This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is RBA Stock Expected to Go Up?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

RBA:TSX Ritchie Bros. Auctioneers Incorporated

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The yield on Australia 10Y Bond Yield rose to 4.38% on July 14, 2025, marking a 0.05 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.13 points and is 0.04 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Australia 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

Ritchie Bros Auctioneers reported CAD27.62B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Ritchie Bros Auctioneers | RBA - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Liabilities:
:Capital and Reserve Bank Reserve Fund-C/ whereby the Reserve Bank Reserve Fund (RBRF) is a general reserve. RBRF provides for potential losses arising from events which are contingent and non-foreseeable, mainly those which arise from movements in market values of the RBA-C/s holdings of Australian dollar and foreign securities as well as from fraud and other non- insured losses or events. On 1 July 2001 the amount of $3 323 million (Contingencies and General Purpose Reserve) was transferred from :Other liabilities-C/ to :Capital and Reserve Bank Reserve Fund-C/.

Prior to July 1996 the series :Exchange settlement balances-C/ primarily reflected deposits of Australian banks, comprising non-callable deposits and, prior to September 1988, Statutory Reserve Deposits and deposits by savings banks. The Statutory Reserve Deposit requirement on trading banks was removed in 1988 and the non-callable deposit requirement was abolished in July 1999. The Bank commenced paying interest on Exchange settlement balances in July 1996.

:RB term deposits-C/ are short-term deposits of institutions holding an Exchange Settlement Account and authorised deposit-taking institutions that are members of RITS.:Deposits of overseas institutions-C/ and :Governments and instrumentalities-C/ include the IMF and central banks.

:Other liabilities-C/ include provisions, current year profit/loss, the counterpart obligation arising from transactions in repurchase agreements, and obligations arising from the outright purchase of securities which have been contracted but not yet settled.

Assets:
:Gold and foreign exchange-C/ assets include foreign exchange holdings invested in government securities and bank deposits, market value of open forward foreign exchange contracts and IMF Special Drawing Rights. Securities sold but contracted for purchase under repurchase agreements are retained on the balance sheet in this category.

:Clearing items-C/ include cheques and bills of other banks, bills receivable and remittances in transit. They may also include amounts owed to the Bank for overnight clearances of financial transactions.

:Australian dollar securities-C/ include Commonwealth Government Securities (CGS) and securities issued by central borrowing authorities of state and territory governments. Securities sold but contracted for purchase under sell repurchase agreements are retained on the balance sheet in this category. Also included are Australian dollar securities purchased but contracted for sale under buy repurchase agreements, being: eligible bank bills, certificates of deposit and debt securities of ADIs; Australian dollar- denominated securities issued by certain foreign governments, foreign government agencies and by highly rated supranational organisations; and selected Australian dollar domestic residential and commercial mortgage-backed securities, asset-backed commercial paper and corporate securities.

:Other assets-C/ include the Bank-C/s holdings of Australian notes and coins, Bank premises and other durable assets, and the Bank-C/s shareholding in the Bank for International Settlements.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Red Bearing, Rolling Ahead (RBC)?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Disclaimer

All information presented here is for display purpose only, and may not be complete nor accurate. This information does not constitute a financial advice, and should not be used to make any investment decisions or financial transactions. This author rejects any claims for liabilities resulting from the use, misuse, or abuse of this information. Use at your own risk.

Motivation

Due to time zone differences between Australia and most of the rest of the world, Australians have the advantage of knowing what happened at markets elsewhere in the world, before the Australian market (ASX) is open in the morning, Sydney time.

This prior knowledge provides an excellent opportunity for arbitrage. In the hands of a savvy day-trader, or a shrewd long-term investor, this information gives you the advantage of predicting the ASX, and achieve potentially significant financial gains.

Method

For the ten years period from 1/7/2010 to 30/6/2020, the daily closing prices for 41 global market indicators are collected from various reliable public-domain sources. We checked the data for error or omissions and normalised all tabulated records in a format that facilitates further analysis and visulaisation.

Those 41 market indicators are what we consider significant measures of various external factors that may affect the performance of the Australian Stock Market, as represented by the ASX200. Those indicators are:

• Nine other major stock market indices from the USA, Europe, and Asia.

