#yahoo finance AAPL

[ismdelhi01]

Courses On Stock Trading

Introduction to Stock Trading

The Introduction to Stock Trading course provides beginners with a comprehensive overview of the stock market and trading practices. Participants learn the fundamental concepts and terminology related to stocks and trading. The course covers topics such as how the stock market functions, the role of stock exchanges, and the different types of stocks available. Participants also gain insights into trading platforms and brokerage accounts, enabling them to navigate the trading process effectively.

Technical Analysis

The Technical Analysis course is designed to equip participants with the skills needed to analyze stock price charts and identify potential trading opportunities. Participants learn about various technical indicators, chart patterns, and trend analysis techniques. They understand how to interpret support and resistance levels, moving averages, oscillators, and other technical tools. By the end of the course, participants will be able to make informed trading decisions based on technical analysis.

Fundamental Analysis

The Fundamental Analysis course focuses on evaluating the financial health and performance of companies to make trading decisions. Participants learn how to analyze financial statements, including balance sheets, income statements, and cash flow statements. They also understand how to assess key financial ratios, industry trends, and competitive positioning. Additionally, the course explores the impact of macroeconomic factors and news events on stock prices, enabling participants to make more accurate predictions.

Options Trading

The "Options Trading" course introduces participants to the world of options and teaches them how to incorporate these instruments into their trading strategies. Participants learn about the various types of options, including calls and puts, and gain an understanding of options pricing models. The course covers options trading strategies, including basic options trades, spreads, and hedging techniques. Participants also learn about managing risk associated with options trading and maximizing profit potential.

Risk Management and Psychology

The Risk Management and Psychology course emphasizes the importance of managing risk and maintaining a disciplined mindset while trading. Participants learn about different risk management techniques, including position sizing, stop-loss orders, and diversification. The course also focuses on the psychological aspects of trading, such as understanding and controlling emotions, developing discipline, and maintaining a trading journal. By the end of the course, participants will have a solid understanding of how to manage risk effectively and cultivate the right mindset for successful trading.

Overall, these courses provide a comprehensive foundation in stock trading, covering essential topics such as market analysis, technical and fundamental analysis, options trading, risk management, and trading psychology. Participants will gain the knowledge and skills necessary to make informed trading decisions and manage risks effectively in the dynamic world of stock markets.

[livewalksite]

The Rise of AI in Mobile Technology: Apple Inc (AAPL)’s Latest Innovations - Yahoo Finance - https://live-walk.site/2024/11/the-rise-of-ai-in-mobile-technology-apple-inc-aapls-latest-innovations-yahoo-finance/

[the-guardian-time]

Apple's iPhone 16 launch event: What investors are watching

Apple’s (AAPL) iPhone 16 launch event — dubbed “It’s Glowtime” — will kick off this afternoon in Cupertino, California. Yahoo Finance Tech Editor Dan Howley joins Catalysts to discuss what investors and consumers can expect from the tech giant, including the next generation of Apple products to some hints about upcoming AI software rollouts. For more expert insight and the latest market action,…

[gkdhaka]

Stocks are at record highs. Investors keep playing the hits.

Stocks are trading at record highs, and the market’s main characters haven’t changed. Yahoo Finance’s data whiz Jared Blikre flagged the stocks making new record highs alongside the indexes on Friday. The names are a who’s who of market leaders with only one exception — Nvidia stock (NVDA) was down after receiving a downgrade from New Street Research. Apple (AAPL), Amazon (AMZN), Alphabet (GOOG,…

[news247worldpressposts]

#Breaking: The #DOJ calls out green messages from non- #iPhones in its antitrust suit against $AAPL

The DOJ calls out green messages from non-iPhones in its antitrust suit against $AAPL: "As a result, iPhone users perceive rival smartphones as being lower quality because the experience of messaging friends and family who do not own iPhones as worse." pic.twitter.com/tXqqFeXaUP — Yahoo Finance (@YahooFinance) March 21, 2024 Source: X

[ltpcalculator]

How do I find Swing stock?

To find information on "Swing stock," you can follow these steps:

Understand What "Swing Stock" Means: Before you start searching, it's important to clarify what you mean by "Swing stock." This term could refer to stocks of companies involved in the swing trading strategy, where traders aim to capture short- to medium-term gains by holding a stock for a period ranging from a few days to several weeks.

