We study the effects of social media on the informativeness of retail trading. Our identification strategy exploits the editorial delay between report submission and publication on Seeking Alpha, a ...popular crowdsourced investment research platform. We find the ability of retail order imbalances to predict the cross-section of stock returns and cash-flow news increases sharply in the intraday post-publication window relative to the pre-publication window. The findings are robust to controlling for report tone and stronger for reports authored by more capable contributors. The evidence suggests that recent technology-enabled innovations in how individuals share information help retail investors become better informed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Generating asset-specific trading signals based on the financial conditions of the assets is one of the challenging problems in automated trading. Various asset trading rules are proposed ...experimentally based on different technical analysis techniques. However, these kind of trading strategies are profitable, extracting new asset-specific trading rules from vast historical data to increase total return and decrease the risk of portfolios is difficult for human experts. Recently, various deep reinforcement learning (DRL) methods are employed to learn the new trading rules for each asset. In this paper, a novel DRL model with various feature extraction modules is proposed. The effect of different input representations on the performance of the models is investigated and the performance of DRL-based models in different markets and asset situations is studied. The proposed model in this work outperformed the other state-of-the-art models in learning single asset-specific trading rules and obtained almost 12.4% more profit over the best state-of-the-art model on the Dow Jones Index in the same time period.
•A model to learn asset-specific trading rules using DRL technique is proposed.•Performance of DRL models in learning trading rules on single assets is studied.•The effects of different feature extraction models and input types are studied.•DRL models trained on OHLC data dominate the candlestick trading rules.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Sentiment during Recessions Garcia, DIEGO
The Journal of finance (New York),
June 2013, Volume:
68, Issue:
3
Journal Article
Peer reviewed
This paper studies the effect of sentiment on asset prices during the 20th century (1905 to 2005). As a proxy for sentiment, we use the fraction of positive and negative words in two columns of ...financial news from the New York Times. The main contribution of the paper is to show that, controlling for other well-known time-series patterns, the predictability of stock returns using news' content is concentrated in recessions. A one standard deviation shock to our news measure during recessions predicts a change in the conditional average return on the DJIA of 12 basis points over one day.
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BFBNIB, FZAB, GIS, IJS, INZLJ, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
Üstelik bu değer kaybının bir noktadan sonra yavaşlayacağına dair görünürde en ufak bir işaret bile yoktu hâlâ.1 Hükümet TL’deki düşüşü durdurmak için 1-17 Aralık döneminde TCMB rezervlerinin ...toplamda 6 milyar USD kadar bir kısmını sattı ama nafile. 20 Aralık’ta yapılan kabine toplantısının ardından Kur Korumalı TL Vadeli Mevduat (KKM) planının duyurulmasıyla beraber, dolar/TL paritesi sert bir düşüşle 13,05’e kadar geriledi ve ertesi gün itibarıyla da 13,50 civarına yerleşti. Gelir dağılımına gelince, döviz kurundaki oynaklığın çok artmış olması, spekülasyon ve kamuya açıklanmamış bilgiye dayalı ticaretin (insider trading) öne çıktığı “kumarhane kapitalizmi”ne zemin hazırlıyordu. Söz konusu işlemler hakkında ayrıntılı bilgi verilmediği için net bir rakamdan bahsetmek zor, yine de gerekli mali kaynaklara erişebilenlerin bu yolla beklenmedik kazançlar elde etmiş olması gayet olası. Küresel enerji, gıda ve emtia fiyatları ile navlunların artmasının yanı sıra ithalata bağımlılığı bir hayli yüksek olan Türkiye’nin en fazla ithalat yaptığı ülkelerde enflasyon eğilimlerinin görülmesi, ödemeler dengesi üstündeki baskının artmasına ve bu enflasyon tablosuna bir de ithalat boyutunun eklenmesine yol açtı.
Washington policy research analysts (WAs) monitor political developments and produce research to interpret the impact of these events. We find institutional clients channel more commissions to ...brokerages providing policy research and commission-allocating institutional clients generate superior returns on their politically sensitive trades. We find that WA policy research reports are associated with significant price and volume reactions. Finally, we find sell-side analysts with access to WA issue superior stock recommendations on politically sensitive stocks. These effects are particularly acute during periods of high political uncertainty. Overall, we uncover a unique and an important conduit through which political information filters into asset prices.
