To Trade Or Not To Trade: Cascading Waterfall Round Robin Rebalancing Mechanism for Cryptocurrencies

Ravi Kashyap
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Abstract

We have designed an innovative portfolio rebalancing mechanism termed the Cascading Waterfall Round Robin Mechanism. This algorithmic approach recommends an ideal size and number of trades for each asset during the periodic rebalancing process, factoring in the gas fee and slippage. The essence of the model we have created gives indications regarding whether trades should be made on individual assets depending on the uncertainty in the micro - asset level characteristics - and macro - aggregate market factors - environments. In the hyper-volatile crypto market, our approach to daily rebalancing will benefit from volatility. Price movements will cause our algorithm to buy assets that drop in prices and sell as they soar. In fact, the buying and selling happen only when certain boundaries are crossed in order to weed out any market noise and ensure sound trade execution. We have provided several numerical examples to illustrate the steps - including the calculation of several intermediate variables - of our rebalancing mechanism. The Algorithm we have developed can be easily applied outside blockchain to investment funds across all asset classes at any trading frequency and rebalancing duration. Shakespeare As A Crypto Trader: To Trade Or Not To Trade, that is the Question, Whether an Optimizer can Yield the Answer, Against the Spikes and Crashes of Markets Gone Wild, To Quench One's Thirst before Liquidity Runs Dry, Or Wait till the Tide of Momentum turns Mild.
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交易还是不交易?加密货币的级联瀑布循环再平衡机制
我们设计了一种创新的投资组合再平衡机制,称为级联瀑布循环机制(Cascading Waterfall Round Robin Mechanism)。在定期再平衡过程中,这种算法会为每种资产推荐理想的交易规模和数量,并将气体费和滑点考虑在内。我们所创建模型的本质是,根据微观(资产层面特征)和宏观(总体市场因素)环境的不确定性,就是否应该对单个资产进行交易给出指示。在波动剧烈的加密货币市场,我们的每日再平衡方法将从波动中获益。价格变动将促使我们的算法在资产价格下跌时买入,在资产价格上涨时卖出。事实上,只有在跨越某些界限时才会进行买卖,以剔除市场噪音,确保交易的稳健执行。我们提供了几个数字示例来说明我们的再平衡机制的步骤,包括几个中间变量的计算。我们开发的算法可以在区块链之外轻松地应用于所有资产类别的投资基金,并且可以适用于任何交易频率和再平衡持续时间。作为加密货币交易者的莎士比亚:是交易还是不交易,这是一个问题,一个优化器是否能给出答案,是在市场疯狂的暴涨和暴跌面前,在流动性枯竭之前饮鸩止渴,还是等待势头转缓。
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