Use a Stock Market Research Platform: There are several online platforms where you can find information about stocks. Some popular ones include Yahoo Finance, Google Finance, Bloomberg, and CNBC. These platforms provide a wide range of information about stocks, including stock prices, historical performance, financial ratios, news, and analyst recommendations.

Enter the Ticker Symbol: If you have a specific company or stock in mind, you'll need to know its ticker symbol. This is a unique set of letters assigned to a stock for trading purposes. For example, the ticker symbol for Apple Inc. is AAPL. You can enter the ticker symbol into the search bar of the chosen stock market research platform to find information about that particular stock.

Analyze the Stock Information: Once you've found the stock you're interested in, you can analyze various aspects of it. This may include looking at its current price, historical price charts, trading volume, market capitalization, earnings reports, and news related to the company. You can also look at technical indicators and analyst opinions to help inform your decision.

Consider Using Trading Platforms: If you're interested in actually buying or selling stocks, you'll need to use a brokerage platform. There are many online brokerage platforms available, such as Robinhood, E*TRADE, TD Ameritrade, and Charles Schwab. These platforms allow you to trade stocks, ETFs, options, and other securities. You'll need to create an account, deposit funds, and then you can place trades for the stocks you're interested in.

Exercise Caution and Do Your Research: Investing in stocks carries risks, and it's important to do your own research and consider seeking advice from a financial advisor before making any investment decisions. Additionally, be wary of scams and fraudulent schemes, especially online.

By following these steps, you should be able to find information about "Swing stock" and make informed decisions about investing in stocks.

LTP Calculator Overview:                                    

LTP Calculator is a comprehensive stock market trading tool that focuses on providing real-time data, particularly the last traded price of various stocks. Its functionality extends beyond a conventional calculator, offering insights and analytics crucial for traders navigating the complexities of the stock market.

Also Available on Play store  -  App

https://play.google.com/store/apps/details?id=com.ltpcalculator.android/

Key Features:

Real-time Last Traded Price:

The core feature of LTP Calculator is its ability to provide users with the latest information on stock prices. This real-time data empowers traders to make timely decisions based on the most recent market movements.

User-Friendly Interface:

Designed with traders in mind, LTP Calculator boasts a user-friendly interface that simplifies complex market data. This accessibility ensures that both novice and experienced traders can leverage the tool effectively.

Analytical Tools:

Beyond basic price information, LTP Calculator incorporates analytical tools that help users assess market trends, volatility, and potential risks. This multifaceted approach enables traders to develop a comprehensive understanding of the stocks they are dealing with.

Customizable Alerts:

Recognizing the importance of staying informed, LTP Calculator allows users to set customizable alerts for specific stocks. This feature ensures that traders receive timely notifications about significant market movements affecting their portfolio.

Vinay Prakash Tiwari - The Visionary Founder:

At the helm of LTP Calculator is Vinay Prakash Tiwari, a renowned figure in the stock market training arena. With a moniker like "Investment Daddy," Tiwari has earned respect for his expertise and commitment to empowering individuals in the financial domain.

Professional Background:

Vinay Prakash Tiwari brings a wealth of experience to the table, having traversed the intricacies of the stock market for several decades. His journey as a stock market trainer has equipped him with insights into the challenges faced by traders, inspiring him to develop tools like LTP Calculator.

Philosophy and Approach:

Tiwari's approach to stock market training revolves around education, empowerment, and simplifying complexities. LTP Calculator reflects this philosophy, offering a tool that aligns with his vision of making stock market information accessible and understandable for all.

Educational Initiatives:

Apart from his contributions as a tool developer, Vinay Prakash Tiwari has actively engaged in educational initiatives. Through online courses, webinars, and seminars, he has shared his knowledge with aspiring traders, reinforcing his commitment to fostering financial literacy.

In conclusion, LTP Calculator stands as a testament to Vinay Prakash Tiwari's dedication to enhancing the trading experience. As the financial landscape continues to evolve, tools like LTP Calculator and visionaries like Tiwari sir play a pivotal role in shaping a more informed and empowered community of traders.

[kaygun]

Clojure/Python Interop Examples

Description of the problem

Today, I am going to write something that I have been playing around with, and found to be extremely useful and fun: deep clojure and python interop. This is done via libpython-clj. You may find the detailed documentation here. The library is but a small part of a large project called scicloj that aims to expand the use of clojure in data science.

