**The easiest way to invest for lazy people**！

**automatic investment plan**Once and for all ？ Of course not. , Which tough guy can resist the heartache that the fixed investment income drops bit by bit ？

see , Recently, the stock market has gone down sharply , So many funders started “ The winner is Mr. Cai , If you lose, it's CAI ” . Many 12 month ,1 Students who just started to cast their ballots in June , The withdrawal of holding fund may exceed the income of years ago . therefore , We need to target revenue at the right stop .

My friends in the group who invest in fixed funds summed up their common ** There are four ways **** Profit strategy **, And use **P****ython visualization ** To realize the fixed investment and stop profit of the fund , I tried , The effect is very good .

The commonly used valuation indexes are p / E ratio and P / B ratio . This paper takes p / E ratio as an example , It refers to the ratio of the total market value of the index component to the total profit . Generally speaking, it is calculated according to the total profit of that year , How many years does it take for the investment to recover its cost . We can compare the historical level of the index , To measure whether an index is overvalued or undervalued .

Here's the Fund ** E Fonda Shanghai and Shenzhen 300ETF join ** For example , The fund is corresponding to Shanghai and Shenzhen 300 Index . We use crawlers or directly copy the web page to obtain Shanghai and Shenzhen 300 The history of the index PE data .

After data acquisition , We take advantage of **matplotlib** drawing , You can get Shanghai and Shenzhen 300 The historical P / E trend of the index .

`plt.figure(dpi=100)`

plt.plot(df["pe"],c="r",ls="--")

a = list(range(1,516,256))

plt.xticks(a,[df["ts"][i] for i in a])

plt.axhline(y=float(line_value_30),c="g",ls="--",lw=2)

plt.axhline(y=float(line_value_median),c="y",ls="--",lw=2)

plt.axhline(y=float(line_value_70),c="b",ls="--",lw=2)

plt.show()

（ Green in the picture 、 yellow 、 The three blue lines represent 30 Quantile value 、 The median and 70 Quantile value .

When the index exceeds 70 Quantile value , Consider continuing to hold Or reduce the position appropriately . When the index is below 30 Quantile value , Consider continuing to buy or keep a fixed investment .

However, according to the valuation strategy to sell also has disadvantages ： One is that the holding time is too long , Second, is it suitable for all industries to sell by valuation method , It's not suitable for those whose performance growth is slowing down or negative .）

The above is what we use ** Python visualization ** Intuitively show the valuation of the current index fund . It's just using Python Let me show you the charm of data analysis , We can actually do it in the future

**Deep data mining and fund stock quantification**！ and ,

**In fact, data analysis is not only about getting data , Store the data , Also need to be able to preprocess the data , extract , Then analysis , Statistics , Report and other operations .**

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