Mind the gap: Tech-based dispute resolutions in global supply blockchains

Blockchain, a type of distributed ledger technology (DLT), can be used for supply chain and is commonly discussed among distribution giants and small players. Blockchain’s actual and perceived benefits, in addition to track-and-trace mandates from regulatory bodies, have driven these discussions. However, there is no mention of how existing dispute resolution processes have been overhauled in favor of blockchain smart contracts, which can be used to manage and resolve disputes. This conversation gap is critical as trust will erode if supply chain partners cannot settle disputes adequately. We highlight the importance of supply chain DLT management and suggest tactics for resolving the inevitable disputes that arise with disparate information. These guidelines, including adopting portable and enforceable contractual terms and a standardized dispute resolution process, can have practical applications beyond blockchain.     

Estimating Firm Behavior under Rationing: a Panel Data Study of the Chinese Manufacturing Industry

The purpose of this paper is to investigate the impacts of rationing on firm behavior. A virtual price approach is adopted to derive the rationed elasticities of variable input demands and output supply under a translog profit function. To illustrate the difference between the rationed and unrationed elasticities, we conduct an analysis using a firm-level annual survey data of China over the period 1985–88. Our estimation results indicate that the values of most elasticities would have been affected significantly if the government had imposed rationing on material inputs. The behavior of Chinese firms would have been seriously distorted in a complicated way. The firms would have over-responded to market signals in making some of their input or output decisions and, at the same time, might have under-reacted, or would have not changed their reaction, in making the other input or output decisions, under a rationing regime.     

资产价格泡沫的宏观调控:识别、传导和应对

以稳物价、促增长为传统目标的宏观政策要不要以及如何对资产价格泡沫进行调控,在理论上和实践上一直存在争议:第一,资本市场的高频联动、金融摩擦、投资者的认知偏差共同造成资产泡沫的根源、泡沫规模和发展规律在识别上都极端困难.第二,利率渠道、信贷渠道、风险承担渠道等传导机制对资产泡沫产生的影响错综复杂.本文从资产泡沫的识别和泡...     

SOME REMARKS ON ARBITRAGE AND PREFERENCES IN SECURITIES MARKET MODELS

We introduce the notion of a market-free-lunch that depends on the preferences of all agents participating in the market. In semimartingale models of securities markets, we characterize no arbitrage (NA) and no-free-lunch-with-vanishing-risk (NFLVR) in terms of the market-free-lunch and show that the difference between NA and NFLVR consists in the selection of the class of monotone, respectively monotone and continuous, utility functions that determines the absence of the market-free-lunch. We also provide a direct proof of the equivalence between the absence of a market-free-lunch, with respect to monotone concave preferences, and the existence of an equivalent (local/sigma) martingale measure.     

Cross-sectional determinants of New Zealand share market returns

We present evidence of the cross-sectional relation between security returns, beta, firm size and book-to-market ratio over the period 1971 to 1993 on the New Zealand sharemarket. Our results suggest that the NZSE-40 market index is not a mean-variance efficient market proxy—the betas calculated with respect to it being of little use for explaining expected returns cross-sectionally. Also, there is a significant positive relation between book-to-market ratio and average return.     

Deriving equity risk premium using dividend futures

In this paper I present a simple stock price decomposition model using the dividend discount model and dividend futures. The main contribution of this paper is the use of dividend futures which represent the risk-adjusted expectations of future dividends. This allows for the calculation of the implied equity risk premium and the decomposition of stock price movements into individual components. Due to the use of daily market data, this method can take into account the structural changes associated with falling interest rates and the Covid-19 pandemic. I empirically show the risk premium development of the S&P 500 Index and Euro Stoxx 50 Index in the last decade.     

企业与行业协会价格串谋行为分析与共同治理——基于不完全合作、非合作博弈的逻辑

本文建立了串谋企业及其行业协会、监管者之间的博弈分析模型.认为影响企业及其行业协会价格串谋概率高低的主要因素是制度安排、串谋成本与监管力度等.价格串谋的治理必定是各方利益主体在很大程度上实行内部治理和外部治理相结合的共同治理,内部治理关键在于理顺共同治理的关系,外部治理关键在于建立信任保障机制,而共同治理的基础是建立有效的信息网络系统.     

Distance and beyond: What drives financial flows to emerging economies?

A major theme in the empirical literature is whether country-specific ‘pull’ or external ‘push’ factors drive international capital flows. In this paper we show that pull-push interactions matter: the response of international investors to country-specific developments depends on global volatility/liquidity stress conditions. We model asset-trade behaviour of investors: with limited information, strong institutional quality ‘pulls’ asset demand; mounting tensions in global markets amplify portfolio adjustments. We derive an empirically testable equation for cross-border bank flows to emerging economies (EMEs) and focus on pull-push interactions that trigger financial vulnerabilities. We find that global volatility amplifies demand for institutional quality, prior to the recent crisis, implying that EMEs with weak institutional settings are exposed to sharp capital retrenchments. In the aftermath of the crisis, the liquidity easing in advanced economies drives down concerns for EMEs' developments, boosting flows and challenging EMEs' ability to use capital controls to mitigate unbridled flows.     

反馈型交易策略与资产价格演化

本文研究投资者的反馈型交易策略和学习机制是如何影响资产价格演化的.首先,运用Markov链方法刻画了反馈型投资者的信念更新机制;其次,运用演化博弈模型分析了正反馈及负反馈这两种交易策略在市场中的演化;最后,构建了市场由基本面投资者和反馈型投资者构成的风险资产价格演化模型,分析了基本面投资者的信息收集成本对其套利行为的影响.仿真结果表明,当基本面投资者的信息收集成本较大时,其套利行为受到限制,持续预期交易者在与基本面投资者的博弈中生存下来,并逐渐将基本面投资者和反转预期交易者赶出市场,使得资产价格持续偏离基本价值,持续预期交易者的财富逐渐增加,而基本面投资者的财富急剧减少.本文提出的模型为泡沫及反泡沫产生的原因提供了一种可能的解释,同时表明,市场监管部门应尽力减小投资者的信息收集成本,从而增强市场的有效性.     

Portfolio allocation and the investment horizon: a multiscaling approach

A new approach is proposed for analysing portfolio allocation over various time scales. This new approach is based on wavelet analysis, which decomposes a given time series on a scale-by-scale basis. Empirical results indicate that, as the investment horizon lengthens, a greater weighting should be allocated to stocks. An explanation for this result is that the mean-reverting property of stock returns causes investors to perceive that stocks are less risky than bonds and T-bills at longer time scales compared with shorter time scales. When we include the effect of risk aversion, it is found that the higher the risk aversion, the less the Sharpe ratio, indicating that a more conservative investor prefers a smoother consumption stream.