The dependencies and the namespace

Let us start with the dependencies

{:deps {clj-python/libpython-clj {:mvn/version "2.024"}}}

Next, the namespace

(ns cl-py (:require [libpython-clj2.require :refer [require-python]] [libpython-clj2.python :refer [py. py.. py.-] :as py]))

and global imports.

(require-python '[numpy :as np]) (require-python '[pandas :as pd]) (require-python '[matplotlib.pyplot :as plt])

A Simple Visualization Example

Let me start with a simple matplotlib visualization example. I am going to use yfinance to use [Yahoo Finance API] to download the market data for a ticker then visualize it as a time-series. The data will be ingested as a pandas dataframe.

(py/from-import yfinance download) (plt/figure :figsize [12 4]) (-> (download "AAPL" :start "2012-01-01") (py/get-attr :Open) (py/call-attr :plot)) (plt/savefig "result.png")

#'cl-py/download Figure(1200x400) AxesSubplot(0.125,0.2;0.775x0.68)

A More Complicated Visualization

In the following example, I am going to pull passenger data from Istanbul Municipality Data Portal. The specific dataset is about number of passengers taking the sea-route in the year 2022. The columns are 'year', 'month', 'company', 'station' and 'passenger'. I am going to display the monthly sums in order.

(let [months ["jan" "feb" "mar" "apr" "may" "jun" "jul" "aug" "sep" "oct" "nov" "dec"] passengers (as-> "https://data.ibb.gov.tr/dataset/20f33ff0-1ab3-4378-9998-486e28242f48/resource/6fbdd928-8c37-43a4-8e6a-ba0fa7f767fb/download/istanbul-deniz-iskeleleri-yolcu-saylar.csv" $ (pd/read_csv $ :encoding "iso8859-15") (py/call-attr $ :to_numpy) (py/->jvm $) (filter (fn [x] (= (x 0) 2022)) $) ;; select year 2022 (map (fn [x] {(x 1) (x 4)}) $) ;; select month and passenger number (apply merge-with + $) ;; monthly sums (sort $) ;; sort wrt month (map #(% 1) $))] ;; get monthly counts only (plt/figure :figsize [12 6]) (plt/bar months passengers) (plt/savefig "passengers.png"))

An Image Processing Example

In our next example, I am going to work with the Olivetti Faces Dataset. I am going to compute the eigen-face of a given random person.

(py/from-import sklearn.datasets fetch_olivetti_faces) (py/from-import sklearn.decomposition PCA) (def faces (fetch_olivetti_faces :data_home "/home/kaygun/local/data/scikit_learn_data/")) (let [N (* 10 (rand-int 40)) X (-> faces (py/get-attr :data) (py/get-item (range N (+ N 10))) (py/call-attr :transpose)) Y (-> (PCA :n_components 1) (py/call-attr :fit_transform X) (py/call-attr :reshape [64 64]))] (plt/figure :figsize [4 4]) (plt/imshow Y :cmap "gray_r") (plt/savefig "eigen-face.png"))

#'cl-py/fetch_olivetti_faces #'cl-py/PCA #'cl-py/faces

A Decision Tree Model

In our next example, I am going to construct a Decision Tree Model using scikit-learn on the Iris dataset. First, I'll split the dataset into train and test datasets, and after I trained the model on the train set, I'll show the confusion matrix on the test dataset.

(py/from-import sklearn.datasets load_iris) (py/from-import sklearn.model_selection train_test_split) (py/from-import sklearn.tree DecisionTreeClassifier) (py/from-import sklearn.metrics confusion_matrix) (def iris (load_iris)) (let [X (py/get-attr iris :data) y (py/get-attr iris :target) [X-train X-test y-train y-test] (train_test_split X y :test_size 0.2) model (DecisionTreeClassifier)] (py/call-attr model :fit X-train y-train) (->> X-test (py/call-attr model :predict) (confusion_matrix y-test)))

#'cl-py/load_iris #'cl-py/train_test_split #'cl-py/DecisionTreeClassifier #'cl-py/confusion_matrix #'cl-py/iris [[ 9 0 0] [ 0 11 1] [ 0 1 8]]

A Support Vector Classifier

In our next example, I am going to write a support vector classifier using scikitlearn on the iris dataset.

