clustering tend to occur simultaneously rather than being substitutes in this market setting.     

Strategic trading and learning about liquidity

Many practitioners point out that the speculative profits of institutional traders are eroded by the difficulty in gauging the price impact of their trades. In this paper, we develop a model of strategic trading where speculators face such a dilemma because of incomplete information about time-varying market liquidity. Unlike the competitive market makers that they trade against, informed traders do not know the distribution of liquidity (“noise”) trades. Instead, they have to learn about liquidity from past prices and trading volume. This learning implies that strategic trades and market statistics such as informational efficiency are path-dependent on past market outcomes. Our paper also has normative implications for practitioners.     

Individual Agents,Firms, and the Real Estate Brokerage Process

This study examines how individual agents affect house selling prices and time on the market while controlling for brokerage firm-specific effects as well as supply and demand conditions that vary by neighborhood. Firm size effects disappear once firm specialization and agent characteristics are taken into account but geographic concentration by firms leads to higher selling prices. For individual agents, neither sex nor selling own listings affects price or selling time, but there are gains from partnering transactions across firms. Agents who specialize in listing properties obtain higher prices for their sellers while those who specialize in selling obtain lower prices for their buyers. Houses nearer to other transactions of an agent sell for higher prices. Finally, greater scale of listing and selling activity by an agent tends to lower selling price or lengthen the time on the market.

Stealth trading: The case of the Tokyo Stock Exchange

The stealth trading hypothesis asserts that informed traders trade strategically by breaking up their orders so as to more easily hide among the liquidity traders. Using data for the Tokyo Stock Exchange (TSE), a pure order-driven market, we find evidence that price changes are driven by small- and medium-size trades, with small trades making the greatest contribution to price change relative to their contribution to trading volume. We also find that large trades explain a greater portion of the cumulative price change on high volatility days. Hence, our results support the stealth trading hypothesis for the TSE.     

Institutional Investment and the Turn-of-the-Month Effect: Evidence from REITs

Many studies have hypothesized that the turn-of-the-month effect is caused by institutional investment. However, there is little evidence to support this hypothesis. This study provides an empirical test that measures the impact of the level of institutional investment on the turn-of-the-month effect using a sample of REITs over the period 1980 to 2004. We find that a significant change in the turn-of-the-month effect occurred following the Omnibus Reconciliation Act of 1993 which relaxed the requirements on the level of institutional investment in REITs. The evidence suggests that the dramatic rise in institutional holdings can account for a good part of this change. However, the impact of institutional investment may not be as large as some researchers have suspected. There is no evidence to suggest that institutional investment impacts returns on the day when the turn-of-the-month effect is most pronounced, suggesting that this calendar anomaly is not caused exclusively by institutional investors in the market.

1-share orders and trades

1-share trades are the most common odd lot trade size, accounting for 9.62% of all odd lot transactions and 3.65% of all trades on NASDAQ in 2012. While 50.41% of 1-share trades result from broken orders, 34.89% of 1-share trades are intentional. We provide substantial evidence that traders use 1-share trades to “ping” for hidden liquidity. In particular, our results indicate that 1-share trades are disproportionately aggressive and also execute against hidden liquidity more than any other odd lot trade size. We also find a relative increase in trading immediately following a 1-share trade. Our results are in line with Clark-Joseph (2014), who suggests that traders may use small, unprofitable trades to detect information from other traders. Specifically, 1-share trades represent the minimum cash outlay necessary to trade, while simultaneously producing the smallest possible effects on a market maker's inventory, and in turn, a security's price.     

The Structure of Chinese Urban Land Prices: Estimates from Benchmark Land Price Data

Taking the recent benchmark land prices published by the Chinese city governments, the paper estimates commercial and residential land price curves of Chinese cities using cross-sectional data, controlling for urban population size and income level. The urban land leasing price–distance relationship is estimated based on the argument that monocentric urban structure is representative for Chinese cities. Both population size and income level are found to positively affect urban land price and price–distance gradients. Commercial land prices are higher than residential land prices except in suburbs or outer central urban areas, where the land prices of different uses converge. In most situations, commercial use price gradients are larger than those of residential use.

Predictable behavior, profits, and attention

Stocks in the Shanghai market that hit upper price limits typically exhibit three characteristics: high returns, high volumes, and news coverage. We show that these price limit events attract investors' attention. Attention-grabbing events lead active individual investors to buy stocks they have not previously owned. Consistent with lowering investor search costs, events that affect a few (many) stocks lead to increased (decreased) buying. Upper price limit events coincide with initial price increases followed by statistically significant price mean reversion over the following week. Rational traders (statistical arbitrageurs) profit in response to attention-based buying. Smart traders accumulate shares on date t, sell shares on date t + 1, and earn a daily average profit of 1.16%. We show the amount they invest predicts the degree of attention-based buying by individual investors. We end by decomposing individual investor trades in order to estimate losses attributable to behavioral biases.     

Size Effects in the Pricing of Corporate Bonds

Large orders for corporate bonds get preferential treatment unlike large orders for stocks on the NYSE. A structural explanation, namely, that the corporate bond market is dealer‐dominated, has been offered for the favorable pricing. In this paper, we offer an additional explanation, namely, that the improved pricing for large orders is due to the net impact such orders have on a market maker's costs. Using a data sample that is substantially free of timing mismatch, we support our assertion by sorting the sample into ‘brokered’ trades, which are trades where the dealer merely crosses buy and sell orders and ‘inventoried’ trades, where the dealer trades out of his inventory. We find that large orders raise information costs, but lower inventory costs for ‘inventoried’ trades. The net result is a smaller price advantage than received by large orders on ‘brokered’ trades which are not subject to these costs.