Market liquidity expected to ease

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Does the mutual fund industry lose its best managers to hedge funds? We find that mutual funds are able bank funding liquidity and market liquidity as a sentiment retain managers with good performance in the face of competition from a growing hedge fund industry.

On the other hand, poor performers are more likely to leave the mutual fund industry. A small fraction of these poor performers find jobs with smaller and younger hedge fund companies, especially when the hedge fund industry is growing rapidly. Analogously, a small fraction of the better performing mutual fund managers are retained by allowing them to manage a hedge fund side-by-side.

The first component -- flow-driven risk -- is large, accounting for approximately 50 percent of market variance, and it is not transient. This risk represents the joint effect of net trade demand and the price impact of that demand i.

We find that flows are largely unpredictable, and lagged flows have no price impact. Flow-driven risk is time varying because price impact is highly variable. Illiquidity rises with market volatility, but not with flow uncertainty. Net selling bank funding liquidity and market liquidity as a sentiment illiquidity, which amplifies downside flow-driven risk.

The findings are consistent with flow-driven shocks resulting from fluctuations in aggregate risk-bearing capacity. Under this interpretation, investors with constant risk tolerance should trade against such shocks i. Quantitatively accounting for the scale of flow-driven risk poses a major challenge for asset pricing theory.

Can the liquidity premium in asset prices, as documented in the exchange-traded equity and bond markets, be generalized to the over-thecounter OTC derivative markets? This liquidity discount, though opposite to that found in equities and bonds, is consistent with the structure of this OTC market and the nature of its demand and supply forces.

Our results suggest that the effect of liquidity on asset prices cannot be generalized without regard to the characteristics of the market. We address three questions relating to the interest rate options market: What is the shape of the smile?

What are the bank funding liquidity and market liquidity as a sentiment determinants of the shape of the smile? Do these determinants have predictive power for the futures shape of the smile and vice versa?

We find a clear smile pattern in interest rate options. The shape of the smile bank funding liquidity and market liquidity as a sentiment over time and is affected in a dynamic manner by yield curve variables and the future uncertainty in the interest rate markets; it also has information about future aggregate default risk.

Our findings are useful for the pricing, hedging and risk management of these derivatives. This study investigates the effects of funding liquidity conditions on price impact and order-book depth using a comprehensive dataset of orders and trades in the Indian government bond market. We measure funding liquidity along both price and quantity dimensions in the repo market, as well as the interaction of the two.

Our price-impact tests provide modest support for the hypothesis that a lower repo rate promotes market liquidity. But, contrary to expectations, the marginal effect of increased funding demand is to lower price impact, improving market liquidity. We show that two channels partially contribute to this result: Time-series regressions show that order-book depth also responds mildly positively to greater funding liquidity.

This is again tempered by the indirect positive effect of tighter funding conditions on order-book depth via greater uninformed bond trading. Overall, the results suggest that there is limited scope for liquidity policy to affect bond market depth or resilience.

Margin credit, defined as the excess debt capacity of investors buying securities on the margin, predicts lower aggregate stock returns very strongly, outperforming other forecasting variables proposed in the literature. Its out-of-sample R-squared of 7.

Asset allocation based on margin credit generates a Sharpe ratio of 0. It avoids the stock market downturns around and Margin credit carries information about future discount rates as well as future cash flows. It anticipates lower future dividend, earnings, and GDP growth and higher future risk measured by higher VIX, average equity correlation, macro and financial uncertainty, and lower intermediary equity ratio.

We study arbitrageur activity following temporary mispricing as a result of TV analyst recommendations using rich, intra-day trader level data. The recommendations move prices in their direction but this effect completely reverses within a week. Individual investors trade in the direction of the recommendation. Given the quick and complete reversal, trading by individual investors can be viewed as a pure liquidity shock i.

Thus, contrarian traders can lean bank funding liquidity and market liquidity as a sentiment the price pressure without worrying about adverse selection. Proprietary traders trade contrarian for both buy and sell recommendations. Institutional investors trade contrarian for sell recommendations, but remain neutral to buy recommendations to avoid holding overnight short positions.

We also find that arbitrageurs assume less aggressive positions in difficult-to-arbitrage stocks such as illiquid stocks. Overall, our evidence points to differential limits to arbitrage faced by different types of arbitrageurs. News bank funding liquidity and market liquidity as a sentiment sentiment is a strong contrarian indicator. The cross-sectional pricing ability of media sentiment is particularly strong when it is based on emotionally-charged, as opposed to fact-based, references in the news media.

Stocks with positive sentiment tend to have higher returns over the prior three years and lower book-to-market ratios than those with negative sentiment. Controlling for these and other characteristics does not eliminate the returns associated with variation in media sentiment. Fund family characteristics and prior performance play an important role in fee determination.

New fund families are likely to charge at- or above-median fees. Initial fees of funds introduced by an existing family are positively related to the prior performance of the family as well as of the investment strategy they follow.

Furthermore, management bank funding liquidity and market liquidity as a sentiment are dynamically adjusted in response to past fund performance. Funds that increase management fee more aggressively experience a bigger drop in subsequent money inflows, and are more likely to maintain their good performance.

This suggests that fee increases, which typically apply only to new investors, may benefit existing investors by mitigating diseconomies of scale. Regret is a proposed explanation for many bank funding liquidity and market liquidity as a sentiment in economics and finance.

Yet very few studies analyze the effect of experienced regret on subsequent decisions in a real-world-setting. We find that after experiencing regret, individuals are more likely to change their decision to place a market or limit order.

Confirming the predictions of regret theory, the effect of regret is stronger following an action rather than inaction, loss on the prior order, and an unusual order strategy for the individual.

Moreover, decisions influenced by regret yield poor returns. The totality of these results rules out rational learning as an explanation. This paper presents a model of liquidity and volatility in which investors extrapolate recent price movements to forecast the volatility of a risky asset.

High perceived volatility leads to high risk premium, low current return, low risk-free rate and illiquid markets. Illiquidity amplifies supply shocks, increasing realized volatility of prices, which feeds into subsequent volatility forecasts.

As a result, clustering of volatility and liquidity arises endogenously. The model helps to unify several known facts about liquidity and volatility, and I find support for its new prediction which links misperception of volatility to liquidity.

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