This paper was accepted by David Sraer, finance.
Supplemental Material:
The data files and online appendix are available at
https://doi.org/10.1287/mnsc.2023.4919
.
Abstract
We study discrete‐time predictable forward processes when trading times do not coincide with performance evaluation times in a binomial tree model for the financial market. The key step in ...the construction of these processes is to solve a linear functional equation of higher order associated with the inverse problem driving the evolution of the predictable forward process. We provide sufficient conditions for the existence and uniqueness and an explicit construction of the predictable forward process under these conditions. Furthermore, we find that these processes are inherently myopic in the sense that optimal strategies do not make use of future model parameters even if these are known. Finally, we argue that predictable forward preferences are a viable framework to model human‐machine interactions occurring in automated trading or robo‐advising. For both applications, we determine an optimal interaction schedule of a human agent interacting infrequently with a machine that is in charge of trading.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In the framework of Islamic Sharia, those types of financial instruments can be used in the Islamic capital market that fully meet the criteria and rules of jurisprudence and are useful from an ...economic point of view. Jurisprudential standards mean the general and private jurisprudential standards of contracts. In the article "Analysis of the Nature and Function of Social Trading from the Point of View of Compliance with Sharia" it was stated that social trading due to having the conditions of correctness of contracts and being free from jurisprudential obstacles such as the unjust enrichment, uncertainty, loss and damage, gambling and usury is an irrevocable contract, and its provisions must be adhered to. Examining the economic function of these transactions according to micro and macroeconomic criteria also indicated that social trading, in addition to being in line with the diverse goals and attitudes of investors, are in line with economic growth and justice, and it can be used in the financial policies of government. These transactions affect the efficiency and liquidity of the market by increasing the amount of investment in the capital market, increasing total production, fair distribution of income, curbing inflation and attracting foreign capital that finally contribute to the economic growth. As a result, the correct use of this instrument in the capital market of Islamic countries is a great opportunity, which can help to improve its development. In this research, the possibility of adapting this instrument to the contracts approved by Islamic jurisprudence is investigated through the jurisprudential analysis method. The results indicate that these instruments can be used in Iran's capital market by using certain contracts such as ju’alah, advocacy and lease.
Using a large-scale Deep Learning approach applied to a high-frequency database containing billions of market quotes and transactions for US equities, we uncover nonparametric evidence for the ...existence of a universal and stationary relation between order flow history and the direction of price moves. The universal price formation model exhibits a remarkably stable out-of-sample accuracy across a wide range of stocks and time periods. Interestingly, these results also hold for stocks which are not part of the training sample, showing that the relations captured by the model are universal and not asset-specific.
The universal model-trained on data from all stocks-outperforms asset-specific models trained on time series of any given stock. This weighs in favor of pooling together financial data from various stocks, rather than designing asset- or sector-specific models, as is currently commonly done. Standard data normalizations based on volatility, price level or average spread, or partitioning the training data into sectors or categories such as large/small tick stocks, do not improve training results. On the other hand, inclusion of price and order flow history over many past observations improves forecast accuracy, indicating that there is path-dependence in price dynamics.
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BFBNIB, NUK, PILJ, SAZU, UL, UM, UPUK
The optimal mean-reverting portfolio (MRP) design problem is an important task for statistical arbitrage, also known as pairs trading, in the financial markets. The target of the problem is to ...construct a portfolio of the underlying assets (possibly with an asset selection target) that can exhibit a satisfactory mean reversion property and a desirable variance property. In this paper, the optimal MRP design problem is studied under an investment leverage constraint representing the total investment positions on the underlying assets. A general problem formulation is proposed by considering the design targets subject to a leverage constraint. To solve the problem, a unified optimization framework based on the successive convex approximation method is developed. The superior performance of the proposed formulation and the algorithms are verified through numerical simulations on both synthetic data and real market data.
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