(py/from-import sklearn.svm SVC) (let [X (py/get-attr iris :data) y (py/get-attr iris :target) [X-train X-test y-train y-test] (train_test_split X y :test_size 0.2) model (SVC :max_iter 1000)] (py/call-attr model :fit X-train y-train) (->> X-test (py/call-attr model :predict) (confusion_matrix y-test)))

#'cl-py/SVC [[ 8 0 0] [ 0 17 0] [ 0 0 5]]

[harbourfronttechnologies]

Algorithmic Trading System in Python, an Example

Developing an algorithmic trading system that consistently generates profits can be a challenging task, as it requires a deep understanding of financial markets, trading strategies, and risk management. To ensure your system is successful, you must consider the following elements: data collection, analysis, and backtesting. In this blog post, we will discuss each element in detail and provide you with the information needed to create an effective algorithmic trading system.

How to develop an algorithmic trading system

Here are some general steps you can follow to create an algorithmic trading system:

Define your trading objectives: Before you start building your trading system, it is important to clearly define your trading objectives. This may include your risk tolerance, investment horizon, and the types of financial instruments you want to trade.

Develop a trading strategy: Next, you will need to develop a trading strategy that outlines the specific rules and conditions for buying and selling financial instruments. This may involve analyzing market trends, identifying technical or fundamental indicators, or using statistical models to predict price movements.

Backtest your strategy: Once you have developed a trading strategy, it is important to backtest it to see how it would have performed in the past. This will allow you to evaluate the effectiveness of your strategy and make any necessary adjustments before implementing it in live trading.

Implement your strategy: Once you have tested and refined your trading strategy, you can implement it using an algorithmic trading platform. This may involve writing code to automate the execution of your trades based on your defined rules and conditions.

Monitor and optimize your system: After implementing your algorithmic trading system, it is important to monitor its performance and make any necessary adjustments to optimize its performance. This may involve adjusting your trading rules or risk management parameters or adding new indicators or data sources to improve the accuracy of your trades.

Example of a trading system in Python

Here is a basic example of Python code that could be used to trade the AAPL stock using the Yahoo Finance API. This code uses the Yahoo Finance API to download the daily price data for the AAPL stock and then sets a threshold for buying and selling based on the mean and standard deviation of the closing prices. It then loops through the data, executing trades based on the current position and the buy and sell thresholds. Finally, it prints the final profit.

import yfinance as yf

import pandas as pd

# Load the AAPL stock data from Yahoo Finance

aapl = yf.Ticker("AAPL").history(period="1d")

# Set the threshold for buying and selling

buy_threshold = aapl['Close'].mean() - aapl['Close'].std()

sell_threshold = aapl['Close'].mean() + aapl['Close'].std()

# Initialize variables to track the position and profit

position = 0

profit = 0

# Loop through the data and execute trades

for index, row in aapl.iterrows():

    if position == 0:

        # If there is no position, check if the price is below the buy threshold

        if row['Close'] < buy_threshold:

            # If it is, buy the stock and update the position

            position = 1

            buy_price = row['Close']

    elif position == 1:

        # If there is a position, check if the price is above the sell threshold

        if row['Close'] > sell_threshold:

            # If it is, sell the stock and update the position and profit

            position = 0

            profit += row['Close'] - buy_price

# Print the final profit

print(f"Profit: ${profit:.2f}")

Closing thoughts

Keep in mind that developing an algorithmic trading system that consistently generates profits is a complex process that requires a strong understanding of financial markets and trading strategies, as well as careful risk management. It is important to approach algorithmic trading with caution and seek professional guidance if you are not familiar with these concepts.

Post Source Here: Algorithmic Trading System in Python, an Example

from Harbourfront Technologies - Feed https://harbourfronts.com/algorithmic-trading-system-python-example/

[newzzwired]

Platform-Based Ecosystems: A Look At ROIIC

Platform-Based Ecosystems: A Look At ROIIC

Khanchit Khirisutchalual As the world emerges from Covid-19, it is interesting to observe Apple (AAPL) and Microsoft (MSFT) as outperformers (in terms of stock price) relative to large cap tech peers. Specifically, I compare against Google (GOOGL), Amazon (AMZN) and Meta (META), with the overarching logic being that they are all platform-based ecosystems. Yahoo FInance (Note: From best to…

[lakannada]

Stock market news live updates: Stocks tumble as earnings season picks up - Yahoo Finance

Stock market news live updates: Stocks tumble as earnings season picks up – Yahoo Finance

U.S. stocks fell sharply into the final hour of trading Monday following news Apple (AAPL) plans to slow hiring and curb spending next year to prepare for a possible recession.[Click here to read what’s moving markets on July 19, 2022] Bloomberg News reported Monday afternoon that the hiring slowdown and cuts to spending will take place across certain divisions and stem from a move to “be more…

