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大家好，我是Le Chiffre。上一篇中采用美cpi，和美联储资产负债表等宏观数据对BTC价格进行初步研究，今天，继续使用宏观数据，美tips和ism制造业指数进行相关统计研究。
Hi, I'm Le Chiffre. Preliminary BTC prices were studied in the previous article using macro-data such as UScpi and the Federal Reserve balance sheet. Today, macro-data continue to be used to conduct relevant statistical studies, such as the Metips and Ism Manufacturing Index.
我们先来看tips10与btc相关定性与定量可视化，如下图所示：
We first look at the qualitative and quantitative visualization of tips10 in relation to btc, as shown in the figure below:
上面这幅图是从2020年1月15日开始，tips10（橙色线）与btc（蓝色线）价格的日频图，从图上我们可以看到，
The above graph starts on January 15, 2020 and shows the daily frequency of the prices of tips10 (Orange Line) and btc (Blue Line).
2020-2021年11月左右tips10与btc整体来看呈现反向关系，我们将上面图分拆子图来看，如下图所示：
In November 2020-2021 and around November 2021, tips10 and btc as a whole showed a reverse relationship, and we looked at the above diagrams as broken down into sub-charts, as shown below:
而这阶段的相关性达到了-0.45，如下图所示：
The relevance of this phase has reached -0.45, as shown in the figure below:
2021年11月-2022年7月左右，tips10开始上涨，btc价格开始下行。
In November 2021 and around July 2022, tips10 began to rise and btc prices began to decline.
而这一阶段的相关系数为-0.89，如下图所示：
The relevant coefficient for this period is -0.89, as shown in the figure below:
2022年7月-2023年5月左右，tips10区间震荡，btc价格整体震荡向上。
In July 2022 and around May 2023, there was a tips10 tremor, with an overall btc price shock upwards.
而这一阶段的相关系数为-0.22，如下图所示：
The relevant coefficient for this period is -0.22, as shown in the figure below:
2023年5月—2023年10月上旬，tips上行，btc价格上下震荡，如下图所示：
May 2023 - early October 2023, tips up, btc prices up and down, as shown in the figure below:
而这一阶段的相关系数为-0.31，如下图所示：
The relevant factor for this period is -0.31, as shown in the figure below:
2023年10月10日—2024年1月初，tips整体下行，btc价格整体上行，如下图所示：
10 October 2023 - early January 2024, tips down as a whole and btc prices up as follows:
而这一阶段的相关系数为-0.84，如下图所示：
The relevant factor for this period is -0.84, as shown in the figure below:
2021年11月-2022年7月
TIPS10指数上涨，BTC价格下行。
TIPS10 index rises and BTC prices go down.
相关系数为-0.89，表明在这个时间段内，TIPS10和BTC价格呈强烈的负相关关系，即TIPS10上涨时，BTC价格更有可能下行。
The correlation factor of -0.89 indicates a strong negative correlation between TIPS10 and BTC prices during this period, i.e., the BTC prices are more likely to fall down when TIPS10 rises.
2022年7月-2023年5月
TIPS10区间震荡，BTC价格整体震荡向上。
TIPS10 tremors, with BTC prices as a whole upwards.
相关系数为-0.22，表明在这个时间段内，TIPS10和BTC价格的负相关关系减弱，两者之间的关系更为弱化。
The correlation factor of -0.22 indicates a weaker relationship between TPS10 and BTC prices during this period.
2023年5月—2023年10月上旬
TIPS上行，BTC价格上下震荡。
TIPS up and down, BTC prices.
相关系数为-0.31，表明在这个时间段内，TIPS和BTC价格之间的负相关关系再次减弱，相关性变得较低。
The correlation factor is -0.31, which indicates that the negative correlation between TPS and BTC prices has weakened again during this period and has become less relevant.
2023年10月10日—2024年1月初：
10 October 2023 - early January 2024:
TIPS整体下行，BTC价格整体上行。
TIPS lines down as a whole and BTC prices up as a whole.
