A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
- Topic classification is ongoing.
- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 41 resources
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Technology transformed the trading of financial assets but has been slower to come to corporate bond trading. Combining proprietary data from MarketAxess with regulatory TRACE data, we investigate how electronic request for quote (RFQ) trading affects bond dealers and trading more generally. We demonstrate that electronic trading remains fairly small and segmented, but has wide-ranging effects on transaction costs and execution quality in both electronic and voice trading, and the interdealer market. We identify features particular to bond markets that have and could continue to limit electronic bond trading growth. We provide an intriguing portrait of a market in transition.
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We explore the link between mutual funds and fragility risk in the corporate bond market. We classify a fund’s trading style based on its responses to signals of large dealer inventories. Trading style is persistent and the majority of funds demand liquidity. Notably, a subset of funds earn positive alpha by intentionally supplying liquidity during periods of sustained customer selling (with transitory price effects). Liquidity-supplying funds maintain their relative trading style when facing large outflows and elevated market stress, thus alleviating fragility risk. Our results add nuance to existing evidence that mutual funds pose a threat to market stability.
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This paper uncovers that expected excess bond returns display a positive correlation with the slope of the yield curve (i.e., yield spread) in expansions but a negative correlation in recessions. We use a macro-finance term structure model with different market prices of risk in expansions and recessions to show that a very accommodating monetary policy in recessions is a key driver of this switch in return predictability.
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We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the bond and equity markets. We find a significantly positive intertemporal relation between expected return and risk in the bond market. We also propose novel measures of systematic and idiosyncratic risk for individual corporate bonds and find a significantly positive cross-sectional relation between systematic risk and expected bond returns, whereas there is no significant link between idiosyncratic risk and future bond returns. We provide an explanation for the significance of systematic (idiosyncratic) risk based on different investor preferences and informational frictions in the bond (equity) market.
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Long-term reversals in corporate bonds are economically and statistically significant in a comprehensive sample spanning the period 1977 to 2017. Such reversals are stronger for bonds with high credit risk and more binding regulatory, capital, and funding liquidity constraints. Bond long-term reversal is not a manifestation of the equity counterpart and is mainly driven by long-term losers. A long-term reversal factor carries a sizable premium and is not explained by long-established equity and bond market factors. Thus, past returns capture investors’ ex-ante risk assessment and the degree of institutional constraints they face, so losing bonds command higher expected returns.
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Hedging short gamma exposure requires trading in the direction of price movements, thereby creating price momentum. Using intraday returns on over 60 futures on equities, bonds, commodities, and currencies between 1974 and 2020, we find strong market intraday momentum everywhere. The return during the last 30 minutes before the market close is positively predicted by the return during the rest of the day (from previous market close to the last 30 minutes). The predictive power is economically and statistically highly significant, and reverts over the next days. We provide novel evidence that links market intraday momentum to the gamma hedging demand from market participants such as market makers of options and leveraged ETFs.
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We examine 24 global factor premiums across equity, bond, commodity, and currency markets via replication and out-of-sample evidence between 1800 and 2016. Replication yields ambiguous evidence within a unified testing framework that accounts for p-hacking. Out-of-sample tests reveal strong and robust presence of the large majority of global factor premiums, with limited out-of-sample decay of the premiums. We find global factor premiums to be generally unrelated to market, downside, or macroeconomic risks in the 217 years of data. These results reveal significant global factor premiums that present a challenge to traditional asset pricing theories.
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We use non-Gaussian features in U.S. macroeconomic data to identify aggregate supply and demand shocks while imposing minimal economic assumptions. Macro risks represent the variables that govern the time-varying variance, skewness, and higher-order moments of these two shocks, with ”good” (”bad”) variance associated with positive (negative) skewness. We document that macro risks significantly contribute to the variation of yields and risk premiums for nominal bonds. While overall bond risk premiums are countercyclical, an increase in aggregate demand variance significantly lowers risk premiums. Macro risks also significantly predict future realized bond return variances.
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Several measures of credit-market booms are known to precede downturns in real economic activity. We offer an early indicator for all known measures of credit booms. Our measure is based on intra-family flow shifts towards high-yield bond mutual funds. It predicts indicators such as growth in financial intermediary balance sheets, increase in shares of high-yield bond issuers, and downturns of various measures of credit spreads. It also directly predicts the business cycle by positively predicting GDP growth and negatively predicting unemployment. Our results provide support for the investor demand-based narrative of credit cycles and can be useful for policymakers.
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Do more talented traders prefer to bet on and against rare events or common events? Bets on rare events include out of the money options. Bets against rare events include the carry trade and investment grade bonds. In a model where traders specialize, equilibrium pricing reflects trading ability: A market with more skilled traders has a larger bid ask spread. We show that lower skill traders bet on and against rare events, while higher skill traders bet on and against frequent events, leading to higher bid-ask spreads in common event assets, and reducing financial markets’ ability to predict rare events.