[sscgovtjobs]

Actress turned entrepreneur, Jessica Alba's The Honest Company values at ~$1.4 billion

Actress turned entrepreneur, Jessica Alba’s The Honest Company values at ~$1.4 billion

The IPO values Honest at $1.44 billion.The company said late Tuesday that it sold 25.8 million shares at $16 each.Honest Company priced its initial public offering on Tuesday slightly above the midpoint of its indicated range, raising $412.8 million. An actress turned entrepreneur, Jessica Alba who has starred in movies such as “Fantastic Four,” included a letter to potential investors in the…

[valuentumbrian]

ALERT: Bull Raids, Short Squeezes and Highly Unusual Market Activity

We are putting short investors on high alert!

By Brian Nelson, CFA

In late 2018, Valuentum published Value Trap, a book that warned to all that would heed its warning that a collapse in the traditional quant value factor was coming and that excessive volatility in the markets caused by price-agnostic trading--or those that aren’t paying attention to fair value estimate calculations--would only build and build to eventually reach extreme and irrational levels. The book, while hugely successful winning award after award, was largely ignored by the media, despite our best efforts to get the word out. Now, the chickens are coming home to roost.

Image Shown: The book Value Trap warned about the impending collapse of the value factor, and during 2020, the value factor registered its worst performance in history. We continue to believe large cap growth is underpriced. Image Source: Bloomberg.

As you are aware (and probably tired of hearing by now), the “value factor” had its worst showing in history during 2020, as predicted, and while broader market indices continue to reflect somewhat reasonable levels of volatility (following the excessive levels during the COVID-19 crash), we’re now starting to see the type of volatility on individual names that we think will only grow in number to eventually become large enough to impact broader market indices in time. Our “Call to Action” in Value Trap remains, and we encourage regulators to promote the application of active management (and enterprise valuation) via policy regulations that limit dangerous vehicles in a bid to ensure market integrity and stability for posterity. Indexing is a wolf in sheep’s clothing, and its bite will leave deep scars in the financial system if not curbed.

To the layman, if you’re a believer in climate change and how this generation is harming the future, it’s far worse what is happening in finance today. Pollution is everywhere. With just ~10% of all trading based on discretionary fundamental fair value analysis, with indexing and quant trading increasing (momentum and trend following algorithms), with mis-education at all-time highs given the documented failures of perceived “truths” in quant finance, future generations may be left with a complete and absolute mess of a financial and market system if we don’t get back to enterprise valuation. Instructors: Teach your students well – teach them enterprise valuation. Make Value Trap required reading.

Gordon Gekko is wrong: Greed is not good. Brokers selling index funds pointing to failed modern portfolio theory as justification and quants running sophisticated algorithms based on short-cut multiple analysis and impractical data will only grow to be a recipe for disaster. Were it not for the swift action of the Fed/Treasury during the depths of the COVID-19 crisis, the financial system would have already witnessed its doom. Many stocks in indexes would have gone to zero, driving underperformance of traditional indexes relative to active management of mammoth proportions, all but securing the demise of Bogle’s folly. Far too many investors are not paying attention to the intrinsic worth of their assets--and counting on the Fed/Treasury to bail out indexers (not active managers) time and time again with tax-payer money is no plan for longevity. Indexing is not free or inexpensive; it has cost the tax payers hundreds of billions, maybe trillions.

We witnessed but a glimpse of irrational market activity and extreme levels of volatility earlier this year. On March 25, 2020, the SEC halted trading in shares of Zoom Technologies (ZOOM) because many were confusing its ticker symbol with a similarly named NASDAQ-listed company, Zoom Video Communications (ZM). More recently, a January 7th tweet by Tesla CEO Elon Musk saying nothing more than “Use Signal” sent shares of the stock Signal Advance (SIGL) over 400%+ higher. The only problem is that Musk was talking about a messaging app called Signal that rivals Facebook’s (FB) Messenger and Apple’s (AAPL) messaging service, not the company listed under the ticker SIGL. Traders may have been engaging in pump-and-dump schemes using misinformation as the tool, as Signal Advance now trades for ~$5.50, down from its irrational high of ~$38 per share.

Image Shown: Shares of Signal Advance (SIGL), a company that uses signal technologies in biomedicine and other areas, shot up aggressively on a tweet from Elon Musk saying to use a completely unrelated messaging app called Signal. Image Source: Yahoo, Twitter.