相关系数为-0.84，表明在这个时间段内，TIPS和BTC价格再次呈现较强的负相关关系，即TIPS下行时，BTC价格更有可能上行。
The correlation factor of -0.84 indicates that the TPS and BTC prices again show a stronger negative correlation during this period, i.e., that BTC prices are more likely to go up when TIPs are down.
在不同的时间段内，TIPS10和BTC价格之间的相关关系经历了变化。总体趋势是，它们之间的负相关性在特定时间段内加强，然后在另一些时间段内减弱。
The relationship between TIPS10 and BTC prices has changed over different time periods. The overall trend is that the negative correlation between them increases over a given time period and then decreases over other time periods.
负相关系数表明在某些时期，TIPS10和BTC价格呈现出相反的趋势，而在另一些时期，它们的趋势可能较为一致或关系较弱。这可能受到不同时间段内宏观经济、市场因素的影响。
Negative correlation coefficients indicate that TIPS10 and BTC prices show the opposite trend in some periods, while in others they may be more consistent or less correlated. This may be influenced by macroeconomic and market factors over different time periods.
接下来，我们看一下先行性关系，如下图所示：
Next, we look at pre-existing relationships, as shown in the figure below:
下面我们将数据平滑一下，取30、60、90、120、150日均线，以及错开周期计算先行性等相关系数，如下图所示：
The following is a smoothing of the data by taking such factors as the average of 30, 60, 90, 120 and 150 days, as well as factors related to staggering the calculation of forwardness, as shown in the figure below:
从上述数据我们可以看到，当平滑周期越大，先行性周期越大，负向相关性越大。
From the above data, we can see that when the smoother cycle is larger, the larger the first cycle, the more relevant the negative direction.
下面我们来看一下ism制造业指数数据的情况，
Now let's look at the manufacturing index data for Ism.
时间周期：2017年9月1日—2023年12月1日
Period: 1 September 2017-1 December 2023
通过可视化定型观察，大体趋势上貌似ism制造业指数对btc价格具有一定的先行性关系。
Through visualization stereotypes, the general trend appears to be that the Ism manufacturing index has a certain priori relationship to the btc price.
下面我们直接看一下相关系数，如下图所示：
Here we will look directly at the correlation coefficient, as shown in the figure below:
但是从定量来看，好像相关性也就那样。这块先不做深入相关性处理，放到后面我们做回归分析的时候，纳入到显著性、回归系数和判定系数。
But quantitatively, it's as if it's relevant as well. This piece is not dealt with in depth, but then, when we do the regression analysis, we include the highlights, the regression factor and the determination factor.
今天我们的内容就到这里，美东时间2024年1月10日下午，美SEC官宣批准现货比特币ETF的上市和交易。至此，btc完全可以视为一种金融资产进行分析和研究，那么首当其冲除了自身基本面，那么就是宏观数据的驱动+构建的相关信号验证机制，这就变为了与传统金融分析工具基本类似了。所以，我们采用宏观数据因子分析，这条路肯定是有用的，它的用处就是为我们提供和指明大的方向。
And here we are today, on the afternoon of January 10, 2024, USSEC officials declared their approval of the listing and trading of the spot bitcoin ETF. So, btc can well be seen as a financial asset for analysis and study, first of all, except for its own fundamentals, which is the associated signal validation mechanism for macrodata-driven plus construction, which is basically similar to the traditional financial analysis tools. So, using macrodata factors, this path is certainly useful, and its purpose is to provide and give us a big direction.
有的人会说，股票和期货都不行，这个就行？每个资产他对宏观敏感度是不一样的，权益最慢，最外圈敏感的是外汇和债券，尤其债券是对宏观数据最为敏感资产之一，而数字货币比债券更为敏感。返回搜狐，查看更多
Some people would say that neither stocks nor futures are good enough. Each asset is different in macro sensitivity, slow in interest, foreign exchange and bonds, especially when they are one of the most sensitive macro-data assets, and digital currencies are more sensitive than bonds. 责任编辑：
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