• The exchange rate of the $AU against 10 world currencies that are most relevant to Australia's international trade.

• Official interest rates by the RBA and the US Feds, as indicators of affinity of foreign funds to Australia.

• Yield rates for governments-issued bonds by 10 countries from Western and Asian economies, as measures of relative availability of credit and cross-border investment. Bonds are grouped into "Short-term" (one year maturity) and "Long-term" (10 to 30 years maturity).

• Since Australia's economy is mainly an exporter of raw materials, we include prices for commodities that are most traded by Australia, as indicators for potential profitability for various relevant sectors of the ASX.

We feed relevant data to a machine learning model, which uses this data to extract heuristic parameters that are used to predict the ASX200 on daily basis, before market opens, and validates predictions at market close, with favourable results.

For more information, please visit the Tableau viz at: https://public.tableau.com/app/profile/yasser.ali.phd/viz/PredictingAustralianStockMarket/Story

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

RBC Bearings (RBC) Stock Forecast: A Rolling Bearing on a Path to Profit

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Mortgage lenders are dealing with the RBA's shift to a tighter monetary policy, as it fights heavy inflation. Since May 2022, the RBA has raised the benchmark cash rate, which flows to interest rates on home loans. This represents a complete reversal of the prevailing approach to monetary policy taken in recent years. Over the course of the pandemic, subdued interest rates, in conjunction with government incentives and relaxed interest rate buffers, encouraged strong mortgage uptake. With the RBA's policy reversal, authorised deposit-taking institutions will need to balance their interest rate spreads to ensure steady profit. A stronger cash rate means more interest income from existing home loans, but also steeper funding costs. Moreover, increasing loan rates mean that prospective homeowners are being cut out of the market, which will slow demand for new home loans. Overall, industry revenue is expected to rise at an annualised 0.4% over the past five years, including an estimated 2.2% jump in 2023-24, to reach $103.4 billion. APRA's regulatory controls were updated in January 2023, with new capital adequacy ratios coming into effect. The major banks have had to tighten up their capital buffers to protect against financial instability. Although the ‘big four’ banks control most home loans, other lenders have emerged to foster competition for new loanees. Technological advances have made online-only mortgage lending viable. However, lenders that don't take deposits are more reliant on wholesale funding markets, which will be stretched under a higher cash rate. Looking ahead, technology spending isn't slowing down, as consumers continue to expect secure and user-friendly online financial services. This investment is even more pressing, given the ongoing threat of cyber-attacks. Industry revenue is projected to inch upwards at an annualised 0.8% over the five years through 2028-29, to $107.7 billion.

Ritchie Bros Auctioneers stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Banks are grappling with a transition from years of loose monetary policy to tighter financial conditions. Soaring inflation prompted an RBA pivot in the face of surging energy, housing and food prices. The RBA hiked the cash rate multiple times from May 2022 to November 2023. Prior to this, banks cashed in on high residential housing prices, with low interest rates and government schemes encouraging strong mortgage uptake over the course of the pandemic. APRA also eased the interest rate buffer in 2019, before raising it in 2021. Interest hikes have pushed up banks' incomes over the past few years. Meanwhile, banks' interest deposit expenses and funding costs have also risen while elevated interest rates have dampened industry profit margins over the past few years. Overall, industry revenue is expected to expand at an annualised 9.3% over the five years through 2024-25, to $259.2 billion. This includes an anticipated slump of 8.3% in 2024-25, as inflationary pressure shows signs of easing, the cash rate easing, weighing on interest income. As banks passed on cash rate rises through higher interest rates, the RBA's policy approach has had a cascading effect on the economy. There’s a lag before these hit customers, with some fixed-rate mortgages gradually rolling over through 2023 and 2024. Banks are securing more interest income from existing loans but must manage inflated borrowing costs and bigger payouts on deposit accounts. Residential housing prices are set to stabilise, while heavy mortgage payments will price out some potential homeowners. Banks will be monitoring consumer spending amid inflationary pressures and spiralling borrowing costs. APRA has strengthened rules for managing interest rate risks, effective from October 2025. The updated Prudential Standard APS 117 requires major financial institutions to implement robust frameworks to manage these risks effectively. The big four will need to keep up with rapid technological change, managing cyber security as consumers embrace online financial services. Competition isn't easing up as smaller technology-focused firms disrupt the finance sector and foreign banks tap into the Australian market. Revenue is projected to climb at an annualised 0.3% over the next five years, to total $262.6 billion in 2029-30.