These are not one-off events. In the early months of 2020, irrational speculation also reached a precipice in the stocks of bankrupt and near-bankrupt companies, as speculators in the popular Robinhood app whipsawed prices of Hertz (HTZ), Whiting Petroleum (WLL), GNC (GNC), and Chesapeake Energy (CHKAQ) around. On June 8, 2020, for example, Hertz’s and Whiting Petroleum’s shares, while still lower significantly on the year, closed approximately 10-fold higher from prices around the time of their respective bankruptcy filings during this mania.

Then there was Hong-Kong listed ArtGo Holdings. The marble-stone miner’s share price ran up 3,800%, nearly 40-fold, during 2019, with the majority coming on news that MSCI would add the stock to its suite of indexes. However, just a couple weeks after the announcement, on November 21, 2019, MSCI pulled a U-turn, saying it would not add the stock to its indexes. The news sent shares of ArtGo Holdings tumbling 98% that Thursday morning, wiping clean an incredible $5.7 billion of market value. The markets are showing signs that the price-discovery mechanism is breaking down, and indexing is not an innocent bystander.

Image Shown: Shares of GameStop have been on an irrationally wild ride recently driven by what looks to have been an orchestrated and highly unethical (and perhaps illegal) short squeeze on the stock. According to some reports, during the pre-market session January 25, GameStop’s shares were up ~80%, and turned red during the trading session, with no fundamental news.

Recent “bull raids,” or aggressive and orchestrated “short squeezes” on stocks, have been the most prominent evidence of excessive volatility and irrational market behavior driven by Reddit WallStreetBets users and Robinhood traders, only exacerbated by price-agnostic trading from traditional quant algorithms. With a short interest of ~150%, GameStop’s (GME) shares, for example, went from a 52-week low of $2.57 in March 2020 to a 52-week high of $159.18 in January, and are now trading at ~$70-$80 per share at the time of this writing--still far above what may be considered to be a fair value estimate of the equity.

There are other instances, too. Other heavily shorted stocks including Express (EXPR), Macerich (MAC), Bed Bath & Beyond (BBBY), and AMC Entertainment (AMC) have been tools of trading madness in recent weeks. At the time of this writing, Express’ shares are up over 90%, Macerich’s are up 16%, Bed Bath & Beyond are up over 8%, and AMC’s are up over 28% -- all on no news other than they are companies with heavy short interest. As with the “fad” of investing in bankrupt companies earlier in 2020, it seems like the trading sharks are circling heavily-shorted names to drive aggressive short-squeezes, often in conjunction with the application of deep out of the money call options.

We’re paying close attention to these dynamics as we monitor our short idea considerations in the Exclusive publication. We’ve put up some tremendous success rates when it comes to short ideas—through October 2020, the success rate for short idea considerations was 92.3% over 52 ideas spanning 52 months--but we’re writing today in part to put our readers on high alert when it comes to short investing. Though we still like our latest two short idea considerations, DoorDash (DASH) and Palantir (PLTR), they have moved against us since we highlighted them. Palantir was up 25% on nothing more than news of a Demo Day. Our thesis on these ideas hasn’t changed, but the market’s behavior certainly has. For short investors, caution is the order of today.

Concluding Thoughts    

We believe a fair value estimate on the S&P 500 (SPY) is 3,530-3,920, and with the S&P 500 trading at ~3,825 at the time of this writing, the markets are fairly valued based on common-sense metrics. You can read about how we value the market in our 2020 recap here. We maintain our view that the areas of big cap tech, large cap growth, and the NASDAQ are attractive, and we continue to point to Facebook (FB) and Alphabet (GOOG) as two of the most undervalued stocks on the market. Large cap growth (SCHG) has outperformed small cap value (IWN) roughly 60 percentage points since the beginning of 2019, or about the time that Value Trap was published. Best Ideas Newsletter holding Korn/Ferry (KFY) is one of the biggest fundamental mispricings we see at the moment.

That said, even though markets are fairly priced and we think certain areas offer bargains, systemic risks are increasing as price-agnostic trading in the likes of quant and indexing has now been augmented by trading from Reddit platforms such as WallStreetBets and Robinhood traders looking to make a big score in the market. We’re still playing it cool, and nothing should be surprising to our readers. We called almost every step of the way in 2020, and extreme and irrational levels of volatility are the next chapter in the book Value Trap. The markets won’t get completely out of whack for years yet, however, and we hope Value Trap, in raising awareness of the pitfalls of the ways of indexing and quant investors, will make it so the path to financial destruction will never materialize.

