Profitability and Data-Snooping Tests of Four Technical Trade Strategies for Cryptocurrency Pair BTC/USDT and ETH/USDT in Cryptocurrency Markets During 2022–2023

We provide a comprehensive investigation into the profitability of technical trading methods applied to the cryptocurrency pairs BTC/USDT and ETH/USDT. By employing rigorous evaluations and incremental examinations, we address the pervasive issue of data-snooping bias that often plagues the evaluation of trading strategies. Our empirical results indicate the lack of profitable technical trading strategies in both the analysis sample and prediction sample periods, even after rigorous adjustments for data snooping. These findings highlight the difficulties associated with selecting profitable technical trading strategies in the dynamic and volatile cryptocurrency market. Market participants, including individual traders, institutional investors, and regulatory bodies, should take note of our findings when making investment decisions based on technical analysis

A dynamic model of house price

In this paper, we build the rationale of the financial intermediate's decision of making loans to potential home buyers over an infinite time horizon. In the first period "good" borrowers with stable future income flows receive loans and buy homes. In later periods, the intermediate securitizes the loans to raise new capital and makes loans to some of the "bad" borrowers with uncertain future income flows. Currently, we simplify the securitization as a tool to raise capital without cost over time. This unrealistic simplification should be improved in later work. The financial intermediate calculates the expected payoffs in different scenarios under the realizations of uncertainty to decide whether to make loans to a new borrower and whether to liquidate a house if the owner is short of liquidity in the short run. After clarifying the sequence of moves of different agents within each period, we compute the financial intermediate's decision rule described by a Bellman equation. Then we simulate borrowers' income realization and produce a figure of house price as well as value function over time

A dynamic model of house price

In this paper, we build the rationale of the financial intermediate's decision of making loans to potential home buyers over an infinite time horizon. In the first period "good" borrowers with stable future income flows receive loans and buy homes. In later periods, the intermediate securitizes the loans to raise new capital and makes loans to some of the "bad" borrowers with uncertain future income flows. Currently, we simplify the securitization as a tool to raise capital without cost over time. This unrealistic simplification should be improved in later work. The financial intermediate calculates the expected payoffs in different scenarios under the realizations of uncertainty to decide whether to make loans to a new borrower and whether to liquidate a house if the owner is short of liquidity in the short run. After clarifying the sequence of moves of different agents within each period, we compute the financial intermediate's decision rule described by a Bellman equation. Then we simulate borrowers' income realization and produce a figure of house price as well as value function over time

Proton Ion Exchange Reaction in Li3 IrO4 : A Way to New H3+ x IrO4 Phases Electrochemically Active in Both Aqueous and Nonaqueous Electrolytes

Progress over the past decade in Li‐insertion compounds has led to a new class of Li‐rich layered oxide electrodes cumulating both cationic and anionic redox processes. Pertaining to this new class of materials are the Li/Na iridate phases, which present a rich crystal chemistry. This work reports on a new protonic iridate phase H3+xIrO4 having a layered structure obtained by room temperature acid‐leaching of Li3IrO4. This new phase shows reversible charge storage properties of 1.5 e− per Ir atom with high rate capabilities in both nonaqueous (vs Li+/Li) and aqueous (vs capacitive carbon) media. It is demonstrated that Li‐insertion in carbonate LiPF6‐based electrolyte occurs through a classical reduction process (Ir5+ ↔ Ir3+), which is accompanied by a well‐defined structural transition. In concentrated H2SO4 electrolyte, this work provides evidence that the overall capacity of 1.7 H+ per Ir results from two additive redox processes with the low potential one showing ohmic limitations. Altogether, the room temperature protonation approach, which can be generalized to various Li‐rich phases containing either 3d, 4d or 5d metals, offers great opportunities for the judicious design of attractive electrode materials

Quantitative spray analysis of diesel fuel and its emulsions using digital image processing

In the present work, an experimental investigation of spray atomization of different liquids has been carried out. An air-assist atomizer operating at low injection pressures valued (4 and 6 bar) has been used to generate sprays of (diesel fuel, 5, 10, and 15% water-emulsified-diesel), respectively. A Photron-SA4 high speed camera has been used for spray imaging at 2000 fps. 20 time intervals (from 5 to 100 ms with 5 ms time difference) are selected for analysis and comparison. Spray macroscopic characteristics (spray penetration, dispersion, cone angle, axial and dispersion velocities) have been extracted by a proposed technique based on image processing using Matlab, where the maximum and minimum (horizontal and vertical) boundaries of the spray are detected, from which the macroscopic spray characteristics are evaluated. The maximum error of this technique is (1.5% for diesel spray) and a little bit higher for its emulsions