Australia's main stock market index, the ASX200, fell to 8580 points on July 11, 2025, losing 0.11% from the previous session. Over the past month, the index has climbed 0.18% and is up 7.80% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Australia. Australia Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Homeownership provides financial and emotional security and often represents an individual or family's most significant investment. House Construction industry contractors build single-unit (detached) dwellings or renovate and repair existing houses. Australia's solid population growth underpins the industry's performance. Still, a long-term shift in housing preferences towards constructing high-density apartments and townhouses has eroded revenue. House construction surged to a record peak in 2021-22 despite the pandemic restrictions and supply chain blockages impeding progress on construction projects. Homebuyers responded to record-low mortgage interest rates, favourable bank lending practices and the stimulus from the Federal Government's HomeBuilder scheme by unprecedented investment in new single-unit house construction and home renovations. As the housing market heated up, builders faced challenges juggling heavy workloads while dealing with supply bottlenecks, skill shortages and rising costs. The industry's revenue performance has taken a hit in recent years as housing investment slumped following the hike in mortgage interest rates as the RBA lifted official cash rates to quell inflation. Meanwhile, the HomeBuilder scheme wound down with the completion of funded projects. Industry revenue is expected to fall by 2.9% in 2024-25 and decline at an annualised 1.5% over the five years through 2024-25 to $76.1 billion. The industry's profit margins have suffered, partly reflecting the supply chain disruptions during the housing boom stemming from the COVID-19 restrictions. These bottlenecks delayed construction projects and inflated input prices for building materials, fuel, capital equipment and skilled labour. Fixed-price contracts and escalating input costs have pushed many homebuilders to the brink. Mounting population pressure and some easing in mortgage interest rates will support the moderate recovery in the industry's performance. Homebuilders may also derive some support from a commitment to construct 1.0 million new homes under the National Housing Accord. Still, much of the focus of residential building construction will shift towards high-density apartment and townhouse developments rather than single-unit houses. Industry revenue is forecast to climb at an annualised 1.4% to $81.6 billion through the end of 2029-30.

Mortgage brokers have benefited from the relatively resilient Australian housing market in recent years. Factors like the previously record-low interest rates, government stimulus and surging residential housing prices have improved loan values and loan volumes for brokers. Stronger commissions for brokers have grown profit margins and raised wages in the industry. Notably, the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services industries levied significant scrutiny on the conduct of mortgage brokers. As a result of the Royal Commission, numerous lenders changed their remuneration models for brokers, and the government even introduced legislation intended to reform the core principles of the industry. These reforms, including a statutory duty to act in the best interest of the borrower, have had varying effects on brokers. Overall, the Mortgage Brokers industry is expected to grow at an annualised 10.6% over the five years through 2024-25, to total $6.2 billion. Subsequent rate hikes introduced by the RBA in response to inflationary pressures have had relatively marginal effects on residential housing prices despite rising residential housing loan rates and the growing unaffordability of mortgages in general. Nonetheless, an expected easing of residential loan rates is set to push up mortgage broker revenue by an estimated 12.9% in 2024-25. Larger brokers have focused on improving their network sizes to improve the scale of their operations. Firms have also reckoned with threats from disruptive fintech operators. Interest rates are set to continue tumbling over the coming years following the RBA's cash rate drop in February 2025. However, the potential for future rate hikes pushing the housing market to a breaking point could have disastrous effects on mortgage brokers. Continued government stimulus in the form of the proposed Help to Buy Scheme and the Housing Australia Future Fund is set to support housing affordability and supply without artificially lowering housing prices and thereby indirectly benefiting broker operations. Overall, industry revenue is forecast to expand at an annualised 3.5% through 2029-30 to total $7.3 billion.

Regal Rexnord reported $10.09B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Regal Rexnord | RBC - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.