We’re available for any questions.

Most Shorted Stocks, short interest as a % of float: GME, FIZZ, DDS, MAC, BBBY, LGND, AMCX, SRG, GOGO, SPWR, AXDX

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Valuentum members have access to our 16-page stock reports, Valuentum Buying Index ratings, Dividend Cushion ratios, fair value estimates and ranges, dividend reports and more. Not a member? Subscribe today. The first 14 days are free.

Brian Nelson owns the SPY, SCHG, DIA, QQQ, VOT, and IWM. Some of the other companies written about in this article may be included in Valuentum's simulated newsletter portfolios. Contact Valuentum for more information about its editorial policies.

[extreme-investor-network]

Stock futures rise as Wall Street heads for winning week

U.S. stock futures resumed gains early Friday after a rally fueled by lighter-than-expected inflation data this week temporarily hit a lull in the previous trading session. Contracts on the S&P 500 climbed 0.4%, with the benchmark index on pace for a fourth straight winning week. Futures tied to the Dow Jones Industrial Average added 100 points or roughly 0.3%. Futures on the technology-heavy Nasdaq composite advanced 0.4%. Electric-vehicle maker Rivian Automotive (RIVN) was on watch after the company on Thursday reported a wider-than-expected loss for the second quarter but maintained its production outlook for the rest of the year. Shares edged 2% higher in pre-market trading after initially stumbling following the results. Apple (AAPL) shares ticked up following a Bloomberg News report that indicated the tech giant expects to sustain iPhone sales in 2022 despite a market slowdown. The company projects it will assemble roughly 220 million iPhones in total this year, per Bloomberg, which cited people familiar with the matter. Apple’s sales and production expectations are typically a closely-guarded secret. An employee arranges Apple iPhones as customers shop at the Apple Store on 5th Avenue shortly after new products went on sale in Manhattan, in New York City, New York, U.S., March 18, 2022. REUTERS/Mike Segar Economic data in recent days has reassured investors that inflationary pressures are beginning to cool across the economy after climbing at a steady pace since early 2021. The producer price index (PPI) on Thursday showed prices fell 0.5% from the prior month compared to expectations of a 0.2% increase. On Wednesday, the consumer price index (CPI) showed prices stayed flat over the month and rose a less-than-expected 8.5% annually. “The fact we're starting to see energy prices come down, that might be a sign of what is more to come for other inflation indicators,” iCapital Network Chief Investment Strategist Anastasia Amoroso told Yahoo Finance Live. “We’re starting to chip away at this inflation issue, and that's a big catalyst for the markets.” CPI data on Wednesday showed the gasoline index fell 7.7% month-over-month in July – the largest drop since April 2020 – as gas prices fall over the past 59 days to dip below $4 a gallon for the first time since March on Thursday, data from AAA showed. Investors have more data on the docket Friday, with import prices due out at 8:30 a.m. ET. and the University of Michigan’s consumer sentiment survey set for release at 10:00 a.m. ET. Original Article Original Article Here: Read the full article

[high-tech-news]

The real cost of buying a new iPhone - Quartz

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Quartz

The real cost of buying a new iPhone Quartz So you've decided to pick up one of Apple's new smartphones—congratulations! They're really quite nice. But are you going to buy just that iPhone? Unless you're completely ornery (like me) or you never drop things, you're probably going to want a case. Apple is selling refurbished iPhone 8 smartphones for $500, and it's an amazing deal (AAPL)Yahoo Finance The iPhone's golden age is over, Apple will only charge fans moreWired.co.uk Apple iPhone 6S Plus vs iPhone 7 Plus: What is the distinction and may I improve?Infosurhoy Yahoo Singapore News -Motley Fool -Along the Boards -Markets Morning all 15 news articles »

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Is Apple stock a great buy on weakness?

Is Apple stock a great buy on weakness?

Apple’s stock (AAPL) looks like a good buy on weakness, argues one strategist. “We actually bought Apple over the last couple of weeks. I mean the name has come down tremendously. So I think you can go in and buy that name. They have such a strong balance sheet and they have a tremendous cash position,” said Crossmark Global Investments chief markets strategist Victoria Fernandez on Yahoo Finance…