nep-fmk New Economics Papers
on Financial Markets
Issue of 2019‒12‒09
seven papers chosen by

  1. Extreme Downside Risk in Asset Returns By Lerby Ergun
  2. Market Participants’ Forecasts of Financial Variables – Can Survey Data Outperform the Random Walk? By Kladivko, Kamil; Österholm, Pär
  3. Asset Price Bubbles in market models with proportional transaction costs By Francesca Biagini; Thomas Reitsam
  4. Deep Reinforcement Learning for Trading By Zihao Zhang; Stefan Zohren; Stephen Roberts
  5. Predicting interest rates in real-time By Alberto Caruso; Laura Coroneo
  6. Bounded Temporal Fairness for FIFO Financial Markets By Vasilios Mavroudis
  7. Quantitative easing and exuberance in stock markets: Evidence from the euro area By Tom Hudepohl; Ryan van Lamoen; Nander de Vette

  1. By: Lerby Ergun
    Abstract: Financial markets can experience sudden and extreme downward movements. Investors are highly concerned about the performance of their assets in such scenarios. Some assets perform badly in a downturn in the market; others have milder reactions. The assets that react mildly are desirable and should sell at a premium. But determining how reactive individual stocks are to extreme market downturns is a difficult task given the small sample of these events. This paper uses a simple methodology to measure the sensitivity of individual stocks to extreme market movements. I count the number of times the market and the individual stock simultaneously pass their individual extreme threshold. I divide the number of these occurrences by the number of times the market is extreme. This measure can be seen as the probability that the asset value will have an extremely negative reaction when the market experiences an extremely negative episode. By sorting individual stocks based on this measure and analyzing the direction and increase in the average return of the sorted stocks, I measure the compensation investors demand for exposure to this risk. I find that investors demand a 3.5 percent risk premium for investing in a stock with high sensitivity to the market relative to one with low sensitivity. This measure characterizes the riskiness of a stock not captured by existing risk factors.
    Keywords: Asset Pricing; Econometric and statistical methods
    JEL: C14 G11 G12
    Date: 2019–12
  2. By: Kladivko, Kamil (Örebro University School of Business); Österholm, Pär (Örebro University School of Business)
    Abstract: In this paper, we evaluate the forecasting precision of survey expectations of the four financial variables in the Prospera survey commissioned by Sveriges Riksbank – one of Sweden’s most important economic surveys. Our analysis shows that the market participants in the survey are able to significantly outperform the random walk for only one horizon and variable, namely the three-month horizon for the repo rate. At the longest horizon for the repo rate, and at all horizons for the five-year government bond yield, the random walk signif-icantly outperforms the market participants. For the exchange-rate data studied – SEK/USD and SEK/EUR – no significant differences in forecasting precision can be established. It accordingly seems that while the Prospera survey might be informative regarding the market participants’ expectations, it does not carry much information about the actual future developments of the exchange rates and interest rates covered by the survey.
    Keywords: Out-of-sample forecasts; Exchange rates; Interest rates
    JEL: E47 G17
    Date: 2019–11–27
  3. By: Francesca Biagini; Thomas Reitsam
    Abstract: We study asset price bubbles in market models with proportional transaction costs $\lambda\in (0,1)$ and finite time horizon $T$ in the setting of [48]. By following [27], we define the fundamental value $F$ of a risky asset $S$ as the price of a super-replicating portfolio for a position terminating in one unit of the asset and zero cash. We then obtain a dual representation for the fundamental value by using the super-replication theorem of [49]. We say that an asset price has a bubble if its fundamental value differs from the ask-price $(1+\lambda)S$. We investigate the impact of transaction costs on asset price bubbles and show that our model intrinsically includes the birth of a bubble.
    Date: 2019–11
  4. By: Zihao Zhang; Stefan Zohren; Stephen Roberts
    Abstract: We adopt Deep Reinforcement Learning algorithms to design trading strategies for continuous futures contracts. Both discrete and continuous action spaces are considered and volatility scaling is incorporated to create reward functions which scale trade positions based on market volatility. We test our algorithms on the 50 most liquid futures contracts from 2011 to 2019, and investigate how performance varies across different asset classes including commodities, equity indices, fixed income and FX markets. We compare our algorithms against classical time series momentum strategies, and show that our method outperforms such baseline models, delivering positive profits despite heavy transaction costs. The experiments show that the proposed algorithms can follow large market trends without changing positions and can also scale down, or hold, through consolidation periods.
    Date: 2019–11
  5. By: Alberto Caruso; Laura Coroneo
    Abstract: We analyse the predictive ability of real-time macroeconomic information for the yield curve of interest rates. We specify a mixed-frequency macro-yields model in real-time that incorporates interest rate surveys and that treats macroeconomic factors as unobservable components. Results indicate that real-time macroeconomic information is helpful to predict interest rates, and that data revisions drive a superior predictive ability of revised macro data over real-time macro data. Moreover, we find that incorporating interest rate surveys in the model can significantly improve its predictive ability.
    Keywords: Government Bonds; Dynamic Factor Models; Real-time Forecasting; Mixed-frequencies.
    JEL: C33 C53 E43 E44 G12
    Date: 2019–11
  6. By: Vasilios Mavroudis
    Abstract: 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.
    Date: 2019–11
  7. By: Tom Hudepohl; Ryan van Lamoen; Nander de Vette
    Abstract: In response to a prolonged period of low inflation, the European Central Bank (ECB) introduced Quantitative Easing (QE) in an attempt to steer inflation to its target of below, but close to, 2% in the medium term. This paper examines whether QE contributes to exuberance in euro area stock markets by using recent advances in bubble detection techniques (the GSADF-test). We do so by linking price developments in 10 euro area stock markets to a series of country specific macro fundamentals and QE. The results indicate that periods of QE coincide with exuberant investor behaviour, even after controlling for improving macro fundamentals.
    Keywords: exuberance; asset price bubbles; unconventional monetary policy; quantitative easing
    JEL: G12 G15 E52 E58
    Date: 2019–12

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