Essays on Chinese Corporate Issuers and Financial Markets

The first two chapters of my dissertation study the US-listed reverse merger firms. In the past decade, a growing number of foreign firms were listed in the United States through reverse merger, a non-IPO listing technique that requires less information disclosure. Using a hand-collected data set of US-listed Chinese firms, this paper answers three questions. First, are the foreign firms still of quality as the bonding theory suggests? No, I find widespread delistings in these firms and lawsuits related to their misconduct. Second, why do the bad firms list? I find that the firms’ directors profit from fast stock sales after listing. Moreover, these firms tend to be US-incorporated reverse mergers that are headquartered in small cities, are audited by small firms, and that change their auditors frequently. Third, how did they learn this technique? Using a social network analysis, I find that the firms are assisted by professionals to help them circumvent the US regulations. Further, I find that the social network of the linked directors facilitates the spread of their misconduct. During the wrongdoers’ listings, the investors in these firms lost at least $811 million. However, the penalties imposed on the wrongdoers only accounted for 4.19% of this loss. In the third chapter, I apply a rule-based textual analysis in the Chinese market to study how the textual information in the news and analyst reports affect the stock return. According to the literature, the market does not underreact to the public news, but the textual information in the analyst reports is not incorporated into the market price immediately in the US, where the analyst reports are not freely public. It remains unknown whether the analyst reports’ text information affects stock return instantly when it becomes freely public. Using a unique Chinese dataset of free and public analyst reports and applying the rule-based textual parsing technique, this chapter investigates the relationship between the abnormal stock return and the corresponding financial news and analyst reports. I find strong evidence that the textual information in the news affects the adjusted overnight return quickly after the news release and there is no effect after. It takes longer for the textual information in the analyst reports to affect the abnormal return; the reports do have significant predictability on a four-week horizon, but not immediately after the report release. The simulation shows that utilizing the market underreaction is a profitable trading strategy. I therefore reject the hypothesis that the underreaction to the analyst reports is because they are not public

A dynamic model of house price

In this paper, we build the rationale of the financial intermediate's decision of making loans to potential home buyers over an infinite time horizon. In the first period "good" borrowers with stable future income flows receive loans and buy homes. In later periods, the intermediate securitizes the loans to raise new capital and makes loans to some of the "bad" borrowers with uncertain future income flows. Currently, we simplify the securitization as a tool to raise capital without cost over time. This unrealistic simplification should be improved in later work. The financial intermediate calculates the expected payoffs in different scenarios under the realizations of uncertainty to decide whether to make loans to a new borrower and whether to liquidate a house if the owner is short of liquidity in the short run. After clarifying the sequence of moves of different agents within each period, we compute the financial intermediate's decision rule described by a Bellman equation. Then we simulate borrowers' income realization and produce a figure of house price as well as value function over time.Real estate market, house price, securitization, mortgage-backed securities, bubble, dynamic forward looking model

Stock Market, Economic Performance, and Presidential Elections

Using stock market and economic data from 1900 to 2008 from 27 separate presidential administrations in the United States (U.S.), including 15 Republican and 12 Democratic, this paper examines the relationships between the market return after each Election Day and economic performance during the presidential term. Using the theoretical framework of political economy , the authors examine how Wall Street’s reaction to a presidential election acts as a predictive measure of future economic performance.The analysis shows that the after election market movement has progressively been more accurate in predicting the future Gross Domestic Product (GDP) growth but not the future unemployment rates. Given that the results show a higher correlation over time, the model appears to provide a good starting point for judging the economic potential of future presidential administrations

Stock Market, Economic Performance, and Presidential Elections

Using stock market and economic data from 1900 to 2008 from 27 separate presidential administrations in the United States (U.S.), including 15 Republican and 12 Democratic, this paper examines the relationships between the market return after each Election Day and economic performance during the presidential term. Using the theoretical framework of political economy , the authors examine how Wall Street’s reaction to a presidential election acts as a predictive measure of future economic performance.The analysis shows that the after election market movement has progressively been more accurate in predicting the future Gross Domestic Product (GDP) growth but not the future unemployment rates. Given that the results show a higher correlation over time, the model appears to provide a good starting point for judging the economic potential of future presidential administrations